the effects of altering discharge policies to alternate

The Effects of Altering Discharge Policies to Alternate Level of CarePatient Flow

by

Lata Grover

A thesis submitted in conformity with the requirementsfor the degree of Master of Health Science

Graduate Department of Institute for Biomedical and Biomaterials EngineeringUniversity of Toronto

c© Copyright 2012 by Lata Grover

Abstract

The Effects of Altering Discharge Policies to Alternate Level of Care Patient Flow

Lata Grover

Master of Health Science

Graduate Department of Institute for Biomedical and Biomaterials Engineering

University of Toronto

2012

Alternate Level of Care (ALC) patients are patients that stay in the acute care setting while waiting to

be transferred to an ALC facility. They are not receiving the appropriate type of care and are occupying

acute care resources. ALC patients occupy 5,200 patient beds everyday in Canada, and 12 percent of these

ALC patients die during their waiting period. This study evaluates Toronto General Hospital’s (TGH)

discharge policy in the General Surgery and General Internal Medicine (GIM) departments using a discrete-

event simulation. For Long-term Care ALC patients, it was found that applying to one extra application

or maximizing the number of short waiting list facilities in their total number of applications significantly

reduces the number of ALC days and the number of died in hospital patients. Knowing if discharge policies

can decrease ALC days is not only significant to TGH but also to other health care institutions.

ii

Acknowledgements

I would like to express my gratitude to my supervisors Dr. David Urbach and Professor Dionne Aleman

for their guidance throughout the whole thesis process. They provided me with the opportunity to do an

operations research project because of my interest in the area, although I came from a Mechanical Engineering

background. They were always available to answer my questions and dedicated a lot of time to improving

my research and writing skills.

I would also like to thank my committee members Professor Michael Carter and Professor Timothy

Chan. Professor Michael Carter’s writings in health care operations research initially sparked my interest

in the area. It was great to receive his comments on my own research. Additionally, using Professor Chan’s

thoughtful feedback considerably helped improve the quality of my analysis.

At the beginning of my project when I was learning about the Alternate Level of Care process, Hsin-

Yi Yang of the University Health Network’s Discharge Office spent several hours explaining details of the

process to me and also managed to match patients with beds simultaneously.

The Division of Clinical Decision Making and Healthcare group provided me with feedback throughout

my Master’s thesis on presentations and ongoing results. They were also a great group to generate ideas

with as well as learn about current health care epidemiology research. I would also like to thank Dr. Urbach

for the opportunity to be part of this group.

I would like to thank Megan Chen and Rossini Yue for their support and giving me opportunities to

learn from other students’ research experiences. My appreciation goes to my classmate Caroline Chen for

proofreading my thesis right after she finished her own thesis defense. Finally, I would like to thank my

family for their continuous support as well.

iii

Contents

1 Introduction 1

1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.2 Institutional priorities and strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.2.1 Ontario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.2.2 Local Health Integration Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

1.3 Using simulations for decision-making . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

2 Objectives 4

3 Literature review 5

3.1 Simulations in the health care setting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

3.1.1 Reducing wait times through health care resource modifications . . . . . . . . . . . . . 5

3.1.2 Reducing wait times through policy change . . . . . . . . . . . . . . . . . . . . . . . . 6

3.1.3 Incorporating human behaviours to simulation . . . . . . . . . . . . . . . . . . . . . . 7

3.2 ALC patients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

3.2.1 Appropriate ALC patient discharge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

3.2.2 Reasons for high ALC days . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

4 Methods 9

4.1 Flowchart generation and validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

4.1.1 General Surgery social worker . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

4.1.2 GIM social worker . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

4.1.3 General Surgery nurse manager . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

4.1.4 Toronto Central CCAC’s client services manager . . . . . . . . . . . . . . . . . . . . . 10

4.1.5 Performance Management representative at SIMS . . . . . . . . . . . . . . . . . . . . 10

4.1.6 Discharge Planning Office . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

4.2 Sources of data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

4.2.1 Combined database . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

4.2.2 Process times . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

4.2.3 Distribution developments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

4.3 Model construction and validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

4.3.1 Validation process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

4.3.2 Models attempted to be validated . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

4.3.3 Description of validated model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

4.3.4 Determining number of model replications required . . . . . . . . . . . . . . . . . . . . 26

4.3.5 Scenarios modelled . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

iv

5 Results 28

5.1 Varying the fixed number of facilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

5.2 Varying the minimum number of facilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

5.3 Defining a short waiting list . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

5.4 Varying the minimum number of facilities with a short waiting list . . . . . . . . . . . . . . . 33

5.5 Increasing the frequency of waiting list updates . . . . . . . . . . . . . . . . . . . . . . . . . . 33

5.6 Varying the facility popularity distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

5.7 Varying the minimum number of facilities with a short waiting lists with varying short waiting

list definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

6 Discussion 38

6.1 Trends for varying the number of applications and short waiting list facilities . . . . . . . . . 38

6.1.1 CCC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

6.1.2 Convalescent care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

6.1.3 LTC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

6.1.4 Palliative . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

6.1.5 Rehabilitation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

6.2 Overall trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

6.3 Increasing the frequency of waiting list updates . . . . . . . . . . . . . . . . . . . . . . . . . . 43

6.4 Varying the facility popularity distributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

6.5 Varying the definition of a short waiting list and the number of short waiting list facilities . . 46

6.6 Data recording improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

6.7 Limitations of model outputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

6.7.1 Applying findings in the real system . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

6.8 Other methods to improve ALC process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

6.9 Recommendations for policy changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

7 Significance and Conclusions 50

Bibliography 50

A Popularity distributions and patient facility discharge histograms 55

A.1 CCC data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

A.2 Convalescent data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

A.3 LTC data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58

A.4 Palliative data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

A.5 Rehabilitation data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

B CCC Results 63

C Convalescent results 67

D Palliative results 71

E Rehabilitation results 75

F Pairwise comparison charts - varying the total number of applications 79

G Pairwise comparison charts - varying quantity of short waiting list facilities 85

v

H Pairwise comparison charts - updating short waiting lists daily 96

I Pairwise comparison charts - varying the definition of a short waiting list 102

J Pairwise comparison charts - varying the facility popularity distribution 108

vi

Chapter 1

Introduction

When an acute care patient no longer requires acute care services, s/he is designated as an Alternate Level

of Care (ALC) patient until s/he leaves the acute care facility. The patient uses the bed as a waiting area

until s/he is able to transfer to the appropriate ALC facility. The types of ALC facilities patients can apply

to include home (with or without support), rehabilitation, complex continuing care (CCC), long-term care

(LTC), group home, a transitional care bed, convalescent care, palliative care, hospice care, retirement home,

shelter, or supportive housing (Cancer Care Ontario, 2009).

This study focuses on ALC patient flow in Toronto General Hospital (TGH)’s General Surgery and

General Internal Medicine (GIM) departments. In TGH, an inter-professional care team and the patient or

his/her substitute decision maker (SDM) determine the appropriate type of facility for the patient (UHN

ALC Discharge Planning Committee, 2010). The Community Care Access Centre (CCAC) becomes involved

if the patient is transferring to LTC and convalescent care. The patient or his/her SDM with a social worker

select which specific facilities to send applications.

The first University Health Network (UHN) Discharge Policy was created on March 30, 2005. It was valid

until May 11, 2010. The second version was valid until December 22, 2010. The third version is currently

still in practice. The policies incorporate applying to a certain number of facilities with short waiting lists.

The wait times are determined by CCAC every 60 days. The policies for each type of ALC facility are

described in Table 1.1.

After the application submissions, the patient waits for the ALC facility’s approval. If approved, s/he

waits for a bed offer. With the CCAC, the patient has 24 hours to accept a bed offer before it expires. For

other types of beds, there is no fixed time but is approximately a few hours. However, for all types of beds,

TGH advises a patient to accept his/her first bed offer (UHN ALC Discharge Planning Committee, 2010).

This study analyzes the effects of changing acute care discharge policies on ALC patient flow. Although

the problem is Canada wide, TGH’s General Surgery and GIM departments are selected as an example to

analyze modified discharge policies.

ALC Facility Policy 1 Policy 2 Policy 3CCC Apply to all – –LTC 3 F with 2 SWL 3 F with 2 SWL 5 F with 3 SWLPalliative Minimum 3 F Apply to all Apply to allRehab Apply to all Apply to all Apply to all

Table 1.1: Progression of UHN discharge policy (F = facilities and SWL = facilities that have a short waitinglist)

1

Chapter 1. Introduction 2

1.1 Motivation

ALC patients using acute care as a waiting area has systemic effects on the health care system. Since acute

care beds are being occupied as a waiting area, patients who do require the acute care setting cannot be

admitted, leading to longer wait times (Burton et al., 2006). Long surgery and emergency room (ER) wait

times can result from post-operative beds being fully occupied (Burton et al., 2006). Patients waiting for

transfer from the ER to another hospital department, which is fully occupied by patients, including ALC

patients, consumes the ER’s resources. The main determinant to urban ER overcrowding is the availability

of staffed acute care beds and intensive care beds (Burton et al., 2006). In Ontario, there is an average of

2,874 ALC patients daily and 823 ER patients waiting for an inpatient bed at any time. This represents 18

percent and 5.2 percent of all acute care beds respectively (excluding paediatric and obstetric beds) (Ontario

Hospital Association, 2011). In the Toronto Central Local Health Integration Network (LHIN), where TGH

is located, the Ontario Hospital Association (2011) reported that ten percent of beds are occupied by ALC

patients.

ALC patients have a 12 percent death rate while waiting (Canadian Institute for Health Information,

2009). They experience increased functional impairment and complex health needs in comparison to a LTC

facility patient (Costa and Hirdes, 2010).

Additionally, ALC patients preoccupy acute care human resources. In a hospital, approximately 50

percent of nurses and 60 percent of caregivers provide care to ALC patients (Ostry et al., 2001). In terms

of caregiver safety, an ALC patient designated area of the hospital will reduce the risk of worker’s injuries.

Through interviews, the injured workers identified the principal reasons for injury as unpredictable and

aggressive behaviour, dementia, heavy lifting and transferring, and higher work loads (Ostry et al., 2001).

The ALC issue affects not only ALC patients, but other patients and health care providers as well.

Furthermore, LTC waits contribute to 39 percent of the total number of ALC days in Ontario (Burton

et al., 2006) where ALC days is defined as the total number of days ALC patients are waiting in acute care.

The second highest contributor to wait times is CCC, which is 20.7 percent of ALC days (Burton et al.,

2006).

Carey et al. (2005) found that in their hospital, 63 percent of all unnecessary length of stay (LOS) days

were due to non-medical delays (discharge planning and discharge destination unavailable). Of the non-

medical delays, 84 percent were due to unavailable nursing facility beds, which shows the possible impact

of improved discharge policies. The efficacy of TGH’s discharge policy to ALC facilities has not previously

been determined, so this study investigates potential patient flow improvements to the policy.

1.2 Institutional priorities and strategies

1.2.1 Ontario

In the Ministry of Health and Long-Term Care (MOHLTC)’s Result Based Plans for 2009- 2010 and 2010-

2011, reducing ER wait times is in its top two priorities (Ministry of Health and Long-Term Care, 2009-2010,

2010-2011). The plan highlights that to reduce ER wait times, ALC patient wait times are to be decreased.

The MOHLTC’s Expert Panel on Alternate Level of Care, established in May 2006, proposed solutions

to solve the ALC problem for Ontario (Burton et al., 2006). The panel grouped its recommendations, and

the following are those that affect acute care facilities: improving system access, integration and patient

flow; provider, patient and family education; best practices within and across health care organizations; and

data, benchmarks and accountability suggestions (Burton et al., 2006).

To improve system flow, integration and patient flow, Burton et al. (2006) suggests to modify discharge

Chapter 1. Introduction 3

policies. TGH has already modified its discharge policies from MOHLTC’s imposed policies by requiring

patients to choose more than one facility with some facilities having short waiting lists. However, varying

policy options should be further analyzed to determine superior discharge policies for reducing ALC days

(Burton et al., 2006).

The Centre for Healthcare Quality Improvement (CHQI) introduced the Flo Collaborative program in

September 2007 to reduce Ontario ALC days. The program promotes preliminary discharge planning and

removing unnecessary delays in the discharge process (Centre for Healthcare Quality Improvement, 2009).

The Flo Collaborative lists primary drivers and secondary drivers that affect the overall goal of decreasing

ALC days. Examples of primary drivers include design of care processes, community capacity, and placement

policies and practices. Examples of secondary drivers include removing unnecessary steps in care, having

the appropriate number of LTC beds, and modifying policies related to patient choice for LTC (Centre for

Healthcare Quality Improvement, 2009).

The MOHLTC’s Expert Panel on Alternate Level of Care and the CHQI both suggest exploring varying

discharge policies, which this research study investigates.

1.2.2 Local Health Integration Networks

The LHINs have created Integrated Health Service Plans (IHSP) for the years 2010-2013. Each LHIN has

identified reducing ALC days as one of its main priorities for the four years (Central East LHIN, 2009; Central

LHIN, 2010-2013; Hamilton Niagara Haldimand Brant LHIN ALC Steering Committee, 2008; North East

LHIN, 2009; North Simcoe Muskoka LHIN, 2009; South East LHIN, 2009; Toronto Central LHIN, 2009).

Many of the recommendations proposed to decrease ALC days involve investing in additional facilities

and beds. The Central, Central East, Hamilton Niagara Haldimand Brant, North Simcoe Muskoka, North

East, South East, and Toronto Central LHINs have identified improving discharge processes as an approach

to reducing ALC days (Central East LHIN, 2009; Central LHIN, 2010-2013; Hamilton Niagara Haldimand

Brant LHIN ALC Steering Committee, 2008; North East LHIN, 2009; North Simcoe Muskoka LHIN, 2009;

South East LHIN, 2009; Toronto Central LHIN, 2009).

It is advantageous to determine if the recommendations proposed will be effective before implementation.

This study uses operations research tools to make this determination.

1.3 Using simulations for decision-making

Models in operations research can be created analytically or through simulation. With more complex sys-

tems, simulations are commonly used (Winston, 2004). Simulations are advantageous because they require

fewer assumptions than analytical methods, some allow monitoring of system interactions for bottleneck

identification, and lengthy simulations can be created. It may be disadvantageous because it can be time-

consuming to build a reliable model, and simulations do not optimize the situation but create “what-if”

scenarios instead (Banks et al., 1996).

Simulation models can be static or dynamic, deterministic or stochastic, and discrete or continuous.

The ALC process is dynamic, as waiting lists vary over time. It is stochastic because patient decisions,

arrival rates, and lengths of care are random. It is discrete because each event such as a patient decision

or transfer is discontinuous. A dynamic, stochastic, discrete simulation is classified as a discrete-event

simulation (Winston, 2004). Discrete-event simulations are common in the health care sector (Angelis et al.,

2003; Brailsford and Schmidt, 2003; Davies and Davies, 1987; Duguay and Chetouane, 2007; Harper and

Gamlin, 2003; Ratcliffe et al., 2001; VanBerkel and Blake, 2007).

Chapter 2

Objectives

The objective of this study is to determine the effects of changing discharge policies imposed on patients

when choosing ALC facilities with the intention of improving patient flow. The study will measure the

total number of ALC days and the number of died in hospital patients in the General Surgery and GIM

departments at TGH using a discrete-event simulation. Discharge policies will vary by the total number of

facilities patients are required to choose and the number of facilities required with short waiting lists.

4

Chapter 3

Literature review

3.1 Simulations in the health care setting

No studies have been found that simulate the wait times between acute care and ALC facilities. The only

simulation studies found to address ALC are a study by Lane and Husemann (2008) and Xie et al. (2006).

Lane and Husemann (2008) mapped out the process from general practitioner referral to dismissal from

ward, including wait times to community services. However, Lane and Husemann (2008) focused on different

routes patients can take in the acute care facility and classify all ALC facilities into one category called

community care. The authors indicated the intention to incorporate system dynamics, but time constraints

only allowed for a generated flow diagram to be used for provoking discussion with health care managers in

a workshop.

Xie et al. (2006) created a model depicting flow on the LTC side between residential care and nursing care

in England using a continuous Markov model. Possible transferring patterns included transferring between

the two types of care, from short to LTC within a facility, or being discharged. Both of these studies did

not simulate the waiting process from acute care to an ALC facility and only model the existing flow, not

possible improvements.

However, researchers have studied decreasing wait times in other health care areas. Wait times can be

reduced by the modification of health care resources (Duguay and Chetouane, 2007; Lane et al., 2000; Perez

et al., 2008; Shim and Kumar, 2010; VanBerkel and Blake, 2007). Studies have also shown that wait times

can be reduced by the modification of policies. It is an appealing way to reduce wait times, as it does

not usually require reallocating resources or additional capital investment in equipment or human resources

(Harper and Gamlin, 2003; Patrick and Puterman, 2007; Ratcliffe et al., 2001; Rohleder and Klassen, 2000;

Tuft and Gallivan, 2001; Vasilakis et al., 2007; Wijewickrama, 2006).

3.1.1 Reducing wait times through health care resource modifications

Shim and Kumar (2010) created a simulation of the Accident and Emergency (A&E) department in a

Singapore hospital. It was found that by adding another payment station and a new ward dedicated to

short-term patients, wait times can be reduced. Duguay and Chetouane (2007) simulated a New Brunswick

ER’s busiest pathways and times to discover that, with a specified budget, one additional nurse and one

additional physician resulted in the largest average reduction in wait times. Furthermore, Lane et al. (2000)

identified that without emergency patients having beds to transfer to in another department, wait times in

the ER will increase. Increasing ward bed capacity in the simulation minimized the problem and avoids

having to cancel elective cases caused by full ward bed occupancy. This problem may be reflected in the

5

Chapter 3. Literature review 6

ALC situation as well. As emergency patients occupy beds intended for elective case patients, ALC patients

can be occupying ward beds.

Perez et al. (2008) modelled a Medellın, Columbia health center to discover that the bottleneck of high

wait times in the health center is the admission center’s low staff level. To solve the problem, staff levels

were increased.

Kumar (2011) created a system dynamics model with elective and non-elective patients entering a ward

and varied the number of beds on weekly waiting lists. The effects on the rejection rate for elective patients

and daily bed waiting lists for non-elective patients were determined.

As a more cost-effective strategy to decrease wait times, existing resources can be reallocated, rather

than added. Bed management is the alteration of bed resources to alter operations. For example, a discrete-

event simulation was used to redistribute beds in the General Surgery department of Capital District Health

Authority in Halifax, Nova Scotia by VanBerkel and Blake (2007). The hospital has two sites where it

performs general surgery with one receiving more non-elective cases because of the site’s ER. By keeping the

total number of beds the same but distributing the beds between the sites, the total wait time for patients

would increase or decrease depending on the bed configuration.

3.1.2 Reducing wait times through policy change

Policy changes can be implemented in scheduling systems to decrease wait times. Through simulation

modelling, Vasilakis et al. (2007) discovered that scheduling patients for a surgery rather than a surgery

with a certain surgeon can decrease wait times. Similarly, Harper and Gamlin (2003) found that in an

ear, nose, and throat clinic simulation, starting appointments earlier and by scheduling patients based off

an algorithm that schedules patients sequentially rather than in blocks, the wait time for a patient’s first

service decreased. Szecket et al. (2012) found that by changing an admission policy to promote more evenly

distributed admissions, there was a reduction in the variance in discharge rates and the LOS time. However,

it is mentioned the reduction in LOS time is mostly for shorter stay patients, and may not apply to the

sicker patients who are applying to other types of facilities after discharge.

A Japan outpatient clinic scheduling system was simulated by Wijewickrama (2006) to reduce patient

wait times but also to minimize the effect on physician idle time. The research study claims to be an

improved model to previous models because of its consideration of walk-in patients, interrelated subunits,

patients who use the clinic other than outpatients, second time consultations, and the dynamic characteristic

of a physician’s schedule. Four tested scheduling policies revealed that the policies that minimized patient

wait times and minimized physician idle times were not the same. Therefore, a hybrid policy that reduced

both outcomes was recommended. Rohleder and Klassen (2000) produced a scheduling simulation that also

reduces patient wait times and physician idle times but addresses patient’s special requests for appointments

at a certain time.

Patrick and Puterman (2007) simulated a diagnostic imaging clinic that images inpatients within a day

and schedules outpatients. Scheduling diagnostic imaging by providing a designated priority to inpatients

reduces outpatient wait times (Patrick and Puterman, 2007). This may be practical for a diagnostic imaging

model but would be impractical in the ALC model, as the patients are waiting to get out of beds required

for high priority patients. The prioritization would have to be based on the patients that potentially enter

their beds.

Several other studies have explored changing scheduling policies. LaGanga and Lawrence (2007) and

Giachetti (2008) simulated reducing wait times by decreasing problems associated with patients missing

outpatient clinic appointments. Zhou et al. (2008) modelled scheduling for the purpose of increasing profit

for a clinic. Tuft and Gallivan (2001) modelled cataract surgery scheduling and measured success using a


priority weighted measure that benefits reduced wait times for the most critical patients.

Policy changes, in relation to transplant allocation, have also been studied to address health care wait

times. Ratcliffe et al. (2001) studied policy changes related to selecting alcoholic liver disease or primary

biliary cirrhosis patients for liver transplant. The policies were evaluated based on the long-term survival

rate of patients with end stage liver disease and the overall cost effectiveness. From the nine policies

tested, the lowest incremental cost effectiveness ratio (total costs with transplantation minus total costs

without transplantation divided by life years gained with transplantation minus life years gained without

transplantation) occurred in a policy where the highest severity patients are given the lowest priority. Zenios

et al. (2000) use a quality-adjusted life years per patient measure to determine the efficacy of a transplantation

allocation policy. The highest rated policy found in this study determines transplant allocation by matching

certain patient characteristics.

Wong et al. (2010) have showed that by changing the daily discharge rates to the average daily discharge

rate or the average weekday discharge rate, the amount of inpatients who occupy the ER can decrease

significantly, thus allowing more ER patients to be admitted. Furthermore, discharge patterns were altered

to find their effects on bed occupancy rates and bed wait times by Zhu (2011). Earlier discharges and varying

discharge distributions were analyzed throughout the day.

No simulation studies have been found that simulate discharge policies with patient choice.

3.1.3 Incorporating human behaviours to simulation

Probability distributions and randomization are currently used to display human behaviour in discrete-event

simulations. Gonsalves and Itoh (2009), Brailsford and Schmidt (2003), and Sanders et al. (2008) have

researched ways to improve this method’s validity. Gonsalves and Itoh (2009) incorporated psychology into

wait time models to highlight that the reason for reducing wait times is to improve patient satisfaction.

However, a patient’s perception of satisfaction can also be improved by factors such as nurses’ consider-

ateness and entertainment facilities, which were incorporated into their simulation model. Brailsford and

Schmidt (2003) also attempted to improve discrete-event simulation through human psychology in a diabetic

retinopathy screening model. Instead of assuming a certain patient percentage will not attend their appoint-

ments, patients would have attributes that would define compliance. The authors indicated that there is

still more research required to make a realistic simulation with human psychology without having several

assumptions. Sanders et al. (2008) discussed using radio frequency identification cards (RFID) in an ER in

order to gather more accurate patient flow information to be used in simulation modelling. However, it is

a proof-of-concept and has not been implemented in a health care setting. Therefore, stochastic behaviour

demonstrated through probability distributions will still be used in this study to model human behaviour.

3.2 ALC patients

ALC is an area within Ontario’s health care system that has not commonly been addressed in the literature,

perhaps because of its fairly new classification. No studies could be found that simulate the process of a

patient leaving from an acute care facility to an ALC facility. However, studies have looked at characteristics

of ALC patients. The mean age of an ALC patient in Ontario is 75.4 years old, and approximately 50 percent

of ALC patients enter the acute care facility for either trauma, neurological and mental illness or disorders,

and cardiovascular and respiratory diseases (Burton et al., 2006). For ALC patients across Canada, 83

percent come into the hospital through the ER (Canadian Institute for Health Information, 2009).

Other areas of ALC patient research include ensuring proper facility placement after acute care (Brosseau

et al., 1996; Chang et al., 2004; Rivlin, 1990; Unsworth, 2001) and determining factors that increase the ALC


problem (Chang et al., 2004; Forrest et al., 2002).

3.2.1 Appropriate ALC patient discharge

ALC patients should be transferred to the appropriate type of facility in order to avoid future transportations

(Chang et al., 2004). In Canada, readmission occurs with 17 percent of ALC patients (Canadian Institute

for Health Information, 2009).

Unsworth (2001) researched types of information required from an orthopaedic or stroke patient to

determine his/her potential appropriate ALC facility between a nursing home, a rehabilitation centre, or the

patient’s home. Similarly, Brosseau et al. (1996) concluded that based on an acute stroke patient’s functional

status at admission, social support and gait status, it can be determined if the patient should go to a private

home, rehabilitation center, or LTC facility.

More specifically, decision models were created by Rivlin (1990) and Chang et al. (2004) to identify the

most appropriate type of care for a patient. Based on the patient’s symptoms, Rivlin (1990) developed, in

the United Kingdom, an assistive tool for deciding acute care patient destination between a nursing home,

a residential home, or a long-stay bed in a nursing environment. Chang et al. (2004) created a flowchart for

discharge planning using an analytical hierarchy model combined with case-based reasoning. An analytical

hierarchy model is a model used for decision-making involving several different stakeholders. It combines

different attributes with appropriate weightings to determine the solution to a problem (Winston, 2004).

The factors Chang et al. (2004) used to generate the decision-making model are based on historical data of

discharges and patient information.

The studies discussed have determined how to ensure appropriate patient transfer after acute care, but

have not explored if this has an effect on ALC days.

3.2.2 Reasons for high ALC days

Forrest et al. (2002) determined that reasons to be transferred to an LTC facility include increasing age,

no spouse or children, and having a psychiatric or neurologic diagnosis. As for reasons for high ALC days,

Forrest et al. (2002) found that the determining factors are longer hospital stays and a requirement for an

LTC facility at the end of acute care. They also found that factors that increase the LOS are no children, a

neurologic or psychiatric diagnosis, and surgery not due to the original reason for admission. However, this

study does not investigate methods to reduce the high ALC days.

Furthermore, Chang et al. (2004) used modelling to predict LTC facility demand until 2020 and LTC’s

financial viability. Chang et al. (2004) used information such as patient and patient family incomes, family

assets, recovery from disability, nursing home services, eligibilities for public programs, and public and

private LTC finances. The study predicted a larger proportion of the population entering LTC facilities, this

population being more financially stable, and increases to LTC expenses (Chang et al., 2004). The study

demonstrates a need to discover methods to reduce ALC days to accommodate the upcoming increasing

demand.

Chapter 4

Methods

A discrete-event simulation was developed to model ALC patient flow. In a simulation model, the system and

its boundary must be clearly distinguished from its environment before modelling can begin. This research

study’s system is the patient flow after finishing receiving acute care services to when the patient transfers

to an ALC facility, goes home, further requires acute care, or dies. The ALC facilities include home, home

with services, respite care, convalescent care, palliative care, retirement homes, CCC, rehabilitation centres,

or LTC.

4.1 Flowchart generation and validation

To model ALC patient flow in TGH’s General Surgery and GIM departments, interviews were performed to

understand the flow. This was done with system experts, including a social worker from General Surgery

and GIM, the General Surgery’s nurse manager, the Toronto Central CCAC’s client services manager,

a Performance Management representative at Shared Information Management Services (SIMS), and the

Discharge Planning Office. Information about the admission and discharge process was also gathered from

the UHN Discharge Planning and Admission Policy and Procedure Manuals.

Following the initial development of the flowchart, a qualitative flowchart review was performed with

each of the system experts. This ensured that any of the revisions were agreed upon by all of the system

experts.

A summary of new information gained from each system expert is listed below. Some information helped

in the development of the final flowchart and others helped determine how the data would be gathered.

4.1.1 General Surgery social worker

• When deciding if a patient should be designated as ALC, a decision is made with all appropriate

health care professionals (occupational therapists, physiotherapists, speech pathologists, respiralogists,

nurses, physicians, and social workers).

• The Discharge Planning Office will provide social workers with bed offer information.

• Patients are first encouraged to travel home. This can be done without services, through the Home at

Last program, home with community services, or the Waiting at Home program. They can also go to

retirement homes if they are financially capable. If these are not appropriate, the patient may then

apply to rehabilitation, convalescent care, palliative care, LTC, or CCC.

9

Chapter 4. Methods 10

• LTC is for patients who require ongoing medications and Personal Support Workers (PSWs). Conva-

lescent care is for those who meet LTC needs but only require care for less than 60 days. For CCC,

patients have a chronic condition that would require physicians daily and probably more advanced

technology than LTC.

• Patients in General Surgery who are non-elective will more likely be the patients who have longer

ALC days. These patients are not as thoroughly assessed to determine if they are good candidates for

surgery.

4.1.2 GIM social worker

The GIM social worker had stated that the flowchart created with the General Surgery department is the

same process experienced in GIM.

4.1.3 General Surgery nurse manager

• The kind of information that is recorded in the Electronic Patient Record (EPR) by General Surgery

during the ALC process was outlined. These fields are summarized in Table 4.1.

• The ALC data in the EPR goes back approximately two years.

4.1.4 Toronto Central CCAC’s client services manager

• When reviewing the developed flowchart with CCAC, it was discovered that the flowchart was de-

scribing more of what the system is supposed to look like opposed to what actually happens in the

system.

• All other types of ALC facilities should be considered before looking at LTC.

• The client services manager deals with patients who are not following the UHN discharge policy. This

is approximated as 20-25 percent of ALC patients. This would include patients who continually refuse

to go home when it is appropriate or to go into an appropriate facility. However, the client services

manager emphasized, that according to Ontario legislation, the patient only has to apply to one facility.

• In the UHN discharge policy, it is indicated that some of the LTC facilities patient choose must have

a short waiting list. Patients are encouraged to apply to all suitable facilities for rehabilitation and

CCC.

• CCAC believes that the process of applying to facilities can pose a large time delay. Therefore, it is

important to involve CCAC as early on in the process as possible.

4.1.5 Performance Management representative at SIMS

• Performance Management performs traditional reporting. Information is reported to CIHI 25 days after

it occurs. Because of the incompleteness of the EPR, they rely on additional sources of information. It

is approximated that the compliance for ALC procedure ordering on the EPR is 75 percent. Within this

data, error exists. Because of this error and compliance rate, the Performance Management department

manually goes through and compares data in the EPR and a database maintained by the Discharge

Planning Office.


• The Performance Management department does not feel that ALC data entry should be entered by

physicians. As social workers are more integrated in the discharge process, they should be given access

to the EPR.

4.1.6 Discharge Planning Office

• Social workers prepare ALC applications and then submit the applications to the Discharge Planning

Office.

• The Waiting at Home program is available for patients in Toronto Central LHIN who are waiting for

LTC and can go home safely with CCAC services for a maximum of eight hours per day of services.

When the patient applies to the Waiting at Home program, s/he must have at least one open application

for a facility and CCAC will assess them in 24-48 hours. If the patient does not get accepted to a

facility within 60 days, s/he is then considered a crisis patient and has to maximize their number of

applications. The Waiting at Home program also existed with rehabilitation and convalescent care

from December 2, 2009 to December 13, 2010.

• The different types of patients types were categorized by the Discharge Planning Office based on their

symptoms. Palliative care is for patients who are dying. Rehabilitation patients are starting to get

better. Convalescent care has a shorter duration than LTC and is not as intense. It is expected that

convalescent care patients will eventually be going home. LTC and CCC are meant for patients who’s

functional status is steady.

• For outpatient rehabilitation, it is likely that the patient can go home and wait to be admitted to these

facilities.

• When applying to LTC, the application will be reviewed by CCAC and then by the actual facility.

When the facility is outside of the Toronto Central LHIN, the application is sent to the Toronto Central

CCAC, then to the appropriate CCAC, and then to the LTC facility.

• There are some CCAC rules that make the system more complex. If the patient gets accepted to a

LTC facility that was not his/her first choice, s/he can go to the facility and keep his/her choices for

higher priority facilities open. S/he is able to transfer to this facility when s/he gets the bed offer.

This rule does not apply if these higher priority facilities are outside of Toronto Central LHIN.

• The convalescent care type was introduced to decrease ALC days, but, from the opinion of the Discharge

Planning Office, it seems like it has actually increased ALC days since its development. For St. Hilda’s,

there are beds open but not filled because of the institutional layers required to navigate through. It

sometimes takes two to three weeks to hear back from a facility.

• Once the Discharge Planning Office sends the application to a facility, the facility can either accept,

reject or request additional information about the patient. The patient can be rejected if s/he may be

medically too active or not be motivated.

The final flowchart is shown in Figure 4.1. The discrete-event simulation was constructed based on this

flowchart.


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RM&R EPR SWDBMedical record number Medical record number

OHIP Number OHIP numberALC designation date Ready for discharge date

Rehab/CCC/LTCH/CCAC Disposition Level of careReferral date Faxed dateAccepted/denied dateAdmitted date Discharge date Discharged dateALC facility Refer facility

Institution Facility

Table 4.1: Names of data fields in the RM&R, EPR and SWDB compared against each other

4.2 Sources of data

Three sources of information were used to gather patient information. The first source of information is

the Record Matching & Referral (RM&R) system, which is maintained by the Discharge Planning Office,

CCAC, and ALC facilities for CCC, rehabilitation, and LTC. It began in 2009 in Toronto Central LHIN and

has progressively gained the usage of eight rehabilitation or CCC facilities and 37 LTC facilities. The second

source of information is the EPR, and the third is a Microsoft Access database maintained by the Discharge

Planning Office. The Discharge Planning Office collects all of the offline information from social workers and

puts it into the this Microsoft Access database, which will be called the social worker’s database (SWBD).

It was not widely used until 2006.

Only data for patients who had their entire ALC status between 2009 and 2010 were gathered. It was

assumed the number of ALC days found from patients who were designated as ALC before January 1, 2009

and still an ALC patient after January 1, 2009 and patients who were designated as ALC before December

31, 2010 but discharged after December 31, 2010 do not contribute significantly to the total number of ALC

days between 2009 and 2010.

The SWDB data was extracted from the Microsoft Access database to an excel file. The excel file was

organized in order to be compared to the other sources of information. The RM&R and EPR data was

requested from SIMS.

After getting access to the three sources, it was discovered that the SWDB included the most patient

entries for TGH General Surgery and GIM and included more data fields required for the model.

The RM&R contained fewer patients, as it only included the patients from CCC, rehabilitation, and LTC.

The information in the RM&R was compared against the SWDB using patient’s Ontario Health Insurance

Plan (OHIP) numbers as a reference.

The EPR categorized the patient as either TGH, Toronto Western Hospital, or Princess Margaret Hospital

with no further departmental information. This set of data could not be treated as its own independent set,

so it had to be compared against the SWDB using Medical Record Numbers (MRNs).

MRNs and OHIP numbers were then be removed and replaced with randomized identification numbers

in order to keep anonymity of the data. To ensure confidentiality, all of the files with patient identifiable data

were kept on the research student’s account on the UHN server. The files were backed up on an encrypted

USB key. Table 4.1 demonstrates which data fields were compared against each other between the three

sources of data.

There were 3920 TGH General Surgery and GIM entries in the SWDB. 2975 entries had ALC designation

dates before 2009 and 162 of the entries after 2010, leaving 783 entries. Entries without an ALC designation

date were kept incase this date could be found from the other two data sources.

There were 1314 entries exported from the EPR between 2006 and 2010. 217 entries had unrecognizable


Mismatch field QuantityAcute care admission date 6Applied facility 23Discharged location 18ALC designation date 97Discharge date 23

Table 4.2: Frequency of mismatched fields between the EPR and SWDB. More than one type of error canoccur in an entry

Health characteristic Quantity Health characteristic QuantityBehavioural Issues Present 163 Mobility scooter 0Dialysis 162 Mobility walker 0Eternal feeding 135 Mobility wheelchair manual 3Equipment needs 135 Mobility wheelchair auto 0Intravenous 128 Respiratory BIPAP 0Oxygen bipap 0 Respiratory CPAC 1Oxygen constant O2 7 Respiratory nebulizer 0Oxygen CPAP 2 Respiratory tracheotomy 0Oxygen intermittent 15 Oxygen therapy 26Oxygen O2 at exercise 0 Bladder 26Oxygen at rest 2 Excretion appliance 26Tracheostomy 89 Suctioning 26Ventilation 89 Wandering support 26Skin condition 89 Smoker/smoking history 25Mobility immobile 13 Transfers 25

Table 4.3: Frequency of patient properties in RM&R

MRNs. Low MRNs were found with only six digits. These were unrecognizable so had to be omitted from

the comparison process. 418 MRNs entries could be matched against the SWDB. However, mismatches were

found in the data fields listed in Table 4.1. The frequency of mismatched fields are listed in Table 4.2.

The RM&R contained 7464 entries with a separate entry for each facility applied to by a patient. 7452

entries had OHIP numbers. Two entries were removed because the OHIP number had less than ten digits.

The dataset included all departments, so entries in the SWDB were used to compare against the RM&R in

order to find discrepancies. 835 of the RM&R entries could be matched against entires in the SWDB.

The RM&R contained fields for patient health characteristics such as whether s/he required dialysis or

ventilation. However, this information was not provided consistently. As well, because the RM&R was

not inclusive of all facility types, these properties would not be available for all patients in the discrete-

event model. Each health characteristic and the number of entries that had information on this health

characteristic are listed in Table 4.3.

When comparing everything against the SWDB, 190 SWDB patient entries could be matched against

EPR and the RM&R. 150 SWDB patient entries could be matched against just the RM&R. 228 SWDB

patient entries could be matched against just the EPR. 215 SWDB patient entries could not be matched

against either of the other two databases.

4.2.1 Combined database

Now that all of the data sources were compared against each other, discrepancies had to be resolved and the

data had to be analyzed to ensure it was realistic.

The combined database only included entries that had the entire ALC status within 2009 and 2010 and

entries without an ALC designation date. If this date was unknown after comparison between the three


Issue Possible reason Assumption/resolutionInconsistent numbering of the fa-cilities in the Refer facility field

These numbers may be prioritiesfor the patient or an arbitrary setof numbers.

Facility priorities were excludedfrom the study.

Mismatched ALC designationdates

Staff delayed recording of date. Earlier date is assumed.

Additional applied facilities inSWDB

There are some cases where thepatient specifies that s/he maywant to apply to a certain appli-cation but does not actually ap-ply to it.

Model assumes the SWDB num-ber of applied facilities is accu-rate and may have an inflated ac-tual number of applications.

Patient does not have any ap-plied facilities but was admittedto an ALC facility

Entry error occurred. Patient must apply to the facilitys/he is discharged to.

SWDB missing information forsome patients with a few ALCdays

If a discharge card was not re-quired, the patients may justbe taken care of and dischargedwithin the General Surgery orGIM unit.

If the patient is found in anotherdata source, they are added tothe combined database.

High rate of discharges to acutecare in EPR

In the EPR, it is quick tochoose a facility with a preced-ing “Acute care - ” term.

If SWDB had the same facilitywithout the prefix, the patient isassumed to go to the ALC facil-ity.

Discrepancies of whether patientwent home with or without ser-vices between data sources

As long as the patient was notdischarged to an ALC facility,the field was not reliable onwhether the patient was goinghome with or without services.

Model does not differentiate be-tween going home with or with-out services.

Table 4.4: Issues found while comparing data sources, possible reasons, and assumptions or resolutions

sources of information, the entry was removed (16 entires). Five duplicate entries were removed. The seven

respite and retirement patents are removed, as these patients do not largely contribute to the total number

of ALC days.

The total ALC LOS was determined by the number of days between the ALC designation date and the

discharge date. If the ALC LOS value was below zero, the entry was removed (six entries).

Unmatched fields were discussed with the Discharge Planning Office. Issues, their possible reasons, and

assumptions that were made to overcome the discrepancies are outlined in Table 4.4.

Finally, six entries are removed due to unexplainable information after discussion with the Discharge

Planning Office. Therefore, 743 entries are used to model the ALC patient flow.

The breakdown of total number of ALC patients can be seen in Figure 4.2 and number of ALC days in

Figure 4.3. The most number of patients apply to rehabilitation facilities, but the most number of ALC days

is for LTC.

The total number of unique facilities that all patients previously applied to in 2009 and 2010 are outlined

in Table 4.5. This is also the number of facilities that will be available for a patient to apply to in the model.


Figure 4.2: Distribution of number of ALC patients applying to each ALC facility type in TGH GeneralSurgery and GIM in 2009 and 2010

Figure 4.3: Distribution of number of ALC days for each ALC facility type in TGH General Surgery andGIM in 2009 and 2010

ALC facility type Total number of facilitiesCCC 12Convalescent 14LTC 67Palliative 17Rehabilitation 27

Table 4.5: Total number of unique facilities patients applied to in 2009 and 2010 for each ALC facility type


Process time CalculationApplication preparation time Application sent date - ALC designation dateApplication review time Accept/deny date - application sent dateBed offer time Admit date - accept date

Table 4.6: Method of calculating process times

4.2.2 Process times

The breakdown of a patient’s ALC LOS was between three process times: application preparation, applica-

tion review, and bed offer time. How these three process times are calculated is outlined in Table 4.6.

Queue times were also collected for going home or having a worsened condition. Worsened conditions

include dying in the hospital or returning back to acute care. As most of this category is patients dying in

the hospital, this queue time will be called the dying in hospital queue. Patients who end up in this category

will be called died in hospital patients.

The data was categorized by ALC facility type (CCC, convalescent, LTC, palliative, rehabilitation) before

creating distributions for the three process times. All of the available process values were collected. There

were not always three distributions for a patient entry, as sometimes a date would be missing.

4.2.3 Distribution developments

Distributions were attempted to be created for each of the three process times, the dying in hospital, and

going home queues for each facility using Stat::Fit (Geer Mountain Software, South Kent, Connecticut). The

results are summarized in Table 4.7.

There were cases where insufficient data points (less than six) were available to create a distribution in

Stat::Fit. For rehabilitation, there were no distributions possible for any of the process times. It was decided

to use discrete distributions, as there was inadequate data for parametric distributions for all facility types.

For example, the died in hospital queue time histogram for each ALC facility type is shown in Figure

4.4. The histogram for the going home queue time for each ALC type is shown in Figure 4.5. The frequency

of different queue times for each ALC facility are shown.

Distributions were also created for the frequency patients chose to apply to different ALC facilities within

each facility type, which will be called the facility popularity distribution. Facility popularity distributions

and histograms for facilities admitting patients, the three process times’ lengths, and the number of appli-

cations created per patient can also be found in Appendix A for each ALC facility type.

4.3 Model construction and validation

The discrete-event simulation was built in Simul8 (Visual8, Mississauga, Ontario). The events in the system

are when a patient applies to a facility, the facility accepts the patient, the facility offers a bed to the patient,

the patient dies, and the patient is able to go home. The events in a discrete-event model change the state

of the system.

The discrete-event model involves stochasticity when modelling patient behaviour. With each new trial,

Simul8 uses a new random stream set.

The flow of patients through the model is demonstrated in Figure 4.6. Probability distributions discussed

in the previous section represent patient behaviour. Patients would enter either the CCC, convalescent, LTC,

palliative, or rehabilitation system after they finished receiving acute care at an inter-arrival rate based on

historical data. The patient then goes through a process where they will apply to facilities. The patient’s

applications will then wait for the facility to accept it and then wait for the actual bed offer. The patient


Process time ALC facility type Available distributionsApplication preparation CCC None

Convalescent TriangularLTC NonePalliative NoneRehab None

Application Review CCC Beta,Chi-squared,Power function,Triangular,Uniform,Weibull

Convalescent TriangularLTC ExponentialPalliative NoneRehab None

Bed offer CCC NoneConvalescent Exponential,

Power function,Triangular

LTC Lognormal,Pearson 5,Pearson 6

Palliative NoneRehab None

Going home CCC NoneConvalescent Gamma,

Pearson 6,Weibull,Lognormal,Erlang

LTC Lognormal,Beta

Palliative NoneRehab Weibull

Dying in hospital CCC NoneConvalescent NonePalliative Lognormal,

Pearson 6,Pearson 5

Rehab Triangular,Rayleigh,Weibull,Power function

Table 4.7: Distributions with Kolmogorov-Smirnov test p-values above 0.05


Figure 4.4: Histogram of died in hospital queue times for each ALC facility type

Figure 4.5: Histogram of going home queue times for each ALC facility type


Figure 4.6: Process of patients travelling through the model

will also have properties representing when s/he may die in the hospital or when s/he will travel home.

Depending on which facility s/he gets admitted to first or if s/he reaches his/her queue time for going home

or dying it the hospital, s/he will go to the appropriate destination type. Each process time was chosen from

a distribution for that process time and that ALC facility type.

Distributions to go home and die in hospital queues are made based on each ALC facility type. Therefore,

it is assumed that there is a trend between these times within an ALC facility type, but this cannot be

extrapolated to all ALC patients.

4.3.1 Validation process

The model outputs are compared against validation values to ensure that the model closely represents the

actual ALC process at TGH’s General Surgery and GIM departments. The values to be validated against

are shown in Table 4.8.

To validate the model, results from various models with the same general flow were compared to the

validated data. Data distributions types, rejection rates, and randomness varied.

4.3.2 Models attempted to be validated

These test scenarios were done for one ALC facility type at a time in order to evaluate and understand the

model outputs. The following are done for CCC. The average ALC LOS per patients would be 30.81 days


Type of ALC facility ALC days Number of died in hospital ALCpatients

CCC 955 4Convalescent care 351 1LTC 4092 11Palliative care 1317 32Rehabilitation care 3601 23

Table 4.8: Values to be validated against for each type of ALC facility over two years for General Surgeryand GIM

Distribution type Average ALC LOS (days)Exponential 16.32Triangular 15.53Uniform 15.66Beta 17.46Weibull 16.44Lognormal 17.03Pearson 6 16.13Pearson 17.03

Table 4.9: CCC average ALC LOS model outputs when varying the application review distribution

for the actual system (955 days and 31 patients).

The outputs of the first model were an average of 15.93 days per patient and 30 patients, not equal to

the validation values. To overcome the lower average ALC LOS, parametric distributions were to be used,

as higher values could be captured from the distribution tails. It was only possible to create parametric

distributions for the application review time in Stat::Fit because of the low number of available process times.

Various application review time distributions that had a p-value above 0.05 from the Stat::Fit goodness of

fit test were modelled. The average ALC LOS model outputs are listed in Table 4.9.

Although varying the distribution type increased the average ALC LOS, the model outputs are still far

from the 30.81 day validation value.

A flaw was realized in the logic. In the model, a patient waits in a queue until s/he reaches his or her

going home or dying in hospital queue time or if s/he receives a bed offer. There are some high values for

bed offer process times, but because there are no dying in hospital or going home queue times longer than

this, the patient will always have another queue time before s/he can reach the long bed offer process times.

In reality, there will be patients who will not want or be able to go home and who are healthy enough to

not die while waiting. A certain percentage of patients will not reach his/her dying in hospital or going home

queue time and will wait for a bed. During a previous meeting with the CCAC Client Services Manager,

she mentioned that she dealt with approximately 20-25 percent of patients who were the more “difficult”

patients to discharge, who are patients who continually refuse to go home when appropriate or reject bed

offers from suitable ALC facilities. Not allowing 25 percent of patients to go home was incorporated into

the model, and this increased the average ALC LOS to 24.69 days for CCC. This methodology was carried

over to the other four ALC facility types. The results were inconsistent (Table 4.10).

It was decided to move focus onto palliative care since the results were 23 percent of the validation

average ALC LOS value. To represent the system more accurately, it was decided to use distributions for

each facility rather than each facility type. Therefore, if bed offer times tended to by higher for Facility A

than Facility B, then this would be represented in the system through individual process time distributions.

However, application preparation times were kept general to each ALC facility type.

Because there was not an appropriate parametric distribution for every process time for each ALC facility


ALC facility type Model output (days) Validation value (days)Convalescent 10.00 11.32LTC 17.85 41.76Palliative 1.38 5.93Rehabilitation 9.77 9.97

Table 4.10: Comparison of model and actual average ALC LOS values when not providing 25 percent ofpatients a died in hospital/home queue time

type, there would not be a parametric distribution for each ALC facility. Discrete distributions were used

again. Although there was an increase in the average LOS, the results were still not close to the expected

validation values.

The next attempt was to go back to the data sources and expand how much information was extracted

from it. Previously, if one of the two dates that determined a process time were unavailable, the data would

be omitted from the discrete distributions. However, all of the total ALC LOS values were known because

each entry had at least an ALC designation date and a discharge date. However, if the only other available

date was the application sent date, from the previous method, an application preparation time would be

extracted, but no other process times. The application review time and bed offer wait time both require

the accept/deny date. Therefore, the total ALC LOS would not be represented in the generated discrete

distributions. To overcome this issue, some assumptions were made when re-extracting process times from

the data. In the previous case, if only the application sent date was known, then it was assumed that the

application review time would be zero and the remainder of the LOS value was due to the bed offer time.

If only the ALC designation date and the discharged date were known, the application preparation and

application review times would be assumed to be zero. The total LOS time would be assumed to be the bed

offer wait time.

If any other process times can be formed, the time difference between the total ALC LOS and the process

time would be assumed to be in the bed offer wait time. If the bed offer wait time is known, the time would

be assumed in the preceding unknown process time.

Therefore, there are two sets of process times created from the combined database. The application

dataset is formed from all of the process times that were possible to create with the available dates. The

method just described that creates three process times for each patient entry will be called the patient

dataset.

The model was still not producing reliable outputs with the patient dataset. Therefore, all of the logic

was removed from the model, and only randomization was retained. Therefore, the patient would only

produce one application, and all of the application process times would be randomly chosen. The shortest

queue logic is removed. Then the factors described below were varied individually to find their effects on the

model outputs.

• Using the patient or application dataset

• Using rejection rates Perhaps, applications with low queue times remained in the system when not

intended to because these applications were actually supposed to be rejected. To determine rejection

rates, the total number of patients admitted to a facility was subtracted from the total number of

applicants to the facility and this calculated number was divided by the number of applicants to the

facility and then multiplied by 100. The rejection rate was applied when the patient was going from

the queue for waiting for an acceptance to the queue for waiting for a bed offer.

• Separating patients going home It is the first priority to send patients home with or without

services, if applicable. Generally, it is where a patient would like to be cared for and is more economical


Model Dataset Rejection rate Going home patientsModel 1 Patient No IntegratedModel 2 Patient Yes IntegratedModel 3 Application No IntegratedModel 4 Application Yes IntegratedModel 5 Application No SeparatedModel 6 Patient Yes SeparatedModel 7 Patient No Separated

Table 4.11: Model developed in palliative care for validation process

Figure 4.7: Percentage of error for average ALC LOS over two years compared to validation values

for the health care system. It also lowers the load on the waiting lists. The delays for going home may

be because of renovations, inadequate care resources, unavailability of family members, or time required

to arrange services. Therefore, varying the ALC discharge policies may not affect this pathway. The

patients who are going home will be separated right after entering the ALC system and would not

create other applications.

Table 4.11 outlines which of the preceding properties are used in each experimented model.

The percentage of error found for each facility’s average ALC LOS values over two years to the expected

validation value are reported in Figure 4.7. The base model only has randomization and not the shortest

queue logic (the shortest queue depicts where the patient goes after acute care).

An issue found with the rejection rate is that it is actually the non-acceptance rate. This rate is higher

than a rejection rate. This was because the non-acceptance rate would include not only patients who were

rejected but also patients who decided to go to another facility. For example, after including the rejection

rate in some instances, all of the items representing a patient would be deleted, and the patient would not

actually exit the system. This method was discarded, as there was no further information available from the

data in order to get an accurate rejection rate.


Figure 4.8: Percentage of error for ALC LOS of model outputs when randomizing each process time andassociating or disassociating all randomized process times

Overall, it was found that the model outputs were less than the expected ALC LOS values. This is most

likely because the system always uses the item with the shortest ALC LOS to represent the patient.

There are two issues that had to be resolved. The first is that there is too much randomization in the

model. This can be seen by the high variability of the base model in Figure 4.7. The second is that the

shortest queue does not always represent the patient’s preferences accurately.

To determine the reason for the high variability, all of the randomization and logic was removed from the

model. The results for randomizing each process time individually and then randomizing all three process

simultaneously are shown in Figure 4.8. The randomization of process times can either be associated or

unassociated. Therefore, the patient can either receive the same three process times a previous patient did,

or s/he will independently receive an application preparation, application review, and bed offer time from

possibly three different patients.

From Figure 4.8, much less variability can be seen with associating process times rather than disasso-

ciating them. Therefore, when adding the next area of randomization when patients choose where to send

their applications, it is added to the model with the three process times randomized and associated with

each other. In Figure 4.9, the results of incorporating the shortest queue logic are shown. Finally, the model

adds the died in hospital and the travelling home queues to the shortest queue logic.

From Figures 4.8 and 4.9, the randomization and the added shortest queue logic were main reasons for

the unvalidated values. There is insufficient information in order to generate reliable datasets to represent

how a patient behaves. The system has to be more deterministic and use as much of the available information

for individual patient preferences. The model should include the same patients from the dataset, and when

further choices are made beyond what is known for that specific patient, then the discrete distributions


Figure 4.9: Percentage of error for ALC LOS of model outputs when introducing the shortest queue logicand the died in hospital and going home pathways

should be used.

4.3.3 Description of validated model

The final model has the same patients for 2009 and 2010 enter the system rather than assuming a new

randomized set of patients. Therefore, the patient’s previous choices of facilities and queue times are known.

When the patient enters the ALC system, either the number of applications required to apply to will be

less than, equal to, or more than how many facilities the patient actually previously applied to. These three

scenarios are explained below.

Number of applications is less than previously applied to The applications will be chosen from

the subset of facilities previously applied to. If the patient was previously discharged to the facility, then the

ALC LOS (sum of the three process times) is known. If the patient previously applied but was discharged

elsewhere, the ALC LOS is not known but it is known that it is more than the previous ALC LOS. This

constraint is applied when choosing process times.

Number of applications is the number previously applied to The applications will be the set of

applications previously applied to. If the patient was previously discharged to the facility, then the ALC

LOS is known. If the patient previously applied but was discharged elsewhere, the ALC LOS is not known

but it is known that it is more than the previous ALC LOS. This constraint is applied when choosing process

times. However, the shortest ALC LOS application is where s/he was admitted to, so this will be where

s/he is discharged.

Number of applications is more than previously applied to The applications will be the appli-

cations applied to and the remainder will be chosen from the facility popularity distribution for the ALC


type. If the patient was previously discharged to the facility, then the ALC LOS is known. If the patient

previously applied to the facility but was discharged elsewhere, the ALC LOS is not known but it is known

that it is more than the previous ALC LOS. This constraint is applied when choosing process times. If the

patient did not previously apply to the facility, there is no known association between the facility and the

patient. The process times are determined from the general distribution for that ALC facility in the ALC

facility type.

Determining died in hospital queue time If a patient died during the ALC process, the patient’s

queue time for dying in hospital would be known. If s/he did not, then it is known that their dying in

hospital queue time would be more than their previous ALC LOS.

Determining going home queue time If a patient previously went home during the ALC process,

the patient’s going home queue time would be known. If s/he did not, then it is known that their going

home queue time would be more than their previous ALC LOS.

If there are no available process time that exceed the minimum constraints, it is assumed the process

times would be a maximum set value. The maximum set value is a value more than the maximum ALC

LOS previously experienced for that ALC facility type.

The bed capacities of facilities are represented by the size of the facility’s bed offer times. The bed offer

times are for TGH General Surgery and GIM patients. Therefore, if the bed offer time is low, then there is a

high turnover rate that allows TGH General Surgery and GIM patients to enter at a faster rate. If the bed

offer time is large, then there is a low turnover rate that makes it less favourable for TGH General Surgery

and GIM patients to enter that facility.

Short waiting list facilities were also incorporated. This was done by subtracting the surpassed time of all

patients in a facility queue from the expected original queue times of all patients in that facility’s waiting list.

The wait times are updated every 60 days, as this is how often CCAC updates their queues. These times are

used to determine whether the facility’s waiting list is considered to be long or short. The definition of a short

waiting list is currently undefined. The ideal short waiting list definition will be determined by modelling

the two previous UHN discharge policies for LTC and varying the short waiting list definition between ten

and 25 days to determine the definition that minimizes ALC days and number of died in hospital patients.

4.3.4 Determining number of model replications required

A certain number of replications of the model have to run to ensure the model outputs have reached steady

state. To determine when steady state had been reached, the model was run in trials sets of ten replications.

For each facility’s average ALC LOS and total number of admitted patients, Student’s t-tests were performed

to compare the averages of trial outputs of n×10 and (n-1)×10 replications to the average of the trial outputs

of (n-1)×10, (n-2)×10, and (n-3)×10 replications. If the p-value was less than 0.05, it would indicate that

there was no significant difference between the model outputs of the two sets of trials, with 95 percent

confidence. Therefore, the model outputs had reached steady state. If the p-value was more than 0.05, n

was increased until steady state was reached.

4.3.5 Scenarios modelled

The two key performance indicators (KPIs) analyzed are the number of ALC days and the number of died

in hospital patients over a one-year period.

Discharge policy scenarios were experimented by changing the fixed number of facilities patients can

apply to, the minimum number of facilities patients can apply to, and the number of facilities with short

waiting lists that can be applied to with varying the total number of applications. This was done for each


Type of discharge policy Number of applications in policyTotal number of applications 0A

1A2A3A4A5A

Minimum number of applications 0A1A2A3A4A5A

Number of facilities with a short waiting list 3A 0SWL3A 1SWL3A 2SWL3A 3SWL4A 0SWL4A 1SWL4A 2SWL4A 3SWL4A 4SWL5A 0SWL5A 1SWL5A 2SWL5A 3SWL5A 4SWL5A 5SWL

Table 4.12: All scenarios modelled (A = number of facilities, SWL = number of facilities with a short waitinglist)

ALC facility type: CCC, convalescent care, LTC, palliative, and rehabilitation. The list of scenarios modelled

is in Table 4.12.

Chapter 5

Results

LTC has the highest number of ALC days per patient. LTC results will be provided in this section. Results

for the other four ALC facility types can be found in the Appendix. Appendix B has CCC results, Appendix

C has convalescent care results, Appendix D has palliative care results, and Appendix E has rehabilitation

results. Appendices F, G, H, and I have pairwise comparison charts that will be referred to later in this

section.

Results in tables and figures will show 95 percent confidence intervals. In tables, the lower and upper

limits of the confidence intervals are shown in brackets. Figures show the intervals with error bars.

5.1 Varying the fixed number of facilities

The total fixed number of facilities required was varied between zero and five. The effects on the ALC system

over a one-year period are reported for the two KPIs. The summary for LTC is found in Table 5.1. Results

for the other ALC facility types are in the Appendix.

5.2 Varying the minimum number of facilities

The total minimum number of facilities required was varied between zero and five. This would be requiring

patients to apply to at least zero, one, two, three, four, or five facilities. The effects on the ALC system over

a one-year period are reported for the two KPIs in Table 5.2. Results for the other ALC facility types are

in the Appendix.

Pairwise comparison charts were made to compare between the scenarios of varying the fixed number of

facilities and minimum number of facilities. The difference of the KPI between the scenario of the row to

the scenario in the column with 95 percent confidence intervals are shown. The pairwise comparison chart

for the number of ALC days in LTC can be found in Table 5.3. The results with a significant difference are

Scenario ALC days Number of died in hospital patients0A 3576.18 (3501.47, 3651.68) 23.49 (23.23, 23.74)1A 2908.92 (2763.80, 3067.72) 15.01 (14.76, 15.25)2A 2331.59 (2128.58, 2552.40) 10.90 (10.67, 11.13)3A 1985.78 (1808.53, 2173.18) 7.22 (7.06, 7.37)4A 1455.56 (1295.11, 1627.59) 4.48 (4.33, 4.63)5A 1112.18 (963.71, 1274.38) 3.18 (3.04, 3.32)

Table 5.1: LTC results for varying the total fixed number of applications

28

Chapter 5. Results 29

Scenario ALC days Number of died in hospital patients0A 2049.41 (2029.09, 2069.87) 5.67 (5.61, 5.72)1A 2049.41 (2029.09, 2069.87) 5.67 (5.61, 5.72)2A 1857.60 (1776.01, 1941.34) 5.45 (5.39, 5.51)3A 1773.55 (1691.23, 1858.63) 5.25 (5.17, 5.32)4A 1401.51 (1272.58, 1539.49) 3.99 (3.85, 4.13)5A 1083.76 (958.33, 1220.54) 3.04 (2.90, 3.17)

Table 5.2: LTC results for varying the minimum number of applications

bolded. The pairwise comparison charts for the other ALC facility types and the number of died in hospital

LTC patients are in Appendix F.


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Figure 5.1: Number of LTC ALC days when varying the fixed and minimum number of facilities

Graphical results comparing varying a fixed number of applications, a minimum number of applications,

and the actual historical data are shown in Figure 5.1 and 5.2. Similar graphs for the other ALC facility

types can be found in the Appendix.

5.3 Defining a short waiting list

Before varying the minimum number of facilities required with a short waiting list, the definition of a short

waiting list must be determined. This was done by varying the definition between ten and 25 days with

UHN’s previous two discharge policies for LTC. These policies are to choose five facilities with at least three

having a short waiting list and to choose three facilities with at least two having a short waiting list. The

number of ALC days and the number of died in hospital patients were analyzed for these discharge policy

scenarios over a two-year period. The results are shown in Figure 5.3.

There are no significant changes in either of the two KPIs. However, with the policy of a total of five

applications, the number of ALC days is decreasing until a short waiting list definition of 16 days and then

begins to steady. With the policy with a total of three applications, the ALC days reaches a minimum range

between a short waiting list definition of 13 and 16 days. The number of died in hospital patients decreases

as the short waiting list definition increases.

Although there are no significant changes in the KPIs, based on the model outputs, to minimize the

number of ALC days and number of died in hospital patients, a short waiting list definition of 16 days is

chosen to model varying the number of short waiting lists facilities in new discharge policies.


Figure 5.2: Number of LTC died in hospital patients when varying the fixed and minimum number of facilities

Figure 5.3: The effects when varying the definition of a short waiting list for UHN’s previous two dischargepolicies are shown when updating wait lists every 60 days and daily. Figure 5.3 (left) shows the effects onthe number of ALC days for LTC patients, and Figure 5.3 (right) shows the effects on the number of diedin hospital patients over one-year.


Scenario ALC days Number of died in hospital patients3A 0SWL 1999.88 (1821.87, 2187.97) 7.46 (7.28, 7.64)3A 1SWL 2004.38 (1827.91, 2190.97) 7.47 (7.30, 7.63)3A 2SWL 2000.29 (1823.68, 2187.59) 7.76 (7.58, 7.94)3A 3SWL 1932.41 (1736.67, 2140.46) 7.77 (7.58, 7.95)4A 0SWL 1475.13 (1314.70, 1647.03) 4.65 (4.50, 4.80)4A 1SWL 1491.71 (1331.09, 1663.58) 4.65 (4.49, 4.80)4A 2SWL 1470.99 (1308.18, 1645.64) 4.64 (4.48, 4.80)4A 3SWL 1446.72 (1272.68, 1634.30) 4.76 (4.59, 4.93)4A 4SWL 1344.74 (1156.01, 1550.14) 4.84 (4.64, 5.04)5A 0SWL 1138.76 (987.59, 1303.91) 3.35 (3.20, 3.49)5A 1SWL 1138.76 (987.59, 1303.91) 3.35 (3.20, 3.49)5A 2SWL 1127.27 (975.30, 1293.52) 3.33 (3.19, 3.47)5A 3SWL 1093.41 (944.66, 1256.31) 3.31 (3.16, 3.455A 4SWL 1055.81 (908.98, 1216.24) 3.28 (3.13, 3.42)5A 5SWL 952.07 (805.73, 1113.13) 3.01 (2.86, 3.15)

Table 5.4: LTC results for varying the number of applications for facilities with short waiting lists (SWL)

5.4 Varying the minimum number of facilities with a short waiting

list

The minimum required number of facilities with a short waiting list is varied with a total of three, four, and

five applications. The number of facilities with short waiting lists is varied between zero and the maximum

number of applications in each situation.

A summary of the the effects of changing short waiting lists required for LTC is shown in Table 5.4 and

graphically in Figures 5.4 and 5.5. The summaries for the other ALC facility types can be found in the

Appendix. It should be noted that the waiting lists are currently not tracked by other ALC facility types,

but the situations are modelled to see what happens if they were tracked and used in discharge policies.

Pairwise comparison charts were created to demonstrate the differences when varying the number of short

waiting list facilities on the two KPIs and can be found in Appendix G.

5.5 Increasing the frequency of waiting list updates

CCAC updates waiting lists every 60 days, and this was reflected in the model. The effects of increasing the

frequency of updating the waiting lists to a daily basis is found on the two KPIs. Daily updates were chosen

as an extreme example to find the largest impact of changing the frequency of updating waiting lists. The

results are shown in Table 5.5 for LTC. Pairwise comparison charts comparing updating waiting lists daily

and every 60 days for each ALC facility type can be found in Appendix H.

5.6 Varying the facility popularity distribution

The facility popularity distribution was varied to determine if the KPI results previously found from the

model were dependent on facilities’ previous popularities. Facilities are now chosen based on the inverse of

the previous popularity distribution or chosen randomly.

The original popularity distribution is a histogram of the frequency of applications to each facility within

the ALC facility type. To create the inverse distribution, the inverse of the frequency to each ALC facility

is taken. The distribution of the inverse frequencies is then normalized. Lastly, each of the normalized


Figure 5.4: Number of ALC days for LTC when varying the required number of short waiting list (SWL)facilities

Figure 5.5: Number of died in hospital patients for LTC when varying the required number of short waitinglist (SWL) facilities


Scenario ALC days Number of died in hospital patients3A 0SWL 1982.63 (1806.91, 2168.25) 7.44 (7.26, 7.62)3A 1SWL 1986.29 (1812.28, 2170.05) 7.44 (7.27, 7.61)3A 2SWL 1960.44 (1773.76, 2159.06) 7.76 (7.58, 7.93)3A 3SWL 1806.65 (1606.75, 2021.73) 7.51 (7.29, 7.73)4A 0SWL 1486.97 (1326.20, 1659.36) 4.73 (4.60, 4.86)4A 1SWL 1486.90 (1326.53, 1658.80) 4.73 (4.60, 4.86)4A 2SWL 1486.26 (1324.58, 1659.67) 4.71 (4.57, 4.85)4A 3SWL 1442.06 (1265.43, 1633.10) 4.65 (4.46, 4.84)4A 4SWL 1316.50 (1135.41, 1514.44) 4.61 (4.42, 4.79)5A 0SWL 1159.93 (1011.67, 1321.35) 3.39 (3.25, 3.53)5A 1SWL 1159.89 (1011.65, 1321.30) 3.39 (3.25, 3.53)5A 2SWL 1157.00 (1008.75, 1318.48) 3.39 (3.25, 3.53)5A 3SWL 1141.62 (992.29, 1304.67) 3.36 (3.20, 3.51)5A 4SWL 1092.75 (941.45, 1258.37) 3.44 (3.30, 3.57)5A 5SWL 950.86 (804.19, 1112.25) 3.01 (2.85, 3.17)

Table 5.5: LTC results for varying the number of applications for facilities with short waiting lists whenupdating the waiting lists daily


Table 5.6: LTC results for varying the number of applications for facilities with short waiting lists with theinverse facility popularity distribution

frequencies are then multiplied by the total number of original applications. The random distribution has

an equal probability of applying to each facility.

The effects of changing patient facility selections to the inverse facility popularity distribution and to

random selections for LTC patients are shown in Table 5.6 and Table 5.7, respectively.

Pairwise comparison charts comparing using the actual, inverse, or random popularity distributions for

each ALC facility type can be found in Appendix J.

5.7 Varying the minimum number of facilities with a short waiting

lists with varying short waiting list definitions

To determine if varying the short waiting list definition has an effect on other discharge policies other than

UHN’s previous two, the discharge policies of a total of three, four, and five applications with varying the

number of short waiting lists facilities required was modelled with a short waiting list definition of ten and



Table 5.7: LTC results for varying the number of applications for facilities with short waiting lists whenselecting facilities randomly


Table 5.8: LTC results for varying the number of applications for facilities with a short waiting list definitionof ten days

25 days.

The results are shown for a short waiting list definition of ten days and 25 days in Table 5.8 and 5.9,

respectively.

Pairwise comparison charts comparing certain scenarios for the three short waiting list definitions for

each ALC facility type can be found in Appendix I.



Table 5.9: LTC results for varying the number of applications for facilities with a short waiting list definitionof 25 days

Chapter 6

Discussion

6.1 Trends for varying the number of applications and short wait-

ing list facilities

The significant trends from the outputs of the models will be discussed in the section. Short waiting lists

are currently not part of the UHN discharge policy for any ALC facility type, except for LTC. However, the

possibility of them being included were modelled, and the results are discussed.

6.1.1 CCC

There is a significant decrease in ALC days when applying to one extra application when either applying

to a minimum or fixed number of facilities with the exception of applying to a minimum of one application

instead of zero. This is because there were no previous CCC patients who did not apply to at least one

facility.

Applying to a minimum number of applications instead of a fixed number for zero, one, two, and three

applications significantly decreases the number of ALC days. Previously, 96.7 percent of patients applied to

three or fewer facilities (Figure A.3). Therefore, patients would mostly be applying to the same number of

applications with both policies for four or more applications.

By changing the policy to one extra fixed or minimum application, the number of died in hospital patients

significantly decreases. However, there is no significant difference with this KPI between requiring patients

to apply to a certain fixed number or minimum number of applications.

When varying the number of short waiting list facilities, with three facilities, there is a significant decrease

in ALC days when applying to all short waiting list facilities opposed to any fewer. With four and five

applications, there were never more than three short waiting list facilities at a time, so it was not possible

to model selecting four or five facilities with short waiting lists.

When applying to a total of five applications, there is a 255 percent decrease in ALC days from the actual

system, and by having the short waiting list policy, ALC days can decrease up to 261 percent. By applying

to four facilities, there is a 208 decrease in ALC days, and introducing a short waiting list policy does not add

any extra benefit. For three facilities, the same figures decrease by 109 percent and 117 percent. Introducing

a short waiting list policy does not have large impact on CCC ALC days.

Currently, CCC patients apply to 1.7 applications on average. If they are required to apply to five, the

number of died in hospital patients can decrease fourfold. There is no effect on number of died in hospital

patients when varying the number of short waiting list facilities.

38

Chapter 6. Discussion 39

6.1.2 Convalescent care

There is a significant decrease in ALC days when applying to one extra application with both a minimum

number and fixed number of applications, except when applying to a minimum of one facility instead of zero

facilities. This is because all convalescent care patients previously applied to at least one facility (Figure

A.6). There is also a significant decrease in ALC days when applying to a minimum number of facilities

versus a fixed number.

With the number of died in hospital patients, the same trend does not follow. The only change of policies

that decreases the number of died in hospital patients by at least one with 95 percent confidence is when

applying to at least one facility instead of applying to none.

The previous average number of applications was 2.64 for convalescent care. By applying to four facilities,

ALC days decrease by about 119 percent, and introducing short waiting lists does not further reduce ALC

days. By applying to five facilities, ALC days decrease by 153 percent, and with short waiting list policies,

ALC days can decrease by an extra 30 percent.

6.1.3 LTC

The effects of applying to a new facility significantly decreases the number of ALC days and the number of

died in hospital patients in one-year, whether the discharge policy is for a fixed number of applications or a

minimum number of applications. There is a significant decrease in ALC days and number of died in hospital

patients when applying to a minimum number of applications versus a fixed number of applications for one,

two, three, and four applications. The magnitude of the change decreases as the number of applications

increases in the discharge policy. When applying to a minimum of five applications versus exactly five

applications, there is a significant decrease in the number of ALC days, but not the number of died in

hospital patients.

In Figure 6.1, the number of short waiting list facilities a patient would apply to without having a shorting

waiting list policy is shown. Patients already independently apply to almost all short waiting list facilities.

However, the average number of facilities with long waiting lists actually applied to increases as the total

number of applications increases. Therefore, there is less of an impact with maximizing the number of short

waiting lists facilities when applying to three facilities versus five facilities.

The previous average number of applications was 2.74 for LTC. By applying to three facilities, ALC days

do not decrease by a notable amount. However, with three facilities all having short waiting lists, ALC days

can decrease by 212 percent. With four applications, ALC days can decrease by 139 percent, and with all

short waiting lists, ALC days decrease by an extra 13 percent. With five applications, ALC days decrease

by 180 percent, and short waiting lists increases this percentage to 215.

In Figure 6.2, the frequency of applications to facilities with various waiting list lengths is shown when

the waiting lists are updated every 60 days or daily. Approximately 65 percent of the popularity distribution

is for facilities with an average waiting list less than 16 days. There will be less of an impact of encouraging

patients to apply to a short waiting list facility until there is a stricter definition of a short waiting list.

Figure 6.2 also shows that by updating waiting lists daily instead of every 60 days, there is a lower frequency

of larger waiting lists (above 45 days).

For LTC, it would be beneficial to encourage patients to apply to as many facilities as possible. There

is a significant decrease in ALC days when applying to short waiting list facilities when applying to at least

four facilities, with the largest changes seen with having all facilities with short waiting lists.


Figure 6.1: Number of facilities with short waiting lists that are applied to without having a requirementfor a certain number of short waiting list facilities in the discharge policy for LTC

Figure 6.2: Frequency of applications to facilities of varying average waiting list sizes in LTC


6.1.4 Palliative

When changing the discharge policy to require one extra application, it decreases both KPIs when requiring

a minimum or fixed number of facilities. There is a significant decrease in the number of ALC days when

applying to a minimum number of facilities versus a fixed number. This trend is only true for the number of

died in hospital patients with zero, one, two, or three applications. Previously, 85.7 percent of palliative care

patients applied to three or fewer facilities (Figure A.12). Therefore, when requiring patients to apply to

more than three facilities, there is a small or no impact between having a fixed number or minimum number

of total facilities in the policy.

The previous average number of applications to palliative care facilities was 2.68. By applying to three

facilities, ALC days decrease to 119 percent, and if all have short waiting lists, ALC days decrease by

another 44 percent. Applying to four facilities decreases ALC days by 194 percent and another 53 percent

with all short waiting lists. ALC days decrease to 277 percent with five facilities and no short waiting list

requirements and to 334 percent with five short waiting list facilities.

With the number of died in hospital patients, by having four applications, the number of patients decreases

by 175 percent from the actual system and to 230 percent with all short waiting lists. Five facilities allows

the figure to decrease by 272 percent and another 78 percent with all short waiting lists.

6.1.5 Rehabilitation

When requiring one extra application in the discharge policy, it decreases both KPIs when applying to a

minimum and fixed number of facilities. There is a significant decrease in both KPIs when applying to a

minimum number of facilities versus a fixed number.

Previously, rehabilitation patients were applying to an average of 2.42 facilities. By applying to three

facilities, ALC days decrease by 146 percent and another 52 percent with all short waiting list facilities. With

four applications, ALC days decrease by approximately 200 percent from the actual ALC days and another

50 percent with all short waiting list facilities. With five facilities, ALC days decrease by 267 percent and

enforcing short waiting lists increases this figure by another 67 percent.

Large changes can be seen with the number of died in hospital patients. By applying to four applications,

there is a 307 decrease in died in hospital patients and this increases to 423 percent by having all short

waiting lists. With five applications, number of died in hospital patients decreases to 680 percent of the

actual figure. By having all five facilities with short waiting list facilities, the number of died in hospital

decreases by another 215 percent.

The larger magnitude of changes for rehabilitation is thought to be because there are many possible

facilities that patients can apply to but the popularity of facilities is not well distributed. By encouraging

patients to apply to other facilities with shorter waiting lists, patients will more quickly be able to leave the

acute care system. However, there is a limitation in the model that does not distinguish rehabilitation types

from each other, so the number of facilities that would appear to be available for the patient are inflated.

This is elaborated later in the discussion.

6.2 Overall trends

Overall trends are shown for varying the minimum and fixed total number of applications and the required

number of short waiting list facilities in Figures 6.3, 6.4, and 6.5. The first column for each ALC facility

type represents the actual number of ALC days.

For CCC, convalescent care, and palliative care, a reduced number of ALC days is seen with the new

discharge policies, but the largest decrease in ALC days is seen in LTC and rehabilitation. By requiring


Figure 6.3: Number of ALC days for all ALC facility types with varying the total fixed number of applications

Figure 6.4: Number of ALC days for all ALC facility types with varying the total minimum number ofapplications


Figure 6.5: Number of ALC days for all ALC facility types with varying the total number of applications(A) and number of required short waiting list (SWL) facilities

patients to apply to five applications, LTC ALC days reduce by about 900 and rehabilitation ALC days by

1200 a year. However, CCC, convalescent, and palliative care ALC days reduced by approximately 300, 80,

and 400 respectively.

When varying the number of short waiting list facilities, the same trends exist. LTC and rehabilitation

can reduce ALC days by approximately 1100 and 1300 days a year, respectively. CCC, convalescent, and

palliative can be reduced up to about 300, 80, and 500 days, respectively with the chosen experimented

discharge policies.

From these numbers just presented, it can be seen that the incorporation of short waiting lists does not

largely affect the number of ALC days. When there are many different available facilities, there is more of

an impact of short waiting lists. This is seen with LTC, palliative care, and rehabilitation.

6.3 Increasing the frequency of waiting list updates

The changes in ALC days for LTC when updating waiting lists daily instead of every 60 days with 95 percent

confidence intervals are outlined in Table 6.1.

For LTC, there is a significant decrease in ALC days when updating waiting lists daily and applying to

a total of three applications or to a total of four applications with three short waiting list facilities. When

there are more than three short waiting list facilities, there is no longer a significant decrease in ALC days

when updating waiting lists daily. When having a smaller total number of facilities, it is more critical where

the patient’s applications are being sent. If a patient is applying to a short waiting list when wait lists are

updated every 60 days, s/he may be applying to a facility that used to but no longer has a short waiting

list. The trend in Table 6.1 is inconsistent with the discharge policies 4A 4SWL, 5A 4SWL, and 5A 5SWL.

However, these results are either insignificant or have a small magnitude of significant change.


Scenario Difference in number of ALC days3A 2SWL -485.1 (-520.7, -449.5)3A 3SWL -474.8 (-517.1, -432.5)4A 3SWL -105.7 (-138.0, -73.8)4A 4SWL -19.1 (-51.2, 12.9)5A 4SWL 38.7 (15.6, 61.7)5A 5SWL -23.2 (-48.1, 1.8)

Table 6.1: Number of LTC ALC days when updating short waiting lists daily minus number of ALC dayswhen updating short waiting lists every 60 days

For CCC and convalescent care, there are several scenarios where an insufficient number of short waiting

list facilities are available when updating the lists daily. For CCC, there is reduction of ALC days when

updating lists daily only when applying to three applications with all of them having short waiting lists.

There is an average reduction of approximately 30 days annually. For convalescent care, ALC days can

significantly decrease up to 30 days annually. There are no significant reductions in number of died in

hospital patients with these two types of care.

For palliative care, there is actually an increase in ALC days when updating lists daily. However, the

maximum significant increase is 10 days a year. The changes in update frequency do not have a large change

in the number of died in hospital patients.

With rehabilitation care facilities, it is not possible to apply to all five short waiting list facilities when

updating the lists daily. However, with the other scenarios, reduction in ALC days can go up to 20 days

a year. There is not a consistent significant reduction in the number of died in hospital patients, and the

magnitudes of the reductions are not high.

Overall, increasing the waiting list update frequency does not have a large impact on the system for

CCC, rehabilitation, convalescent and palliative care. For LTC, the impact of updating waiting lists more

frequently when a small number of short waiting list facilities is required is large. However, it is unknown if

CCAC can manage this increased frequency.

6.4 Varying the facility popularity distributions

Varying facility popularity distributions were attempted in order to determine if the model results were

affected by how patients were previously selecting facilities.

For LTC, the two KPIs were analyzed for a total of three, four, and five applications with either zero short

waiting list facilities or all short waiting list facilities with three facility popularity distribution types: the

original facility popularity distribution, the inverse popularity distribution, and randomly choosing facilities.

The change of KPIs for LTC are summarized with 95 percent confidence intervals in Table 6.2.

There is a significant increase in the number of ALC days and the number of died in hospital patients

when using either the inverse facility popularity distribution or selecting the facilities randomly with a larger

increase using the inverse distribution.

When using the inverse facility popularity distribution, there is a significant decrease in ALC days when

applying to one extra application. When applying to a total of four applications, there is a significant

decrease in ALC facilities when applying to all short waiting list facilities. When applying to a total of five

applications, there is a significant decrease in ALC days when changing the discharge policy to apply to one

extra short waiting list facility after applying to at least one short waiting list facility.

When selecting facilities randomly, for every extra application, there is a significant decrease in ALC

days. When changing the policy from having a total of three or four applications and requiring zero facilities


Scenario Difference in number of ALC days Difference in number of died inhospital patients

3A 3SWL I 315.8 (274.5, 357.0) 1.2 (0.9, 1.4)4A 0SWL I 431.4 (401.5, 461.3) 1.6 (1.4, 1.8)4A 4SWL I 566.3 (533.7, 598.9) 2.3 (2.0, 2.6)5A 0SWL I 598.8 (567.4, 630.2) 2.0 (1.8, 2.2)5A 5SWL I 690.0 (653.2, 726.9) 3.1 (2.9, 3.4)3A 3SWL R 175.8 (132.1, 219.5) 0.7 (0.4, 0.9)4A 0SWL R 262.4 (231.5, 293.3) 0.8 (0.6, 1.0)4A 4SWL R 329.5 (291.9, 367.1) 1.4 (1.2, 1.7)5A 0SWL R 344.7 (310.4, 379.0) 1.0 (0.9, 1.3)5A 5SWL R 381.3 (350.5, 412.1) 1.4 (1.2, 1.6)

Table 6.2: Difference of KPIs annually when either using the inverse facility popularity distribution or arandom distribution instead of the original facility popularity distribution while varying the discharge policyfor the total number of applications with all or none having short waiting lists (I = inverse, R = random)

with a short waiting list to any positive number of short waiting list facilities, there is a significant decrease

in the number of ALC days. With a discharge policy of a total of five applications and two short waiting list

facilities, there is a significant decrease in ALC days when applying to any more short waiting list facilities.

However, none of the average decreases in ALC days have a magnitude of more than 100 days a year.

For LTC, independent of how patients select facilities, one extra application and maximizing the number

of short waiting list facilities will decrease ALC days. However, the way that patients currently select facilities

produces the least amount of ALC days.

For CCC and rehabilitation, there is an increase in ALC days and died in hospital patients when using

the inverse or a random facility popularity distribution. For CCC, using the inverse distribution increases

ALC days up to 120 days annually and 100 days for the random distribution. The number of died in hospital

patients never significantly increases by at least one patient. For rehabilitation, ALC days when using the

inverse and random distribution can increase up to 615 and 440 days, respectively. The average increase in

number of died in hospital patients can go up to eight patients (inverse) and five patients (random) annually.

For convalescent and palliative care, using the inverse and random facility popularity distribution reduces

the number of ALC days and number of died in hospital patients. For convalescent care, the number of ALC

days can be reduced up to 40 days annually, and there is not a large reduction in number of died in hospital

patients. The average reduction in ALC days for palliative care can go up to 130 days with the inverse

distribution and 60 days for the random distribution. The average reduction in the number of died in

hospital patients can be up to four patients (inverse) and two patients (random) annually.

The impact of varying the facility popularity distribution is largest for LTC and rehabilitation. The

method of choosing LTC is already affected by short waiting list policies, so if patients choose facilities by

the inverse facility popularity distribution, they may just be choosing the long waiting list facilities. For

rehabilitation, patients may already be applying to the shorter waiting time facilities as well.

For CCC and convalescent care, there is generally a reduction in ALC days when applying to one extra

application but not when applying to more short waiting list facilities. For palliative and rehabilitation care,

there is a reduction in ALC days when applying to an extra application and an extra short waiting list

facility.


6.5 Varying the definition of a short waiting list and the number

of short waiting list facilities

The definition of a short waiting list was varied between 10, 16, and 25 days with the scenarios: 3A 3SWL,

4A 4SWL, and 5A 5SWL.

For CCC, having more than three short waiting list facilities was not possible.

For convalescent care, having a smaller definition of a short waiting list reduces ALC days (maximum of

16 days annually) and does not have a large change on the number of died in hospital patients.

For LTC, the average change of ALC days ranges from decreasing by 31.5 (95% 4.2, 58.8) days (changing

to a 10 day definition with scenario 4A 4SWL) to increasing by 34.2 (95% 10.65, 57.75) days (changing

to a 25 day definition with scenario 5A 5SWL). The number of died in hospital patients can reduce up to

two patients annually (changing to 10 day definition with 5A 5SWL) by using a smaller short waiting list

definition.

By using a 25 day short waiting list definition in palliative care, ALC days can increase up to 11 days

and has no effect on the number of died in hospital patients. Lowering the definition to 10 days will not

affect ALC days and has inconsistent effects on the number of died in hospital patients.

For rehabilitation, there is a significant increase in ALC days of ten days when using a 25 day short

waiting list definition only when applying to three applications. There are no large changes in the number

of died in hospital patients.

Between all ALC facility types, generally, changing the definition to ten days will improve the two KPIs

or keep them the same. However, the magnitude of the change is smaller than requiring more facilities to

be applied to, having facilities with short waiting list, and varying the popularity of facilities.

6.6 Data recording improvements

There are several assumptions that were required when compiling data between the three sources of data

because of mismatched or missing information summarized in the Methods section. The most probable

scenario was assumed when not enough information was available. This makes the data not as reliable, and

the unreliability may be reflected in the model results.

To remove the assumptions from the data, the following changes in the SWDB are recommended.

• Adding patient preferences It can then be modelled properly which of all applied facilities a

patient would have picked if s/he could only pick one. Also, if a patient had to pick a new facility,

the distribution would include preferences on top of general popularity of facilities, more accurately

reflecting patients’ choices.

• Adding facility rejection rates It would be beneficial to know how often a facility rejects a patient.

In the model, rejections are represented by very long waits that would never be reached.

• Adding patient rejection rates The model does not have any patient rejection rates incorporated.

Therefore, there may be a facility that patients are encouraged to apply to, but once they receive the

offer, they decide to reject the facility.

To improve future data quality, it is encouraged that the SWDB be kept up-to-date, as this is the most

reliable source for ALC information between the three sources. It is recommended that social workers be

provided access to the EPR for ALC designation dates and discharge dates, as they are the most involved in

the ALC discharge process among the inter-professional care team. Signifiant reduced discharge rates have

been found on days that social workers commonly take off (Galati et al., 2011; Wong et al., 2010).


Type of ALC facility SubtypesCCC Low Tolerance Long Duration (LTLD)

Non Low Tolerance Low DurationHome Home with CCAC Services

Home with Community ServicesHome without Services

Palliative Palliative hospital placementResidential hospice care

Rehabilitation CardiacGeriatricLow Tolerance Long Duration (LTLD)Musculoskeletal (MSK)Neurological

Table 6.3: Types of care within main ALC facility types (Cancer Care Ontario, 2010)

There is also a high amount of variability with randomizing the dataset demonstrated in the validation

process. This may be contributed to the small dataset. Because of the late start of the RM&R and the

incorporation of ALC data in the EPR, it was chosen to restrict data collection from entries after its intro-

duction. The RM&R and EPR did not provide much additional information, so it would be recommended

for similar studies to look at a dataset of a larger duration from just the SWDB.

6.7 Limitations of model outputs

It is assumed that a patient can go to any facility in his/her facility type (CCC, convalescent, LTC, palliative,

and rehabilitation). Additional patterns of patient flow may have been found by separating the facilities into

the categories described in Table 6.3. However, there were not enough entries or patient information to go

into this level of detail. Additionally, patients may be limited in the number of facilities they can apply to

based on their specific health needs. However, this data was not available for all patients. The frequency of

available characteristics is described in Table 4.3. If this data was available, the number of ALC days would

most likely increase, as the applications would not be as evenly distributed among all the ALC facilities.

This model assumed that patients will take their first bed offers. If this does not occur, the number of

ALC days would be underestimated in the system.

It was found that some patients would transfer internally within TGH but still remain an ALC patient.

Therefore, they would travel from GIM to department X. These further details could only be found when

discussing case to case with the Discharge Planning Office. Because this was unrealistic, it had to be assumed

that these scenarios were insignificant when calculating the KPIs.

In the developed model, the died in hospital queue time is assumed to be a time from the died in hospital

distribution. The distribution only includes values from patients who did die in TGH from General Surgery

or GIM between 2009 and 2010, and the probability distribution has no information about the patients who

ended up going to an ALC facility or going home. Therefore, the patients may have a lower life expectancy

than in reality. The Kaplan-Meier survival curve is a method that may have overcome this. The survival

curves have a survival rate that decreases with increasing time (Goel et al., 2010). The steepness of the

curve in the ALC system could be an indicator of the health state of the patient type (Utley et al., 2000).

The Kaplan-Meier survival curve is able to censor patients as they go to an ALC facility or home. Therefore,

when a patient exits the ALC system, s/he decreases the survival rate if s/he dies, or s/he will decrease the

denominator of patients the curve is analyzing from if s/he goes to an ALC facility or home (Goel et al.,

2010). The incorporation of the Kaplin-Meier survival curve would no longer give the patients a died in


hospital queue time. Instead, everyday, for each patient, the model would determine if the patient will die

or stay in his/her current queue based on the survival rate of that day s/he is in the ALC system.

Varying discharge rates between days of the week have not been taken into account. Significant variation

between weekends, holidays, and regular weekdays exist (Wong et al., 2009). Therefore, if a patient was

discharged before on a Monday, and their ALC LOS decreases by two in the simulation, s/he may not be able

to be admitted to a certain LTC facility on that day. Similarly, if a patient was previously discharged on a

weekend, and the simulation allows them to be discharged on a weekday, the possible reduced discharge time

is not incorporated in the results. It is assumed that balancing these two scenarios will allow the varying

discharge rates to be insignificant in the model outputs.

However, these assumptions exist in all simulated discharge policy scenarios. Therefore, the policies can

still be compared against each other.

6.7.1 Applying findings in the real system

According to the Ontario legislation, patients are only obligated to pick one facility and can decline any

facilities that they do not want. The UHN discharge policy and the simulated policies promote patients to

apply to more facilities in order to improve the efficiency of the system. However, it is the patient’s right

to pick the facility that s/he prefers. This underestimates the model output’s ALC days. However, this

limitation exists in all scenarios, so the scenarios may still be comparable against each other.

All of the discharge policies experimented are best case scenarios if the discharge policies are followed

by every TGH General Surgery and GIM patient. In practice, the policies will not always be followed. The

patient may only want to apply to facilities close to his/her home, there may not be enough appropriate

facilities for the patient, and sometimes in practice, policies are just not followed. Therefore, in reality, for

each of the experimented policies, the number of ALC days will be higher than what is found in the model.

The results better represent changes of practice rather than changes of policy.

CCAC indicates that if a patient has a first, second, and third choice, and s/he gets admitted and

discharged to a facility other than his/her first, s/he may go to this facility and keep his/her application

for his/her preference open. The Discharge Planning Office is unsure if this is actually followed by CCAC,

as CCAC’s attention may be emphasized on acute care discharges. This study’s results would be of higher

significance if this option is available since patients can still eventually get into their first choice even if

initially, they are discharged to another facility.

As for the economic impact, OHIP pays $225 for each day for each patient in a semi- private or ward bed.

From this model, in LTC, if all patients apply to four beds instead of three, it will save the MOHLTC an

average of $111,240 a year. If all patients apply to five instead of three, it will save the MOHLTC an average

of $188,843 per year. This is only for TGH General Surgery and GIM. Thomas et al. (2005) found that for

University of Alabama’s Birmingham Trauma Center, the annual cost of delayed patients is $715,403 with

an average delay of six days.

The model does not take into account of any future fluctuations in ALC patient designation rates or

facility popularities. This is based on an ALC patient population leaving a teaching acute care facility.

Some of the patient behaviour may not be similar to other hospitals.

6.8 Other methods to improve ALC process

This study explores ways to change the ALC system without changing the ALC system infrastructure

(number of beds, health care human resources etc.) but only changing acute care discharge policies. This is

not the only solution that is needed to completely reduce the number of ALC days to zero.


Another method to improve the ALC system is to remove institutional layers. As suggested by the

Discharge Planning Office, some of the delays in the application process are because it takes time for a LTC

facility to receive an application because CCAC reviews it first. For St. Hilda’s facility, in 2009 it was not

regulated by CCAC, but in 2010, when it did enter its legislation, the number of ALC days for patients going

to St. Hilda’s increased.

However, CCAC feels that by introducing them in the process even before the ALC designation, they

will be able to accelerate the application process.

The Waiting at Home program was created to encourage patients to travel home if they are willing and

able to with services. This reduces the load on the acute care side as well as the ALC facilities. Additionally,

patients have the opportunity to receive care in their own home. Some of the patients who are in the Waiting

at Home program are waiting for a bed offer, and others remain at home if they find that the services are

adequate for their needs.

6.9 Recommendations for policy changes

It is recommended that social workers try to maximize the number of applications their patients are applying

to. There are also reductions in the number of ALC days found when maximizing the number of short waiting

list facilities. However, social workers should prioritize increasing the number of total facilities as this has

a larger reduction in the number of ALC days and number of died in hospital patients than altering the

number of short waiting list facilities.

These quantitative effects are for TGH General Surgery and GIM. However, it is believed that the

trends can be extrapolated to other facilities. The behaviours of patients are assumed to be generalizable

for other CCC, convalescent, LTC, palliative, or rehabilitation patients, not just TGH General Surgery or

GIM patients. The results for the specific number of ALC days or died in hospital patients will not be

generalizable, but the comparison between discharge policies can be. Therefore, it is still recommended to

maximize the number of facilities patients are applying to and also to increase the number of short waiting

list facilities.

Chapter 7

Significance and Conclusions

Through modification of discharge policies in a simulation study, the effects of systemic changes can be

measured by total ALC days and number of died in hospital patients. Exploring and analyzing model

variations showed that it is important to maximize the number of applications that patients apply to,

regardless of what type of care s/he is applying to in order to reduce the number of ALC days and number of

died in hospital patients for the system. It is also beneficial to examine if the facilities patients are applying

to have long or short waiting lists.

This conclusion is based on the available ALC data. This data was not consistently reliable and limited

in how it depicted patients’ behaviour. There is a need to improve the quality and reliability of ALC data.

Every LHIN has reducing ALC days on their 2010-2013 IHSP list of priorities. In addition, the Toronto

Central LHIN and many other LHINs intend to reduce ALC days by improving discharge planning. Deter-

mining if changing discharge policies actually decreases ALC days is valuable for TGH’s General Surgery

department, in addition to other departments and other institutions.

50

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Appendix A

Popularity distributions and patient

facility discharge histograms

A.1 CCC data

Figure A.1: Histogram of applications and admissions to CCC facilities

55

Appendix A. Popularity distributions and patient facility discharge histograms 56

Figure A.2: Histogram of CCC application preparation, application review, and bed offer queue times

Figure A.3: Histogram of the total number of CCC facilities applied to by a patient


A.2 Convalescent data

Figure A.4: Histogram of applications and admissions to convalescent care facilities

Figure A.5: Histogram of convalescent application preparation, application review, and bed offer queue times


Figure A.6: Histogram of the total number of convalescent care facilities applied to by a patient

A.3 LTC data

Figure A.7: Histogram of applications and admissions to LTC facilities


Figure A.8: Histogram of LTC application preparation, application review, and bed offer queue times

Figure A.9: Histogram of the total number of LTC facilities applied to by a patient


A.4 Palliative data

Figure A.10: Histogram of applications and admissions to palliative care facilities

Figure A.11: Histogram of palliative application preparation, application review, and bed offer queue times


Figure A.12: Histogram of the total number of palliative care facilities applied to by a patient

A.5 Rehabilitation data

Figure A.13: Histogram of applications and admissions to rehabilitation facilities


Figure A.14: Histogram of rehabilitation application preparation, application review, and bed offer queue

times

Figure A.15: Histogram of the total number of rehabilitation facilities applied to by a patient

Appendix B

CCC Results

Scenario ALC days Number of died in hospital patients

0 A 601.18 (568.86, 634.38) 9.29 (9.06, 9.52)

1 A 487.74 (401.49, 580.97) 2.36 (2.28, 2.43)

2 A 463.82 (372.89, 563.02) 1.72 (1.66, 1.77)

3 A 436.34 (376.52, 500.18) 1.24 (1.19, 1.29)

4 A 230.04 (189.45, 274.61) 0.72 (0.66, 0.77)

5 A 187.29 (163.24, 213.95) 0.46 (0.41, 0.51)

Table B.1: CCC results for varying fixed number of applications


0 A 477.50 (477.50, 477.50) 2.00 (2.00, 2.00)

1 A 477.50 (477.50, 477.50) 2.00 (2.00, 2.00)

2 A 478.31 (450.95, 506.64) 1.64 (1.59, 1.68)

3 A 431.09 (389.63, 474.88) 1.18 (1.12, 1.23)

4 A 236.42 (201.99, 273.95) 0.73 (0.67, 0.79)

5 A 187.29 (163.24, 213.95) 0.46 (0.41, 0.51)

Table B.2: CCC results for varying the minimum number of applications

63

Appendix B. CCC Results 64

Figure B.1: Number of ALC days for CCC when varying the fixed and minimum number of facilities

Figure B.2: Number of died in hospital patients for CCC when varying the fixed and minimum number of

facilities



3A 0SWL 436.34 (376.52, 500.18) 1.24 (1.19, 1.29)

3A 1SWL 437.39 (376.65, 502.27) 1.24 (1.19, 1.29)

3A 2SWL 431.64 (372.19, 495.12) 1.24 (1.19, 1.29)

3A 3SWL 406.83 (341.06, 478.41) 1.25 (1.16, 1.34)

4A 0SWL 230.04 (189.45, 274.61) 0.72 (0.66, 0.77)

4A 1SWL 230.14 (189.41, 274.89) 0.72 (0.66, 0.77)

4A 2SWL 236.10 (193.81, 282.46) 0.76 (0.70, 0.82)

4A 3SWL 236.55 (194.94, 282.24) 0.82 (0.75, 0.89)

4A 4SWL Not enough SWL facilities Not enough SWL facilities

5A 0SWL 187.29 (163.24, 213.95) 0.46 (0.41, 0.51)

5A 1SWL 187.46 (163.34, 214.19) 0.46 (0.41, 0.51)

5A 2SWL 184.74 (160.98, 211.06) 0.45 (0.40, 0.50)

5A 3SWL 182.65 (157.52, 210.50) 0.42 (0.37, 0.47)



Table B.3: CCC results for varying the number of applications for facilities with short waiting lists

Figure B.3: Number of ALC days for CCC when varying the required number of SWL facilities


Figure B.4: Number of died in hospital patients for CCC when varying the required number of SWL facilities

Appendix C

Convalescent results


0 A 288.08 (279.99, 296.26) 4.07 (3.96, 4.18)

1 A 217.32 (194.17, 242.44) 2.36 (2.28, 2.43)

2 A 202.21 (180.51, 225.32) 0.82 (0.75, 0.88)

3 A 184.14 (168.50, 200.50) 0.57 (0.54, 0.60)

4 A 148.34 (128.98, 169.25) 0.50 (0.50, 0.50)

5 A 95.43 (78.66, 114.25) 0.43 (0.40, 0.46)

Table C.1: Convalescent care results for varying fixed number of applications


0 A 175.50 (175.50, 175.50) 0.50 (0.50, 0.50)

1 A 175.50 (175.50, 175.50) 0.50 (0.50, 0.50)

2 A 174.42 (169.33, 179.60) 0.50 (0.50, 0.50)

3 A 171.65 (163.74, 179.79) 0.50 (0.50, 0.50)

4 A 138.09 (124.37, 152.51) 0.50 (0.50, 0.50)

5 A 111.74 (96.37, 128.33) 0.39 (0.35, 0.43)

Table C.2: Convalescent care results for varying the minimum number of applications

67

Appendix C. Convalescent results 68

Figure C.1: Number of ALC days for convalescent care when varying the fixed and minimum number of

facilities

Figure C.2: Number of died in hospital patients for convalescent care when varying the fixed and minimum

number of facilities



3A 0SWL 184.03 (168.34, 200.46) 0.58 (0.54, 0.61)

3A 1SWL 183.71 (168.34, 199.81) 0.57 (0.54, 0.60)

3A 2SWL 181.13 (165.78, 197.19) 0.57 (0.54, 0.60)

3A 3SWL 185.45 (169.70, 201.82) 0.59 (0.55, 0.63)

4A 0SWL 147.34 (128.66, 167.40) 0.51 (0.50, 0.51)

4A 1SWL 148.18 (128.90, 168.99) 0.50 (0.50, 0.50)

4A 2SWL 145.87 (126.99, 166.20) 0.50 (0.50, 0.50)

4A 3SWL 143.77 (125.00, 164.02) 0.50 (0.50, 0.50)

4A 4SWL 147.64 (129.07, 167.54) 0.51 (0.50, 0.51)

5A 0SWL 114.56 (96.40, 134.65) 0.38 (0.34, 0.42)

5A 1SWL 113.70 (95.75, 133.56) 0.38 (0.34, 0.42)

5A 2SWL 111.69 (94.14, 131.12) 0.39 (0.35, 0.43)

5A 3SWL 110.71 (93.66, 129.49) 0.39 (0.35, 0.43)

5A 4SWL 110.07 (91.20, 131.04) 0.43 (0.40, 0.46)

5A 5SWL 95.43 (78.66, 114.25) 0.43 (0.40, 0.46)

Table C.3: Convalescent care results for varying the number of applications for facilities with short waiting

lists

Figure C.3: Number of ALC days for convalescent care when varying the required number of SWL facilities


Figure C.4: Number of died in hospital patients for convalescent care when varying the required number of

SWL facilities

Appendix D

Palliative results


0 A 1206.42 (1176.76, 1236.43) 43.52 (43.10, 43.93)

1 A 852.13 (775.10, 934.91) 25.47 (25.06, 25.88)

2 A 678.27 (625.16, 734.55) 18.47 (18.22, 18.71)

3 A 555.27 (519.48, 592.99) 14.21 (14.05, 14.36)

4 A 245.88 (216.61, 277.43) 9.11 (8.91, 9.31)

5 A 245.88 (216.61, 277.43) 9.11 (8.91, 9.31)

Table D.1: Palliative results for varying fixed number of applications


0 A 658.50 (658.50, 658.50) 16.00 (16.00, 16.00)

1 A 656.98 (651.50, 662.49) 16.00 (16.00, 16.00)

2 A 610.35 (592.52, 628.67) 15.21 (15.13, 15.29)

3 A 541.12 (517.31, 565.84) 13.88 (13.75, 14.00)

4 A 332.44 (303.54, 362.88) 9.05 (8.84, 9.26)

5 A 240.33 (218.36, 263.51) 5.93 (5.73, 6.12)

Table D.2: Palliative results for varying the minimum number of applications

71

Appendix D. Palliative results 72

Figure D.1: Number of ALC days for palliative care when varying the fixed and minimum number of facilities

Figure D.2: Number of died in hospital patients for palliative care when varying the fixed and minimum




3A 0SWL 555.27 (519.48, 592.99) 14.21 (14.05, 14.36)

3A 1SWL 542.41 (503.03, 584.13) 13.96 (13.78, 14.13)

3A 2SWL 483.91 (439.39, 531.07) 13.23 (13.01, 13.45)

3A 3SWL 405.07 (362.98, 449.99) 11.82 (11.58, 12.06)

4A 0SWL 340.00 (306.39, 375.61) 9.11 (8.91, 9.31)

4A 1SWL 351.36 (315.40, 389.59) 9.16 (8.95, 9.36)

4A 2SWL 346.37 (308.50, 386.67) 9.17 (8.96, 9.38)

4A 3SWL 309.01 (272.19, 348.30) 8.61 (8.37, 8.84)

4A 4SWL 266.67 (233.91, 302.01) 6.97 (6.71, 7.23)

5A 0SWL 245.88 (216.61, 277.43) 5.87 (5.66, 6.08)

5A 1SWL 247.21 (218.46, 278.11) 5.98 (5.78, 6.17)

5A 2SWL 250.25 (221.40, 281.12) 6.16 (5.94, 6.37)

5A 3SWL 244.56 (214.06, 277.40) 5.65 (5.43, 5.87)

5A 4SWL 227.54 (197.09, 260.45) 5.50 (5.29, 5.71)

5A 5SWL 196.92 (173.10, 222.70) 4.57 (4.38, 4.75)

Table D.3: Palliative results for varying the number of applications for facilities with short waiting lists

Figure D.3: Number of ALC days for palliative care when varying the required number of SWL facilities


Figure D.4: Number of died in hospital patients for palliative care when varying the required number of

SWL facilities

Appendix E

Rehabilitation results


0 A 3190.94 (3134.34, 3248.06) 59.04 (58.26, 59.81)

1 A 2193.82 (2102.43, 2288.46) 24.28 (23.83, 24.72)

2 A 1572.51 (1487.59, 1661.21) 11.20 (10.85, 11.54)

3 A 1226.63 (1162.15, 1294.01) 6.63 (6.45, 6.81)

4 A 874.86 (821.20, 930.68) 3.75 (3.61, 3.88)

5 A 613.91 (579.22, 650.03) 1.69 (1.56, 1.82)

Table E.1: Rehabilitation results for varying fixed number of applications


0 A 1800.50 (1800.50, 1800.50) 11.50 (11.50, 11.50)

1 A 1800.09 (1796.90, 1803.29) 11.50 (11.50, 11.50)

2 A 1416.62 (1379.51, 1454.55) 6.43 (6.30, 6.56)

3 A 1182.01 (1145.56, 1219.32) 4.98 (4.89, 5.06)

4 A 860.81 (824.94, 897.68) 3.24 (3.15, 3.32)

5 A 609.60 (578.33, 642.00) 1.47 (1.36, 1.57)

Table E.2: Rehabilitation results for varying the minimum number of applications

75

Appendix E. Rehabilitation results 76

Figure E.1: Number of ALC days for rehabilitation care when varying the fixed and minimum number of

facilities

Figure E.2: Number of died in hospital patients for rehabilitation care when varying the fixed and minimum




Table E.3: Rehabilitation results for varying the number of applications for facilities with short waiting lists

Figure E.3: Number of ALC days for rehabilitation care when varying the required number of SWL facilities


Figure E.4: Number of died in hospital patients for rehabilitation care when varying the required number of

SWL facilities

Appendix F

Pairwise comparison charts - varying

the total number of applications

79

Appendix F. Pairwise comparison charts - varying the total number of applications 80

0A

1A

2A

3A

4A

5A

Orig

inal

Min

1A

Min

2A

Min

3A

Min

4A

Min

5A

0A

0(0,0)

48.1

(40.4

,55.8

)

97.9

(91.2

,104.6

)164.8

(159.6

,170.1

)346.2

(334.9

,357.5

)398.3

(390.2

,406.4

)113.4

(110.5

,116.3

)113.4

(110.5

,116.3

)123.6

(120.5

,126.7

)172.5

(167.7

,177.4

)347

(335.8

,358.2

)398.3

(390.2

,406.4

)

1A

–0

(0,0)

49.8

(42.2

,57.4

)116.7

(107.8

,125.7

)298.1

(283.6

,312.7

)350.2

(339.7

,360.7

)65.3

(58,72.7

)65.3

(58,72.7

)75.5

(68,83)

124.4

(115.7

,133.1

)298.9

(284.7

,313.2

)350.2

(339.7

,360.7

)2A

––

0(0,0)

66.9

(59.4

,74.5

)248.3

(235,

261.6

)300.4

(290.9

,309.9

)15.6

(9.6

,21.5

)15.6

(9.6

,21.5

)25.7

(19.7

,31.7

)74.7

(66.9

,82.4

)249.1

(236,

262.3

)300.4

(290.9

,309.9

)3A

––

–0

(0,0)

181.4

(169.3

,193.5

)233.5

(224.3

,242.7

)-51.4

(-55.9

,-46.8

)-51.4

(-55.9

,-46.8

)-41.2

(-45.8

,-36.7

)7.7

(2.2

,13.2

)182.2

(170.4

,194)

233.5

(224.3

,242.7

)4A

––

––

0(0,0)

52.1

(39.9

,64.3

)-232.8

(-244.2

,-221.4

)-232.8

(-244.2

,-221.4

)-222.6

(-234,

-211.3

)-173.7

(-185.2

,-162.1

)0.8

(-2

.3,3.9

)52.1

(39.9

,64.3

)

5A

––

––

–0

(0,0)

-284.9

(-292.7

,-277.1

)-284.9

(-292.7

,-277.1

)-274.7

(-282.6

,-266.9

)-225.8

(-234.7

,-216.9

)-51.3

(-63.6

,-39.1

)0

(0,0)

Orig

inal

––

––

––

0(0,0)

0(0,0)

10.1

(9.4

,10.9

)59.1

(54.9

,63.3

)233.6

(222.3

,244.8

)284.9

(277.1

,292.7

)M

in1A

––

––

––

–0

(0,0)

10.1

(9.4

,10.9

)59.1

(54.9

,63.3

)233.6

(222.3

,244.8

)284.9

(277.1

,292.7

)M

in2A

––

––

––

––

0(0,0)

49

(44.7

,53.2

)223.4

(212.2

,234.7

)274.7

(266.9

,282.6

)M

in3A

––

––

––

––

–0

(0,0)

174.5

(162.9

,186)

225.8

(216.9

,234.7

)M

in4A

––

––

––

––

––

0(0,0)

51.3

(39.1

,63.6

)M

in5A

––

––

––

––

––

–0

(0,0)

Tab

leF

.1:

CC

Cre

sult

sfo

rva

ryin

gth

efi

xed

an

dm

inim

um

nu

mb

erof

ap

pli

cati

on

son

the

tota

lnu

mb

erof

AL

Cd

ays

0A

1A

2A

3A

4A

5A

Orig

inal

Min

1A

Min

2A

Min

3A

Min

4A

Min

5A

0A

0(0,0)

6.9

(6.7

,7.2

)7.6

(7.4

,7.8

)8.1

(7.8

,8.3

)8.6

(8.3

,8.8

)8.8

(8.6

,9.1

)7.3

(7.1

,7.5

)7.3

(7.1

,7.5

)7.7

(7.4

,7.9

)8.1

(7.9

,8.4

)8.6

(8.3

,8.8

)8.8

(8.6

,9.1

)

1A

–0

(0,0)

0.6

(0.6

,0.7

)1.1

(1,1.2

)1.6

(1.5

,1.7

)1.9

(1.8

,2)

0.4

(0.3

,0.4

)0.4

(0.3

,0.4

)0.7

(0.6

,0.8

)1.2

(1.1

,1.3

)1.6

(1.5

,1.7

)1.9

(1.8

,2)

2A

––

0(0,0)

0.5

(0.4

,0.6

)1

(0.9

,1.1

)1.3

(1.2

,1.3

)-0.3

(-0.3

,-0.2

)-0.3

(-0.3

,-0.2

)0.1

(0,0.2

)0.5

(0.5

,0.6

)1

(0.9

,1.1

)1.3

(1.2

,1.3

)3A

––

–0

(0,0)

0.5

(0.4

,0.6

)0.8

(0.7

,0.9

)-0.8

(-0.8

,-0.7

)-0.8

(-0.8

,-0.7

)-0.4

(-0.5

,-0.3

)0.1

(0,0.1

)0.5

(0.4

,0.6

)0.8

(0.7

,0.9

)4A

––

––

0(0,0)

0.3

(0.2

,0.3

)-1.3

(-1.3

,-1.2

)-1.3

(-1.3

,-1.2

)-0.9

(-1,-0.8

)-0.5

(-0.5

,-0.4

)0

(-0

.1,0)

0.3

(0.2

,0.3

)5A

––

––

–0

(0,0)

-1.5

(-1.6

,-1.5

)1.5

(-1.6

,-1.5

)-1.2

(-1.2

,-1.1

)-0.7

(-0.8

,-0.6

)-0.3

(-0.4

,-0.2

)0

(0,0)

Orig

inal

––

––

––

0(0,0)

0(0,0)

0.4

(0.3

,0.4

)0.8

(0.8

,0.9

)1.3

(1.2

,1.3

)1.5

(1.5

,1.6

)M

in1A

––

––

––

–0

(0,0)

0.4

(0.3

,0.4

)0.8

(0.8

,0.9

)1.3

(1.2

,1.3

)1.5

(1.5

,1.6

)M

in2A

––

––

––

––

0(0,0)

0.5

(0.4

,0.5

)0.9

(0.8

,1)

1.2

(1.1

,1.2

)M

in3A

––

––

––

––

–0

(0,0)

0.4

(0.4

,0.5

)0.7

(0.6

,0.8

)M

in4A

––

––

––

––

––

0(0,0)

0.3

(0.2

,0.4

)M

in5A

––

––

––

––

––

–0

(0,0)

Tab

leF

.2:

CC

Cre

sult

sfo

rva

ryin

gth

efi

xed

an

dm

inim

um

nu

mb

erof

ap

pli

cati

on

son

tota

lnu

mb

erof

die

din

hosp

ital

pati

ents


0A

1A

2A

3A

4A

5A

Orig

inal

Min

1A

Min

2A

Min

3A

Min

4A

Min

5A

0A

0(0,0)

62.5

(57.4

,67.6

)

85.4

(80.3

,90.5

)101

(96.4

,105.6

)140.7

(135.6

,145.9

)185.3

(179.8

,190.8

)112

(107.7

,116.4

)112

(107.7

,116.4

)114.4

(110,

118.8

)118.5

(114,

122.9

)151.4

(146.6

,156.2

)177.1

(171.9

,182.3

)

1A

–0

(0,0)

22.9

(18,27.8

)38.5

(34,42.9

)78.2

(73,83.4

)122.8

(117.5

,128)

49.5

(45.2

,53.8

)49.5

(45.2

,53.8

)51.9

(47.5

,56.2

)55.9

(51.6

,60.3

)88.9

(84.4

,93.4

)114.6

(110.1

,119.1

)2A

––

0(0,0)

15.6

(12.2

,19)

55.3

(51.3

,59.4

)99.9

(95.5

,104.3

)26.6

(24,29.3

)26.6

(24,29.3

)29

(26.4

,31.6

)33.1

(30.4

,35.7

)66

(62.5

,69.6

)91.7

(88.2

,95.2

)

3A

––

–0

(0,0)

39.7

(35.5

,44)

84.3

(79.4

,89.2

)11

(8.8

,13.3

)11

(8.8

,13.3

)13.4

(11.2

,15.7

)17.5

(15.3

,19.7

)50.4

(47.3

,53.5

)76.1

(73,79.2

)4A

––

––

0(0,0)

44.6

(39.4

,49.7

)-28.7

(-32.3

,-25.1

)-28.7

(-32.3

,-25.1

)-26.3

(-29.9

,-22.7

)-22.3

(-26,-18.6

)10.7

(7.4

,14)

36.4

(32.6

,40.2

)

5A

––

––

–0

(0,0)

-73.3

(-77.3

,-69.2

)-73.3

(-77.3

,-69.2

)-70.9

(-74.9

,-66.9

)-66.8

(-70.9

,-62.8

)-33.9

(-38.4

,-29.4

)-8.2

(-12.6

,-3.8

)

Orig

inal

––

––

––

0(0,0)

0(0,0)

2.4

(2,2.8

)6.4

(5.8

,7.1

)39.4

(37,41.7

)65.1

(62.4

,67.7

)M

in1A

––

––

––

–0

(0,0)

2.4

(2,2.8

)6.4

(5.8

,7.1

)39.4

(37,41.7

)65.1

(62.4

,67.7

)M

in2A

––

––

––

––

0(0,0)

4.1

(3.3

,4.8

)37

(34.7

,39.3

)62.7

(60.1

,65.3

)M

in3A

––

––

––

––

–0

(0,0)

33

(30.5

,35.4

)58.6

(56,61.3

)M

in4A

––

––

––

––

––

0(0,0)

25.7

(22.6

,28.8

)M

in5A

––

––

––

––

––

–0

(0,0)

Tab

leF

.3:

Con

vale

scen

tre

sult

sfo

rva

ryin

gth

efi

xed

an

dm

inim

um

nu

mb

erof

ap

pli

cati

on

son

tota

lnu

mb

erof

AL

Cd

ays

0A

1A

2A

3A

4A

5A

Orig

inal

Min

1A

Min

2A

Min

3A

Min

4A

Min

5A

0A

0(0,0)

2.9

(2.8

,3)

3.3

(3.1

,3.4

)3.5

(3.4

,3.6

)3.6

(3.5

,3.7

)3.6

(3.5

,3.8

)3.6

(3.5

,3.7

)3.6

(3.5

,3.7

)3.6

(3.5

,3.7

)3.6

(3.5

,3.7

)3.6

(3.5

,3.7

)3.7

(3.6

,3.8

)

1A

–0

(0,0)

0.4

(0.3

,0.5

)0.6

(0.5

,0.7

)0.7

(0.6

,0.8

)0.8

(0.7

,0.8

)0.7

(0.6

,0.8

)0.7

(0.6

,0.8

)0.7

(0.6

,0.8

)0.7

(0.6

,0.8

)0.7

(0.6

,0.8

)0.8

(0.7

,0.9

)2A

––

0(0,0)

0.2

(0.2

,0.3

)0.3

(0.3

,0.4

)0.4

(0.3

,0.5

)0.3

(0.3

,0.4

)0.3

(0.3

,0.4

)0.3

(0.3

,0.4

)0.3

(0.3

,0.4

)0.3

(0.3

,0.4

)0.4

(0.3

,0.5

)3A

––

–0

(0,0)

0.1

(0,0.1

)0.1

(0.1

,0.2

)0.1

(0,0.1

)0.1

(0,0.1

)0.1

(0,0.1

)0.1

(0,0.1

)0.1

(0,0.1

)0.2

(0.1

,0.2

)4A

––

––

0(0,0)

0.1

(0,0.1

)0

(0,0)

0(0,0)

0(0,0)

0(0,0)

0(0,0)

0.1

(0.1

,0.2

)5A

––

––

–0

(0,0)

-0.1

(-0

.1,0)

-0.1

(-0

.1,0)

-0.1

(-0

.1,0)

-0.1

(-0

.1,0)

-0.1

(-0

.1,0)

0(0,0.1

)

Orig

inal

––

––

––

0(0,0)

0(0,0)

0(0,0)

0(0,0)

0(0,0)

0.1

(0.1

,0.2

)M

in1A

––

––

––

–0

(0,0)

0(0,0)

0(0,0)

0(0,0)

0.1

(0.1

,0.2

)M

in2A

––

––

––

––

0(0,0)

0(0,0)

0(0,0)

0.1

(0.1

,0.2

)M

in3A

––

––

––

––

–0

(0,0)

0(0,0)

0.1

(0.1

,0.2

)M

in4A

––

––

––

––

––

0(0,0)

0.1

(0.1

,0.2

)M

in5A

––

––

––

––

––

–0

(0,0)

Tab

leF

.4:

Con

vale

scen

tre

sult

sfo

rva

ryin

gth

efi

xed

an

dm

inim

um

nu

mb

erof

ap

pli

cati

on

son

tota

lnu

mb

erof

die

din

hosp

ital

pati

ents


0A

1A

2A

3A

4A

5A

Orig

inal

Min

1A

Min

2A

Min

3A

Min

4A

Min

5A

0A

0(0,0)

8.5

(8.2

,8.8

)12.6

(12.3

,12.9

)16.3

(16,16.6

)19

(18.7

,19.3

)20.3

(20,20.6

)17.5

(17.2

,17.7

)17.8

(17.6

,18.1

)18

(17.8

,18.3

)18.2

(18,18.5

)19.5

(19.2

,19.8

)20.5

(20.1

,20.8

)

1A

–0

(0,0)

4.1

(3.8

,4.4

)7.8

(7.5

,8.1

)10.5

(10.2

,10.8

)11.8

(11.5

,12.1

)9

(8.8

,9.3

)9.3

(9.1

,9.6

)9.6

(9.3

,9.8

)9.8

(9.5

,10)

11

(10.7

,11.3

)12

(11.7

,12.3

)2A

––

0(0,0)

3.7

(3.4

,4)

6.4

(6.2

,6.7

)7.7

(7.4

,8)

4.9

(4.7

,5.1

)5.2

(5,5.5

)5.5

(5.2

,5.7

)5.7

(5.4

,5.9

)6.9

(6.6

,7.2

)7.9

(7.6

,8.1

)3A

––

–0

(0,0)

2.7

(2.5

,2.9

)4

(3.8

,4.2

)1.2

(1.1

,1.4

)1.6

(1.4

,1.7

)1.8

(1.6

,1.9

)2

(1.8

,2.1

)3.2

(3,3.4

)4.2

(4,4.4

)4A

––

––

0(0,0)

1.3

(1.1

,1.5

)-1.5

(-1.7

,-1.4

)-1.2

(-1.3

,-1)

-1

(-1.1

,-0.8

)-0.8

(-0.9

,-0.6

)0.5

(0.3

,0.7

)1.4

(1.2

,1.6

)5A

––

––

–0

(0,0)

-2.8

(-3,-2.7

)-2.5

(-2.6

,-2.3

)-2.3

(-2.4

,-2.1

)-2.1

(-2.2

,-1.9

)-0.8

(-1,-0.6

)0.1

(0,0.3

)

Orig

inal

––

––

––

0(0,0)

0.3

(0.3

,0.4

)0.6

(0.5

,0.6

)0.8

(0.7

,0.8

)2

(1.9

,2.1

)3

(2.8

,3.1

)M

in1A

––

––

––

–0

(0,0)

0.2

(0.1

,0.3

)0.4

(0.3

,0.5

)1.7

(1.5

,1.8

)2.6

(2.5

,2.8

)M

in2A

––

––

––

––

0(0,0)

0.2

(0.1

,0.3

)1.5

(1.3

,1.6

)2.4

(2.3

,2.6

)M

in3A

––

––

––

––

–0

(0,0)

1.3

(1.1

,1.4

)2.2

(2.1

,2.4

)M

in4A

––

––

––

––

––

0(0,0)

1(0.8

,1.2

)M

in5A

––

––

––

––

––

–0

(0,0)

Tab

leF

.5:

LT

Cre

sult

sfo

rva

ryin

gth

efi

xed

an

dm

inim

um

nu

mb

erof

ap

pli

cati

on

son

tota

lnu

mb

erof

die

din

hosp

ital

pati

ents


0A

1A

2A

3A

4A

5A

Orig

inal

Min

1A

Min

2A

Min

3A

Min

4A

Min

5A

0A

0(0,0)

343.2

(329.9

,356.6

)

518.4

(503.3

,533.5

)649.8

(633.1

,666.4

)863.8

(846.6

,881)

959.3

(942.8

,975.8

)547.4

(531.1

,563.7

)549.4

(533.1

,565.7

)597.4

(581.2

,613.6

)668.1

(651.5

,684.7

)873.3

(855.5

,891.1

)964.1

(947.7

,980.5

)

1A

–0

(0,0)

175.2

(163.9

,186.4

)306.5

(295.1

,318)

520.6

(509,

532.2

)616.1

(605.1

,627)

204.2

(193.6

,214.8

)206.2

(195.5

,216.8

)254.2

(243.5

,264.9

)324.9

(313.8

,336)

530.1

(517.9

,542.3

)620.9

(609.8

,632)

2A

––

0(0,0)

131.4

(123.9

,138.8

)345.4

(336.9

,354)

440.9

(433.3

,448.5

)29

(22.3

,35.8

)31

(24.2

,37.8

)79

(72.1

,86)

149.7

(142.8

,156.7

)354.9

(346.1

,363.7

)445.7

(438.4

,453.1

)3A

––

–0

(0,0)

214.1

(207.5

,220.6

)309.5

(304.3

,314.8

)-102.3

(-106.2

,-98.5

)-100.4

(-104.3

,-96.5

)-52.3

(-56.8

,-47.9

)18.4

(14,22.7

)223.5

(217.1

,229.9

)314.4

(309.4

,319.3

)4A

––

––

0(0,0)

95.5

(89,102)

-316.4

(-321.5

,-311.3

)-314.5

(-319.5

,-309.4

)-266.4

(-271.6

,-261.2

)-195.7

(-201.4

,-190)

9.5

(4.6

,14.4

)100.3

(93.9

,106.8

)5A

––

––

–0

(0,0)

-411.9

(-415.3

,-408.4

)-409.9

(-413.4

,-406.5

)-361.9

(-365.8

,-357.9

)-291.2

(-295.7

,-286.6

)-86

(-91.8

,-80.2

)4.8

(2.6

,7.1

)

Orig

inal

––

––

––

0(0,0)

2(1.6

,2.3

)50

(48.3

,51.7

)120.7

(118.1

,123.3

)325.9

(321.3

,330.5

)416.7

(413.5

,420)

Min

1A

––

––

––

–0

(0,0)

48.1

(46.3

,49.8

)118.8

(116.1

,121.4

)323.9

(319.3

,328.5

)414.8

(411.5

,418)

Min

2A

––

––

––

––

0(0,0)

70.7

(67.7

,73.7

)275.9

(271,

280.7

)366.7

(362.8

,370.6

)M

in3A

––

––

––

––

–0

(0,0)

205.2

(199.8

,210.5

)296

(291.8

,300.2

)M

in4A

––

––

––

––

––

0(0,0)

90.8

(85.1

,96.6

)M

in5A

––

––

––

––

––

–0

(0,0)

Tab

leF

.6:

Pal

liat

ive

resu

lts

for

vary

ing

the

fixed

an

dm

inim

um

nu

mb

erof

ap

pli

cati

on

son

tota

lnu

mb

erof

AL

Cd

ays

0A

1A

2A

3A

4A

5A

Orig

inal

Min

1A

Min

2A

Min

3A

Min

4A

Min

5A

0A

0(0,0)

18

(17.6

,18.5

)

25.1

(24.6

,25.5

)29.3

(28.9

,29.7

)34.4

(33.9

,34.9

)37.6

(37.2

,38.1

)27.5

(27.1

,27.9

)27.5

(27.1

,27.9

)28.3

(27.9

,28.7

)29.6

(29.2

,30.1

)34.5

(34,34.9

)37.6

(37.1

,38)

1A

–0

(0,0)

7(6.6

,7.4

)11.3

(10.9

,11.7

)16.4

(15.9

,16.8

)19.6

(19.2

,20)

9.5

(9.1

,9.9

)9.5

(9.1

,9.9

)10.3

(9.8

,10.7

)11.6

(11.2

,12)

16.4

(16,16.9

)19.5

(19.1

,20)

2A

––

0(0,0)

4.3

(4,4.5

)9.4

(9.1

,9.7

)12.6

(12.3

,12.9

)2.5

(2.2

,2.7

)2.5

(2.2

,2.7

)3.3

(3,3.5

)4.6

(4.3

,4.9

)9.4

(9.1

,9.7

)12.5

(12.3

,12.8

)3A

––

–0

(0,0)

5.1

(4.8

,5.3

)8.3

(8.1

,8.6

)-1.8

(-1.9

,-1.6

)-1.8

(-1.9

,-1.6

)-1

(-1.2

,-0.8

)0.3

(0.2

,0.5

)5.2

(4.9

,5.4

)8.3

(8,8.5

)4A

––

––

0(0,0)

3.2

(2.9

,3.5

)-6.9

(-7.1

,-6.7

)-6.9

(-7.1

,-6.7

)-6.1

(-6.3

,-5.9

)-4.8

(-5,-4.5

)0.1

(-0

.2,0.3

)3.2

(2.9

,3.4

)5A

––

––

–0

(0,0)

-10.1

(-10.3

,-9.9

)-10.1

(-10.3

,-9.9

)-9.3

(-9.6

,-9.1

)-8

(-8.2

,-7.8

)-3.2

(-3.4

,-2.9

)-0

.1(-0

.3,0.1

)

Orig

inal

––

––

––

0(0,0)

0(0,0)

0.8

(0.7

,0.9

)2.1

(2,2.2

)7

(6.7

,7.2

)10.1

(9.9

,10.3

)M

in1A

––

––

––

–0

(0,0)

0.8

(0.7

,0.9

)2.1

(2,2.2

)7

(6.7

,7.2

)10.1

(9.9

,10.3

)M

in2A

––

––

––

––

0(0,0)

1.3

(1.2

,1.5

)6.2

(5.9

,6.4

)9.3

(9.1

,9.5

)M

in3A

––

––

––

––

–0

(0,0)

4.8

(4.6

,5.1

)8

(7.7

,8.2

)M

in4A

––

––

––

––

––

0(0,0)

3.1

(2.9

,3.4

)M

in5A

––

––

––

––

––

–0

(0,0)

Tab

leF

.7:

Pal

liat

ive

resu

lts

for

vary

ing

the

fixed

an

dm

inim

um

nu

mb

erof

ap

pli

cati

ons

on

tota

lnu

mb

erof

die

din

hosp

ital

pati

ents


0A

1A

2A

3A

4A

5A

Orig

inal

Min

1A

Min

2A

Min

3A

Min

4A

Min

5A

0A

0(0,0)

988.4

(974.7

,1002.1

)

1606.3

(1590.3

,1622.3

)1958

(1943.4

,1972.5

)2316.9

(2300.7

,2333.1

)2577.8

(2561.7

,2594)

1391.2

(1376.1

,1406.4

)1391.7

(1376.5

,1406.8

)1775.6

(1759.5

,1791.7

)2013.4

(1998,

2028.8

)2334.7

(2318.8

,2350.7

)2582.8

(2566.5

,2599)

1A

–0

(0,0)

617.9

(609.1

,626.7

)969.6

(960.7

,978.4

)1328.5

(1318.6

,1338.5

)1589.5

(1579.6

,1599.3

)402.8

(394.8

,410.9

)403.3

(395.2

,411.4

)787.2

(778.1

,796.3

)1025

(1015.8

,1034.3

)1346.3

(1336.9

,1355.8

)1594.4

(1584.8

,1604)

2A

––

0(0,0)

351.6

(343.1

,360.2

)710.6

(700.9

,720.3

)971.5

(961.8

,981.2

)-215.1

(-222.7

,-207.5

)-214.6

(-222.2

,-207)

169.3

(160,

178.5

)407.1

(398.5

,415.8

)728.4

(718.8

,738)

976.4

(967.8

,985.1

)3A

––

–0

(0,0)

358.9

(352.5

,365.4

)619.9

(613.2

,626.6

)-566.7

(-571.5

,-562)

-566.3

(-571.1

,-561.5

)-182.4

(-188.1

,-176.6

)55.5

(49.7

,61.3

)376.8

(370.2

,383.4

)624.8

(618.2

,631.4

)4A

––

––

0(0,0)

260.9

(253.3

,268.6

)-925.7

(-931.1

,-920.2

)-925.2

(-930.7

,-919.8

)-541.3

(-547.8

,-534.9

)-303.5

(-310.6

,-296.4

)17.8

(10.7

,25)

265.9

(258.3

,273.4

)5A

––

––

–0

(0,0)

-1186.6

(-1191.6

,-1181.7

)-1186.2

(-1191.1

,-1181.2

)-802.3

(-809.1

,-795.4

)-564.4

(-570.8

,-558)

-243.1

(-249.5

,-236.8

)4.9

(-0

.5,10.3

)

Orig

inal

––

––

––

0(0,0)

0.5

(0.3

,0.6

)384.4

(379.8

,388.9

)622.2

(617.8

,626.6

)943.5

(938.6

,948.4

)1191.5

(1186.8

,1196.3

)M

in1A

––

––

––

–0

(0,0)

383.9

(379.3

,388.5

)621.8

(617.4

,626.1

)943.1

(938.2

,947.9

)1191.1

(1186.3

,1195.8

)M

in2A

––

––

––

––

0(0,0)

237.8

(232,

243.7

)559.1

(552.5

,565.8

)807.2

(800.4

,813.9

)M

in3A

––

––

––

––

–0

(0,0)

321.3

(314.3

,328.3

)569.3

(562.8

,575.9

)M

in4A

––

––

––

––

––

0(0,0)

248

(241.9

,254.2

)M

in5A

––

––

––

––

––

–0

(0,0)

Tab

leF

.8:

Reh

abil

itat

ion

resu

lts

for

vary

ing

the

fixed

and

min

imu

mnum

ber

of

ap

pli

cati

on

son

the

nu

mb

erof

AL

Cd

ays

0A

1A

2A

3A

4A

5A

Orig

inal

Min

1A

Min

2A

Min

3A

Min

4A

Min

5A

0A

0(0,0)

34.8

(34.1

,35.5

)

47.8

(47.1

,48.6

)52.4

(51.6

,53.2

)55.3

(54.5

,56.1

)57.3

(56.6

,58.1

)47.5

(46.8

,48.3

)47.5

(46.8

,48.3

)52.6

(51.8

,53.4

)54.1

(53.3

,54.8

)55.8

(55,56.6

)57.6

(56.8

,58.4

)

1A

–0

(0,0)

13.1

(12.6

,13.5

)17.6

(17.2

,18.1

)20.5

(20.1

,21)

22.6

(22.1

,23)

12.8

(12.3

,13.2

)12.8

(12.3

,13.2

)17.8

(17.4

,18.3

)19.3

(18.9

,19.7

)21

(20.6

,21.5

)22.8

(22.4

,23.3

)2A

––

0(0,0)

4.6

(4.2

,4.9

)7.5

(7.1

,7.8

)9.5

(9.2

,9.9

)-0

.3(-0

.7,0)

-0.3

(-0

.7,0)

4.8

(4.4

,5.1

)6.2

(5.9

,6.6

)8

(7.6

,8.3

)9.7

(9.4

,10.1

)3A

––

–0

(0,0)

2.9

(2.7

,3.1

)4.9

(4.7

,5.2

)-4.9

(-5.1

,-4.7

)-4.9

(-5.1

,-4.7

)0.2

(0,0.4

)1.7

(1.5

,1.8

)3.4

(3.2

,3.6

)5.2

(5,5.4

)4A

––

––

0(0,0)

2.1

(1.9

,2.2

)-7.8

(-7.9

,-7.6

)-7.8

(-7.9

,-7.6

)-2.7

(-2.9

,-2.5

)-1.2

(-1.4

,-1.1

)0.5

(0.3

,0.7

)2.3

(2.1

,2.4

)5A

––

––

–0

(0,0)

-9.8

(-9.9

,-9.7

)-9.8

(-9.9

,-9.7

)-4.7

(-4.9

,-4.6

)-3.3

(-3.4

,-3.1

)-1.5

(-1.7

,-1.4

)0.2

(0.1

,0.3

)

Orig

inal

––

––

––

0(0,0)

0(0,0)

5.1

(4.9

,5.2

)6.5

(6.4

,6.6

)8.3

(8.2

,8.4

)10

(9.9

,10.1

)M

in1A

––

––

––

–0

(0,0)

5.1

(4.9

,5.2

)6.5

(6.4

,6.6

)8.3

(8.2

,8.4

)10

(9.9

,10.1

)M

in2A

––

––

––

––

0(0,0)

1.5

(1.3

,1.6

)3.2

(3,3.4

)5

(4.8

,5.1

)M

in3A

––

––

––

––

–0

(0,0)

1.7

(1.6

,1.9

)3.5

(3.4

,3.6

)M

in4A

––

––

––

––

––

0(0,0)

1.8

(1.6

,1.9

)M

in5A

––

––

––

––

––

–0

(0,0)

Tab

leF

.9:

Reh

abil

itat

ion

resu

lts

for

vary

ing

the

fixed

an

dm

inim

um

nu

mb

erof

ap

pli

cati

on

son

tota

lnu

mb

erof

die

din

hosp

ital

pati

ents

Appendix G


quantity of short waiting list facilities

85

Appendix G. Pairwise comparison charts - varying quantity of short waiting list facilities86

3A

-0SW

L3A

-1SW

L3A

-2SW

L3A

-3SW

L4A

-0SW

L4A

-1SW

L4A

-2SW

L4A

-3SW

L4A

-4SW

L5A

-0SW

L5A

-1SW

L5A

-2SW

L5A

-3SW

L5A

-4SW

L5A

-5SW

L

3A

-0SW

L0

(0,0)

0.7

(-2

.8,

4.3

)2

(-3

.7,7.7

)19.8

(10.2

,29.5

)183.8

(171.9

,195.7

)183.7

(171.7

,195.6

)228.8

(218.6

,239.1

)178.1

(165,

191.2

)N/A

247.8

(237,

258.5

)234.7

(225.5

,243.9

)238.1

(229,

247.3

)301

(293.3

,308.8

)N/A

N/A

3A

-1SW

L–

0(0,0

)1.3

(-4

.3,6.8

)19.1

(9.6

,28.6

)183

(171.1

,194.9

)182.9

(171,

194.9

)228.1

(218,

238.2

)177.4

(164.4

,190.4

)N/A

247

(236.7

,257.4

)234

(225.4

,242.6

)237.4

(228.8

,246)

300.3

(292.6

,308)

N/A

N/A

3A

-2SW

L–

–0

(0,0)

17.8

(7.1

,28.6

)181.7

(168.9

,194.6

)181.7

(168.8

,194.6

)226.8

(215.9

,237.7

)176.1

(162.6

,189.7

)N/A

245.8

(234.9

,256.6

)232.7

(223.3

,242.2

)236.1

(226.9

,245.3

)299

(291.8

,306.3

)N/A

N/A

3A

-3SW

L–

––

0(0,0

)163.9

(151.1

,176.7

)163.8

(150.9

,176.7

)209

(196.8

,221.1

)158.3

(144.2

,172.4

)N/A

227.9

(215.5

,240.3

)214.9

(203.2

,226.5

)218.3

(207.5

,229.1

)281.2

(269.7

,292.7

)N/A

N/A

4A

-0SW

L–

––

–0

(0,0)

-0.1

(-1

.1,

0.9

)45.1

(33.1

,57)

-5.6

(-1

4.5

,3.2

)N/A

64

(50.7

,77.3

)51

(39.1

,62.9

)54.4

(42.5

,66.2

)117.3

(104.9

,129.6

)N/A

N/A

4A

-1SW

L–

––

––

0(0,0)

45.1

(33.1

,57.2

)-5

.5(-1

4.3

,3.2

)N/A

64.1

(50.7

,77.5

)51

(39,63.1

)54.4

(42.4

,66.4

)117.4

(104.9

,129.8

)N/A

N/A

4A

-2SW

L–

––

––

–0

(0,0)

-50.7

(-64.9

,-36.4

)N/A

19

(7.7

,30.2

)5.9

(-0

.9,

12.7

)9.3

(3,15.6

)72.2

(63.1

,81.4

)N/A

N/A

4A

-3SW

L–

––

––

––

0(0,0)

N/A

69.6

(54.8

,84.5

)56.6

(42.7

,70.5

)60

(46.1

,73.8

)122.9

(109,

136.8

)N/A

N/A

4A

-4SW

L–

––

––

––

–N/A

N/A

N/A

N/A

N/A

N/A

N/A

5A

-0SW

L–

––

––

––

––

0(0,0)

-13

(-19.5

,-6.6

)-9.6

(-16.6

,-2.7

)53.3

(40,

66.6

)N/A

N/A

5A

-1SW

L–

––

––

––

––

–0

(0,0)

3.4

(-1

,7.7

)66.3

(56.9

,75.7

)N/A

N/A

5A

-2SW

L–

––

––

––

––

––

0(0,0)

62.9

(53.4

,72.4

)N/A

N/A

5A

-3SW

L–

––

––

––

––

––

–0

(0,0)

N/A

N/A

5A

-4SW

L–

––

––

––

––

––

––

N/A

N/A

5A

-5SW

L–

––

––

––

––

––

––

–N/A

Tab

leG

.1:

CC

Cre

sult

sfo

rva

ryin

gth

enu

mb

erof

short

wait

ing

list

faci

liti

eson

the

nu

mb

erof

AL

Cd

ays


3A

-0SW

L3A

-1SW

L3A

-2SW

L3A

-3SW

L4A

-0SW

L4A

-1SW

L4A

-2SW

L4A

-3SW

L4A

-4SW

L5A

-0SW

L5A

-1SW

L5A

-2SW

L5A

-3SW

L5A

-4SW

L5A

-5SW

L

3A

-0SW

L0

(0,0)

0(0,0)

0(-0

.1,0.1

)0

(-0

.1,0.1

)0.5

(0.4

,0.6

)0.5

(0.4

,0.6

)0.5

(0.4

,0.6

)0.4

(0.3

,0.5

)N/A

0.8

(0.7

,0.9

)0.8

(0.7

,0.9

)0.8

(0.7

,0.9

)0.8

(0.7

,0.9

)N/A

N/A

3A

-1SW

L–

0(0,0

)0

(-0

.1,0.1

)0

(-0

.1,0.1

)0.5

(0.4

,0.6

)0.5

(0.4

,0.6

)0.5

(0.4

,0.6

)0.4

(0.3

,0.5

)N/A

0.8

(0.7

,0.9

)0.8

(0.7

,0.9

)0.8

(0.7

,0.9

)0.8

(0.7

,0.9

)N/A

N/A

3A

-2SW

L–

–0

(0,0)

0(-0

.1,0.1

)0.5

(0.4

,0.6

)0.5

(0.4

,0.6

)0.5

(0.4

,0.6

)0.4

(0.3

,0.5

)N/A

0.8

(0.7

,0.9

)0.8

(0.7

,0.9

)0.8

(0.7

,0.9

)0.8

(0.7

,0.9

)N/A

N/A

3A

-3SW

L–

––

0(0,0

)0.5

(0.4

,0.6

)0.5

(0.4

,0.6

)0.5

(0.4

,0.6

)0.4

(0.3

,0.5

)N/A

0.8

(0.7

,0.9

)0.8

(0.7

,0.9

)0.8

(0.7

,0.9

)0.8

(0.7

,0.9

)N/A

N/A

4A

-0SW

L–

––

–0

(0,0)

0(0,0)

0(-0

.1,0)

-0.1

(-0

.2,0)

N/A

0.3

(0.2

,0.3

)0.3

(0.2

,0.3

)0.3

(0.2

,0.3

)0.3

(0.2

,0.4

)N/A

N/A

4A

-1SW

L–

––

––

0(0,0)

0(-0

.1,0)

-0.1

(-0

.2,0)

N/A

0.3

(0.2

,0.3

)0.3

(0.2

,0.3

)0.3

(0.2

,0.3

)0.3

(0.2

,0.4

)N/A

N/A

4A

-2SW

L–

––

––

–0

(0,0)

-0.1

(-0

.1,0)

N/A

0.3

(0.2

,0.4

)0.3

(0.2

,0.4

)0.3

(0.2

,0.4

)0.3

(0.3

,0.4

)N/A

N/A

4A

-3SW

L–

––

––

––

0(0,0)

N/A

0.4

(0.3

,0.4

)0.4

(0.3

,0.4

)0.4

(0.3

,0.5

)0.4

(0.3

,0.5

)N/A

N/A

4A

-4SW

L–

––

––

––

–N/A

N/A

N/A

N/A

N/A

N/A

N/A

5A

-0SW

L–

––

––

––

––

0(0,0)

0(0,0)

0(0,0)

0(0,0.1

N/A

N/A

5A

-1SW

L–

––

––

––

––

–0

(0,0)

0(0,0)

0(0,0.1

)N/A

N/A

5A

-2SW

L–

––

––

––

––

––

0(0,0)

0(0,0.1

)N/A

N/A

5A

-3SW

L–

––

––

––

––

––

–0

(0,0)

N/A

N/A

5A

-4SW

L–

––

––

––

––

––

––

N/A

N/A

5A

-5SW

L–

––

––

––

––

––

––

–N/A

Tab

leG

.2:

CC

Cre

sult

sfo

rva

ryin

gth

enu

mb

erof

short

wait

ing

list

faci

liti

eson

the

nu

mb

erof

die

din

hosp

ital

pati

ents


3A

-0SW

L3A

-1SW

L3A

-2SW

L3A

-3SW

L4A

-0SW

L4A

-1SW

L4A

-2SW

L4A

-3SW

L4A

-4SW

L5A

-0SW

L5A

-1SW

L5A

-2SW

L5A

-3SW

L5A

-4SW

L5A

-5SW

L

3A

-0SW

L0

(0,0)

-0.3

(-0

.9,

0.4

)

-0.5

(-1

.7,

0.7

)-0

.6(-1

.6,

0.4

)41.2

(38.2

,44.2

)40.8

(38,

43.7

)40.3

(37.3

,43.3

)41.3

(38.5

,44.2

)41.5

(38.6

,44.4

)70.9

(67.5

,74.3

)70.6

(67.2

,74.1

)72.1

(68.9

,75.3

)71.2

(67.4

,75)

74.2

(70.2

,78.2

)85.2

(80.6

,89.8

)

3A

-1SW

L–

0(0,0)

-0.2

(-1

.3,

0.8

)-0

.3(-1

.2,

0.5

)41.5

(38.5

,44.5

)41.1

(38.3

,44)

40.6

(37.6

,43.5

)41.6

(38.8

,44.4

)41.8

(38.8

,44.7

)71.2

(67.9

,74.5

)70.9

(67.6

,74.3

)72.4

(69.3

,75.5

)71.4

(67.7

,75.2

)74.5

(70.5

,78.4

)85.5

(81,90)

3A

-2SW

L–

–0

(0,0)

-0.1

(-0

.5,

0.3

)41.7

(38.6

,44.8

)41.3

(38.3

,44.4

)40.8

(37.9

,43.8

)41.8

(39.2

,44.5

)42

(39.3

,44.8

)71.4

(68,

74.8

)71.2

(67.7

,74.6

)72.6

(69.4

,75.8

)71.7

(67.9

,75.4

)74.7

(70.8

,78.6

)85.7

(81.3

,90.1

)3A

-3SW

L–

––

0(0,0)

41.8

(38.8

,44.9

)41.5

(38.5

,44.4

)40.9

(38.1

,43.8

)42

(39.3

,44.6

)42.1

(39.4

,44.9

)71.5

(68.2

,74.9

)71.3

(67.9

,74.7

)72.7

(69.6

,75.9

)71.8

(68.1

,75.5

)74.8

(70.9

,78.7

)85.8

(81.5

,90.1

)

4A

-0SW

L–

––

–0

(0,0)

-0.4

(-1

.2,

0.4

)-0

.9(-2

.2,

0.4

)0.1

(-1

.4,1.6

)0.3

(-1

.3,1.9

)29.7

(25.1

,34.3

)29.4

(24.8

,34)

30.9

(26.6

,35.2

)29.9

(25.1

,34.8

)33

(28.3

,37.6

)44

(38.5

,49.4

)4A

-1SW

L–

––

––

0(0,0)

-0.5

(-1

.8,

0.8

)0.5

(-0

.9,1.9

)0.7

(-0

.8,2.2

)30.1

(25.6

,34.6

)29.8

(25.3

,34.3

)31.3

(27.1

,35.5

)30.3

(25.6

,35.1

)33.4

(28.6

,38.1

)44.4

(39,

49.7

)4A

-2SW

L–

––

––

–0

(0,0)

1(0,2.1

)1.2

(0.1

,2.3

)30.6

(26.1

,35)

30.3

(25.9

,34.8

)31.8

(27.7

,35.9

)30.9

(26.3

,35.4

)33.9

(29.2

,38.6

)44.9

(39.7

,50)

4A

-3SW

L–

––

––

––

0(0,0)

0.2

(-0

.4,0.7

)29.6

(25.3

,33.8

)29.3

(25,

33.6

)30.8

(26.8

,34.8

)29.8

(25.4

,34.3

)32.9

(28.3

,37.4

)43.9

(38.8

,48.9

)4A

-4SW

L–

––

––

––

–0

(0,0)

29.4

(25.1

,33.7

)29.1

(24.8

,33.4

)30.6

(26.6

,34.6

)29.7

(25.1

,34.2

)32.7

(28.2

,37.2

)43.7

(38.5

,48.8

)

5A

-0SW

L–

––

––

––

––

0(0,0)

-0.3

(-0

.9,

0.4

)1.2

(-0

.3,2.7

)0.3

(-2

.6,3.2

)3.3

(-0

.8,7.4

)14.3

(9.4

,19.2

)5A

-1SW

L–

––

––

––

––

–0

(0,0)

1.5

(-0

.2,3.1

)0.5

(-2

.5,3.5

)3.5

(-0

.5,7.6

)14.6

(9.7

,19.4

)5A

-2SW

L–

––

––

––

––

––

0(0,0)

-0.9

(-3

.8,

1.9

)2.1

(-1

.8,6)

13.1

(8.2

,17.9

)5A

-3SW

L–

––

––

––

––

––

–0

(0,0)

3(-1

.2,7.2

)14

(9.2

,18.8

)5A

-4SW

L–

––

––

––

––

––

––

0(0,0)

11

(6.5

,15.5

)5A

-5SW

L–

––

––

––

––

––

––

–0

(0,0)

Tab

leG

.3:

Con

vale

scen

tre

sult

sfo

rva

ryin

gth

enu

mb

erof

short

wait

ing

list

faci

liti

eson

the

nu

mb

erof

AL

Cd

ays


3A

-0SW

L3A

-1SW

L3A

-2SW

L3A

-3SW

L4A

-0SW

L4A

-1SW

L4A

-2SW

L4A

-3SW

L4A

-4SW

L5A

-0SW

L5A

-1SW

L5A

-2SW

L5A

-3SW

L5A

-4SW

L5A

-5SW

L

3A

-0SW

L0

(0,0)

0(0,0)

0(0,0)

0(-0

.1,0)

0.1

(0,0.1

)0.1

(0,0.1

)0.1

(0,0.1

)0.1

(0,0.1

)0.1

(0,0.1

)0.2

(0.1

,0.2

)0.2

(0.1

,0.2

)0.2

(0.1

,0.2

)0.2

(0.1

,0.2

)0.1

(0.1

,0.2

)0.1

(0.1

,0.2

)

3A

-1SW

L–

0(0,0)

0(0,0)

0(-0

.1,0)

0.1

(0,0.1

)0.1

(0,0.1

)0.1

(0,0.1

)0.1

(0,0.1

)0.1

(0,0.1

)0.2

(0.1

,0.2

)0.2

(0.1

,0.2

)0.2

(0.1

,0.2

)0.2

(0.1

,0.2

)0.1

(0.1

,0.2

))

0.1

(0.1

,0.2

)

3A

-2SW

L–

–0

(0,0)

0(-0

.1,0)

0.1

(0,0.1

)0.1

(0,0.1

)0.1

(0,0.1

)0.1

(0,0.1

)0.1

(0,0.1

)0.2

(0.1

,0.2

)0.2

(0.1

,0.2

)0.2

(0.1

,0.2

)0.2

(0.1

,0.2

)0.1

(0.1

,0.2

)0.1

(0.1

,0.2

)

3A

-3SW

L–

––

0(0,0)

0.1

(0,0.1

)0.1

(0,0.1

)0.1

(0,0.1

)0.1

(0,0.1

)0.1

(0,0.1

)0.2

(0.2

,0.3

)0.2

(0.2

,0.3

)0.2

(0.1

,0.3

)0.2

(0.1

,0.3

)0.2

(0.1

,0.2

)0.2

(0.1

,0.2

)

4A

-0SW

L–

––

–0

(0,0)

0(0,0)

0(0,0)

0(0,0)

0(0,0)

0.1

(0.1

,0.2

)0.1

(0.1

,0.2

)0.1

(0.1

,0.2

)0.1

(0.1

,0.2

)0.1

(0,0.1

)0.1

(0,0.1

)

4A

-1SW

L–

––

––

0(0,0)

0(0,0)

0(0,0)

0(0,0)

0.1

(0.1

,0.2

)0.1

(0.1

,0.2

)0.1

(0.1

,0.2

)0.1

(0.1

,0.2

)0.1

(0,0.1

)0.1

(0,0.1

)

4A

-2SW

L–

––

––

–0

(0,0)

0(0,0)

0(0,0)

0.1

(0.1

,0.2

)0.1

(0.1

,0.2

)0.1

(0.1

,0.2

)0.1

(0.1

,0.2

)0.1

(0,0.1

)0.1

(0,0.1

)

4A

-3SW

L–

––

––

––

0(0,0)

0(0,0)

0.1

(0.1

,0.2

)0.1

(0.1

,0.2

)0.1

(0.1

,0.2

)0.1

(0.1

,0.2

)0.1

(0,0.1

)0.1

(0,0.1

)

4A

-4SW

L–

––

––

––

–0

(0,0)

0.1

(0.1

,0.2

)0.1

(0.1

,0.2

)0.1

(0.1

,0.2

)0.1

(0.1

,0.2

)0.1

(0,0.1

)0.1

(0,0.1

)

5A

-0SW

L–

––

––

––

––

0(0,0)

0(0,0)

0(0,0)

0(0,0)

-0.1

(-0

.1,0)

-0.1

(-0

.1,0)

5A

-1SW

L–

––

––

––

––

–0

(0,0)

0(0,0)

0(0,0)

-0.1

(-0

.1,0)

-0.1

(-0

.1,0)

5A

-2SW

L–

––

––

––

––

––

0(0,0)

0(0,0)

0(-0

.1,0)

0(-0

.1,0)

5A

-3SW

L–

––

––

––

––

––

–0

(0,0)

0(-0

.1,0)

0(-0

.1,0)

5A

-4SW

L–

––

––

––

––

––

––

0(0,0)

0(0,0)

5A

-5SW

L–

––

––

––

––

––

––

–0

(0,0)

Tab

leG

.4:

Con

vale

scen

tre

sult

sfo

rva

ryin

gth

enu

mb

erof

short

wait

ing

list

faci

liti

eson

the

nu

mb

erof

die

din

hosp

ital

pati

ents


3A

-0SW

L3A

-1SW

L3A

-2SW

L3A

-3SW

L4A

-0SW

L4A

-1SW

L4A

-2SW

L4A

-3SW

L4A

-4SW

L5A

-0SW

L5A

-1SW

L5A

-2SW

L5A

-3SW

L5A

-4SW

L5A

-5SW

L

3A

-0SW

L0

(0,0)

-6.9

(-1

5.9

,2.1

)

-4.4

(-3

0.6

,21.8

)53.9

(16.1

,91.8

)490.7

(458.7

,522.7

)477.1

(444.8

,509.3

)493.8

(461.9

,525.8

)524

(488.8

,559.3

)612.8

(576.3

,649.4

)826.3

(793.2

,859.3

)826.3

(793.2

,859.3

)836

(803.4

,868.6

)864.9

(831.8

,898)

902

(869,

935)

996.4

(961.3

,1031.4

)

3A

-1SW

L–

0(0,0)

2.5

(-2

2.1

,27.1

)60.8

(23.7

,98)

497.6

(466.3

,528.9

)484

(452.6

,515.4

)500.7

(469.6

,531.8

)530.9

(497.1

,564.8

)619.7

(583.8

,655.6

)833.2

(801,

865.4

)833.2

(801,

865.4

)842.9

(811.2

,874.6

)871.8

(840,

903.6

)908.9

(877,

940.8

)1003.3

(968.6

,1038)

3A

-2SW

L–

–0

(0,0)

58.3

(25.1

,91.5

)495.1

(464,

526.2

)481.5

(449.6

,513.4

)498.2

(466.1

,530.4

)528.4

(493.9

,563)

617.2

(579.5

,655)

830.7

(799.3

,862.1

)830.7

(799.3

,862.1

)840.4

(808.7

,872.1

)869.3

(837.6

,901)

906.4

(873.9

,938.9

)1000.8

(964.2

,1037.3

)3A

-3SW

L–

––

0(0,0)

436.8

(400.9

,472.6

)423.2

(387,

459.3

)439.9

(403.1

,476.7

)470.1

(431,

509.2

)558.9

(517.5

,600.3

)772.3

(736.7

,808)

772.3

(736.7

,808)

782.1

(746.1

,818.1

)811

(773.6

,848.4

)848.1

(810.5

,885.7

)942.4

(901,

983.9

)

4A

-0SW

L–

––

–0

(0,0)

-13.6

(-18.2

,-9.1

)3.1

(-6

.5,

12.8

)33.3

(15.3

,51.4

)122.1

(97.5

,146.8

)335.6

(309,

362.1

)335.6

(309,

362.1

)345.3

(319.1

,371.5

)374.2

(347.8

,400.6

)411.3

(387.5

,435.1

)505.7

(481.4

,529.9

)4A

-1SW

L–

––

––

0(0,0)

16.7

(7.3

,26.1

)47

(29.7

,64.2

)135.7

(111,

160.5

)349.2

(322.1

,376.2

)349.2

(322.1

,376.2

)358.9

(332.3

,385.5

)387.8

(360.9

,414.8

)424.9

(401.1

,448.8

)519.3

(494.5

,544.1

)4A

-2SW

L–

––

––

–0

(0,0)

30.2

(13.6

,46.8

)119

(93.5

,144.5

)332.4

(306.5

,358.4

)332.4

(306.5

,358.4

)342.2

(316.6

,367.7

)371.1

(345.5

,396.6

)408.2

(384.4

,432)

502.5

(478,

527)

4A

-3SW

L–

––

––

––

0(0,0)

88.8

(63.2

,114.4

)302.2

(271.4

,333)

302.2

(271.4

,333)

312

(281.8

,342.1

)340.9

(310.3

,371.4

)378

(349.6

,406.3

)472.3

(444.9

,499.8

)4A

-4SW

L–

––

––

––

–0

(0,0)

213.4

(181.1

,245.8

)213.4

(181.1

,245.8

)223.2

(191.2

,255.1

)252.1

(219.8

,284.3

)289.2

(259.8

,318.6

)383.5

(355.2

,411.9

)

5A

-0SW

L–

––

––

––

––

0(0,0)

0(0,0)

9.7

(5.1

,14.3

)38.6

(28.9

,48.3

)75.7

(59.6

,91.9

)170.1

(148.9

,191.3

)5A

-1SW

L–

––

––

––

––

–0

(0,0)

9.7

(5.1

,14.3

)38.6

(28.9

,48.3

)75.7

(59.6

,91.9

)170.1

(148.9

,191.3

)5A

-2SW

L–

––

––

––

––

––

0(0,0)

28.9

(19.7

,38.1

)66

(50.2

,81.8

)160.4

(140.3

,180.4

)5A

-3SW

L–

––

––

––

––

––

–0

(0,0)

37.1

(22.2

,52)

131.5

(111.7

,151.2

)5A

-4SW

L–

––

––

––

––

––

––

0(0,0)

94.4

(75.8

,113)

5A

-5SW

L–

––

––

––

––

––

––

–0

(0,0)

Tab

leG

.5:

LT

Cre

sult

sfo

rva

ryin

gth

enu

mb

erof

short

wait

ing

list

faci

liti

eson

the

nu

mb

erof

AL

Cd

ays


3A

-0SW

L3A

-1SW

L3A

-2SW

L3A

-3SW

L4A

-0SW

L4A

-1SW

L4A

-2SW

L4A

-3SW

L4A

-4SW

L5A

-0SW

L5A

-1SW

L5A

-2SW

L5A

-3SW

L5A

-4SW

L5A

-5SW

L

3A

-0SW

L0

(0,0)

0(-0

.1,

0.1

)-0.3

(-0.5

,-0.1

)-0.3

(-0.5

,-0.1

)2.8

(2.6

,3)

2.8

(2.6

,3)

2.8

(2.6

,3)

2.7

(2.5

,2.9

)2.6

(2.4

,2.9

)4.1

(3.9

,4.3

)4.1

(3.9

,4.3

)4.1

(3.9

,4.3

)4.2

(3.9

,4.4

)4.2

(4,4.4

)4.5

(4.2

,4.7

)

3A

-1SW

L–

0(0,0)

-0.3

(-0.5

,-0.1

)-0.3

(-0.5

,-0.1

)2.8

(2.6

,3)

2.8

(2.6

,3)

2.8

(2.6

,3)

2.7

(2.5

,2.9

)2.6

(2.4

,2.9

)4.1

(3.9

,4.3

)4.1

(3.9

,4.3

)4.1

(3.9

,4.3

)4.2

(3.9

,4.4

)4.2

(4,4.4

)4.5

(4.2

,4.7

)

3A

-2SW

L–

–0

(0,0)

0(-0

.2,0.2

)3.1

(2.9

,3.3

)3.1

(2.9

,3.3

)3.1

(2.9

,3.3

)3

(2.8

,3.2

)2.9

(2.7

,3.2

)4.4

(4.2

,4.6

)4.4

(4.2

,4.6

)4.4

(4.2

,4.7

)4.5

(4.2

,4.7

)4.5

(4.2

,4.7

)4.8

(4.5

,5)

3A

-3SW

L–

––

0(0,0)

3.1

(2.9

,3.3

)3.1

(2.9

,3.3

)3.1

(2.9

,3.4

)3

(2.8

,3.2

)2.9

(2.6

,3.2

)4.4

(4.2

,4.7

)4.4

(4.2

,4.7

)4.4

(4.2

,4.7

)4.5

(4.2

,4.7

)4.5

(4.2

,4.7

)4.8

(4.5

,5)

4A

-0SW

L–

––

–0

(0,0)

0(0,0)

0(-0

.1,0.1

)-0

.1(-0

.3,0)

-0.2

(-0

.4,0)

1.3

(1.1

,1.5

)1.3

(1.1

,1.5

)1.3

(1.1

,1.5

)1.3

(1.1

,1.6

)1.4

(1.2

,1.6

)1.6

(1.4

,1.8

)

4A

-1SW

L–

––

––

0(0,0)

0(-0

.1,0.1

)-0

.1(-0

.3,0)

-0.2

(-0

.4,0)

1.3

(1.1

,1.5

)1.3

(1.1

,1.5

)1.3

(1.1

,1.5

)1.3

(1.1

,1.6

)1.4

(1.2

,1.6

)1.6

(1.4

,1.8

)

4A

-2SW

L–

––

––

–0

(0,0)

-0.1

(-0

.3,0)

-0.2

(-0

.4,0)

1.3

(1.1

,1.5

)1.3

(1.1

,1.5

)1.3

(1.1

,1.5

)1.3

(1.1

,1.6

)1.4

(1.2

,1.6

)1.6

(1.4

,1.8

)

4A

-3SW

L–

––

––

––

0(0,0)

-0.1

(-0

.3,

0.1

)1.4

(1.2

,1.7

)1.4

(1.2

,1.7

)1.4

(1.2

,1.7

)1.5

(1.2

,1.7

)1.5

(1.3

,1.7

)1.8

(1.5

,2)

4A

-4SW

L–

––

––

––

–0

(0,0)

1.5

(1.3

,1.7

)1.5

(1.3

,1.7

)1.5

(1.3

,1.7

)1.5

(1.3

,1.8

)1.6

(1.4

,1.8

)1.8

(1.6

,2.1

)

5A

-0SW

L–

––

––

––

––

0(0,0)

0(0,0)

0(0,0.1

)0

(0,0.1

)0.1

(-0

.1,0.2

)0.3

(0.1

,0.5

)

5A

-1SW

L–

––

––

––

––

–0

(0,0)

0(0,0.1

)0

(0,0.1

)0.1

(-0

.1,0.2

)0.3

(0.1

,0.5

)

5A

-2SW

L–

––

––

––

––

––

0(0,0)

0(0,0.1

)0.1

(-0

.1,0.2

)0.3

(0.1

,0.5

)

5A

-3SW

L–

––

––

––

––

––

–0

(0,0)

0(-0

.1,0.2

)0.3

(0.1

,0.5

)

5A

-4SW

L–

––

––

––

––

––

––

0(0,0)

0.3

(0.1

,0.4

)

5A

-5SW

L–

––

––

––

––

––

––

–0

(0,0)

Tab

leG

.6:

LT

Cre

sult

sfo

rva

ryin

gth

enu

mb

erof

short

wait

ing

list

faci

liti

eson

the

nu

mb

erof

die

din

hosp

ital

pati

ents


3A

-0SW

L3A

-1SW

L3A

-2SW

L3A

-3SW

L4A

-0SW

L4A

-1SW

L4A

-2SW

L4A

-3SW

L4A

-4SW

L5A

-0SW

L5A

-1SW

L5A

-2SW

L5A

-3SW

L5A

-4SW

L5A

-5SW

L

3A

-0SW

L0

(0,0)

12.1

(6.5

,17.6

)

69.6

(62.1

,77.2

)148.2

(141.8

,154.7

)214.1

(207.5

,220.6

)203.3

(196.7

,209.9

)207.6

(200.7

,214.5

)245.1

(239.2

,251.1

)288.4

(282.3

,294.4

)309.5

(304.3

,314.8

)308.1

(302.8

,313.4

)303.9

(298.4

,309.5

)309.5

(304.1

,314.8

)329.1

(323.5

,334.6

)355.2

(350.8

,359.7

)

3A

-1SW

L–

0(0,0)

57.5

(49.2

,65.9

)136.2

(128.8

,143.5

)202

(194.3

,209.7

)191.2

(183.6

,198.8

)195.5

(187.6

,203.4

)233

(226,

240.1

)276.3

(269.9

,282.7

)297.5

(291.4

,303.5

)296

(289.9

,302.2

)291.9

(285.4

,298.3

)297.4

(291.1

,303.7

)317

(310.8

,323.2

)343.2

(337.5

,348.9

)3A

-2SW

L–

–0

(0,0)

78.6

(71.7

,85.5

)144.5

(136.8

,152.1

)133.7

(125.3

,142.1

)138

(129.8

,146.2

)175.5

(167.8

,183.2

)218.8

(211.2

,226.3

)239.9

(232.4

,247.5

)238.5

(230.9

,246.2

)234.3

(226.9

,241.8

)239.9

(232.8

,246.9

)259.5

(252,

266.9

)285.6

(278.7

,292.6

)3A

-3SW

L–

––

0(0,0)

65.8

(59,

72.6

)55.1

(47.6

,62.5

)59.3

(52,

66.7

)96.9

(90.5

,103.3

)140.1

(134.3

,146)

161.3

(155.4

,167.2

)159.9

(154.2

,165.6

)155.7

(149.2

,162.1

)161.2

(156.2

,166.2

)180.8

(175.4

,186.3

)207

(201.5

,212.5

)

4A

-0SW

L–

––

–0

(0,0)

-10.8

(-15.5

,-6.1

)-6.5

(-12.7

,-0.3

)31.1

(24.9

,37.2

)74.3

(67.8

,80.8

)95.5

(89,

102)

94.1

(87.5

,100.7

)89.9

(83.8

,95.9

)95.4

(89.5

,101.3

)115

(109,

121)

141.2

(135.3

,147)

4A

-1SW

L–

––

––

0(0,0)

4.3

(-2

.8,

11.4

)41.8

(35.5

,48.1

)85.1

(78.8

,91.4

)106.2

(99.7

,112.8

)104.8

(98.2

,111.5

)100.6

(94.6

,106.7

)106.2

(99.8

,112.6

)125.8

(119.2

,132.4

)151.9

(145.9

,157.9

)4A

-2SW

L–

––

––

–0

(0,0)

37.5

(31.2

,43.9

)80.8

(73.6

,88)

101.9

(95.4

,108.5

)100.5

(93.9

,107.2

)96.3

(89.2

,103.5

)101.9

(95.2

,108.5

)121.5

(115.2

,127.8

)147.7

(141.4

,153.9

)4A

-3SW

L–

––

––

––

0(0,0)

43.2

(37.9

,48.6

)64.4

(58.8

,70)

63

(57.6

,68.4

)58.8

(53.3

,64.3

)64.3

(59.5

,69.2

)83.9

(78.2

,89.6

)110.1

(105.2

,115.1

)4A

-4SW

L–

––

––

––

–0

(0,0)

21.2

(16.1

,26.3

)19.8

(14.6

,24.9

)15.6

(10.3

,20.8

)21.1

(16.2

,26)

40.7

(35.4

,46)

66.9

(62.3

,71.4

)

5A

-0SW

L–

––

––

––

––

0(0,0)

-1.4

(-4

.1,

1.3

)-5.6

(-9.8

,-1.4

)-0

.1(-4

.5,

4.4

)19.5

(15.1

,23.9

)45.7

(41.6

,49.8

)5A

-1SW

L–

––

––

––

––

–0

(0,0)

-4.2

(-8,

-0.4

)1.3

(-2

.9,5.6

)20.9

(16.7

,25.2

)47.1

(43.4

,50.8

)5A

-2SW

L–

––

––

––

––

––

0(0,0)

5.5

(1.1

,9.9

)25.1

(20.5

,29.8

)51.3

(47.4

,55.3

)5A

-3SW

L–

––

––

––

––

––

–0

(0,0)

19.6

(15.4

,23.8

)45.8

(42,

49.6

)5A

-4SW

L–

––

––

––

––

––

––

0(0,0)

26.2

(22.4

,30)

5A

-5SW

L–

––

––

––

––

––

––

–0

(0,0)

Tab

leG

.7:

Pal

liat

ive

resu

lts

for

vary

ing

the

nu

mb

erof

short

wait

ing

list

faci

liti

eson

the

nu

mb

erof

AL

Cd

ays


3A

-0SW

L3A

-1SW

L3A

-2SW

L3A

-3SW

L4A

-0SW

L4A

-1SW

L4A

-2SW

L4A

-3SW

L4A

-4SW

L5A

-0SW

L5A

-1SW

L5A

-2SW

L5A

-3SW

L5A

-4SW

L5A

-5SW

L

3A

-0SW

L0

(0,0)

0.3

(0.1

,0.4

)1

(0.7

,1.2

)2.4

(2.1

,2.6

)5.1

(4.8

,5.3

)5.1

(4.8

,5.3

)5

(4.8

,5.3

)5.6

(5.3

,5.9

)7.2

(6.9

,7.5

)8.3

(8.1

,8.6

)8.2

(8,8.5

)8.1

(7.8

,8.3

)8.6

(8.3

,8.8

)8.7

(8.5

,8.9

)9.6

(9.4

,9.9

)

3A

-1SW

L–

0(0,0)

0.7

(0.5

,1)

2.1

(1.8

,2.4

)4.8

(4.6

,5.1

)4.8

(4.5

,5.1

)4.8

(4.5

,5.1

)5.4

(5.1

,5.6

)7

(6.7

,7.3

)8.1

(7.8

,8.3

)8

(7.7

,8.2

)7.8

(7.5

,8.1

)8.3

(8,8.6

)8.5

(8.2

,8.7

)9.4

(9.1

,9.7

)

3A

-2SW

L–

–0

(0,0)

1.4

(1.1

,1.7

)4.1

(3.8

,4.4

)4.1

(3.8

,4.4

)4.1

(3.7

,4.4

)4.6

(4.3

,4.9

)6.3

(5.9

,6.6

)7.4

(7.1

,7.6

)7.3

(7,7.5

)7.1

(6.7

,7.4

)7.6

(7.3

,7.9

)7.7

(7.4

,8)

8.7

(8.4

,8.9

)

3A

-3SW

L–

––

0(0,0)

2.7

(2.4

,3)

2.7

(2.3

,3)

2.7

(2.3

,3)

3.2

(2.9

,3.6

)4.9

(4.5

,5.2

)6

(5.6

,6.3

)5.8

(5.5

,6.2

)5.7

(5.4

,6)

6.2

(5.8

,6.5

)6.3

(6,6.6

)7.3

(6.9

,7.6

)

4A

-0SW

L–

––

–0

(0,0)

0(-0

.2,0.1

)-0

.1(-0

.3,

0.2

)0.5

(0.2

,0.8

)2.1

(1.8

,2.4

)3.2

(2.9

,3.5

)3.1

(2.8

,3.4

)3

(2.7

,3.2

)3.5

(3.1

,3.8

)3.6

(3.3

,3.9

)4.5

(4.3

,4.8

)

4A

-1SW

L–

––

––

0(0,0)

0(-0

.3,0.3

)0.6

(0.3

,0.8

)2.2

(1.9

,2.5

)3.3

(3,3.6

)3.2

(2.9

,3.5

)3

(2.7

,3.3

)3.5

(3.2

,3.8

)3.7

(3.4

,4)

4.6

(4.3

,4.9

)

4A

-2SW

L–

––

––

–0

(0,0)

0.6

(0.3

,0.9

)2.2

(1.9

,2.5

)3.3

(3,3.6

)3.2

(2.9

,3.4

)3

(2.7

,3.3

)3.5

(3.2

,3.8

)3.7

(3.4

,4)

4.6

(4.3

,4.9

)

4A

-3SW

L–

––

––

––

0(0,0)

1.6

(1.3

,1.9

)2.7

(2.4

,3)

2.6

(2.3

,3)

2.5

(2.1

,2.8

)3

(2.6

,3.3

)3.1

(2.8

,3.4

)4

(3.7

,4.3

)

4A

-4SW

L–

––

––

––

–0

(0,0)

1.1

(0.8

,1.4

)1

(0.7

,1.3

)0.8

(0.5

,1.1

)1.3

(1,1.7

)1.5

(1.1

,1.8

)2.4

(2.1

,2.7

)

5A

-0SW

L–

––

––

––

––

0(0,0)

-0.1

(-0

.3,

0.1

)-0

.3(-0

.6,0)

0.2

(0,0.5

)0.4

(0.1

,0.6

)1.3

(1,1.6

)

5A

-1SW

L–

––

––

––

––

–0

(0,0)

-0.2

(-0

.5,

0.1

)0.3

(0.1

,0.6

)0.5

(0.2

,0.7

)1.4

(1.2

,1.7

)

5A

-2SW

L–

––

––

––

––

––

0(0,0)

0.5

(0.2

,0.8

)0.7

(0.4

,1)

1.6

(1.3

,1.9

)

5A

-3SW

L–

––

––

––

––

––

–0

(0,0)

0.2

(-0

.1,0.4

)1.1

(0.8

,1.4

)

5A

-4SW

L–

––

––

––

––

––

––

0(0,0)

0.9

(0.7

,1.2

)

5A

-5SW

L–

––

––

––

––

––

––

–0

(0,0)

Tab

leG

.8:

Pal

liat

ive

resu

lts

for

vary

ing

the

nu

mb

erof

short

wait

ing

list

faci

liti

eson

the

nu

mb

erof

die

din

hosp

ital

pati

ents


3A

-0SW

L3A

-1SW

L3A

-2SW

L3A

-3SW

L4A

-0SW

L4A

-1SW

L4A

-2SW

L4A

-3SW

L4A

-4SW

L5A

-0SW

L5A

-1SW

L5A

-2SW

L5A

-3SW

L5A

-4SW

L5A

-5SW

L

3A

-0SW

L0

(0,0)

39.5

(32.7

,46.3

)

175.8

(166.1

,185.5

)299

(288.7

,309.2

)344.2

(336.4

,351.9

)352

(344.4

,359.6

)400.5

(390.9

,410)

485.3

(475.8

,494.8

)563

(553.2

,572.9

)597.8

(590.9

,604.7

)599.2

(592.2

,606.2

)629.1

(620.5

,637.7

)677.1

(669.1

,685)

724

(716.6

,731.5

)765.9

(758.4

,773.4

)

3A

-1SW

L–

0(0,0)

136.3

(126.1

,146.6

)259.5

(248.5

,270.5

)304.7

(296.7

,312.7

)312.5

(304.2

,320.9

)361

(351,

371)

445.8

(436.2

,455.5

)523.6

(513.8

,533.4

)558.4

(550.8

,565.9

)559.7

(552,

567.5

)589.7

(580.2

,599.1

)637.6

(628.4

,646.8

)684.6

(676.7

,692.4

)726.4

(717.9

,734.9

)3A

-2SW

L–

–0

(0,0)

123.2

(110.5

,135.8

)168.4

(158.2

,178.5

)176.2

(165.5

,186.8

)224.7

(212.8

,236.5

)309.5

(297,

322)

387.2

(375.5

,398.9

)422

(411.2

,432.8

)423.4

(413.1

,433.8

)453.3

(441.2

,465.5

)501.3

(489.5

,513)

548.2

(538.4

,558.1

)590.1

(579.7

,600.5

)3A

-3SW

L–

––

0(0,0)

45.2

(34.8

,55.6

)53

(42.8

,63.3

)101.5

(90.7

,112.3

)186.3

(173.3

,199.4

)264.1

(252,

276.2

)298.9

(289.3

,308.4

)300.3

(290.3

,310.2

)330.2

(318.6

,341.7

)378.1

(367.1

,389.1

)425.1

(414.6

,435.6

)466.9

(458,

475.9

)

4A

-0SW

L–

––

–0

(0,0)

7.8

(1.5

,14.2

)56.3

(47.7

,64.9

)141.1

(131,

151.3

)218.9

(209.7

,228)

253.7

(247.2

,260.1

)255.1

(247.9

,262.2

)285

(276.4

,293.6

)332.9

(324.8

,341)

379.9

(372.9

,386.9

)421.7

(414.7

,428.8

)4A

-1SW

L–

––

––

0(0,0)

48.5

(40.1

,56.9

)133.3

(123,

143.6

)211

(201.9

,220.2

)245.8

(239.7

,252)

247.2

(239.9

,254.5

)277.1

(268.2

,286.1

)325.1

(317.2

,332.9

)372.1

(364.2

,379.9

)413.9

(406.6

,421.2

)4A

-2SW

L–

––

––

–0

(0,0)

84.8

(73.7

,95.9

)162.6

(152.7

,172.5

)197.4

(188.4

,206.3

)198.8

(189.6

,208)

228.7

(218.3

,239)

276.6

(267.8

,285.4

)323.6

(314.6

,332.6

)365.4

(356.8

,374)

4A

-3SW

L–

––

––

––

0(0,0)

77.7

(65.7

,89.8

)112.5

(102.8

,122.2

)113.9

(103.5

,124.3

)143.8

(132.2

,155.4

)191.8

(180.9

,202.6

)238.7

(228.9

,248.6

)280.6

(270.1

,291.1

)4A

-4SW

L–

––

––

––

–0

(0,0)

34.8

(25.1

,44.5

)36.2

(27.4

,45)

66.1

(54.5

,77.7

)114

(104,

124.1

)161

(152.1

,169.9

)202.8

(194,

211.7

)

5A

-0SW

L–

––

––

––

––

0(0,0)

1.4

(-3

.5,6.2

)31.3

(23.9

,38.7

)79.2

(71.8

,86.6

)126.2

(119.4

,133)

168

(161.4

,174.7

)5A

-1SW

L–

––

––

––

––

–0

(0,0)

29.9

(22,

37.8

)77.8

(70.4

,85.3

)124.8

(118.5

,131.2

)166.7

(159.7

,173.6

)5A

-2SW

L–

––

––

––

––

––

0(0,0)

47.9

(38.9

,57)

94.9

(86.7

,103.1

)136.7

(127.8

,145.7

)5A

-3SW

L–

––

––

––

––

––

–0

(0,0)

47

(39.6

,54.4

)88.8

(80.7

,96.9

)5A

-4SW

L–

––

––

––

––

––

––

0(0,0)

41.8

(34.7

,48.9

)5A

-5SW

L–

––

––

––

––

––

––

–0

(0,0)

Tab

leG

.9:

Reh

abil

itat

ion

resu

lts

for

vary

ing

the

nu

mb

erof

short

wait

ing

list

faci

liti

eson

the

nu

mb

erof

AL

Cd

ays


3A

-0SW

L3A

-1SW

L3A

-2SW

L3A

-3SW

L4A

-0SW

L4A

-1SW

L4A

-2SW

L4A

-3SW

L4A

-4SW

L5A

-0SW

L5A

-1SW

L5A

-2SW

L5A

-3SW

L5A

-4SW

L5A

-5SW

L

3A

-0SW

L0

(0,0)

-0.1

(-0

.3,

0.2

)

0.8

(0.5

,1)

0.6

(0.3

,0.9

)2.6

(2.4

,2.9

)2.9

(2.7

,3.1

)3

(2.7

,3.2

)3.3

(3.1

,3.6

)3.6

(3.3

,3.9

)4.8

(4.5

,5)

4.7

(4.5

,5)

5(4.8

,5.2

)5

(4.8

,5.2

)5.3

(5,5.6

)5.2

(4.9

,5.5

)

3A

-1SW

L–

0(0,0)

0.8

(0.6

,1.1

)0.7

(0.4

,1)

2.7

(2.5

,2.9

)3

(2.8

,3.2

)3

(2.8

,3.3

)3.4

(3.1

,3.7

)3.7

(3.4

,3.9

)4.9

(4.6

,5.1

)4.8

(4.6

,5)

5.1

(4.9

,5.3

)5.1

(4.8

,5.3

)5.4

(5.1

,5.6

)5.3

(5,5.5

)

3A

-2SW

L–

–0

(0,0)

-0.1

(-0

.4,

0.2

)1.9

(1.6

,2.1

)2.2

(1.9

,2.4

)2.2

(2,2.4

)2.6

(2.3

,2.9

)2.8

(2.6

,3.1

)4

(3.8

,4.3

)4

(3.8

,4.2

)4.3

(4,4.5

)4.2

(4,4.5

)4.5

(4.3

,4.8

)4.4

(4.2

,4.7

)

3A

-3SW

L–

––

0(0,0)

2(1.8

,2.2

)2.3

(2,2.5

)2.4

(2.1

,2.6

)2.7

(2.4

,3)

3(2.7

,3.2

)4.2

(3.9

,4.4

)4.1

(3.9

,4.3

)4.4

(4.1

,4.6

)4.4

(4.1

,4.6

)4.7

(4.4

,4.9

)4.6

(4.3

,4.8

)

4A

-0SW

L–

––

–0

(0,0)

0.3

(0.1

,0.5

)0.4

(0.2

,0.5

)0.7

(0.5

,0.9

)1

(0.8

,1.2

)2.2

(2,2.3

)2.1

(1.9

,2.3

)2.4

(2.2

,2.6

)2.4

(2.2

,2.5

)2.7

(2.5

,2.8

)2.6

(2.4

,2.8

)

4A

-1SW

L–

––

––

0(0,0)

0.1

(-0

.1,0.3

)0.4

(0.2

,0.6

)0.7

(0.5

,0.9

)1.9

(1.7

,2)

1.8

(1.7

,2)

2.1

(1.9

,2.3

)2.1

(1.9

,2.2

)2.4

(2.2

,2.6

)2.3

(2.1

,2.5

)

4A

-2SW

L–

––

––

–0

(0,0)

0.4

(0.1

,0.6

)0.6

(0.4

,0.9

)1.8

(1.6

,2)

1.8

(1.6

,1.9

)2

(1.8

,2.2

)2

(1.8

,2.2

)2.3

(2.1

,2.5

)2.2

(2,2.5

)

4A

-3SW

L–

––

––

––

0(0,0)

0.3

(0,0.5

)1.5

(1.2

,1.7

)1.4

(1.2

,1.6

)1.7

(1.5

,1.9

)1.7

(1.4

,1.9

)2

(1.8

,2.2

)1.9

(1.6

,2.1

)

4A

-4SW

L–

––

––

––

–0

(0,0)

1.2

(1,1.4

)1.1

(0.9

,1.3

)1.4

(1.2

,1.6

)1.4

(1.2

,1.6

)1.7

(1.5

,1.9

)1.6

(1.4

,1.8

)

5A

-0SW

L–

––

––

––

––

0(0,0)

-0.1

(-0

.2,

0.1

)0.2

(0.1

,0.4

)0.2

(0,0.4

)0.5

(0.3

,0.7

)0.4

(0.2

,0.6

)

5A

-1SW

L–

––

––

––

––

–0

(0,0)

0.3

(0.1

,0.5

)0.3

(0.1

,0.4

)0.6

(0.4

,0.7

)0.5

(0.3

,0.7

)

5A

-2SW

L–

––

––

––

––

––

0(0,0)

0(-0

.2,0.2

)0.3

(0.1

,0.5

)0.2

(0,0.4

)

5A

-3SW

L–

––

––

––

––

––

–0

(0,0)

0.3

(0.1

,0.5

)0.2

(0,0.4

)

5A

-4SW

L–

––

––

––

––

––

––

0(0,0)

-0.1

(-0

.3,

0.1

)5A

-5SW

L–

––

––

––

––

––

––

–0

(0,0)

Tab

leG

.10:

Reh

abil

itat

ion

resu

lts

for

vary

ing

the

nu

mb

erof

short

wait

ing

list

faci

liti

eson

the

nu

mb

erof

die

din

hosp

ital

pati

ents

Appendix H

Pairwise comparison charts - updating

short waiting lists daily

96

Appendix H. Pairwise comparison charts - updating short waiting lists daily 97

3A

-2SW

L60

3A

-3SW

L60

4A

-3SW

L60

4A

-4SW

L60

5A

-4SW

L60

5A

-5SW

L60

3A

-2SW

LD

3A

-3SW

LD

4A

-3SW

LD

4A

-4SW

LD

5A

-4SW

LD

5A

-5SW

LD

3A

-2SW

L60

0(0,0)

13.9

(3.9

,23.9

)171.2

(156.6

,185.9

)N/A

N/A

N/A

0.5

(-5

.5,6.6

)41.1

(28,54.1

)176.9

(163.2

,190.5

)N/A

N/A

N/A

3A

-3SW

L60

–0

(0,0)

157.3

(142.5

,172.1

)N/A

N/A

N/A

-13.4

(-23.2

,-3.5

)27.1

(13.6

,40.7

)162.9

(149,

176.9

)N/A

N/A

N/A

4A

-3SW

L60

––

0(0,0)

N/A

N/A

N/A

-170.7

(-184.5

,-156.9

)-130.2

(-147.6

,-112.7

)5.6

(-2

.6,13.9

)N/A

N/A

N/A

4A

-4SW

L60

––

–N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

5A

-4SW

L60

––

––

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

5A

-5SW

L60

––

––

–N/A

N/A

N/A

N/A

N/A

N/A

N/A

3A

-2SW

LD

––

––

––

0(0,0)

40.5

(27.7

,53.4

)176.3

(163.1

,189.5

)N/A

N/A

N/A

3A

-3SW

LD

––

––

––

–0

(0,0)

135.8

(118.6

,153)

N/A

N/A

N/A

4A

-3SW

LD

––

––

––

––

0(0,0)

N/A

N/A

N/A

4A

-4SW

LD

––

––

––

––

–N/A

N/A

N/A

5A

-4SW

LD

––

––

––

––

––

N/A

N/A

5A

-5SW

LD

––

––

––

––

––

–N/A

Tab

leH

.1:

CC

Cre

sult

sfo

ru

pd

atin

gth

esh

ort

wait

ing

list

sd

ail

y(D

)co

mp

are

dto

the

up

dati

ng

ever

y60

day

s(6

0)

on

the

nu

mb

erof

AL

Cd

ays

3A

-2SW

L60

3A

-3SW

L60

4A

-3SW

L60

4A

-4SW

L60

5A

-4SW

L60

5A

-5SW

L60

3A

-2SW

LD

3A

-3SW

LD

4A

-3SW

LD

4A

-4SW

LD

5A

-4SW

LD

5A

-5SW

LD

3A

-2SW

L60

0(0,0)

0(-0

.1,0.1

)0.4

(0.3

,0.5

)N/A

N/A

N/A

-0.1

(-0

.1,0)

0.1

(0,0.2

)0.5

(0.4

,0.6

)N/A

N/A

N/A

3A

-3SW

L60

–0

(0,0)

0.4

(0.3

,0.5

)N/A

N/A

N/A

0(-0

.1,0.1

)0.1

(0,0.2

)0.5

(0.4

,0.6

)N/A

N/A

N/A

4A

-3SW

L60

––

0(0,0)

N/A

N/A

N/A

-0.5

(-0.6

,-0.4

)-0.3

(-0.4

,-0.2

)0.1

(0,0.2

)N/A

N/A

N/A

4A

-4SW

L60

––

–N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

5A

-4SW

L60

––

––

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

5A

-5SW

L60

––

––

–N/A

N/A

N/A

N/A

N/A

N/A

N/A

3A

-2SW

LD

––

––

––

0(0,0)

0.1

(0,0.2

)0.6

(0.5

,0.6

)N/A

N/A

N/A

3A

-3SW

LD

––

––

––

–0

(0,0)

0.4

(0.3

,0.5

)N/A

N/A

N/A

4A

-3SW

LD

––

––

––

––

0(0,0)

N/A

N/A

N/A

4A

-4SW

LD

––

––

––

––

–N/A

N/A

N/A

5A

-4SW

LD

––

––

––

––

––

N/A

N/A

5A

-5SW

LD

––

––

––

––

––

–N/A

Tab

leH

.2:

CC

Cre

sult

sfo

ru

pd

atin

gth

esh

ort

wai

tin

gli

sts

dail

y(D

)co

mp

are

dto

the

up

dati

ng

ever

y60

day

s(6

0)

on

the

nu

mb

erof

die

din

hosp

ital

pati

ents


3A

-2SW

L60

3A

-3SW

L60

4A

-3SW

L60

4A

-4SW

L60

5A

-4SW

L60

5A

-5SW

L60

3A

-2SW

LD

3A

-3SW

LD

4A

-3SW

LD

4A

-4SW

LD

5A

-4SW

LD

5A

-5SW

LD

3A

-2SW

L60

0(0,0)

-3.9

(-6.3

,-1.5

)38

(34.1

,41.9

)37.2

(33.6

,40.9

)70.3

(65.9

,74.7

)81.3

(76.3

,86.3

)5.7

(2.4

,9.1

)23.6

(20.1

,27.1

)44

(40.2

,47.8

)60.1

(56.2

,63.9

)N/A

N/A

3A

-3SW

L60

–0

(0,0)

41.9

(38.4

,45.4

)41.2

(38.1

,44.2

)74.2

(70.6

,77.9

)85.2

(81.3

,89.2

)9.7

(6.7

,12.7

)27.5

(24.6

,30.5

)47.9

(45,50.9

)64

(60.8

,67.2

)N/A

N/A

4A

-3SW

L60

––

0(0,0)

-0.8

(-4

.5,2.9

)32.3

(27.5

,37.1

)43.3

(38.1

,48.6

)-32.3

(-36.2

,-28.3

)-14.4

(-18.6

,-10.2

)6

(2.1

,9.9

)22.1

(17.8

,26.4

)N/A

N/A

4A

-4SW

L60

––

–0

(0,0)

33.1

(28.4

,37.7

)44.1

(39.5

,48.7

)-31.5

(-35.2

,-27.8

)-13.6

(-17.2

,-10.1

)6.8

(3.2

,10.3

)22.9

(19,26.7

)N/A

N/A

5A

-4SW

L60

––

––

0(0,0)

11

(6.5

,15.5

)-64.6

(-69,

-60.1

)-4

6.7

(-5

1.2

,-4

2.2

)-26.3

(-31,

-21.6

)-10.2

(-15,

-5.5

)N/A

N/A

5A

-5SW

L60

––

––

–0

(0,0)

-75.6

(-80.3

,-70.8

)-57.7

(-62.3

,-53.1

)-37.3

(-41.6

,-33.1

)-21.2

(-26,

-16.5

)N/A

N/A

3A

-2SW

LD

––

––

––

0(0,0)

17.9

(13.9

,21.8

)38.2

(34.3

,42.1

)54.3

(50.5

,58.1

)N/A

N/A

3A

-3SW

LD

––

––

––

–0

(0,0)

20.4

(16.4

,24.3

)36.5

(32.2

,40.8

)N/A

N/A

4A

-3SW

LD

––

––

––

––

0(0,0)

16.1

(12.4

,19.8

)N/A

N/A

4A

-4SW

LD

––

––

––

––

–0

(0,0)

N/A

N/A

5A

-4SW

LD

––

––

––

––

––

N/A

N/A

5A

-5SW

LD

––

––

––

––

––

N/A

Tab

leH

.3:

Con

vale

scen

tre

sult

sfo

ru

pd

atin

gth

esh

ort

wait

ing

list

sd

ail

y(D

)co

mp

are

dto

the

up

dati

ng

ever

y60

day

s(6

0)

on

the

nu

mb

erof

AL

Cd

ays

3A

-2SW

L60

3A

-3SW

L60

4A

-3SW

L60

4A

-4SW

L60

5A

-4SW

L60

5A

-5SW

L60

3A

-2SW

LD

3A

-3SW

LD

4A

-3SW

LD

4A

-4SW

LD

5A

-4SW

LD

5A

-5SW

LD

3A

-2SW

L60

0(0,0)

0(-0

.1,0)

0.1

(0,0.1

)0.1

(0,0.1

)0.1

(0.1

,0.2

)0.1

(0.1

,0.2

)0

(0,0.1

)0

(-0

.1,0)

0.1

(0,0.1

)0.1

(0.1

,0.1

)N/A

N/A

3A

-3SW

L60

–0

(0,0)

0.1

(0.1

,0.1

)0.1

(0,0.1

)0.2

(0.1

,0.2

)0.2

(0.1

,0.2

)0

(0,0.1

)0

(-0

.1,0)

0.1

(0.1

,0.1

)0.1

(0.1

,0.2

)N/A

N/A

4A

-3SW

L60

––

0(0,0)

0(0,0)

0.1

(0,0.1

)0.1

(0,0.1

)0

(-0

.1,0)

-0.1

(-0.1

,-0.1

)0

(0,0)

0(0,0.1

)N/A

N/A

4A

-4SW

L60

––

–0

(0,0)

0.1

(0,0.1

)0.1

(0,0.1

)0

(-0

.1,0)

-0.1

(-0.1

,-0.1

)0

(0,0)

0(0,0.1

)N/A

N/A

5A

-4SW

L60

––

––

0(0,0)

0(0,0)

-0.1

(-0.2

,-0.1

)-0.2

(-0.2

,-0.1

)-0

.1(-0

.1,0)

0(-0

.1,0)

N/A

N/A

5A

-5SW

L60

––

––

–0

(0,0)

-0.1

(-0.2

,-0.1

)-0.2

(-0.2

,-0.1

)-0

.1(-0

.1,0)

0(-0

.1,0)

N/A

N/A

3A

-2SW

LD

––

––

––

0(0,0)

-0.1

(-0

.1,0)

0(0,0.1

)0.1

(0,0.1

)N/A

N/A

3A

-3SW

LD

––

––

––

–0

(0,0)

0.1

(0.1

,0.1

)0.1

(0.1

,0.2

)N/A

N/A

4A

-3SW

LD

––

––

––

––

0(0,0)

0(0,0.1

)N/A

N/A

4A

-4SW

LD

––

––

––

––

–0

(0,0)

N/A

N/A

5A

-4SW

LD

––

––

––

––

––

N/A

N/A

5A

-5SW

LD

––

––

––

––

––

–N/A

Tab

leH

.4:

Con

vale

scen

tre

sult

sfo

ru

pd

atin

gth

esh

ort

wait

ing

list

sd

ail

y(D

)co

mp

are

dto

the

up

dati

ng

ever

y60

day

s(6

0)

on

the

nu

mb

erof

die

din

hosp

ital

pat

ients


3A

-2SW

L60

3A

-3SW

L60

4A

-3SW

L60

4A

-4SW

L60

5A

-4SW

L60

5A

-5SW

L60

3A

-2SW

LD

3A

-3SW

LD

4A

-3SW

LD

4A

-4SW

LD

5A

-4SW

LD

5A

-5SW

LD

3A

-2SW

L60

0(0,0)

58.3

(25.1

,91.5

)528.4

(493.9

,563)

617.2

(579.5

,655)

906.4

(873.9

,938.9

)1000.8

(964.2

,1037.3

)485.1

(449.5

,520.7

)533.1

(497.9

,568.3

)634.1

(595.2

,673)

636.4

(597.5

,675.2

)867.7

(836.8

,898.7

)1023.9

(990.5

,1057.3

)3A

-3SW

L60

–0

(0,0)

470.1

(431,

509.2

)558.9

(517.5

,600.3

)848.1

(810.5

,885.7

)942.4

(901,

983.9

)426.8

(384.2

,469.4

)474.8

(432.5

,517.1

)575.8

(529.6

,622)

578

(532.4

,623.7

)809.4

(772.5

,846.3

)965.6

(928.9

,1002.2

)4A

-3SW

L60

––

0(0,0)

88.8

(63.2

,114.4

)378

(349.6

,406.3

)472.3

(444.9

,499.8

)-43.3

(-73.8

,-12.9

)4.7

(-2

7.4

,36.7

)105.7

(73.3

,138)

107.9

(75.1

,140.7

)339.3

(310.4

,368.1

)495.5

(465.6

,525.3

)4A

-4SW

L60

––

–0

(0,0)

289.2

(259.8

,318.6

)383.5

(355.2

,411.9

)-132.1

(-162.4

,-101.8

)-84.1

(-115.7

,-52.5

)16.9

(-1

5,48.7

)19.1

(-1

2.9

,51.2

)250.5

(221.5

,279.5

)406.7

(375.9

,437.5

)5A

-4SW

L60

––

––

0(0,0)

94.4

(75.8

,113)

-421.3

(-448.5

,-394.1

)-373.3

(-398.6

,-348)

-272.3

(-300.4

,-244.2

)-270

(-298.4

,-241.7

)-38.7

(-61.7

,-15.6

)117.5

(94.1

,141)

5A

-5SW

L60

––

––

–0

(0,0)

-515.6

(-543.7

,-487.6

)-467.6

(-493.7

,-441.6

)-366.7

(-392.6

,-340.8

)-364.4

(-390.5

,-338.3

)-133

(-157.3

,-108.8

)23.2

(-1

.8,48.1

)

3A

-2SW

LD

––

––

––

0(0,0)

48

(25.2

,70.8

)149

(115.3

,182.6

)151.2

(116.7

,185.8

)382.6

(350.6

,414.6

)538.8

(507.8

,569.8

)3A

-3SW

LD

––

––

––

–0

(0,0)

101

(72.2

,129.7

)103.2

(73.6

,132.8

)334.6

(306.4

,362.7

)490.8

(461.4

,520.1

)4A

-3SW

LD

––

––

––

––

0(0,0)

2.3

(-2

.2,6.7

)233.6

(203.6

,263.6

)389.8

(359.1

,420.5

)4A

-4SW

LD

––

––

––

––

–0

(0,0)

231.3

(201,

261.7

)387.5

(356.6

,418.5

)5A

-4SW

LD

––

––

––

––

––

0(0,0)

156.2

(135.1

,177.3

)5A

-5SW

LD

––

––

––

––

––

–0

(0,0)

Tab

leH

.5:

LT

Cre

sult

sfo

ru

pd

atin

gth

esh

ort

wait

ing

list

sdail

y(D

)co

mp

are

dto

the

up

dati

ng

ever

y60

day

s(6

0)

on

the

nu

mb

erof

AL

Cd

ays

3A

-2SW

L60

3A

-3SW

L60

4A

-3SW

L60

4A

-4SW

L60

5A

-4SW

L60

5A

-5SW

L60

3A

-2SW

LD

3A

-3SW

LD

4A

-3SW

LD

4A

-4SW

LD

5A

-4SW

LD

5A

-5SW

LD

3A

-2SW

L60

0(0,0)

0(-0

.2,0.2

)3

(2.8

,3.2

)3.1

(2.8

,3.4

)4.5

(4.2

,4.7

)4.8

(4.5

,5)

0(-0

.2,0.2

)0.3

(0,0.5

)3.1

(2.9

,3.3

)3.2

(2.9

,3.4

)4.3

(4.1

,4.5

)4.8

(4.5

,5)

3A

-3SW

L60

–0

(0,0)

3(2.8

,3.2

)3.1

(2.8

,3.4

)4.5

(4.2

,4.7

)4.8

(4.5

,5)

0(-0

.2,0.2

)0.3

(0,0.5

)3.1

(2.9

,3.4

)3.2

(2.9

,3.4

)4.3

(4.1

,4.6

)4.8

(4.5

,5)

4A

-3SW

L60

––

0(0,0)

0.1

(-0

.2,0.4

)1.5

(1.3

,1.7

)1.8

(1.5

,2)

-3

(-3.2

,-2.8

)-2.8

(-3,-2.5

)0.1

(-0

.1,0.3

)0.2

(-0

.1,0.4

)1.3

(1.1

,1.6

)1.8

(1.5

,2)

4A

-4SW

L60

––

–0

(0,0)

1.4

(1.1

,1.7

)1.6

(1.3

,1.9

)-3.1

(-3.4

,-2.8

)-2.9

(-3.2

,-2.5

)0

(-0

.3,0.3

)0

(-0

.3,0.3

)1.2

(0.9

,1.5

)1.6

(1.3

,1.9

)

5A

-4SW

L60

––

––

0(0,0)

0.3

(0.1

,0.4

)-4.5

(-4.7

,-4.2

)-4.2

(-4.5

,-4)

-1.4

(-1.6

,-1.1

)-1.3

(-1.6

,-1.1

)-0

.2(-0

.3,0)

0.3

(0.1

,0.5

)

5A

-5SW

L60

––

––

–0

(0,0)

-4.8

(-5,-4.5

)-4.5

(-4.8

,-4.2

)-1.6

(-1.9

,-1.4

)-1.6

(-1.8

,-1.4

)-0.4

(-0.6

,-0.2

)0

(-0

.2,0.2

)

3A

-2SW

LD

––

––

––

0(0,0)

0.2

(0,0.5

)3.1

(2.9

,3.4

)3.2

(2.9

,3.4

)4.3

(4.1

,4.6

)4.7

(4.5

,5)

3A

-3SW

LD

––

––

––

–0

(0,0)

2.9

(2.6

,3.1

)2.9

(2.6

,3.2

)4.1

(3.8

,4.3

)4.5

(4.2

,4.8

)4A

-3SW

LD

––

––

––

––

0(0,0)

0(-0

.2,0.3

)1.2

(1,1.5

)1.6

(1.4

,1.9

)4A

-4SW

LD

––

––

––

––

–0

(0,0)

1.2

(1,1.4

)1.6

(1.3

,1.8

)5A

-4SW

LD

––

––

––

––

––

0(0,0)

0.4

(0.2

,0.6

)5A

-5SW

LD

––

––

––

––

––

–0

(0,0)

Tab

leH

.6:

LT

Cre

sult

sfo

ru

pd

atin

gth

esh

ort

wai

tin

glist

sdail

y(D

)co

mp

are

dto

the

up

dati

ng

ever

y60

day

s(6

0)

on

the

nu

mb

erof

die

din

hosp

ital

pati

ents


3A

-2SW

L60

3A

-3SW

L60

4A

-3SW

L60

4A

-4SW

L60

5A

-4SW

L60

5A

-5SW

L60

3A

-2SW

LD

3A

-3SW

LD

4A

-3SW

LD

4A

-4SW

LD

5A

-4SW

LD

5A

-5SW

LD

3A

-2SW

L60

0(0,0)

78.6

(71.7

,85.5

)175.5

(167.8

,183.2

)218.8

(211.2

,226.3

)259.5

(252,

266.9

)285.6

(278.7

,292.6

)-10.2

(-18.5

,-1.8

)88.2

(79.6

,96.9

)171

(162,

179.9

)223.9

(216.8

,230.9

)258

(250.6

,265.4

)292.7

(285.8

,299.5

)3A

-3SW

L60

–0

(0,0)

96.9

(90.5

,103.3

)140.1

(134.3

,146)

180.8

(175.4

,186.3

)207

(201.5

,212.5

)-88.8

(-95.9

,-81.6

)9.6

(2.2

,17)

92.3

(84.7

,99.9

)145.2

(139.7

,150.8

)179.4

(173.6

,185.1

)214

(208.4

,219.6

)4A

-3SW

L60

––

0(0,0)

43.2

(37.9

,48.6

)83.9

(78.2

,89.6

)110.1

(105.2

,115.1

)-185.7

(-192.9

,-178.5

)-87.3

(-94.1

,-80.4

)-4

.6(-1

1.1

,2)

48.3

(43.1

,53.6

)82.5

(77.1

,87.9

)117.1

(112.1

,122.2

)4A

-4SW

L60

––

–0

(0,0)

40.7

(35.4

,46)

66.9

(62.3

,71.4

)-228.9

(-236.6

,-221.2

)-130.5

(-137.6

,-123.4

)-47.8

(-53.9

,-41.6

)5.1

(0.2

,10)

39.2

(34,44.5

)73.9

(69.1

,78.7

)5A

-4SW

L60

––

––

0(0,0)

26.2

(22.4

,30)

-269.6

(-276.7

,-262.5

)-171.2

(-177.8

,-164.6

)-88.5

(-94.6

,-82.4

)-35.6

(-40.2

,-31)

-1.5

(-5

.8,2.9

)33.2

(28.5

,37.9

)5A

-5SW

L60

––

––

–0

(0,0)

-295.8

(-302.4

,-289.2

)-197.4

(-203.6

,-191.1

)-114.7

(-120.3

,-109)

-61.8

(-66.2

,-57.4

)-27.6

(-31.3

,-24)

7(3.2

,10.8

)

3A

-2SW

LD

––

––

––

0(0,0)

98.4

(89.7

,107.1

)181.1

(173.2

,189)

234

(226.9

,241.2

)268.1

(260.8

,275.5

)302.8

(296,

309.6

)3A

-3SW

LD

––

––

––

–0

(0,0)

82.7

(75.2

,90.3

)135.6

(129.3

,142)

169.7

(163.6

,175.9

)204.4

(198.6

,210.2

)4A

-3SW

LD

––

––

––

––

0(0,0)

52.9

(47.1

,58.7

)87

(81.5

,92.6

)121.7

(115.8

,127.6

)4A

-4SW

LD

––

––

––

––

–0

(0,0)

34.1

(29,39.3

)68.8

(64.6

,73)

5A

-4SW

LD

––

––

––

––

––

0(0,0)

34.7

(30.5

,38.8

)5A

-5SW

LD

––

––

––

––

––

–0

(0,0)

Tab

leH

.7:

Pal

liat

ive

resu

lts

for

up

dat

ing

the

short

wait

ing

list

sd

ail

y(D

)co

mp

are

dto

the

up

dati

ng

ever

y60

day

s(6

0)

on

the

nu

mb

erof

AL

Cd

ays

3A

-2SW

L60

3A

-3SW

L60

4A

-3SW

L60

4A

-4SW

L60

5A

-4SW

L60

5A

-5SW

L60

3A

-2SW

LD

3A

-3SW

LD

4A

-3SW

LD

4A

-4SW

LD

5A

-4SW

LD

5A

-5SW

LD

3A

-2SW

L60

0(0,0)

1.4

(1.1

,1.7

)4.6

(4.3

,4.9

)6.3

(5.9

,6.6

)7.7

(7.4

,8)

8.7

(8.4

,8.9

)0.4

(0.1

,0.7

)2.3

(1.9

,2.6

)5.2

(4.9

,5.5

)6.6

(6.3

,7)

8(7.6

,8.3

)11.2

(10.9

,11.5

)3A

-3SW

L60

–0

(0,0)

3.2

(2.9

,3.6

)4.9

(4.5

,5.2

)6.3

(6,6.6

)7.3

(6.9

,7.6

)-1

(-1.3

,-0.7

)0.9

(0.5

,1.2

)3.8

(3.5

,4.1

)5.2

(4.9

,5.5

)6.5

(6.2

,6.9

)9.8

(9.5

,10.1

)4A

-3SW

L60

––

0(0,0)

1.6

(1.3

,1.9

)3.1

(2.8

,3.4

)4

(3.7

,4.3

)-4.2

(-4.5

,-3.9

)-2.4

(-2.7

,-2)

0.6

(0.3

,0.9

)2

(1.7

,2.3

)3.3

(3,3.6

)6.6

(6.4

,6.7

)

4A

-4SW

L60

––

–0

(0,0)

1.5

(1.1

,1.8

)2.4

(2.1

,2.7

)-5.9

(-6.2

,-5.5

)-4

(-4.3

,-3.6

)-1

(-1.4

,-0.7

)0.4

(0.1

,0.7

)1.7

(1.3

,2)

5(4.7

,5.2

)

5A

-4SW

L60

––

––

0(0,0)

0.9

(0.7

,1.2

)-7.3

(-7.6

,-7)

-5.5

(-5.8

,-5.1

)-2.5

(-2.8

,-2.2

)-1.1

(-1.4

,-0.8

)0.2

(-0

.1,0.5

)3.5

(3.2

,3.7

)

5A

-5SW

L60

––

––

–0

(0,0)

-8.3

(-8.5

,-8)

-6.4

(-6.7

,-6.1

)-3.5

(-3.8

,-3.1

)-2

(-2.3

,-1.7

)-0.7

(-1,-0.4

)2.5

(2.2

,2.8

)

3A

-2SW

LD

––

––

––

0(0,0)

1.9

(1.6

,2.2

)4.8

(4.5

,5.1

)6.2

(6,6.5

)7.6

(7.3

,7.8

)10.8

(10.6

,11)

3A

-3SW

LD

––

––

––

–0

(0,0)

2.9

(2.6

,3.3

)4.4

(4,4.7

)5.7

(5.3

,6)

8.9

(8.6

,9.2

)4A

-3SW

LD

––

––

––

––

0(0,0)

1.4

(1.1

,1.7

)2.7

(2.4

,3.1

)6

(5.7

,6.3

)4A

-4SW

LD

––

––

––

––

–0

(0,0)

1.3

(1,1.6

)4.6

(4.3

,4.8

)5A

-4SW

LD

––

––

––

––

––

0(0,0)

3.3

(3,3.5

)5A

-5SW

LD

––

––

––

––

––

–0

(0,0)

Tab

leH

.8:

Pal

liat

ive

resu

lts

for

up

dat

ing

the

shor

tw

ait

ing

list

sd

ail

y(D

)co

mp

are

dto

the

up

dati

ng

ever

y60

day

s(6

0)

on

the

nu

mb

erof

die

din

hosp

ital

pat

ients


3A

-2SW

L60

3A

-3SW

L60

4A

-3SW

L60

4A

-4SW

L60

5A

-4SW

L60

5A

-5SW

L60

3A

-2SW

LD

3A

-3SW

LD

4A

-3SW

LD

4A

-4SW

LD

5A

-4SW

LD

5A

-5SW

LD

3A

-2SW

L60

0(0,0)

139.2

(124.4

,154)

313.5

(301.3

,325.8

)386.7

(375.3

,398.1

)535.8

(525.3

,546.3

)581.2

(570.1

,592.2

)-9

.2(-2

0.4

,2.1

)130.4

(119.3

,141.5

)323.1

(311.7

,334.5

)404

(392.5

,415.5

)545.2

(535.7

,554.6

)N/A

3A

-3SW

L60

–0

(0,0)

174.3

(161.2

,187.4

)247.5

(234.9

,260.1

)396.6

(383.9

,409.3

)441.9

(430.1

,453.7

)-148.4

(-160.8

,-136)

-8.8

(-2

1.3

,3.7

)183.9

(171.8

,195.9

)264.8

(252.5

,277)

405.9

(393.9

,417.9

)N/A

4A

-3SW

L60

––

0(0,0)

73.2

(61.8

,84.6

)222.3

(212.6

,232.1

)267.7

(256.7

,278.6

)-322.7

(-334,

-311.4

)-183.1

(-194.5

,-171.7

)9.6

(-1

,20.2

)90.5

(80.4

,100.5

)231.6

(222,

241.3

)N/A

4A

-4SW

L60

––

–0

(0,0)

149.1

(139.4

,158.9

)194.5

(184.9

,204)

-395.9

(-405.9

,-385.8

)-256.3

(-266.3

,-246.3

)-63.6

(-72.7

,-54.5

)17.3

(7.8

,26.8

)158.4

(149.2

,167.7

)N/A

5A

-4SW

L60

––

––

0(0,0)

45.3

(36.9

,53.7

)-545

(-554.2

,-535.8

)-405.4

(-414.8

,-396.1

)-212.8

(-221.9

,-203.6

)-131.8

(-140.3

,-123.4

)9.3

(1.6

,17)

N/A

5A

-5SW

L60

––

––

–0

(0,0)

-590.3

(-599.8

,-580.9

)-450.7

(-461.7

,-439.8

)-258.1

(-267.7

,-248.4

)-177.2

(-186.6

,-167.7

)-36

(-44.1

,-27.9

)N/A

3A

-2SW

LD

––

––

––

0(0,0)

139.6

(128.8

,150.4

)332.3

(322.7

,341.9

)413.2

(402.8

,423.5

)554.3

(545.6

,563.1

)N/A

3A

-3SW

LD

––

––

––

0(0,0)

192.7

(182.5

,202.8

)273.6

(263.1

,284)

414.7

(405,

424.4

)N/A

4A

-3SW

LD

––

––

––

–0

(0,0)

80.9

(71.9

,89.9

)222.1

(213.6

,230.5

)N/A

4A

-4SW

LD

––

––

––

––

0(0,0)

141.2

(133.1

,149.2

)N/A

5A

-4SW

LD

––

––

––

––

–0

(0,0)

N/A

5A

-5SW

LD

––

––

––

––

––

N/A

Tab

leH

.9:

Reh

abil

itat

ion

resu

lts

for

up

dat

ing

the

short

wait

ing

list

sd

ail

y(D

)co

mp

are

dto

the

up

dati

ng

ever

y60

day

s(6

0)

on

the

nu

mb

erof

AL

Cd

ays

3A

-2SW

L60

3A

-3SW

L60

4A

-3SW

L60

4A

-4SW

L60

5A

-4SW

L60

5A

-5SW

L60

3A

-2SW

LD

3A

-3SW

LD

4A

-3SW

LD

4A

-4SW

LD

5A

-4SW

LD

5A

-5SW

LD

3A

-2SW

L60

0(0,0)

0.5

(0.2

,0.8

)2.9

(2.7

,3.2

)3.2

(2.9

,3.5

)4.8

(4.6

,5.1

)4.7

(4.4

,4.9

)-0

.2(-0

.5,0.2

)0.2

(-0

.2,0.5

)3.3

(3,3.6

)2.9

(2.6

,3.2

)4.7

(4.4

,4.9

)N/A

3A

-3SW

L60

–0

(0,0)

2.4

(2.2

,2.7

)2.7

(2.4

,3)

4.3

(4,4.6

)4.1

(3.9

,4.4

)-0.7

(-1,-0.3

)-0

.4(-0

.7,0)

2.8

(2.5

,3.1

)2.4

(2.1

,2.7

)4.1

(3.9

,4.4

)N/A

4A

-3SW

L60

––

0(0,0)

0.3

(0,0.6

)1.9

(1.7

,2.1

)1.7

(1.5

,1.9

)-3.1

(-3.4

,-2.8

)-2.8

(-3.1

,-2.5

)0.4

(0.1

,0.6

)0

(-0

.2,0.3

)1.7

(1.5

,2)

N/A

4A

-4SW

L60

––

–0

(0,0)

1.6

(1.4

,1.8

)1.4

(1.2

,1.7

)-3.4

(-3.7

,-3.1

)-3.1

(-3.4

,-2.8

)0.1

(-0

.2,0.3

)-0

.3(-0

.6,0)

1.4

(1.2

,1.7

)N/A

5A

-4SW

L60

––

––

0(0,0)

-0.2

(-0

.4,0)

-5

(-5.3

,-4.7

)-4.7

(-4.9

,-4.4

)-1.5

(-1.8

,-1.3

)-1.9

(-2.1

,-1.7

)-0

.2(-0

.4,0)

N/A

5A

-5SW

L60

––

––

–0

(0,0)

-4.8

(-5.1

,-4.5

)-4.5

(-4.8

,-4.2

)-1.4

(-1.6

,-1.1

)-1.7

(-2,-1.5

)0

(-0

.2,0.2

)N/A

3A

-2SW

LD

––

––

––

0(0,0)

0.3

(0,0.7

)3.5

(3.2

,3.7

)3.1

(2.8

,3.4

)4.8

(4.5

,5.1

)N/A

3A

-3SW

LD

––

––

––

–0

(0,0)

3.1

(2.8

,3.4

)2.8

(2.5

,3.1

)4.5

(4.2

,4.8

)N/A

4A

-3SW

LD

––

––

––

––

0(0,0)

-0.4

(-0.6

,-0.1

)1.4

(1.1

,1.6

)N/A

4A

-4SW

LD

––

––

––

––

–0

(0,0)

1.7

(1.5

,2)

N/A

5A

-4SW

LD

––

––

––

––

––

0(0,0)

N/A

5A

-5SW

LD

––

––

––

––

––

–N/A

Tab

leH

.10:

Reh

abil

itat

ion

resu

lts

for

up

dat

ing

the

short

wait

ing

list

sd

ail

y(D

)co

mp

are

dto

the

up

dati

ng

ever

y60

day

s(6

0)

on

the

nu

mb

erof

die

din

hosp

ital

pat

ients

Appendix I


the definition of a short waiting list

102

Appendix I. Pairwise comparison charts - varying the definition of a short waiting list103

3A

-3

SW

L10

days

3A

-3

SW

L16

days

3A

-3

SW

L25

days

4A

-4

SW

L10

days

4A

-4

SW

L16

days

4A

-4

SW

L25

days

5A

-5

SW

L10

days

5A

-5

SW

L16

days

5A

-5

SW

L25

days

3A

-3

SW

L10

days

0(0,0)

1(-1

.8,3.8

)1

(-1

.8,3.8

)N/A

N/A

N/A

N/A

N/A

N/A

3A

-3

SW

L16

days

–0

(0,0)

-0.1

(-0

.1,0)

N/A

N/A

N/A

N/A

N/A

N/A

3A

-3

SW

L25

days

––

0(0,0)

N/A

N/A

N/A

N/A

N/A

N/A

4A

-4

SW

L10

days

––

–N/A

N/A

N/A

N/A

N/A

N/A

4A

-4

SW

L16

days

––

––

N/A

N/A

N/A

N/A

N/A

4A

-4

SW

L25

days

––

––

–N/A

N/A

N/A

N/A

5A

-5

SW

L10

days

––

––

––

N/A

N/A

N/A

5A

-5

SW

L16

days

––

––

––

–N/A

N/A

5A

-5

SW

L25

days

––

––

––

––

N/A

Tab

leI.

1:C

CC

resu

lts

for

vary

ing

the

defi

nit

ion

ofa

short

wait

ing

list

bet

wee

n10,

16

an

d25

day

son

the

dis

charg

ep

oli

cysc

enari

os

wit

ha

hig

hnu

mb

erof

faci

liti

esw

ith

ash

ort

wai

tin

gli

stre

qu

ired

onth

enu

mb

erof

AL

Cd

ays

3A

-3

SW

L10

days

3A

-3

SW

L16

days

3A

-3

SW

L25

days

4A

-4

SW

L10

days

4A

-4

SW

L16

days

4A

-4

SW

L25

days

5A

-5

SW

L10

days

5A

-5

SW

L16

days

5A

-5

SW

L25

days

3A

-3

SW

L10

days

0(0,0)

0(0,0)

0(0,0)

N/A

N/A

N/A

N/A

N/A

N/A

3A

-3

SW

L16

days

–0

(0,0)

0(0,0)

N/A

N/A

N/A

N/A

N/A

N/A

3A

-3

SW

L25

days

––

0(0,0)

N/A

N/A

N/A

N/A

N/A

N/A

4A

-4

SW

L10

days

––

–N/A

N/A

N/A

N/A

N/A

N/A

4A

-4

SW

L16

days

––

––

N/A

N/A

N/A

N/A

N/A

4A

-4

SW

L25

days

––

––

–N/A

N/A

N/A

N/A

5A

-5

SW

L10

days

––

––

––

N/A

N/A

N/A

5A

-5

SW

L16

days

––

––

––

–N/A

N/A

5A

-5

SW

L25

days

––

––

––

––

N/A

Tab

leI.

2:C

CC

resu

lts

for

vary

ing

the

defi

nit

ion

ofa

short

wait

ing

list

bet

wee

n10,

16

an

d25

day

son

the

dis

charg

ep

oli

cysc

enari

os

wit

ha

hig

hnu

mb

erof

faci

liti

esw

ith

ash

ort

wai

tin

gli

stre

qu

ired

onth

enu

mb

erof

die

din

hosp

ital

pati

ents


3A

-3

SW

L10

days

3A

-3

SW

L16

days

3A

-3

SW

L25

days

4A

-4

SW

L10

days

4A

-4

SW

L16

days

4A

-4

SW

L25

days

5A

-5

SW

L10

days

5A

-5

SW

L16

days

5A

-5

SW

L25

days

3A

-3

SW

L10

days

0(0,0)

0(-0

.6,0.6

)-1

.1(-2

.3,0.1

)45.1

(41.1

,49.2

)41.1

(38.1

,44.1

)39.3

(36,42.6

)95.9

(92.1

,99.8

)85.2

(81.3

,89.2

)79.7

(75.9

,83.5

)3A

-3

SW

L16

days

–0

(0,0)

-1.1

(-2

.2,0)

45.2

(41.1

,49.2

)41.2

(38.1

,44.2

)39.3

(35.9

,42.6

)96

(92.1

,99.8

)85.2

(81.3

,89.2

)79.7

(75.9

,83.5

)3A

-3

SW

L25

days

––

0(0,0)

46.2

(42.2

,50.2

)42.2

(39.2

,45.3

)40.4

(37,43.7

)97

(93.1

,101)

86.3

(82.3

,90.3

)80.8

(76.9

,84.7

)

4A

-4

SW

L10

days

––

–0

(0,0)

-4

(-6.8

,-1.2

)-5.9

(-9.7

,-2.1

)50.8

(45.5

,56.1

)40.1

(34.9

,45.3

)34.5

(29.8

,39.3

)4A

-4

SW

L16

days

––

––

0(0,0)

-1.9

(-4

.6,0.8

)54.8

(50.6

,59)

44.1

(39.5

,48.7

)38.5

(34.5

,42.6

)4A

-4

SW

L25

days

––

––

–0

(0,0)

56.7

(51.7

,61.6

)46

(40.9

,51)

40.4

(35.9

,45)

5A

-5

SW

L10

days

––

––

––

0(0,0)

-10.7

(-14.4

,-7)

-16.3

(-20.7

,-11.8

)5A

-5

SW

L16

days

––

––

––

–0

(0,0)

-5.5

(-8.9

,-2.2

)5A

-5

SW

L25

days

––

––

––

––

0(0,0)

Tab

leI.

3:C

onva

lesc

ent

resu

lts

for

vary

ing

the

defi

nit

ion

of

ash

ort

wait

ing

list

bet

wee

n10,

16

an

d25

day

son

the

dis

charg

ep

oli

cysc

enari

os

wit

ha

hig

hnu

mb

erof

faci

liti

esw

ith

ash

ort

wai

tin

gli

stre

qu

ired

on

the

nu

mb

erof

AL

Cd

ays

3A

-3

SW

L10

days

3A

-3

SW

L16

days

3A

-3

SW

L25

days

4A

-4

SW

L10

days

4A

-4

SW

L16

days

4A

-4

SW

L25

days

5A

-5

SW

L10

days

5A

-5

SW

L16

days

5A

-5

SW

L25

days

3A

-3

SW

L10

days

0(0,0)

0(-0

.1,0)

0(0,0)

0.1

(0,0.1

)0.1

(0,0.1

)0.1

(0,0.1

)-0.4

(-0.5

,-0.4

)0.1

(0.1

,0.2

)0.2

(0.1

,0.2

)3A

-3

SW

L16

days

–0

(0,0)

0(0,0.1

)0.1

(0,0.1

)0.1

(0,0.1

)0.1

(0,0.1

)-0.4

(-0.4

,-0.4

)0.2

(0.1

,0.2

)0.2

(0.1

,0.2

)3A

-3

SW

L25

days

––

0(0,0)

0(0,0.1

)0

(0,0.1

)0

(0,0.1

)-0.5

(-0.5

,-0.4

)0.1

(0.1

,0.2

)0.1

(0.1

,0.2

)

4A

-4

SW

L10

days

––

–0

(0,0)

0(0,0)

0(0,0)

-0.5

(-0.5

,-0.5

)0.1

(0,0.1

)0.1

(0.1

,0.1

)4A

-4

SW

L16

days

––

––

0(0,0)

0(0,0)

-0.5

(-0.5

,-0.5

)0.1

(0,0.1

)0.1

(0.1

,0.1

)4A

-4

SW

L25

days

––

––

–0

(0,0)

-0.5

(-0.5

,-0.5

)0.1

(0,0.1

)0.1

(0.1

,0.1

)

5A

-5

SW

L10

days

––

––

––

0(0,0)

0.6

(0.5

,0.6

)0.6

(0.6

,0.6

)5A

-5

SW

L16

days

––

––

––

–0

(0,0)

0(0,0)

5A

-5

SW

L25

days

––

––

––

––

0(0,0)

Tab

leI.

4:C

onva

lesc

ent

resu

lts

for

vary

ing

the

defi

nit

ion

of

ash

ort

wait

ing

list

bet

wee

n10,

16

an

d25

day

son

the

dis

charg

ep

oli

cysc

enari

os

wit

ha

hig

hnu

mb

erof

faci

liti

esw

ith

ash

ort

wai

tin

gli

stre

qu

ired

on

the

nu

mb

erof

die

din

hosp

ital

pati

ents


3A

-3

SW

L10

days

3A

-3

SW

L16

days

3A

-3

SW

L25

days

4A

-4

SW

L10

days

4A

-4

SW

L16

days

4A

-4

SW

L25

days

5A

-5

SW

L10

days

5A

-5

SW

L16

days

5A

-5

SW

L25

days

3A

-3

SW

L10

days

0(0,0)

3.2

(-3

1.7

,38.1

)28.3

(5.8

,50.7

)530.6

(497.3

,563.9

)562.1

(527,597.2

)566.1

(532,600.3

)917.5

(883.1

,952)

945.6

(911.8

,979.4

)911.4

(876,946.8

)

3A

-3

SW

L16

days

–0

(0,0)

25.1

(-1

2.7

,62.9

)527.4

(489.1

,565.7

)558.9

(517.5

,600.3

)563

(521.3

,604.6

)914.3

(873.7

,955)

942.4

(901,983.9

)908.2

(868.6

,947.9

)3A

-3

SW

L25

days

––

0(0,0)

502.3

(465.2

,539.5

)533.8

(496.8

,570.8

)537.9

(502.3

,573.5

)889.3

(853.7

,924.8

)917.4

(882.5

,952.2

)883.1

(845.6

,920.7

)

4A

-4

SW

L10

days

––

–0

(0,0)

31.5

(4.2

,58.8

)35.6

(14.3

,56.8

)386.9

(358.2

,415.7

)415

(388.8

,441.3

)380.8

(351.3

,410.3

)4A

-4

SW

L16

days

––

––

0(0,0)

4.1

(-2

4.5

,32.6

)355.4

(326.3

,384.6

)383.5

(355.2

,411.9

)349.3

(316.8

,381.9

)4A

-4

SW

L25

days

––

––

–0

(0,0)

351.4

(322.3

,380.5

)379.5

(355.1

,403.9

)345.3

(316.8

,373.8

)

5A

-5

SW

L10

days

––

––

––

0(0,0)

28.1

(1.5

,54.7

)-6

.1(-2

6.5

,14.2

)5A

-5

SW

L16

days

––

––

––

–0

(0,0)

-34.2

(-57.8

,-10.7

)5A

-5

SW

L25

days

––

––

––

––

0(0,0)

Tab

leI.

5:LT

Cre

sult

sfo

rva

ryin

gth

ed

efin

itio

nof

ash

ort

wait

ing

list

bet

wee

n10,

16

an

d25

day

son

the

dis

charg

ep

oli

cysc

enari

os

wit

ha

hig

hnu

mb

erof

faci

liti

esw

ith

ash

ort

wai

tin

gli

stre

qu

ired

onth

enu

mb

erof

AL

Cd

ays

3A

-3

SW

L10

days

3A

-3

SW

L16

days

3A

-3

SW

L25

days

4A

-4

SW

L10

days

4A

-4

SW

L16

days

4A

-4

SW

L25

days

5A

-5

SW

L10

days

5A

-5

SW

L16

days

5A

-5

SW

L25

days

3A

-3

SW

L10

days

0(0,0)

-0.3

(-0

.5,0)

0(-0

.1,0.2

)2.9

(2.6

,3.2

)2.7

(2.4

,2.9

)2.9

(2.7

,3.2

)2.5

(2.3

,2.7

)4.5

(4.3

,4.7

)4.6

(4.4

,4.9

)3A

-3

SW

L16

days

–0

(0,0)

0.3

(0.1

,0.5

)3.2

(2.9

,3.4

)2.9

(2.6

,3.2

)3.2

(2.9

,3.5

)2.8

(2.6

,3)

4.8

(4.5

,5)

4.9

(4.6

,5.1

)3A

-3

SW

L25

days

––

0(0,0)

2.9

(2.6

,3.2

)2.6

(2.4

,2.9

)2.9

(2.7

,3.2

)2.5

(2.3

,2.7

)4.5

(4.2

,4.7

)4.6

(4.3

,4.9

)

4A

-4

SW

L10

days

––

–0

(0,0)

-0.2

(-0

.5,0)

0(-0

.1,0.2

)-0.4

(-0.6

,-0.2

)1.6

(1.3

,1.8

)1.7

(1.5

,2)

4A

-4

SW

L16

days

––

––

0(0,0)

0.3

(0.1

,0.5

)-0

.2(-0

.4,0)

1.8

(1.6

,2.1

)2

(1.7

,2.2

)4A

-4

SW

L25

days

––

––

–0

(0,0)

-0.4

(-0.6

,-0.3

)1.6

(1.3

,1.8

)1.7

(1.4

,1.9

)

5A

-5

SW

L10

days

––

––

––

0(0,0)

2(1.9

,2.1

)2.1

(1.9

,2.3

)5A

-5

SW

L16

days

––

––

––

–0

(0,0)

0.1

(-0

.1,0.3

)5A

-5

SW

L25

days

––

––

––

––

0(0,0)

Tab

leI.

6:LT

Cre

sult

sfo

rva

ryin

gth

ed

efin

itio

nof

ash

ort

wait

ing

list

bet

wee

n10,

16

an

d25

day

son

the

dis

charg

ep

oli

cysc

enari

os

wit

ha

hig

hnu

mb

erof

faci

liti

esw

ith

ash

ort

wai

tin

gli

stre

qu

ired

onth

enu

mb

erof

die

din

hosp

ital

pati

ents


3A

-3

SW

L10

days

3A

-3

SW

L16

days

3A

-3

SW

L25

days

4A

-4

SW

L10

days

4A

-4

SW

L16

days

4A

-4

SW

L25

days

5A

-5

SW

L10

days

5A

-5

SW

L16

days

5A

-5

SW

L25

days

3A

-3

SW

L10

days

0(0,0)

0.4

(-5

.7,6.4

)-10.7

(-16.6

,-4.8

)140.7

(134.1

,147.4

)140.5

(133.9

,147.1

)131.6

(125.1

,138.1

)210

(204.2

,215.8

)207.4

(201.2

,213.6

)203.1

(197.1

,209)

3A

-3

SW

L16

days

–0

(0,0)

-11.1

(-16.3

,-5.9

)140.4

(134.4

,146.3

)140.1

(134.3

,146)

131.2

(125.7

,136.8

)209.6

(204,215.2

)207

(201.5

,212.5

)202.7

(196.6

,208.8

)3A

-3

SW

L25

days

––

0(0,0)

151.5

(146.1

,156.8

)151.2

(145.2

,157.2

)142.3

(136.1

,148.5

)220.7

(215,226.5

)218.1

(212.8

,223.4

)213.8

(208.4

,219.2

)

4A

-4

SW

L10

days

––

–0

(0,0)

-0.3

(-4

.6,4.1

)-9.2

(-14.1

,-4.2

)69.3

(64.1

,74.5

)66.6

(62.3

,71)

62.3

(57.2

,67.4

)4A

-4

SW

L16

days

––

––

0(0,0)

-8.9

(-13.4

,-4.4

)69.5

(64.6

,74.5

)66.9

(62.3

,71.4

)62.6

(57.4

,67.8

)4A

-4

SW

L25

days

––

––

–0

(0,0)

78.4

(73.5

,83.3

)75.8

(70.8

,80.8

)71.5

(65.8

,77.2

)

5A

-5

SW

L10

days

––

––

––

0(0,0)

-2.6

(-6

,0.8

)-7

(-10.7

,-3.2

)5A

-5

SW

L16

days

––

––

––

–0

(0,0)

-4.3

(-7.8

,-0.8

)5A

-5

SW

L25

days

––

––

––

––

0(0,0)

Tab

leI.

7:P

alli

ativ

ere

sult

sfo

rva

ryin

gth

ed

efin

itio

nof

ash

ort

wait

ing

list

bet

wee

n10,

16

an

d25

day

son

the

dis

charg

ep

oli

cysc

enari

os

wit

ha

hig

hnu

mb

erof

faci

liti

esw

ith

ash

ort

wai

tin

gli

stre

qu

ired

onth

enu

mb

erof

AL

Cd

ays

3A

-3

SW

L10

days

3A

-3

SW

L16

days

3A

-3

SW

L25

days

4A

-4

SW

L10

days

4A

-4

SW

L16

days

4A

-4

SW

L25

days

5A

-5

SW

L10

days

5A

-5

SW

L16

days

5A

-5

SW

L25

days

3A

-3

SW

L10

days

0(0,0)

-0.4

(-0.8

,-0.1

)-0.4

(-0.7

,-0.2

)4.5

(4.2

,4.8

)4.4

(4.1

,4.7

)4.5

(4.2

,4.8

)2.4

(2.2

,2.6

)6.8

(6.5

,7.1

)7

(6.7

,7.3

)3A

-3

SW

L16

days

–0

(0,0)

0(-0

.3,0.3

)5

(4.6

,5.3

)4.9

(4.5

,5.2

)4.9

(4.6

,5.2

)2.8

(2.6

,3.1

)7.3

(6.9

,7.6

)7.4

(7.1

,7.8

)3A

-3

SW

L25

days

––

0(0,0)

5(4.7

,5.3

)4.9

(4.5

,5.2

)4.9

(4.6

,5.3

)2.8

(2.6

,3.1

)7.3

(6.9

,7.6

)7.4

(7.1

,7.7

)

4A

-4

SW

L10

days

––

–0

(0,0)

-0.1

(-0

.4,0.2

)0

(-0

.4,0.3

)-2.2

(-2.4

,-1.9

)2.3

(2,2.6

)2.4

(2.1

,2.7

)4A

-4

SW

L16

days

––

––

0(0,0)

0.1

(-0

.2,0.4

)-2

(-2.3

,-1.8

)2.4

(2.1

,2.7

)2.6

(2.2

,2.9

)4A

-4

SW

L25

days

––

––

–0

(0,0)

-2.1

(-2.4

,-1.9

)2.3

(2,2.6

)2.5

(2.2

,2.8

)

5A

-5

SW

L10

days

––

––

––

0(0,0)

4.4

(4.3

,4.6

)4.6

(4.4

,4.8

)5A

-5

SW

L16

days

––

––

––

–0

(0,0)

0.2

(-0

.1,0.4

)5A

-5

SW

L25

days

––

––

––

––

0(0,0)

Tab

leI.

8:P

alli

ativ

ere

sult

sfo

rva

ryin

gth

ed

efin

itio

nof

ash

ort

wait

ing

list

bet

wee

n10,

16

an

d25

day

son

the

dis

charg

ep

oli

cysc

enari

os

wit

ha

hig

hnu

mb

erof

faci

liti

esw

ith

ash

ort

wai

tin

gli

stre

qu

ired

onth

enu

mb

erof

die

din

hosp

ital

pati

ents


3A

-3

SW

L10

days

3A

-3

SW

L16

days

3A

-3

SW

L25

days

4A

-4

SW

L10

days

4A

-4

SW

L16

days

4A

-4

SW

L25

days

5A

-5

SW

L10

days

5A

-5

SW

L16

days

5A

-5

SW

L25

days

3A

-3

SW

L10

days

0(0,0)

-2.9

(-1

0.3

,4.6

)-12.8

(-22.5

,-3.1

)244.1

(230.9

,257.2

)244.6

(231.2

,258)

241.8

(227.9

,255.7

)440.1

(429,451.1

)439.1

(427.7

,450.5

)434.1

(422.8

,445.4

)3A

-3

SW

L16

days

–0

(0,0)

-9.9

(-17.8

,-2.1

)246.9

(234.3

,259.5

)247.5

(234.9

,260.1

)244.7

(231.5

,257.9

)442.9

(431.6

,454.2

)441.9

(430.1

,453.7

)436.9

(426,447.8

)

3A

-3

SW

L25

days

––

0(0,0)

256.9

(244.9

,268.9

)257.4

(245.6

,269.2

)254.6

(241.7

,267.5

)452.9

(442.5

,463.2

)451.9

(441.1

,462.7

)446.9

(436.2

,457.5

)

4A

-4

SW

L10

days

––

–0

(0,0)

0.6

(-4

.8,5.9

)-2

.2(-1

1,6.6

)196

(186.6

,205.4

)195

(185.2

,204.8

)190

(180.4

,199.6

)4A

-4

SW

L16

days

––

––

0(0,0)

-2.8

(-1

0.3

,4.8

)195.4

(186,204.9

)194.5

(184.9

,204)

189.5

(180.5

,198.4

)4A

-4

SW

L25

days

––

––

–0

(0,0)

198.2

(187.7

,208.8

)197.3

(186.4

,208.1

)192.3

(182.2

,202.3

)

5A

-5

SW

L10

days

––

––

––

0(0,0)

-1(-6

.5,4.6

)-6

(-1

2.5

,0.5

)5A

-5

SW

L16

days

––

––

––

–0

(0,0)

-5(-1

0.7

,0.7

)5A

-5

SW

L25

days

––

––

––

––

0(0,0)

Tab

leI.

9:R

ehab

ilit

atio

nre

sult

sfo

rva

ryin

gth

ed

efin

itio

nof

ash

ort

wait

ing

list

bet

wee

n10,

16

an

d25

day

son

the

dis

charg

ep

oli

cysc

enari

os

wit

ha

hig

hnu

mb

erof

faci

liti

esw

ith

ash

ort

wai

tin

gli

stre

qu

ired

on

the

nu

mb

erof

AL

Cd

ays

3A

-3

SW

L10

days

3A

-3

SW

L16

days

3A

-3

SW

L25

days

4A

-4

SW

L10

days

4A

-4

SW

L16

days

4A

-4

SW

L25

days

5A

-5

SW

L10

days

5A

-5

SW

L16

days

5A

-5

SW

L25

days

3A

-3

SW

L10

days

0(0,0)

0(-0

.1,0.2

)-0

.1(-0

.3,0.1

)2.7

(2.3

,3)

2.7

(2.4

,3.1

)2.9

(2.5

,3.2

)4.5

(4.2

,4.7

)4.2

(3.9

,4.4

)4.2

(3.9

,4.5

)3A

-3

SW

L16

days

–0

(0,0)

-0.1

(-0

.4,0.1

)2.6

(2.3

,2.9

)2.7

(2.4

,3)

2.8

(2.5

,3.2

)4.4

(4.2

,4.7

)4.1

(3.9

,4.4

)4.2

(3.9

,4.5

)3A

-3

SW

L25

days

––

0(0,0)

2.8

(2.5

,3.1

)2.9

(2.5

,3.2

)3

(2.6

,3.3

)4.6

(4.3

,4.8

)4.3

(4,4.6

)4.3

(4,4.6

)

4A

-4

SW

L10

days

––

–0

(0,0)

0.1

(0,0.2

)0.2

(0,0.4

)1.8

(1.6

,2)

1.5

(1.3

,1.8

)1.5

(1.3

,1.8

)4A

-4

SW

L16

days

––

––

0(0,0)

0.1

(0,0.3

)1.7

(1.5

,1.9

)1.4

(1.2

,1.7

)1.5

(1.2

,1.7

)4A

-4

SW

L25

days

––

––

–0

(0,0)

1.6

(1.4

,1.8

)1.3

(1.1

,1.6

)1.3

(1.1

,1.6

)

5A

-5

SW

L10

days

––

––

––

0(0,0)

-0.3

(-0.4

,-0.1

)-0.3

(-0.4

,-0.1

)5A

-5

SW

L16

days

––

––

––

–0

(0,0)

0(-0

.1,0.1

)5A

-5

SW

L25

days

––

––

––

––

0(0,0)

Tab

leI.

10:

Reh

abil

itat

ion

resu

lts

for

vary

ing

the

defi

nit

ion

of

ash

ort

wait

ing

list

bet

wee

n10,

16

an

d25

day

son

the

dis

charg

ep

oli

cysc

enari

os

wit

ha

hig

hnu

mb

erof

faci

liti

esw

ith

ash

ort

wai

tin

gli

stre

qu

ired

on

the

nu

mb

erof

die

din

hosp

ital

pati

ents

Appendix J


the facility popularity distribution

108

Appendix J. Pairwise comparison charts - varying the facility popularity distribution 109

3A

-3SW

L4A

-0SW

L4A

-4SW

L5A

-0SW

L5A

-5SW

L3A

-3SW

LI

4A

-0SW

LI

4A

-4SW

LI

5A

-0SW

LI

5A

-5SW

LI

3A

-3SW

LR

4A

-0SW

LR

4A

-4SW

LR

5A

-0SW

LR

5A

-5SW

LR

3A

-3SW

L0

(0,0)

163.9

(151.1

,176.7

)

N/A

227.9

(215.5

,240.3

)N/A

-17.5

(-31.4

,-3.6

)32.6

(16.5

,48.7

)N/A

105.8

(88.1

,123.4

)N/A

-5.9

(-1

9.7

,7.9

)60.3

(43.7

,76.8

)N/A

136

(119.3

,152.7

)N/A

4A

-0SW

L–

0(0,0)

N/A

64

(50.7

,77.3

)N/A

-181.4

(-196.4

,-166.4

)

-131.3

(-148.2

,-114.4

)

N/A

-58.2

(-77.4

,-38.9

)N/A

-169.8

(-184.8

,-154.8

)

-103.6

(-121.6

,-85.6

)

N/A

-27.9

(-45.6

,-10.2

)N/A

4A

-4SW

L–

–N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

5A

-0SW

L–

––

0(0,0)

N/A

-245.4

(-258.1

,-232.8

)

-195.3

(-210.2

,-180.4

)

N/A

-122.2

(-138.4

,-105.9

)

N/A

-233.8

(-249.4

,-218.2

)

-167.6

(-185,

-150.3

)N/A

-91.9

(-108.5

,-75.3

)

N/A

5A

-5SW

L–

––

–N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

3A

-3SW

LI

––

––

–0

(0,0)

50.1

(37.5

,62.8

)N/A

123.3

(106.1

,140.5

)N/A

11.6

(-4

,27.3

)77.8

(60.1

,95.4

)N/A

153.5

(136.2

,170.8

)N/A

4A

-0SW

LI

––

––

––

0(0,0)

N/A

73.1

(56.8

,89.4

)N/A

-38.5

(-55.4

,-21.6

)27.7

(8.8

,46.5

)N/A

103.4

(85.7

,121)

N/A

4A

-4SW

LI

––

––

––

–N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

5A

-0SW

LI

––

––

––

––

0(0,0)

N/A

-111.6

(-130.9

,-92.4

)

-45.5

(-65.9

,-25)

N/A

30.2

(12.4

,48.1

)N/A

5A

-5SW

LI

––

––

––

––

–N/A

N/A

N/A

N/A

N/A

N/A

3A

-3SW

LR

––

––

––

––

––

0(0,0)

66.2

(48.6

,83.7

)N/A

141.9

(125.2

,158.5

)N/A

4A

-0SW

LR

––

––

––

––

––

–0

(0,0)

N/A

75.7

(57.7

,93.7

)N/A

4A

-4SW

LR

––

––

––

––

––

––

N/A

N/A

N/A

5A

-0SW

LR

––

––

––

––

––

––

–0

(0,0)

N/A

Tab

leJ.1

:C

CC

resu

lts

wh

enva

ryin

gth

enum

ber

ofsh

ort

wait

ing

list

faci

liti

es,

tota

lnu

mb

erof

ap

pli

cati

on

s,an

dth

ety

pe

of

faci

lity

pop

ula

rity

dis

trib

uti

on

(I=

inve

rse

ofac

tual

faci

lity

pop

ula

rity

dis

trib

uti

on,

R=

choosi

ng

faci

lity

ran

dom

ly)

on

the

nu

mb

erof

AL

Cd

ays


3A

-3SW

L4A

-0SW

L4A

-4SW

L5A

-0SW

L5A

-5SW

L3A

-3SW

LI

4A

-0SW

LI

4A

-4SW

LI

5A

-0SW

LI

5A

-5SW

LI

3A

-3SW

LR

4A

-0SW

LR

4A

-4SW

LR

5A

-0SW

LR

5A

-5SW

LR

3A

-3SW

L0

(0,0)

0.5

(0.4

,0.6

)1.3

(1.2

,1.3

)0.8

(0.7

,0.9

)N/A

-0.3

(-0.4

,-0.2

)-0

.1(-0

.2,0)

N/A

0.2

(0.1

,0.3

)1.3

(1.2

,1.3

)-0.3

(-0.4

,-0.2

)0

(-0

.1,0.1

)N/A

0.5

(0.4

,0.6

)N/A

4A

-0SW

L–

0(0,0)

0.7

(0.7

,0.8

)0.3

(0.2

,0.3

)N/A

-0.8

(-0.9

,-0.7

)-0.6

(-0.7

,-0.5

)N/A

-0.4

(-0.4

,-0.3

)0.7

(0.7

,0.8

)-0.8

(-0.9

,-0.7

)-0.5

(-0.6

,-0.4

)N/A

-0.1

(-0

.2,0)

N/A

4A

-4SW

L–

–0

(0,0)

-0.5

(-0.5

,-0.4

)N/A

-1.5

(-1.6

,-1.4

)-1.3

(-1.4

,-1.3

)N/A

-1.1

(-1.2

,-1)

0(0,0)

-1.5

(-1.6

,-1.4

)-1.2

(-1.3

,-1.2

)N/A

-0.8

(-0.9

,-0.7

)N/A

5A

-0SW

L–

––

0(0,0)

N/A

-1.1

(-1.2

,-1)

-0.9

(-1,

-0.8

)N/A

-0.6

(-0.7

,-0.5

)0.5

(0.4

,0.5

)-1.1

(-1.2

,-1)

-0.8

(-0.9

,-0.7

)N/A

-0.3

(-0.4

,-0.2

)N/A

5A

-5SW

L–

––

–N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

3A

-3SW

LI

––

––

–0

(0,0)

0.2

(0.1

,0.3

)N/A

0.5

(0.3

,0.6

)1.5

(1.4

,1.6

)0

(-0

.1,0.1

)0.3

(0.2

,0.4

)N/A

0.8

(0.6

,0.9

)N/A

4A

-0SW

LI

––

––

––

0(0,0)

N/A

0.3

(0.2

,0.4

)1.3

(1.3

,1.4

)-0.2

(-0.3

,-0.1

)0.1

(0,0.2

)N/A

0.6

(0.5

,0.7

)N/A

4A

-4SW

LI

––

––

––

–N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

5A

-0SW

LI

––

––

––

––

0(0,0)

1.1

(1,1.2

)-0.5

(-0.6

,-0.3

)-0.2

(-0.3

,-0.1

)N/A

0.3

(0.2

,0.4

)N/A

5A

-5SW

LI

––

––

––

––

–0

(0,0)

-1.5

(-1.6

,-1.4

)-1.2

(-1.3

,-1.2

)N/A

-0.8

(-0.9

,-0.7

)N/A

3A

-3SW

LR

––

––

––

––

––

0(0,0)

0.3

(0.2

,0.4

)N/A

0.7

(0.6

,0.9

)N/A

4A

-0SW

LR

––

––

––

––

––

–0

(0,0)

N/A

0.5

(0.3

,0.6

)N/A

4A

-4SW

LR

––

––

––

––

––

––

N/A

N/A

N/A

5A

-0SW

LR

––

––

––

––

––

––

–0

(0,0)

N/A

Tab

leJ.2

:C

CC

resu

lts

wh

enva

ryin

gth

enum

ber

ofsh

ort

wait

ing

list

faci

liti

es,

tota

lnu

mb

erof

ap

pli

cati

on

s,an

dth

ety

pe

of

faci

lity

pop

ula

rity

dis

trib

uti

on

(I=

inve

rse

ofac

tual

faci

lity

pop

ula

rity

dis

trib

uti

on,

R=

choosi

ng

faci

lity

ran

dom

ly)

on

the

nu

mb

erof

die

din

hosp

ital

pati

ents


3A

-3SW

L4A

-0SW

L4A

-4SW

L5A

-0SW

L5A

-5SW

L3A

-3SW

LI

4A

-0SW

LI

4A

-4SW

LI

5A

-0SW

LI

5A

-5SW

LI

3A

-3SW

LR

4A

-0SW

LR

4A

-4SW

LR

5A

-0SW

LR

5A

-5SW

LR

3A

-3SW

L0

(0,0)

41

(37.8

,44.2

)

41.2

(38.1

,44.2

)70.9

(67.6

,74.3

)85.2

(81.3

,89.2

)12.5

(10.8

,14.3

)52.7

(48.6

,56.9

)81.1

(76.5

,85.6

)91.5

(87.8

,95.2

)N/A

9(7.1

,10.9

)49.2

(45.7

,52.7

)64.8

(60.3

,69.2

)88.1

(84.4

,91.8

)123.6

(119.7

,127.4

)

4A

-0SW

L–

0(0,0)

0.1

(-1

.1,1.4

)29.9

(25.5

,34.3

)44.2

(39.7

,48.7

)-28.5

(-31.9

,-25.1

)11.7

(7.2

,16.2

)40

(34.6

,45.5

)50.5

(46,

54.9

)N/A

-32

(-35.4

,-28.6

)8.2

(4.3

,12.1

)23.7

(18.6

,28.9

)47.1

(42.5

,51.6

)82.6

(77.7

,87.5

)4A

-4SW

L–

–0

(0,0)

29.8

(25.4

,34.2

)44.1

(39.5

,48.7

)-28.6

(-31.8

,-25.4

)11.6

(7.3

,15.9

)39.9

(34.6

,45.2

)50.3

(46,

54.7

)N/A

-32.1

(-35.3

,-28.9

)8.1

(4.2

,11.9

)23.6

(18.3

,28.9

)46.9

(42.4

,51.5

)82.4

(77.6

,87.3

)5A

-0SW

L–

––

0(0,0)

14.3

(9.4

,19.2

)-58.4

(-61.9

,-55)

-18.2

(-23.6

,-12.9

)10.1

(4.9

,15.3

)20.6

(16.1

,25)

N/A

-61.9

(-65.3

,-58.5

)-21.7

(-26.3

,-17.1

)-6.2

(-11.2

,-1.1

)17.1

(12.7

,21.5

)52.6

(47.7

,57.6

)5A

-5SW

L–

––

–0

(0,0)

-72.7

(-77,

-68.4

)-32.5

(-37.9

,-27.1

)-4

.2(-9

.9,

1.5

)6.3

(1.1

,11.4

)N/A

-76.2

(-80.4

,-72)

-36

(-40.8

,-31.2

)-20.5

(-25.8

,-15.2

)2.8

(-2

.1,7.8

)38.3

(33.3

,43.4

)

3A

-3SW

LI

––

––

–0

(0,0)

40.2

(36,

44.4

)68.5

(64.1

,73)

79

(75.2

,82.7

)N/A

-3.5

(-5.2

,-1.7

)36.7

(33.1

,40.2

)52.2

(47.8

,56.6

)75.6

(72,

79.1

)111.1

(107.3

,114.8

)

4A

-0SW

LI

––

––

––

0(0,0)

28.3

(22.3

,34.4

)38.8

(33.8

,43.7

)N/A

-43.7

(-48,

-39.4

)-3

.5(-7

,0)

12

(6.5

,17.6

)35.4

(30,

40.7

)70.9

(65.2

,76.6

)

4A

-4SW

LI

––

––

––

–0

(0,0)

10.4

(5.4

,15.5

)N/A

-72

(-76.5

,-67.6

)-31.9

(-37.4

,-26.3

)-16.3

(-21.7

,-10.9

)7

(2,12)

42.5

(37.3

,47.7

)

5A

-0SW

LI

––

––

––

––

0(0,0)

N/A

-82.5

(-86.1

,-78.8

)-42.3

(-46.8

,-37.7

)-26.7

(-32,

-21.4

)-3

.4(-7

.7,

0.9

)32.1

(27.7

,36.5

)

5A

-5SW

LI

––

––

––

––

–N/A

N/A

N/A

N/A

N/A

N/A

3A

-3SW

LR

––

––

––

––

––

0(0,0)

40.2

(36.7

,43.7

)55.7

(51.5

,60)

79.1

(75.8

,82.3

)114.6

(110.7

,118.4

)

4A

-0SW

LR

––

––

––

––

––

–0

(0,0)

15.6

(10.7

,20.5

)38.9

(34.6

,43.1

)74.4

(69.3

,79.5

)

4A

-4SW

LR

––

––

––

––

––

––

0(0,0)

23.3

(18.9

,27.8

)58.8

(53.6

,64)

5A

-0SW

LR

––

––

––

––

––

––

–0

(0,0)

35.5

(30.5

,40.5

)

5A

-5SW

LR

––

––

––

––

––

––

––

0(0,0)

Tab

leJ.3

:C

onva

lesc

ent

resu

lts

wh

enva

ryin

gth

enu

mb

erof

short

wait

ing

list

faci

liti

es,

tota

lnum

ber

of

ap

pli

cati

on

s,an

dth

ety

pe

of

faci

lity

pop

ula

rity

dis

trib

uti

on(I

=in

vers

eof

actu

alfa

cili

typ

opu

lari

tyd

istr

ibu

tion

,R

=ch

oosi

ng

faci

lity

ran

dom

ly)

on

the

nu

mb

erof

AL

Cd

ays


3A

-3SW

L4A

-0SW

L4A

-4SW

L5A

-0SW

L5A

-5SW

L3A

-3SW

LI

4A

-0SW

LI

4A

-4SW

LI

5A

-0SW

LI

5A

-5SW

LI

3A

-3SW

LR

4A

-0SW

LR

4A

-4SW

LR

5A

-0SW

LR

5A

-5SW

LR

3A

-3SW

L0

(0,0)

0.1

(0,

0.1

)0.1

(0,0.1

)0.2

(0.2

,0.3

)0.2

(0.1

,0.2

)0

(0,0.1

)0.1

(0.1

,0.1

)0.1

(0.1

,0.2

)0.3

(0.2

,0.3

)N/A

0(0,0.1

)0.1

(0.1

,0.1

)0.2

(0.1

,0.2

)0.3

(0.2

,0.3

)0.4

(0.3

,0.4

)

4A

-0SW

L–

0(0,0)

0(0,0)

0.1

(0.1

,0.2

)0.1

(0,0.1

)0

(-0

.1,0)

0(0,0)

0.1

(0,0.1

)0.2

(0.1

,0.2

)N/A

0(-0

.1,0)

0(0,0)

0.1

(0,0.1

)0.2

(0.2

,0.3

)0.3

(0.2

,0.3

)

4A

-4SW

L–

–0

(0,0)

0.1

(0.1

,0.2

)0.1

(0,0.1

)0

(-0

.1,0)

0(0,0)

0.1

(0,0.1

)0.2

(0.1

,0.2

)N/A

0(-0

.1,0)

0(0,0)

0.1

(0,0.1

)0.2

(0.2

,0.3

)0.3

(0.2

,0.3

)

5A

-0SW

L–

––

0(0,0)

-0.1

(-0

.1,0)

-0.2

(-0.2

,-0.1

)-0.1

(-0.2

,-0.1

)-0

.1(-0

.1,0)

0(0,0.1

)N/A

-0.2

(-0.2

,-0.1

)-0.1

(-0.2

,-0.1

)0

(-0

.1,0)

0.1

(0,0.1

)0.1

(0.1

,0.2

)

5A

-5SW

L–

––

–0

(0,0)

-0.1

(-0.2

,-0.1

)-0

.1(-0

.1,0)

0(-0

.1,0)

0.1

(0,0.2

)N/A

-0.1

(-0.2

,-0.1

)-0

.1(-0

.1,0)

0(0,0.1

)0.1

(0.1

,0.2

)0.2

(0.1

,0.3

)

3A

-3SW

LI

––

––

–0

(0,0)

0(0,0.1

)0.1

(0.1

,0.1

)0.2

(0.2

,0.3

)N/A

0(0,0)

0(0,0.1

)0.1

(0.1

,0.2

)0.2

(0.2

,0.3

)0.3

(0.3

,0.4

)

4A

-0SW

LI

––

––

––

0(0,0)

0.1

(0,0.1

)0.2

(0.1

,0.2

)N/A

0(-0

.1,0)

0(0,0)

0.1

(0,0.1

)0.2

(0.2

,0.2

)0.3

(0.2

,0.3

)

4A

-4SW

LI

––

––

––

–0

(0,0)

0.1

(0.1

,0.2

)N/A

-0.1

(-0.1

,-0.1

)-0

.1(-0

.1,0)

0(0,0.1

)0.2

(0.1

,0.2

)0.2

(0.2

,0.3

)

5A

-0SW

LI

––

––

––

––

0(0,0)

N/A

-0.2

(-0.3

,-0.2

)-0.2

(-0.2

,-0.1

)-0

.1(-0

.2,0)

0(0,0.1

)0.1

(0,0.2

)

5A

-5SW

LI

––

––

––

––

–N/A

N/A

N/A

N/A

N/A

N/A

3A

-3SW

LR

––

––

––

––

––

0(0,0)

0(0,0.1

)0.1

(0.1

,0.2

)0.2

(0.2

,0.3

)0.3

(0.3

,0.4

)

4A

-0SW

LR

––

––

––

––

––

–0

(0,0)

0.1

(0,0.1

)0.2

(0.2

,0.2

)0.3

(0.2

,0.3

)

4A

-4SW

LR

––

––

––

––

––

––

0(0,0)

0.1

(0.1

,0.2

)0.2

(0.1

,0.3

)

5A

-0SW

LR

––

––

––

––

––

––

–0

(0,0)

0.1

(0,0.1

)

5A

-5SW

LR

––

––

––

––

––

––

––

0(0,0)

Tab

leJ.4

:C

onva

lesc

ent

resu

lts

wh

enva

ryin

gth

enu

mb

erof

short

wait

ing

list

faci

liti

es,

tota

lnum

ber

of

ap

pli

cati

on

s,an

dth

ety

pe

of

faci

lity

pop

ula

rity

dis

trib

uti

on(I

=in

vers

eof

actu

alfa

cili

typ

opu

lari

tyd

istr

ibu

tion

,R

=ch

oosi

ng

faci

lity

ran

dom

ly)

on

the

nu

mb

erof

die

din

hosp

ital

pati

ents


3A

-3SW

L4A

-0SW

L4A

-4SW

L5A

-0SW

L5A

-5SW

L3A

-3SW

LI

4A

-0SW

LI

4A

-4SW

LI

5A

-0SW

LI

5A

-5SW

LI

3A

-3SW

LR

4A

-0SW

LR

4A

-4SW

LR

5A

-0SW

LR

5A

-5SW

LR

3A

-3SW

L0

(0,0)

436.8

(400.9

,472.6

)

558.9

(517.5

,600.3

)772.3

(736.7

,808)

942.4

(901,

983.9

)-315.8

(-357,

-274.5

)5.3

(-3

5.7

,46.4

)-7

.4(-5

0.4

,35.6

)173.6

(133.9

,213.2

)252.4

(211.5

,293.3

)-175.8

(-219.5

,-132.1

)

174.4

(126.3

,222.5

)229.4

(182.2

,276.7

)427.7

(381.7

,473.6

)561.1

(520.1

,602.1

)

4A

-0SW

L–

0(0,0)

122.1

(97.5

,146.8

)335.6

(309,

362.1

)505.7

(481.4

,529.9

)-752.5

(-789.7

,-715.4

)

-431.4

(-461.3

,-401.5

)

-444.2

(-479.8

,-408.7

)

-263.2

(-297.5

,-228.9

)

-184.4

(-218.3

,-150.5

)

-612.6

(-648.4

,-576.7

)

-262.4

(-293.3

,-231.5

)

-207.3

(-246.4

,-168.3

)

-9.1

(-4

1.6

,23.4

)124.4

(94,

154.8

)

4A

-4SW

L–

–0

(0,0)

213.4

(181.1

,245.8

)383.5

(355.2

,411.9

)-874.7

(-910.2

,-839.1

)

-553.6

(-585.5

,-521.6

)

-566.3

(-598.9

,-533.7

)

-385.3

(-421.4

,-349.3

)

-306.5

(-341.8

,-271.2

)

-734.7

(-771.5

,-697.8

)

-384.5

(-418.5

,-350.6

)

-329.5

(-367.1

,-291.9

)

-131.2

(-166.1

,-96.3

)

2.2

(-3

1.2

,35.7

)

5A

-0SW

L–

––

0(0,0)

170.1

(148.9

,191.3

)-1088.1

(-1124,

-1052.2

)

-767

(-796.2

,-737.8

)-779.8

(-813.6

,-745.9

)

-598.8

(-630.2

,-567.4

)

-519.9

(-553.8

,-486)

-948.1

(-989.3

,-906.9

)

-598

(-634.6

,-561.3

)-542.9

(-578.5

,-507.3

)

-344.7

(-379,

-310.4

)-211.2

(-245.1

,-177.3

)5A

-5SW

L–

––

–0

(0,0)

-1258.2

(-1295.9

,-1220.5

)

-937.1

(-964.6

,-909.6

)

-949.9

(-981.9

,-917.8

)

-768.9

(-802,

-735.7

)-690

(-726.9

,-653.2

)-1118.2

(-1158.1

,-1078.4

)

-768.1

(-798.1

,-738)

-713

(-747.7

,-678.3

)-514.8

(-544.6

,-484.9

)

-381.3

(-412.1

,-350.5

)

3A

-3SW

LI

––

––

–0

(0,0)

321.1

(283.8

,358.4

)308.3

(268.2

,348.5

)489.3

(449.3

,529.3

)568.2

(531.4

,605)

140

(102,

177.9

)490.1

(448.5

,531.8

)545.2

(503.6

,586.7

)743.4

(700.3

,786.6

)876.9

(834.5

,919.3

)

4A

-0SW

LI

––

––

––

0(0,0)

-12.8

(-4

1.2

,15.7

)168.2

(137.1

,199.3

)247.1

(214.6

,279.5

)-181.1

(-222.3

,-139.9

)

169

(138.1

,200)

224.1

(185.1

,263.1

)422.3

(390.3

,454.3

)555.8

(522.2

,589.4

)

4A

-4SW

LI

––

––

––

–0

(0,0)

181

(147.7

,214.3

)259.8

(225,

294.7

)-168.4

(-210.3

,-126.4

)

181.8

(144.2

,219.4

)236.9

(199.6

,274.1

)435.1

(398.9

,471.3

)568.6

(532.1

,605.1

)

5A

-0SW

LI

––

––

––

––

0(0,0)

78.9

(52.6

,105.1

)-349.4

(-395,

-303.7

)0.8

(-4

1,42.6

)55.9

(16,

95.8

)254.1

(219.3

,288.9

)387.6

(355.2

,420)

5A

-5SW

LI

––

––

––

––

–0

(0,0)

-428.2

(-471.2

,-385.2

)

-78

(-120.4

,-35.7

)-2

3(-6

3.1

,17.1

)175.3

(138,

212.5

)308.7

(274,

343.5

)

3A

-3SW

LR

––

––

––

––

––

0(0,0)

350.2

(313.4

,386.9

)405.2

(365.1

,445.4

)603.5

(565,

641.9

)736.9

(696.4

,777.4

)

4A

-0SW

LR

––

––

––

––

––

–0

(0,0)

55.1

(21.5

,88.6

)253.3

(222.3

,284.3

)386.8

(354.5

,419)

4A

-4SW

LR

––

––

––

––

––

––

0(0,0)

198.2

(159.7

,236.8

)331.7

(294.1

,369.3

)

5A

-0SW

LR

––

––

––

––

––

––

–0

(0,0)

133.5

(106.4

,160.5

)

5A

-5SW

LR

––

––

––

––

––

––

––

0(0,0)

Tab

leJ.5

:LT

Cre

sult

sw

hen

vary

ing

the

nu

mb

erof

short

wait

ing

list

faci

liti

es,

tota

lnu

mb

erof

ap

pli

cati

ons,

an

dth

ety

pe

of

faci

lity

pop

ula

rity

dis

trib

uti

on

(I=

inve

rse

ofac

tual

faci

lity

pop

ula

rity

dis

trib

uti

on,

R=

choosi

ng

faci

lity

ran

dom

ly)

on

the

nu

mb

erof

AL

Cd

ays


3A

-3SW

L4A

-0SW

L4A

-4SW

L5A

-0SW

L5A

-5SW

L3A

-3SW

LI

4A

-0SW

LI

4A

-4SW

LI

5A

-0SW

LI

5A

-5SW

LI

3A

-3SW

LR

4A

-0SW

LR

4A

-4SW

LR

5A

-0SW

LR

5A

-5SW

LR

3A

-3SW

L0

(0,0)

3.1

(2.9

,3.3

)2.9

(2.6

,3.2

)4.4

(4.2

,4.7

)4.8

(4.5

,5)

-1.2

(-1.4

,-0.9

)1.5

(1.3

,1.8

)0.6

(0.4

,0.8

)2.5

(2.2

,2.7

)1.6

(1.4

,1.9

)-0.7

(-0.9

,-0.4

)2.3

(2.1

,2.6

)1.5

(1.2

,1.8

)3.3

(3.1

,3.6

)3.4

(3.1

,3.6

)

4A

-0SW

L–

0(0,0)

-0.2

(-0

.4,0)

1.3

(1.1

,1.5

)1.6

(1.4

,1.8

)-4.3

(-4.5

,-4)

-1.6

(-1.8

,-1.4

)-2.5

(-2.7

,-2.3

)-0.7

(-0.9

,-0.4

)-1.5

(-1.7

,-1.2

)-3.8

(-4,

-3.6

)-0.8

(-1,

-0.6

)-1.6

(-1.9

,-1.4

)0.2

(0,0.4

)0.3

(0,0.5

)

4A

-4SW

L–

–0

(0,0)

1.5

(1.3

,1.7

)1.8

(1.6

,2.1

)-4.1

(-4.4

,-3.8

)-1.4

(-1.6

,-1.1

)-2.3

(-2.6

,-2)

-0.5

(-0.7

,-0.2

)-1.3

(-1.6

,-1)

-3.6

(-3.9

,-3.3

)-0.6

(-0.8

,-0.3

)-1.4

(-1.7

,-1.2

)0.4

(0.2

,0.7

)0.4

(0.2

,0.7

)

5A

-0SW

L–

––

0(0,0)

0.3

(0.1

,0.5

)-5.6

(-5.8

,-5.3

)-2.9

(-3.1

,-2.7

)-3.8

(-4.1

,-3.6

)-2

(-2.2

,-1.8

)-2.8

(-3,

-2.5

)-5.1

(-5.4

,-4.8

)-2.1

(-2.3

,-1.9

)-2.9

(-3.2

,-2.7

)-1.1

(-1.3

,-0.9

)-1.1

(-1.3

,-0.8

)5A

-5SW

L–

––

–0

(0,0)

-5.9

(-6.2

,-5.7

)-3.2

(-3.4

,-3)

-4.2

(-4.4

,-3.9

)-2.3

(-2.5

,-2.1

)-3.1

(-3.4

,-2.9

)-5.4

(-5.7

,-5.2

)-2.4

(-2.6

,-2.2

)-3.3

(-3.5

,-3)

-1.4

(-1.6

,-1.2

)-1.4

(-1.6

,-1.2

)

3A

-3SW

LI

––

––

–0

(0,0)

2.7

(2.5

,2.9

)1.8

(1.5

,2)

3.6

(3.4

,3.9

)2.8

(2.5

,3.1

)0.5

(0.2

,0.7

)3.5

(3.3

,3.7

)2.7

(2.4

,2.9

)4.5

(4.2

,4.8

)4.5

(4.3

,4.8

)

4A

-0SW

LI

––

––

––

0(0,0)

-0.9

(-1.1

,-0.7

)0.9

(0.7

,1.1

)0.1

(-0

.1,0.3

)-2.2

(-2.4

,-2)

0.8

(0.6

,1)

0(-0

.3,0.2

)1.8

(1.6

,2)

1.8

(1.6

,2.1

)

4A

-4SW

LI

––

––

––

–0

(0,0)

1.9

(1.6

,2.1

)1

(0.8

,1.3

)-1.3

(-1.5

,-1)

1.7

(1.5

,2)

0.9

(0.6

,1.1

)2.7

(2.5

,3)

2.8

(2.5

,3)

5A

-0SW

LI

––

––

––

––

0(0,0)

-0.8

(-1.1

,-0.6

)-3.2

(-3.4

,-2.9

)-0

.1(-0

.3,

0.1

)-1

(-1.2

,-0.7

)0.9

(0.7

,1.1

)0.9

(0.7

,1.1

)

5A

-5SW

LI

––

––

––

––

–0

(0,0)

-2.3

(-2.6

,-2.1

)0.7

(0.5

,0.9

)-0

.1(-0

.4,

0.1

)1.7

(1.5

,1.9

)1.7

(1.5

,2)

3A

-3SW

LR

––

––

––

––

––

0(0,0)

3(2.8

,3.2

)2.2

(1.9

,2.4

)4

(3.8

,4.3

)4.1

(3.8

,4.3

)

4A

-0SW

LR

––

––

––

––

––

–0

(0,0)

-0.8

(-1,

-0.6

)1

(0.8

,1.2

)1

(0.8

,1.3

)

4A

-4SW

LR

––

––

––

––

––

––

0(0,0)

1.8

(1.6

,2.1

)1.9

(1.6

,2.1

)

5A

-0SW

LR

––

––

––

––

––

––

–0

(0,0)

0(-0

.2,0.2

)

5A

-5SW

LR

––

––

––

––

––

––

––

0(0,0)

Tab

leJ.6

:LT

Cre

sult

sw

hen

vary

ing

the

nu

mb

erof

short

wait

ing

list

faci

liti

es,

tota

lnu

mb

erof

ap

pli

cati

ons,

an

dth

ety

pe

of

faci

lity

pop

ula

rity

dis

trib

uti

on

(I=

inve

rse

ofac

tual

faci

lity

pop

ula

rity

dis

trib

uti

on,

R=

choosi

ng

faci

lity

ran

dom

ly)

on

the

nu

mb

erof

die

din

hosp

ital

pati

ents


3A

-3SW

L4A

-0SW

L4A

-4SW

L5A

-0SW

L5A

-5SW

L3A

-3SW

LI

4A

-0SW

LI

4A

-4SW

LI

5A

-0SW

LI

5A

-5SW

LI

3A

-3SW

LR

4A

-0SW

LR

4A

-4SW

LR

5A

-0SW

LR

5A

-5SW

LR

3A

-3SW

L0

(0,0)

65.8

(59,

72.6

)

140.1

(134.3

,146)

161.3

(155.4

,167.2

)207

(201.5

,212.5

)108.8

(102.2

,115.3

)184.1

(178.4

,189.8

)271.4

(265.9

,276.9

)285

(279.7

,290.3

)328

(322.6

,333.4

)57.2

(50.8

,63.6

)118

(111.9

,124)

203.6

(197.6

,209.6

)213.1

(207.7

,218.5

)262

(256.3

,267.7

)

4A

-0SW

L–

0(0,0)

74.3

(67.8

,80.8

)95.5

(89,

102)

141.2

(135.3

,147)

42.9

(35.9

,49.9

)118.2

(111.8

,124.7

)205.6

(199.7

,211.4

)219.2

(214,

224.3

)262.2

(256.9

,267.5

)-8.6

(-15.4

,-1.8

)52.2

(45.7

,58.6

)137.8

(131.4

,144.2

)147.3

(141.7

,152.9

)196.2

(190.6

,201.7

)4A

-4SW

L–

–0

(0,0)

21.2

(16.1

,26.3

)66.9

(62.3

,71.4

)-31.4

(-37.7

,-25)

43.9

(38.7

,49.2

)131.3

(126.3

,136.2

)144.9

(140.3

,149.4

)187.9

(183.7

,192.1

)-82.9

(-89.2

,-76.6

)-22.1

(-27.5

,-16.8

)63.5

(58.4

,68.6

)73

(68.3

,77.7

)121.9

(117.1

,126.6

)5A

-0SW

L–

––

0(0,0)

45.7

(41.6

,49.8

)-52.5

(-58.3

,-46.7

)22.8

(17.9

,27.6

)110.1

(105.7

,114.5

)123.7

(119.8

,127.6

)166.8

(162.9

,170.6

)-104.1

(-109.2

,-99)-43.3

(-48.4

,-38.2

)42.3

(38.1

,46.5

)51.8

(47.6

,56)

100.7

(96.4

,104.9

)5A

-5SW

L–

––

–0

(0,0)

-98.2

(-103.1

,-93.3

)

-22.9

(-27,

-18.9

)64.4

(60.8

,67.9

)78

(74.7

,81.3

)121

(117.6

,124.4

)-149.8

(-154.8

,-144.8

)

-89

(-93.7

,-84.3

)-3

.4(-7

.6,

0.8

)6.1

(2.5

,9.7

)55

(51.7

,58.3

)

3A

-3SW

LI

––

––

–0

(0,0)

75.3

(69.7

,80.9

)162.6

(157.4

,167.8

)176.2

(170.9

,181.5

)219.3

(214.2

,224.3

)-51.6

(-57.4

,-45.8

)9.2

(2.8

,15.6

)94.8

(89.4

,100.3

)104.3

(98.8

,109.9

)153.2

(148,

158.4

)

4A

-0SW

LI

––

––

––

0(0,0)

87.3

(83.3

,91.4

)100.9

(97,

104.9

)144

(140,

148)

-126.9

(-132.2

,-121.5

)

-66.1

(-71.2

,-61)

19.5

(14.7

,24.4

)29

(24.8

,33.3

)77.9

(73.7

,82.1

)

4A

-4SW

LI

––

––

––

–0

(0,0)

13.6

(10.4

,16.8

)56.7

(53.3

,60)

-214.2

(-219.1

,-209.3

)

-153.4

(-158.4

,-148.4

)

-67.8

(-71.9

,-63.7

)-58.3

(-62.3

,-54.3

)-9.4

(-13.3

,-5.5

)

5A

-0SW

LI

––

––

––

––

0(0,0)

43.1

(40.6

,45.5

)-227.8

(-232.5

,-223.1

)

-167

(-171.4

,-162.7

)-81.4

(-85.5

,-77.3

)-71.9

(-75.6

,-68.2

)-23

(-26.3

,-19.7

)

5A

-5SW

LI

––

––

––

––

–0

(0,0)

-270.8

(-275.5

,-266.2

)

-210.1

(-214.4

,-205.7

)

-124.4

(-128.2

,-120.7

)

-114.9

(-118.5

,-111.4

)

-66.1

(-69.2

,-62.9

)

3A

-3SW

LR

––

––

––

––

––

0(0,0)

60.8

(55,

66.5

)146.4

(141,

151.8

)155.9

(150.6

,161.1

)204.8

(199.9

,209.7

)

4A

-0SW

LR

––

––

––

––

––

–0

(0,0)

85.6

(80.5

,90.7

)95.1

(90.4

,99.8

)144

(139.2

,148.8

)

4A

-4SW

LR

––

––

––

––

––

––

0(0,0)

9.5

(5.5

,13.5

)58.4

(54.5

,62.2

)

5A

-0SW

LR

––

––

––

––

––

––

–0

(0,0)

48.9

(45.4

,52.4

)

5A

-5SW

LR

––

––

––

––

––

––

––

0(0,0)

Tab

leJ.7

:P

alli

ativ

ere

sult

sw

hen

vary

ing

the

nu

mb

erof

short

wait

ing

list

faci

liti

es,to

talnu

mb

erof

ap

pli

cati

on

s,an

dth

ety

pe

of

faci

lity

pop

ula

rity

dis

trib

uti

on

(I=

inve

rse

ofac

tual

faci

lity

pop

ula

rity

dis

trib

uti

on,

R=

choosi

ng

faci

lity

ran

dom

ly)

on

the

nu

mb

erof

AL

Cd

ays


3A

-3SW

L4A

-0SW

L4A

-4SW

L5A

-0SW

L5A

-5SW

L3A

-3SW

LI

4A

-0SW

LI

4A

-4SW

LI

5A

-0SW

LI

5A

-5SW

LI

3A

-3SW

LR

4A

-0SW

LR

4A

-4SW

LR

5A

-0SW

LR

5A

-5SW

LR

3A

-3SW

L0

(0,0)

2.7

(2.4

,3)

4.9

(4.5

,5.2

)6

(5.6

,6.3

)7.3

(6.9

,7.6

)3.3

(3,3.6

)6.1

(5.8

,6.4

)8.6

(8.3

,8.9

)8.9

(8.7

,9.2

)9.9

(9.6

,10.1

)1.8

(1.4

,2.1

)4.2

(4,4.5

)6.8

(6.5

,7.1

)7.3

(7,7.6

)8.6

(8.3

,8.9

)

4A

-0SW

L–

0(0,0)

2.1

(1.8

,2.4

)3.2

(2.9

,3.5

)4.5

(4.3

,4.8

)0.6

(0.3

,0.8

)3.4

(3.1

,3.6

)5.9

(5.6

,6.1

)6.2

(6,6.4

)7.1

(6.9

,7.4

)-0.9

(-1.3

,-0.6

)1.5

(1.3

,1.8

)4.1

(3.8

,4.4

)4.6

(4.4

,4.9

)5.9

(5.6

,6.1

)

4A

-4SW

L–

–0

(0,0)

1.1

(0.8

,1.4

)2.4

(2.1

,2.7

)-1.6

(-1.9

,-1.2

)1.2

(0.9

,1.5

)3.7

(3.5

,4)

4.1

(3.8

,4.3

)5

(4.7

,5.3

)-3.1

(-3.4

,-2.7

)-0.6

(-0.9

,-0.3

)2

(1.6

,2.3

)2.5

(2.2

,2.8

)3.7

(3.4

,4)

5A

-0SW

L–

––

0(0,0)

1.3

(1,1.6

)-2.7

(-3,

-2.4

)0.1

(-0

.1,0.4

)2.6

(2.4

,2.9

)3

(2.7

,3.2

)3.9

(3.7

,4.1

)-4.2

(-4.5

,-3.9

)-1.7

(-2,

-1.4

)0.9

(0.6

,1.1

)1.4

(1.1

,1.7

)2.6

(2.4

,2.9

)

5A

-5SW

L–

––

–0

(0,0)

-4

(-4.3

,-3.7

)-1.2

(-1.4

,-1)

1.3

(1.1

,1.6

)1.7

(1.4

,1.9

)2.6

(2.4

,2.8

)-5.5

(-5.8

,-5.1

)-3

(-3.3

,-2.7

)-0.4

(-0.7

,-0.2

)0.1

(-0

.2,0.3

)1.3

(1.1

,1.6

)

3A

-3SW

LI

––

––

–0

(0,0)

2.8

(2.6

,3)

5.3

(5.1

,5.6

)5.7

(5.4

,5.9

)6.6

(6.4

,6.8

)-1.5

(-1.8

,-1.2

)1

(0.7

,1.2

)3.5

(3.3

,3.8

)4.1

(3.8

,4.3

)5.3

(5.1

,5.6

)

4A

-0SW

LI

––

––

––

0(0,0)

2.5

(2.3

,2.7

)2.8

(2.6

,3)

3.8

(3.6

,4)

-4.3

(-4.6

,-4)

-1.8

(-2.1

,-1.6

)0.7

(0.5

,1)

1.3

(1,1.5

)2.5

(2.3

,2.7

)

4A

-4SW

LI

––

––

––

–0

(0,0)

0.3

(0.2

,0.5

)1.3

(1.1

,1.4

)-6.8

(-7.1

,-6.5

)-4.3

(-4.6

,-4.1

)-1.8

(-2,

-1.5

)-1.3

(-1.5

,-1)

0(-0

.2,0.2

)

5A

-0SW

LI

––

––

––

––

0(0,0)

0.9

(0.8

,1.1

)-7.1

(-7.4

,-6.9

)-4.7

(-4.9

,-4.5

)-2.1

(-2.3

,-1.9

)-1.6

(-1.8

,-1.4

)-0.3

(-0.5

,-0.1

)

5A

-5SW

LI

––

––

––

––

–0

(0,0)

-8.1

(-8.3

,-7.8

)-5.6

(-5.8

,-5.4

)-3

(-3.3

,-2.8

)-2.5

(-2.7

,-2.3

)-1.3

(-1.4

,-1.1

)

3A

-3SW

LR

––

––

––

––

––

0(0,0)

2.5

(2.2

,2.8

)5

(4.7

,5.4

)5.5

(5.2

,5.9

)6.8

(6.5

,7.1

)

4A

-0SW

LR

––

––

––

––

––

–0

(0,0)

2.6

(2.3

,2.8

)3.1

(2.8

,3.3

)4.3

(4.1

,4.6

)

4A

-4SW

LR

––

––

––

––

––

––

0(0,0)

0.5

(0.3

,0.8

)1.8

(1.5

,2)

5A

-0SW

LR

––

––

––

––

––

––

–0

(0,0)

1.3

(1.1

,1.5

)

5A

-5SW

LR

––

––

––

––

––

––

––

0(0,0)

Tab

leJ.8

:P

alli

ativ

ere

sult

sw

hen

vary

ing

the

nu

mb

erof

short

wait

ing

list

faci

liti

es,to

talnu

mb

erof

ap

pli

cati

on

s,an

dth

ety

pe

of

faci

lity

pop

ula

rity

dis

trib

uti

on

(I=

inve

rse

ofac

tual

faci

lity

pop

ula

rity

dis

trib

uti

on,

R=

choosi

ng

faci

lity

ran

dom

ly)

on

the

nu

mb

erof

die

din

hosp

ital

pati

ents


3A

-3SW

L4A

-0SW

L4A

-4SW

L5A

-0SW

L5A

-5SW

L3A

-3SW

LI

4A

-0SW

LI

4A

-4SW

LI

5A

-0SW

LI

5A

-5SW

LI

3A

-3SW

LR

4A

-0SW

LR

4A

-4SW

LR

5A

-0SW

LR

5A

-5SW

LR

3A

-3SW

L0

(0,0)

29.5

(17.9

,41)

247.5

(234.9

,260.1

)290.4

(279.9

,300.9

)441.9

(430.1

,453.7

)-616

(-631.8

,-600.3

)-506.4

(-518.8

,-494)

-305.4

(-319.4

,-291.4

)

-314.4

(-328.7

,-300.2

)

-35.9

(-50.2

,-21.6

)-435.3

(-449.4

,-421.3

)

-309.5

(-322.9

,-296)

-103.1

(-119.1

,-87)-81.5

(-95.3

,-67.6

)172.3

(157.6

,186.9

)

4A

-0SW

L–

0(0,0)

218

(208.8

,227.2

)260.9

(253.3

,268.6

)412.5

(404.5

,420.4

)-645.5

(-658.1

,-632.9

)

-535.9

(-546.2

,-525.5

)

-334.9

(-347.3

,-322.5

)

-343.9

(-355.1

,-332.7

)

-65.4

(-76.7

,-54.1

)-464.8

(-477.5

,-452.1

)

-338.9

(-348.8

,-329.1

)

-132.6

(-145.8

,-119.3

)

-110.9

(-120.7

,-101.2

)

142.8

(130.6

,155)

4A

-4SW

L–

–0

(0,0)

42.9

(34.6

,51.3

)194.5

(184.9

,204)

-863.5

(-876.6

,-850.4

)

-753.9

(-764.6

,-743.1

)

-552.9

(-565,

-540.7

)-561.9

(-572.6

,-551.2

)

-283.4

(-295.6

,-271.2

)

-682.8

(-695.2

,-670.4

)

-556.9

(-568.2

,-545.6

)

-350.6

(-364.6

,-336.5

)

-328.9

(-339.4

,-318.5

)

-75.2

(-87.9

,-62.5

)

5A

-0SW

L–

––

0(0,0)

151.5

(143.8

,159.3

)-906.4

(-919.1

,-893.7

)

-796.8

(-807.3

,-786.3

)

-595.8

(-607.5

,-584.1

)

-604.9

(-615.2

,-594.5

)

-326.3

(-337.8

,-314.9

)

-725.7

(-737.6

,-713.8

)

-599.9

(-609.6

,-590.2

)

-393.5

(-405.8

,-381.3

)

-371.9

(-381.7

,-362.1

)

-118.1

(-129.7

,-106.6

)5A

-5SW

L–

––

–0

(0,0)

-1057.9

(-1071.1

,-1044.8

)

-948.3

(-958.5

,-938.1

)

-747.3

(-759.3

,-735.3

)

-756.4

(-767.5

,-745.3

)

-477.8

(-489.5

,-466.2

)

-877.3

(-890.5

,-864.1

)

-751.4

(-761.1

,-741.7

)

-545

(-558.6

,-531.5

)-523.4

(-533.7

,-513.1

)

-269.7

(-281.6

,-257.7

)

3A

-3SW

LI

––

––

–0

(0,0)

109.6

(95.5

,123.8

)310.6

(296.1

,325.1

)301.6

(288.1

,315)

580.1

(564.9

,595.2

)180.7

(165,

196.4

)306.5

(292.7

,320.4

)512.9

(499,

526.8

)534.5

(521.1

,547.9

)788.3

(771.9

,804.6

)

4A

-0SW

LI

––

––

––

0(0,0)

201

(186.6

,215.4

)191.9

(178.9

,204.9

)470.5

(456.8

,484.2

)71.1

(57,

85.1

)196.9

(185.6

,208.3

)403.3

(388.7

,417.8

)424.9

(413.8

,436)

678.6

(665.4

,691.9

)

4A

-4SW

LI

––

––

––

–0

(0,0)

-9(-2

2.8

,4.7

)269.5

(255,

284)

-129.9

(-146.1

,-113.7

)

-4.1

(-1

6.9

,8.8

)202.3

(187.7

,216.9

)223.9

(210.1

,237.8

)477.7

(462.8

,492.6

)

5A

-0SW

LI

––

––

––

––

0(0,0)

278.5

(266.5

,290.5

)-120.9

(-133.6

,-108.2

)

5(-6

.3,16.2

)211.3

(196.9

,225.7

)233

(221.2

,244.8

)486.7

(473.2

,500.2

)

5A

-5SW

LI

––

––

––

––

–0

(0,0)

-399.4

(-413.7

,-385.1

)

-273.5

(-286.4

,-260.7

)

-67.2

(-82.9

,-51.4

)-45.6

(-58.2

,-33)

208.2

(193.3

,223.1

)

3A

-3SW

LR

––

––

––

––

––

0(0,0)

125.9

(113.4

,138.3

)332.2

(316.9

,347.5

)353.9

(340.9

,366.8

)607.6

(591.6

,623.5

)

4A

-0SW

LR

––

––

––

––

––

–0

(0,0)

206.4

(192.9

,219.8

)228

(216.1

,239.9

)481.7

(469.1

,494.3

)

4A

-4SW

LR

––

––

––

––

––

––

0(0,0)

21.6

(7.8

,35.4

)275.4

(259.4

,291.3

)

5A

-0SW

LR

––

––

––

––

––

––

–0

(0,0)

253.7

(242,

265.5

)

5A

-5SW

LR

––

––

––

––

––

––

––

0(0,0)

Tab

leJ.9

:R

ehabil

itat

ion

resu

lts

wh

enva

ryin

gth

enu

mb

erof

short

wait

ing

list

faci

liti

es,

tota

lnu

mb

erof

ap

pli

cati

on

s,an

dth

ety

pe

of

faci

lity

pop

ula

rity

dis

trib

uti

on(I

=in

vers

eof

actu

alfa

cili

typ

opu

lari

tyd

istr

ibu

tion

,R

=ch

oosi

ng

faci

lity

ran

dom

ly)

on

the

nu

mb

erof

AL

Cd

ays


3A

-3SW

L4A

-0SW

L4A

-4SW

L5A

-0SW

L5A

-5SW

L3A

-3SW

LI

4A

-0SW

LI

4A

-4SW

LI

5A

-0SW

LI

5A

-5SW

LI

3A

-3SW

LR

4A

-0SW

LR

4A

-4SW

LR

5A

-0SW

LR

5A

-5SW

LR

3A

-3SW

L0

(0,0)

1.7

(1.4

,1.9

)2.7

(2.4

,3)

3.7

(3.5

,4)

4.1

(3.9

,4.4

)-7.6

(-8,

-7.2

)-2

(-2.3

,-1.7

)-3.2

(-3.6

,-2.7

)0.1

(-0

.2,0.3

)0.3

(-0

.1,0.6

)-5.3

(-5.7

,-5)

-0.4

(-0.7

,-0.1

)-0.9

(-1.4

,-0.5

)1.7

(1.4

,2)

2(1.7

,2.3

)

4A

-0SW

L–

0(0,0)

1(0.8

,1.3

)2.1

(1.9

,2.2

)2.5

(2.2

,2.7

)-9.3

(-9.7

,-9)

-3.7

(-3.9

,-3.5

)-4.9

(-5.2

,-4.5

)-1.6

(-1.9

,-1.4

)-1.4

(-1.7

,-1.1

)-7

(-7.4

,-6.7

)-2.1

(-2.3

,-1.9

)-2.6

(-3,

-2.3

)0

(-0

.2,0.2

)0.3

(0,0.5

)

4A

-4SW

L–

–0

(0,0)

1(0.8

,1.2

)1.4

(1.2

,1.7

)-10.3

(-10.7

,-10)

-4.7

(-5,

-4.5

)-5.9

(-6.3

,-5.5

)-2.7

(-2.9

,-2.4

)-2.4

(-2.8

,-2.1

)-8

(-8.4

,-7.7

)-3.1

(-3.4

,-2.9

)-3.7

(-4,

-3.3

)-1

(-1.3

,-0.7

)-0.7

(-1,

-0.4

)5A

-0SW

L–

––

0(0,0)

0.4

(0.2

,0.6

)-11.4

(-11.7

,-11)

-5.8

(-6,

-5.5

)-6.9

(-7.3

,-6.5

)-3.7

(-3.9

,-3.5

)-3.5

(-3.8

,-3.1

)-9.1

(-9.4

,-8.7

)-4.2

(-4.4

,-3.9

)-4.7

(-5,

-4.3

)-2

(-2.3

,-1.8

)-1.8

(-2,

-1.5

)5A

-5SW

L–

––

–0

(0,0)

-11.8

(-12.2

,-11.4

)-6.2

(-6.4

,-5.9

)-7.3

(-7.7

,-6.9

)-4.1

(-4.3

,-3.9

)-3.9

(-4.2

,-3.6

)-9.5

(-9.8

,-9.1

)-4.6

(-4.8

,-4.3

)-5.1

(-5.4

,-4.7

)-2.4

(-2.7

,-2.2

)-2.2

(-2.4

,-1.9

)

3A

-3SW

LI

––

––

–0

(0,0)

5.6

(5.2

,6)

4.5

(4,4.9

)7.7

(7.3

,8.1

)7.9

(7.5

,8.3

)2.3

(1.8

,2.8

)7.2

(6.8

,7.6

)6.7

(6.3

,7.1

)9.3

(8.9

,9.7

)9.6

(9.2

,10)

4A

-0SW

LI

––

––

––

0(0,0)

-1.1

(-1.5

,-0.8

)2.1

(1.8

,2.3

)2.3

(2,2.6

)-3.3

(-3.7

,-2.9

)1.6

(1.3

,1.8

)1.1

(0.8

,1.4

)3.7

(3.5

,4)

4(3.7

,4.3

)

4A

-4SW

LI

––

––

––

–0

(0,0)

3.2

(2.8

,3.7

)3.5

(3,3.9

)-2.2

(-2.7

,-1.7

)2.7

(2.3

,3.1

)2.2

(1.8

,2.7

)4.9

(4.4

,5.3

)5.1

(4.7

,5.6

)

5A

-0SW

LI

––

––

––

––

0(0,0)

0.2

(-0

.1,0.6

)-5.4

(-5.8

,-5)

-0.5

(-0.7

,-0.2

)-1

(-1.4

,-0.6

)1.7

(1.4

,1.9

)1.9

(1.6

,2.2

)

5A

-5SW

LI

––

––

––

––

–0

(0,0)

-5.6

(-6,

-5.2

)-0.7

(-1.1

,-0.4

)-1.2

(-1.6

,-0.8

)1.4

(1.1

,1.7

)1.7

(1.3

,2)

3A

-3SW

LR

––

––

––

––

––

0(0,0)

4.9

(4.5

,5.3

)4.4

(4,4.8

)7

(6.7

,7.4

)7.3

(7,7.7

)

4A

-0SW

LR

––

––

––

––

––

–0

(0,0)

-0.5

(-0.9

,-0.2

)2.1

(1.9

,2.4

)2.4

(2.1

,2.7

)

4A

-4SW

LR

––

––

––

––

––

––

0(0,0)

2.6

(2.3

,3)

2.9

(2.5

,3.3

)

5A

-0SW

LR

––

––

––

––

––

––

–0

(0,0)

0.3

(0,0.5

)

5A

-5SW

LR

––

––

––

––

––

––

––

0(0,0)

Tab

leJ.1

0:R

ehab

ilit

atio

nre

sult

sw

hen

vary

ing

the

nu

mb

erof

short

wait

ing

list

faci

liti

es,

tota

lnu

mb

erof

ap

pli

cati

on

s,an

dth

ety

pe

of

faci

lity

pop

ula

rity

dis

trib

uti

on(I

=in

vers

eof

actu

alfa

cili

typ

opu

lari

tyd

istr

ibu

tion

,R

=ch

oosi

ng

faci

lity

ran

dom

ly)

on

the

nu

mb

erof

die

din

hosp

ital

pati

ents

the effects of altering discharge policies to alternate

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