Emergency Medicine Australasia (2004) 16, 201–207

Blackwell Publishing, Ltd. Original ResearchA casemix model for access block

A casemix model for estimating the impact of hospital access block on the emergency departmentPeter StuartDepartment of Emergency Medicine, Lyell McEwin Health Service, Elizabeth Vale, South Australia, Australia

Abstract

Objective: To determine the ED activity and costs resulting from access block.

Methods: A casemix model (AWOOS) was developed to measure activity due to access block.Using data from four hospitals between 1998 and 2002, ED activity was measured usingthe urgency and disposition group (UDG) casemix model and the AWOOS model withthe purpose of determining the change in ED activity due to access block.

Results: Whilst the mean length of stay in ED (admitted patients) increased by 93% between1998 and 2002, mean UDG activity increased by 0.63% compared to a mean increase inAWOOS activity of 24.5%. The 23.9% difference between UDG and AWOOS activityrepresents the (unmeasured) increase in ED activity and costs for the period 1998–2002resulting from access block.

Conclusion: The UDG system significantly underestimates the activity in EDs experiencing markedaccess block.

Key words: access block, ambulatory casemix, emergency hospital services, hospital funding, overcrowding.

Introduction

First recognized in health care more than two decadesago in the United States,1 access block has been a morerecent development in Australia. Its rapid growth hasled to the problem being identified by the AustralasianCollege for Emergency Medicine as the single largestbarrier to the delivery of adequate emergency care.2Access block represents a failure of the health system

and refers to the situation where patients requiringemergency hospital admission spend greater than 8 hin an ED because they are unable to gain access toappropriate hospital beds.3,4 It is associated with adecrease in ED efficiency, decreased quality of care2,5–7

an increase in the inpatient length of stay8 and anincreased risk for adverse events.9–11

The urgency and disposition group (UDG) ambu-latory casemix model has been used since 1998/1999 to

Correspondence: Dr Peter Stuart, Director, Department of Emergency Medicine, Lyell McEwin Health Service, Haydown Road, Elizabeth Vale, SA 5112, Australia. Email: Peter.Stuart@nwahs.sa.gov.au

Peter Stuart, MBBS, DipRACOG, FACEM, MPH, Director.

Conflicts of interest: None

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measure activity levels in South Australian Hospitalemergency departments and provides a method fordetermining funding based on activity targets.12,13 Atthe time the UDG casemix model was introduced, themajority of public teaching hospitals in SouthAustralia did not experience significant access block.The aim of the present study is to determine the EDactivity and costs resulting from access block.

Methods

Emergency department directors at four SouthAustralian urban ACEM accredited public teachinghospitals were approached for permission to usecasemix and access block data for the period 1998–2002. Access block data included the proportion ofadmitted patients who are transferred to the wardmore than 8 h after presentation to the ED4 and themean length of stay for admitted/transferred patientsdefined as the time between presentation to the ED to thetime of departure from the ED. As the hospitals share thesame electronic database14 and these times representmandatory fields, data were captured for all patients.

The four hospitals comprise a mixture of tertiaryreferral and large urban centres and include both adultand mixed adult-paediatric emergency departmentswith a combined annual ED census of 172 000 (withindividual department attendances ranging from32 000 and 50 000 patients). In 2002 the proportion ofadmitted/transferred patients waiting in excess of 8 hin the ED varied between 13% to 54%. To protect theinterests of the participating hospitals the individualcasemix data from each site were de-identified in thestudy.

Development of the AWOOS model

The South Australian UDG casemix model has 11urgency and disposition groups, with outcome as theprimary variable and priority as a secondary variable.12

The model incorporates a weighting for each groupand when applied to the number of presentations ineach group, termed occasions of service (OOS), a totalvalue of the amount of weighted occasion of service (orWOOS) can be determined. The version of the modelused in South Australia and the associated weightingfactor for each UDG is shown in Table 1.15

Using the UDG casemix model as a starting point,the access block adjusted weighted occasions of service(AWOOS) model was developed. The AWOOS model

incorporates two modifying variables to firstly takeinto account the increased length of stay (i.e. treatmenttime in the ED) that results from access block (lengthof stay factor) and secondly, measure the additionalcost resulting from this increased activity (access blockcost ratio). Combining the ‘access block cost ratio’ withthe ‘length of stay factor’ results in a correction thattakes into account the increased the length of stay andED costs resulting from access block.

Length of stay factorAt the time the UDG casemix model was developed themean length of stay in the ED for admitted patientswas 220 min.12 In developing the AWOOS model itseemed reasonable to assume that the UDG modelwould most accurately reflect ED activity and costwhen the mean length of stay (LOS) for admittedpatients in the ED approximates 220 min. Howeverwhere the mean length of stay exceeded 220 min, theadditional cost of providing care to admitted patientsin the ED may not be captured by the UDG casemixmodel. The first step in developing the new model wasto therefore include an adjustment for the mean lengthof stay. This is performed by calculating the ‘length ofstay factor’, which is the additional time spent bypatients in the ED waiting for a bed due to accessblock. This is expressed as a proportion of the timerequired for initial ED assessment/management (takenas 220 min based on the UDG costing study).12 Theequation for this is shown below.

Table 1. The urgency and disposition group model (UDG) used inSouth Australian hospitals15

Outcome Priority Weight

Died All triage 2.988Admitted /transferred Triage 1 5.379

Triage 2 2.870Triage 3 2.623Triage 4 2.247Triage 5 2.247

Home Triage 1 2.137Triage 2 2.000

Triage 3 1.735

Triage 4 1.430

Triage 5 1.152

Length of stay factor =(Mean LOS 220)

220−

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Mean LOS = Mean length of stay in the ED foradmitted/transferred patients = mean time of presenta-tion to time of departure from the ED (measured inminutes).

Access block cost ratioFor most patients the cost (per hour) associated withthe continued care whilst waiting for an inpatient bedis likely to differ from the initial ED cost (per hour)associated with the initial assessment and management.To adjust for this cost differential an access block costratio is calculated by comparing the cost (per hour) forthe period waiting in the ED for an inpatient bed (postadmission phase in the ED) to the cost per hour for theED assessment/management (pre-admission phase inthe ED).

The AWOOS modelCombining the access block cost ratio with the length ofstay factor results in a correction that takes intoaccount not only the length of stay resulting fromaccess block, but provides an adjustment to reflect theincreased cost of patient care. This AWOOS correctionfactor is shown below.

AWOOS correction factor = 1 + Access block cost ratio× Length of stay factor

The AWOOS correction factor is utilized to adjust theweighting in the UDG casemix model for each of thefive ‘admitted’ groups to reflect the increased activitydue to access block and provide a measure of the costsassociated with this increased activity. The weightsfor the home and died groups in the UDG model arenot adjusted. A worked example is shown in Figure 1.The revised WOOS value is known as the access blockadjusted weighted occasion of service or AWOOS.

Determining the access block cost ratio: A pilot study

To enable the model to be utilized to estimate theactivity and costs of access block it is necessary todetermine the access block cost ratio. With the aim ofproviding a broad estimate for the access block costratio a small pilot study was undertaken at LyellMcEwin Health Service, an urban 200 bed hospitalaccredited for training in emergency medicine. The

Emergency Department has an annual census of40 000 patients (one third paediatric) and at the time ofpilot study 41% of admitted/transferred patientswaited greater than 8 h in the ED. The EmergencyDepartment electronic patient database14 was used toobtain the data required to calculate the UDG casemix,mean length of stay and the proportion of access blockamongst patients admitted or transferred.

A convenience sample of two (National TriageScale)16 category 2 and three category 3 admittedadult ED patients (one mental health, one surgical,three medical) were followed prospectively duringtheir stay in the ED. Utilizing the same approach tothat undertaken in the costing studies that formed thebasis for the UDG casemix model,12,13 the (present day)costs in each case were identified and measured for theduration of the patient’s stay in the ED. These includedall consumable goods used for medical treatment,meals, linen, medical imaging, laboratory costs, medical,nursing and ancillary staff costs and ED managementoverheads. Hospital overheads were not measured inthe study.

Medical and nursing staff costs/hour werecalculated by taking the total (present day) cost /annum for medical and nursing staff in the ED and

Access blockratiocost

Cost/hour (post admission phase)Cost/hour (pre-admission phase)

=

=

=

Figure 1. A worked example of the adjusted weighted occasionsof service (AWOOS) casemix model. No adjustment is made for thehome or died urgency and disposition groups.

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dividing the number of full time equivalent (FTE)hours/annum to determine the costs/hour for medicaland nursing staff. This method enabled the EDoverhead costs for medical and nursing managementto be incorporated into the model. The clerical andancillary staff costs were calculated using a similarprocess taking the total (present day) cost per annum,but dividing this by patient census. This took intoaccount that clerical and ancillary staff input topatient management was similar in most cases (e.g.booking in the patient, assisting with the transfer ofthe patient out of the department, or to imaging or tothe ward, use of the IT system). The hospital clinicalsupplies department, pharmacy, pathology providerand imaging department provided the data of the costsof the relevant goods and services.

For the pre-admission phase of care, the medical andnursing hours were based on the UDG costing model12

that had utilized a time in motion process to determinemean medical and nursing time by triage category. Forexample, the mean time spent by a medical officercaring for a category 3 patient was 64 min, whilst thenursing time was 53 min. In the development of themodel, the amount of medical time required to managepatients post admission medical was required. Follow-ing discussions with ED medical staff this was con-servatively estimated to be 5 min/hour (but noted bystaff to vary significantly due to factors such as pain,severity of underlying illness, risk of violence/suicide,age of the patient). The nursing time was estimatedfrom the hospital EXCELCARE program,17 utilizingthe documented nursing care undertaken during thepatient’s time in the ED. This included nursing observ-ations, tests (e.g. repeat, ECG, blood glucose level deter-mination), administration of medications, assistancerequired with meals, toileting and linen change.

To calculate the access block cost ratio, the (dollar)cost /hour for the period exceeding 220 min (postadmission phase) was compared to the cost/hour forthe first 220 min of the attendance (pre-admissionphase).

Statistical analysis

Correlation between UDG casemix activity and degreeof access block for the period 1998–2002 at each of thestudy hospitals was determined using the Pearson’s(product-moment) correlation coefficient (r). This wascompared with the AWOOS model with theexpectation that the AWOOS model would be morestrongly correlated to the proportion of access blockthan the UDG model. To estimate the proportionalincrease in ED activity resulting from access block thechange to activity levels was measured using the UDGcasemix system and AWOOS model over the period1998–2002. The difference in the proportional changeto UDG activity and AWOOS activity identified the(unmeasured) activity and costs resulting from accessblock. A significance level of P < 0.05 was used and95% confidence intervals measured. Statistical analysisutilized STATA 8.0 statistical package.18

Results

Over the 5-year study period, combined data for thefour hospitals showed that the total occasions ofservice increased by 0.47% (range −5.9% to 13.0%),mean length of stay for admitted/transferred patientsincreased by 93% (range 21% to 183%) and UDGactivity increased by 0.63% (range −5.6% to 6.1%)(Table 2). Although all hospitals experienced access

Table 2. Percent change to occasions of service (OOS), length of ED stay for admitted/transferred patients (LOS), urgency and dispositiongroup (UDG) activity and adjusted weighted occasions of service (AWOOS) activity for the period 1998–2002. Correlation between UDG modeland access block indicator, AWOOS model and access block indicator and the difference between UDG and AWOOS measured activity overthe period 1998–2002

OOS 1998/2002

LOS 1998/2002

UDG activity 1998/2002

AWOOS activity 1998/2002

Difference AWOOS/UDG

1998/2002

Correlation UDG to

access block

Correlation AWOOS to

access block

Hospital A 13% 21% 6.1% 11.2% 5.1% 0.91 (P = 0.03) 0.95 (P < 0.01)Hospital B −1.3% 47% 1.7% 15.3% 13.6% 0.31 (P = 0.4) 0.84 (P < 0.01)Hospital C −5.9% 122% 0.03% 25.3% 25.3% 0.02 (P = 0.98) 0.99 (P < 0.01)Hospital D −5.8% 183% −5.3% 46.1% 51.4% −0.56 (P = 0.08) 0.90 (P = 0.04)Mean: all hospitals 0.46% 93% 0.63% 24.5% 23.9%

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block in 2002 there was a wide variation in theproportion of patients waiting greater than 8 h in theED ranging from 16% to 63%.

The AWOOS model was strongly correlated to thedegree of access block at all of four study hospitals(r = 0.84–0.99, P < 0.05). UDG measured activity showedeither no correlation or was negatively correlated withaccess block at three hospitals, whilst one hospital(Hospital A) showed a positive correlation (0.915, P = 0.03)between UDG activity and the degree of access block(Table 2).

Compared with the other study hospitals, HospitalA was the only one of the group to experience an increasein occasions of service over the 5-year study period (13%),had the smallest increase in length of stay (21%), andhad the lowest level of access block for 2002 (16%).

In the pilot study, the access block cost ratio for thefive subjects ranged between 0.4 and 0.62 with a meanof 0.51 (95% CI 0.38, 0.64). A breakdown of theindividual cost factors associated with the ED stay isshown in Table 3. In comparison to the pre-admissioncosts, the major cost factor in the post admissionperiod was nursing (accounting for 17% of pre-admission cost but responsible for 66% of the postadmission costs). Medical staffing, althoughresponsible for a third of pre-admission costs, showeda moderate decrease in the post admission period.

Compared to the small change in UDG activity(0.63%) over the 5-year period, the AWOOS measuredcasemix activity showed a mean increase of 24.5%(range 11.6% to 46.1%) (Table 2). The increased(unmeasured) activity and costs resulting from accessblock over the period 1998–2002 was 23.9% (range5.1% to 51.4%).

Discussion

The study found a lack of correlation between thedegree of access block and UDG casemix activity inthe three hospitals demonstrating the largest increasein the length of stay for admitted/transferred patients.Utilizing a model developed to take into account theincreased length of stay and economic factorsassociated with access block it was found that theUDG casemix system underestimated activity and EDcosts over a 5-year period by a mean of 23.9% (range5.1% to 51.4%).

It is significant that, of the five cost driversidentified (Table 4) during the development of the UDGmodel12 treatment time (or length of ED stay) providedthe highest contribution to cost variance reduction andshowed ‘a linear increase in total cost the longer apatient remained in the ED’.12 This finding has beenconfirmed in other studies.19 In developing the UDGcasemix system it was decided to remove treatmenttime from the model as its inclusion ‘might create

Table 3. Priority status, clinical presentation, length of stay and breakdown of costs for the five cases used to estimate the access block costratio

Case Priority(NTS)

Presentation LOS Hours

Access block cost ratio

Proportion of total costsDrugs Goods

servicesTests Nursing Medical Ancillary

1 3 Medical 42.3 48% 6% 11% 9% 54% 18% 1%2 3 Medical 54.1 42% 7% 7% 9% 57% 19% 1%3 2 Surgical 47.0 62% 2% 9% 5% 65% 18% 1%4 2 Medical 29.3 40% 4% 7% 14% 56% 18% 1%5 3 Mental health 49.3 61% 1% 14% 0% 55% 29% 1%

Mean values 44.4 51% 4% 10% 8% 57% 20% 1%

Pre-admission Costs 3% 8% 36% 17% 32% 1%

Post admission Costs 4% 10% 1% 66% 14% 1%

Table 4. The five principle cost drivers and associated costvariance reduction identified during the development of the urgencyand disposition groups casemix model12

Cost driver Cost variance reduction (%)

Treatment time (minutes) 33.6Outcome (five categories) 28.6Main Diagnostic categories

(36 categories)24.4

Priority (five levels) 23.9Age (four groups) 12.5

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undesirable gaming (keeping the patient longer in theED to influence higher funding)’.12 As the studyillustrates, if the UDG casemix system is applied in thecontext of access block (the effect of which is tomarkedly increase length of ED stay) it will result in asignificant underestimation of ED activity. Thisseverely limits the use of the model to compare activitybetween hospitals or across years where the meanlength of ED stay differs significantly.

With the rapid development of access block inAustralian hospitals, much of the burden of this healthsystem failure has been born by EDs. The use of theUDG casemix system as a measure of ED activitysignificantly underestimates actual levels of activity,which has the potential for under funding ofdepartments with a marked degree of access block.It is timely that a casemix model is developed tomeasure ED activity in the context of increasingaccess block.

The AWOOS model provides a practical approachto measuring the impact of access block on EDworkload and importantly provides a model forevaluating the economic costs to the health system.There is evidence that as EDs become increasinglyburdened with excessive workload demands as aresult of access block, their efficiency is compromised.7It is therefore not surprising that in severe cases theUDG measured activity may actually decrease asexemplified by the negative correlation between UDGactivity and degree of access block seen at hospital D(r = −0.56). This may lead to the false conclusion thatthe ED activity has decreased and there is a decreasedrequirement for resources to meet demand. This hasthe result of further compounding the workloadpressures on an already stressed ED.

An essential component in developing the AWOOSmodel was to ensure that it could be used to estimatethe economic costs for the increased activity resultingfrom access block and provide a useful tool for healtheconomists in determining allocation of resources formanaging emergency demand. The access block costratio is a key factor in the model and represents theproportional cost per hour for providing care of anadmitted patient waiting for a bed in the ED comparedto the cost per hour of the initial ED assessment andmanagement process. It is important to note that thepresent study provides only an estimate of the accessblock cost ratio. It is limited by the small sample ofadult subjects studied at a single hospital and theindirect methods used to estimate medical and nursingtime. A multicentre trial is required to provide a more

precise estimation for this cost ratio and to explore forthe possibility of geographical variation.

The AWOOS model has a number of limitations. Asit is designed for departments with access block itcannot be practically applied where the mean ED LOSis below 220 min. The model does not take into accounta possible change in the length of stay for dischargedpatients due to access block or changes to clinicalpractice.20 For admitted patients, the model assumesthat the costs/hour are fixed within the pre- and postadmission periods. Whilst the post admission costscould be expected to vary only slightly over a shorterpost admission phase (e.g. 4–8 h) they have the potentialto show more significant variation over longer periods.The mean time of admission represents a central partof the AWOOS model and is dependent on a range offactors including staffing, geography, medical practice,access to diagnostic investigations and availability ofinpatient registrars. As the pilot study could not beused to provide a valid measure of the mean ‘time ofadmission’, the results of the multicentre UDG studywere used as a basis for the estimate. It is possiblehowever, that this time may have altered as a result ofaccess block and/or changes to the factors above andfurther research is recommended.

Conclusion

The urgency and disposition casemix system does notmeasure the activity or costs associated with accessblock and as a consequence, significantly under-estimates the activity in EDs experiencing markedaccess block. The AWOOS casemix model adjusts forincreased workload and costs resulting from accessblock and may be a more reliable indicator of EDactivity than the UDG model in the era of access block.

Acknowledgements

The author thanks Ms Annette Williams, Ms JoRobertson, Mr Ian Rowbottom, Ms Diane Rogowskiand Ms Karen Harlin.

Accepted 7 March 2004

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