efficiency of operations of regional ......report on the audit undertaken on efficiency of...

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M A R C H 2 0 1 5 1THE EFFICIENCY

OF OPERATIONS OF REGIONALREFERRAL HOSPITALS IN UGANDA

V A L U E F O R M O N E Y A U D I T R E P O R T

MARCH 2015

T H E R E P U B L I C O F U G A N D A

OFFICE OF THE AUDITOR GENERAL

EFFICIENCY OF OPERATIONS OF REGIONAL REFERRAL

HOSPITALS IN UGANDA


T H E R E P U B L I C O F U G A N D A

THE EFFICIENCYOF OPERATIONS OF REGIONAL

REFERRAL HOSPITALS IN UGANDA

V A L U E F O R M O N E Y A U D I T R E P O R T

MARCH 2015

AUDITOR GENERAL’S MESSAGE

AUDITOR GENERAL’S MESSAGE

31st March 2015

The Rt. Hon. Speaker of ParliamentParliament of UgandaKampala

REPORT OF THE AUDITOR GENERAL ON THE EFFICIENCY OF OPERATIONS OF REGIONAL REFERRAL HOSPITALS IN UGANDA

In accordance with Article 163 (3) of the Constitution, I hereby submit my report on the audit undertaken on Efficiency of Operations of Regional Referral Hospitals in Uganda.

My office intends to carry out a follow – up at an appropriate time regarding actions taken in relation to the recommendations in this report.

I would like to thank my staff who undertook this audit, the consultants from the Swedish National Audit Office for the technical support provided, and the staff of Ministry of Health and regional referral hospitals for the assistance offered to my staff during the period of the audit.

John F. S. MuwangaAUDITOR GENERAL

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M A R C H 2 0 1 5ii THE EFFICIENCYOF OPERATIONS OF REGIONALREFERRAL HOSPITALS IN UGANDA

TABLE OF CONTENTS

LIST OF TABLES ............................................................................................................iv

LIST OF FIGURES ...........................................................................................................iv

LIST OF ACRONYMS .......................................................................................................v

EXECUTIVE SUMMARY ..................................................................................................vi

CHAPTER ONE ............................................................................................................... 2

INTRODUCTION ...........................................................................................................2

1.1 BACK GROUND ...................................................................................................2

1.2 MOTIVATION ........................................................................................................2

1.3 DESCRIPTION OF THE AUDIT AREA ..................................................................31.3.1 General Description ............................................................................3

1.3.2 Legal Framework for RRHs ................................................................3

1.3.3 Mission and Vision ...............................................................................3

1.3.4 Organizational Structure .....................................................................3

1.3.5 Funding ................................................................................................4

1.4 AUDIT OBJECTIVES ............................................................................................4

1.5 AUDIT QUESTIONS .............................................................................................4

1.6 AUDIT SCOPE .....................................................................................................5

CHAPTER TWO .............................................................................................................. 7

THEORETICAL FRAMEWORK AND AUDIT METHODOLOGY ......................................7

2.1 AUDIT METHODOLOGY .......................................................................................7

2.1.1 Sampling ..............................................................................................7

2.1.2 Data Collection methods .....................................................................7

2.1.3 Data Envelopment Analysis.................................................................8

2.1.4 Data Analysis .......................................................................................8

2.2 THEORETICAL FRAMEWORK OF DEA ...............................................................82.2.1 Previous Studies ..................................................................................8

2.2.2 The Data Set ........................................................................................9

2.2.3 Model Specification .............................................................................9

2.2.4 Sensitivity Analysis ............................................................................10

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M A R C H 2 0 1 5 iiiTHE EFFICIENCY


CHAPTER THREE ......................................................................................................... 13

SYSTEMS AND PROCESS DESCRIPTION .................................................................13

3.1 PROCESS DESCRIPTION .................................................................................133.1.1 Budgeting ..........................................................................................13

3.1.2 Outpatient service .............................................................................13

3.1.3 Inpatient service ................................................................................13

3.1.4 Procurement and movement of drugs .............................................14

3.2 ROLES AND RESPONSIBILITIES OF KEY PLAYERS ........................................14

CHAPTER FOUR ........................................................................................................... 18

FINDINGS AND RECOMMENDATIONS .....................................................................18

4.1 RESULTS ...........................................................................................................18

4.1.1 Efficiency Scores of RRHs ......................................................................18

4.2 UTILISATION OF KEY INPUTS ..........................................................................20

4.2.1 Analysis of Medicines Management and Utilisation .............................20

4.2.2 Infrastructure Usage ..............................................................................23

4.2.3 Staffing....................................................................................................30

GLOSSARY OF TERMS ........................................................................................................33

APPENDICES .................................................................................................................35

APPENDIX I: DETAILS OF INTERVIEWS CONDUCTED ................................................35

APPENDIX II: ORGANOGRAM ........................................................................................36

APPENDIX III: DETAILS OF DEA THEORETICAL FRAMEWORK. ...................................37

APPENDIX IV: SUMMARY OF PREVIOUS DEA STUDIES ON HOSPITALS .....................38

APPENDIX V: ILLUSTRATION OF THE POTENTIAL SAVING ON RECURRENT EXPENDITURE PER RRH IN 2012/13 .....................................................41

APPENDIX VI: SENSITIVITY ANALYSIS ...........................................................................42

APPENDIX VII: GRAPHS AND TABLES ............................................................................45

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M A R C H 2 0 1 5ivTHE EFFICIENCYOF OPERATIONS OF REGIONALREFERRAL HOSPITALS IN UGANDA

LIST OF TABLES

Table 1: Budget allocations and releases to RRHs for the Financial years 2011/12, 2012/13 and 2013/14 ..........................................................................................4

Table 2: Summary statistics for the variable of the preferred model per.....................10

Table 3: Different models in the sensitivity analysis ......................................................11

Table 4: Annual percentage efficiency scores per RRH for the periods 2011/12 - 13/14 .................................................................................................18

Table 5: Drug Expenditure per standard unit of output for each RRH over the period 2011/12-2013/14 ...............................................................................................20

Table 6: Bed occupancy rates, Average Length of Stay and Floor admissions per RRH in the period 2011-2014 ...................................................................................23

Table 7: Absenteeism Rates for Health Workers at Health Centres in 2011/12..........24

Table 8: Quantity and Value of Idle Equipment found in 5 RRHs ..................................27

Table 9: Number of X-ray images produced per machine for the Financial Year 2013/14 .....................................................................................28

Table 10: Number of ultra sound images produced per scanner for the Financial Year 2013/14 .....................................................................................29

Table 11: Staffing Situation of Medical Consultants per RRH in 2013/14 ......................31

LIST OF FIGURES

Figure 1: Process for Procurement and Movement of drugs in Hospitals. ....................14

Figure 2: Graph showing the Average Admissions Vs Average Length of Stay. .............25

Figure 3: Graph showing the relationship between medical specialists and ALOS in 2013/14 .............................................................................................................25

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M A R C H 2 0 1 5 vTHE EFFICIENCY


LIST OF ACRONYMS AND ABBREVIATIONS

ALOS Average Length of Stay

BOR Bed Occupancy Rate

CRS Constant Returns to Scale

FY Financial Year

GoU Government of Uganda

DEA Data Envelopment Analysis

HSSP Health Sector Strategic Plan

MMR Maternal Mortality Rate

MoFPED Ministry of Finance, Planning and Economic Development

MoH Ministry of Health

NMS National Medical Stores

OPD Out-Patients Department

RRHs Regional Referral Hospitals

RTS Returns to Scale

SUO Standard Unit of Output

VRS Variable Returns to Scale

EXECUTIVE SUMMARY

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M A R C H 2 0 1 5vi THE EFFICIENCYOF OPERATIONS OF REGIONALREFERRAL HOSPITALS IN UGANDA

The Office of the Auditor General undertook a value for money audit of the operations of Regional Referral Hospitals (RRHs) to assess their efficiency in delivery of healthcare services at the regional level in Uganda. The overall objective of the audit was to assess whether there was efficient allocation and utilisation of resources in RRHs with specific focus on utilisation of medicines, health workers and infrastructure. The audit employed a benchmarking technique called the Data Envelopment Analysis (DEA) to determine the overall efficiency scores for each RRH over a period of three years. DEA compares different entities considering the resources used and services provided. The technique identifies the most efficient units or best practice units and the inefficient units in which real efficiency improvements are possible.

KEY FINDINGSBased on the results of this audit, the average inefficiency scores were 6%, 13% and 9% in the financial years (FY) 2011/12, 2012/13 and 2013/14, respectively. This implies that for instance in 2013/14, all the inefficient hospitals had the potential to reduce their inputs by 9% in total, while continuing to produce the same level of output. Approximately 50% of the RRHs exhibited this potential for improvement (input saving potential). Although there was an improvement in efficiency between 2012/13 and 2013/2014, there was still a considerable variation in the inefficiency levels of individual hospitals, ranging from 1% to 33%. The RRHs of Mbale, Moroto, Mubende, Masaka and Hoima were relatively efficient over the three years while Arua, Jinja, Kabale, Lira and Mbarara RRHs were relatively inefficient and hence had room for improvements over all the three years under review.

The sensitivity analysis conducted to ascertain the behaviour of the model, due to changes in the mix of the inputs and outputs, did not show much change in the score and rankings of the RRHs. This showed comprehensiveness of the input and output variables used and confirmed the credibility of the preferred model used in this audit.

As explained below, this audit has identified some of the potential areas that hospitals need to address in order to improve the efficiency with which they deliver their services.

1. Medicines and other health supplies• RRHs continued to have and accumulate expired drugs while also experiencing stock-

out of certain drugs over the 3 years under review. Expired items represent wastage of resources as they are purchased using funds that could be put to other areas of operation. They also take up space in the stores and more funds are required to ensure their safe destruction.

• A comparison was made of expenditures on medicines and health supplies with the standard unit of output to generate medicines utilized per unit of output1.It was observed that the value of medicines used per unit of output ranged between UGX 995 to UGX 2,417 (143% difference) in 2013/14, UGX 1,190 to 3,590 (200% difference)

1Ministry of Health Uganda generates a composite output measure called the Standard Unit of Output that converts all hospital outputs into outpatient equivalents. A unit of output is the equivalent of one outpatient treated (Refer to chapter 2 for the detailed definition)

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M A R C H 2 0 1 5 viiTHE EFFICIENCY


in 2012/13 and UGX 1,031 to 3,177 (208% difference) in 2011/12. Whereas, there is no standard average amount of the value of drugs consumed by each patient, a hospital spending less for each patient will likely treat more patients using a given expenditure on drugs. Mbale RRH was the best performing hospital since it spent the least amount on drugs to treat one unit of output (the equivalent of one outpatient). Kabale, Soroti, Mbarara and Arua had the largest room for improvement compared to other RRHs in drug utilisation. The high variation in utilisation of drugs for each unit of output could be partly attributed to the extent of expiry of medicines and other health supplies at the affected hospitals and different preferences of treatment options by clinicians.

2. Infrastructure• Bed occupancy rates (BOR) over the 3 years ranged from 51% to 235%. Analysis

of data showed that that seven of the thirteen RRHs experienced floor admissions ranging from an average of 6 patients to 445 patients per day over the review period. Hospitals with BOR between 80% and 90% are considered to be operating optimally2. A bed occupancy rate below 80% implies that a hospital has many unutilized beds. For instance, it was noted that in Lira RRH, the 16-bed Intensive Care Unit (ICU) was unutilised while 7 out of 13 beds in the ICU of Jinja were not utilised. This partially contributed to their low average bed occupancy rates of 68% and 65% respectively.

Bed occupancy rates above 100% are caused by a huge influx of patients due to operational weaknesses in Health centre II, III and IVs. One such weakness is absenteeism of health workers in these health centres, prompting a large number of patients to seek health services from the referral hospital for conditions which a health centre should be capable of handling.

• It was observed that the number of hospitals that met the target Average Length of Stay (ALOS) of five days were increasing over the three year period. However, four (4) RRHs: Arua, Kabale, Moroto and Mubende showed no improvement in their ALOS over the three-year period, that is, their ALOS was increasing.

• It was noted that some of the infrastructure in RRHs was lying idle and/or under-utilized. This included beds, mattresses in Gulu and Lira and ICU equipment in Jinja and Lira. Money spent on the purchase of these items, estimated at $77,200 in total, could have been used for more pressing needs. In addition, such capital assets being left idle in stores could depreciate before the hospital derives the intended benefits.

• Analysis of data relating to X-ray and ultra sound machines utilisation (only functional machines for FY 2013/14) revealed that the RRHs exhibited big differences in the number of examinations conducted per machine for FY 2013/14. For X-ray machines, the annual number of examinations ranged between 887 in Arua to 8,782 in Masaka while number of ultra sound scans ranged between 629 images per scanner annually in Kabale to 6,309 in Gulu. It was also observed that a number of X-ray machines and ultra sound scanners were non-functional and this further limited the output of this vital equipment. That was an indication that availability of equipment is not commensurate to need.

2Annual Health sector performance report 2013/14 page 53.

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M A R C H 2 0 1 5viiiTHE EFFICIENCYOF OPERATIONS OF REGIONALREFERRAL HOSPITALS IN UGANDA

3. Health workersRRHs lacked some specialized staff to deliver the services. At the time of the audit, most of RRHs visited had not achieved the required number of consultants, as per the established structure, to handle the specialized services.

KEY RECOMMENDATIONS1. Committees should be instituted in the inefficient RRHs to re-examine their

operational procedures with the view of identifying slacks in the utilisation of resources. This could be done by interacting with the efficient RRHs to ascertain the usage of inputs especially in the consistently efficient RRHs that is Mbale, Moroto, Mubende, Masaka and Hoima.

2. The Ministry of Health should ensure that budget allocations for drugs are commensurate to the output of hospitals so that stock-outs do not affect the provision of services in hospitals.

3. RRHs are advised to ensure that all clinicians adhere to treatment guidelines of the MOH while making prescriptions so that medicines supplied by NMS are well utilized. It is also recommended that a study on the stock-out levels of medicines be instituted in the RRHs to ascertain the impact on service delivery.

4. Stock taking exercises should be emphasized. This would enable the hospitals keep track of drug stocks, stock outs and thus provide a basis for planning.

5. The MoH should expedite the development of a system for redistribution of medicines and coordination between various players in the health system. RRHs should strengthen the tracking system of consumption patterns of medicines and other health supplies so that expected future orders do not materially differ from current plans.

6. The District Directors of Health Services at the districts should address the operational weaknesses in the Health centre II, III and IVs such as absenteeism, lack of medicines which results in the RRHs being overstretched.

7. Shortage of health workers should be addressed by putting in place mechanisms that would attract and retain these professionals to the RRHs.

8. RRHs with unutilised and underutilised equipment should consider redistributing them to other health units that would put these items to better use.

9. The MOH is advised to develop staffing structures suitable for the needs of RRHs.

OVERALL CONCLUSIONThe results of the efficiency study of the operations of RRHs using the data envelopment analysis technique have shown that 50% of the RRHs were relatively efficient in the utilization of their resources. The remaining inefficient hospitals exhibited potential for improvements if appropriate interventions were made to address the slacks in the utilization of the key inputs such as medicines, infrastructure, /equipment and human resource.

With reduced inefficiency, RRHs stand to reap significant input savings from their activities. This would ensure improvements in the coverage and quality of health services.

CHAPTER ONE

1

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M A R C H 2 0 1 52 THE EFFICIENCYOF OPERATIONS OF REGIONALREFERRAL HOSPITALS IN UGANDA

CHAPTER ONE

INTRODUCTION

1.1 BACK GROUNDIn Africa, particularly sub-Saharan Africa, poor health of the population is generally a known reality and Uganda is no exception to this. The healthcare delivery systems remain too inadequate to meet the needs of the ever-growing population. This has raised concerns by policy makers and planners on whether health services are being delivered efficiently by hospitals.

In Uganda, hospital services are provided under a four-tier health care system, that is, primary, secondary, tertiary and quaternary with Regional Referral Hospitals being major contributors to essential clinical care because of their provision of specialist clinical services.

This audit covered thirteen out of the fourteen Regional Referral Hospitals in Uganda, namely: Arua, Fort Portal, Gulu, Hoima, Jinja, Kabale, Lira, Masaka, Mbale, Mbarara, Moroto, Mubende and Soroti.

1.2 MOTIVATIONA number of international treaties3 oblige the Government of Uganda to commit sufficient resources and establish a comprehensive healthcare framework that meets the health needs of the citizens. Besides, the State has a duty to guarantee the right to health to all its citizens.

In order to deliver the required health services, the Government of Uganda (GoU) endeavoured to put in place a regulatory framework4 in line with the 1995 Constitution of the Republic of Uganda (as amended). The regulatory framework spells out the services of hospitals at different levels including Regional Referral Hospitals (RRHs), in providing the healthcare needs of the population.

Over the past three financial years 2011/12, 2012/13 and 2013/14, there has been an 18% increment in the funding of RRHs from UGX 53.86 billion to UGX 63.56 billion.5

Despite the increment in funding of RRHs, over the years, there are investigative and research reports,6 as well as press reports, about the declining quality of health services in the country, mainly attributed to the lack of drugs/ stock outs, shortage of health workers, delays in accessing healthcare services in every referral hospital, mismanagement of hospital infrastructure, overcrowding of hospital facilities, among others; with dire

31International treaties such as the International Covenant on Economic, Social and Cultural Rights (ICESCR), the Universal Declaration of Human Rights (UDHR), the Convention on the Rights of the Child and a number of other non-binding declarations such as the Alma Ata Declaration and the Millennium Declaration, the Abuja Declaration, among others41999 National Health Policy, the public health ACT 1935, Health Sector Strategic Plan and the National Hospital Policy 20055Estimates of Revenue and Expenditure for FYs 2011/12 (page 26), 2012/13(page 27), 2013/14 (page 29)6HURINET-U report on State of Uganda’s RRHs, 2012, Parliamentary Health Committee report, 2012 ,OAG annual report, 2012, Budget Monitoring and Accountability Unit(BMAU) report 2012 and The World Bank Service Delivery Report,2013

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consequences, including avoidable deaths of patients. This has raised concerns as to whether these hospitals are operating efficiently with the resources availed to them.

There is need for efficient provision of clinical and non-clinical services to attain a healthy population as an input for economic development.

The inefficiency in RRHs is an issue that needs to be addressed if Uganda is to reap significant savings from all activities carried out by RRHs and meet its Millennium Development Goals (MDGs) related to health.

It is against this background that the Office of the Auditor General decided to undertake an independent assessment of the operations of the RRHs to ascertain their efficiency in delivery of health care services at the regional level in Uganda.

1.3 DESCRIPTION OF THE AUDIT AREA

1.3.1 General DescriptionUganda has 14 self-accounting RRHs which are responsible for delivering a complementary, integrated, and continuous package of health care to achieve a common national goal. RRHs offer specialised services such as Psychiatry, Ear, Nose and Throat (ENT), Radiology, Pathology, Ophthalmology, higher level surgical and medical services, including teaching and research. This is in addition to the services offered at general hospitals. RRHs are required to provide care for a population of 2,000,000 people, have a bed capacity of 500, employ an average of 349 members of staff and maintain all the relevant health equipment as prescribed by the Ministry of Health (MoH).

1.3.2 Legal Framework for RRHsThe Uganda Hospital Policy provides for RRHs as part of the health service delivery system of Uganda. The policy states that RRHs offer all services of general hospitals in addition to specialized services such as psychiatry, Ear, Nose and Throat (ENT), radiology, pathology, ophthalmology, higher level surgical and medical services, including teaching and research.

1.3.3 Mission and VisionRRHs derive their visions and missions from that of the Health sector which is:

Vision “A healthy and productive population that contributes to social-economic growth and national development”

Mission “To provide the highest possible level of health services to all people in Uganda through delivery of promotive, preventive, curative, palliative and rehabilitative health services at all levels.”

1.3.4 Organizational StructureRRHs have the Management Board as the highest authority which provides oversight on the activities of the hospital. The executive function is headed by the Hospital Director. (For details, refer to Appendix II)

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M A R C H 2 0 1 54THE EFFICIENCYOF OPERATIONS OF REGIONALREFERRAL HOSPITALS IN UGANDA

1.3.5 FundingThe Government of Uganda (GoU) budget allocation to the 13 (thirteen) RRHs under review for the Financial Years 2011/12 to 2013/14 amounted to an average of shs59 billion while the releases amounted to an average of shs.57.8 billion.

Table 1: Budget allocations and releases to RRHs for the Financial years 2011/12, 2012/13 and 2013/14

RRH 2011/12UGX (bn)

2012/13UGX (bn)

2013/14 UGX (bn)

BUDGET RELEASE BUDGET RELEASE BUDGET

ARUA 3.93 4.07 5.60 5.37 5.01

FORT PORTAL 5.98 6.49 4.40 4.79 5.52

GULU 3.32 3.92 5.64 5.90 5.17

HOIMA 4.51 4.84 4.04 3.90 4.81

JINJA 5.66 6.04 5.98 5.71 5.9

KABALE 3.02 3.54 4.04 3.90 4.55

MASAKA 4.88 5.19 4.86 4.65 4.59

MBALE 5.91 6.39 5.85 6.17 6.09

SOROTI 3.27 3.70 5.26 5.02 5.24

LIRA 4.18 4.57 4.59 4.38 4.09

MBARARA 4.76 5.36 4.54 5.35 5.35

MUBENDE 2.15 n/a 2.48 2.40 3.73

MOROTO 2.11 1.86 2.49 2.15 3.51TOTAL 53.68 55.97 59.77 59.69 63.56

Source: Estimates of Revenue and expenditure FY 2011/12 to 2013/14 and audited accounts of FY 2011/12-2013/14

*Releases for FY 2013/14 not included because audited accounts for the RRHs had not been finalised.

1.4 AUDIT OBjECTIVESThe overall objective of the audit was to assess whether there is efficient allocation and utilisation of resources in RRHs.

The specific objectives of the audit were:

a) To determine the overall efficiency score of each RRH with respect to the provision of health services.

b) To assess and compare the efficiency in utilisation of key inputs, that is, health infrastructure (beds and equipment), health workforce and medicines and other health supplies in RRHs.

1.5 AUDIT QUESTIONSa) What are the overall efficiency scores for each RRH with respect to provision of health

services?

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b) To what extent does the utilisation of health infrastructure, health work force and medicines and other health supplies affect the efficient operation of the regional referral hospitals?

1.6 AUDIT SCOPEThe audit focused on efficiency in the RRHs with emphasis on how the health workforce, infrastructure (beds and equipment), and drugs as inputs are transformed into outputs of inpatient services, outpatient services, and diagnostic services.

The study covered three financial years: 2011/12, 2012/13, 2013/14 in order to assess the trend in the performance of RRHs.

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2CHAPTER TWO

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CHAPTER TWO

2. THEORETICAL FRAMEWORK AND AUDIT METHODOLOGY

2.1 AUDIT METHODOLOGYThe audit was carried out in accordance with the International Organization of Supreme Audit Institutions (INTOSAI) Performance Auditing Standards and Performance Auditing guidelines prescribed in the Value for Money Audit Manual of the Office of the Auditor General (OAG). The standards require that the audit is planned in a manner which ensures that an audit of high quality is carried out in an economic, efficient and effective way and in a timely manner.

2.1.1 SamplingOut of the fourteen (14) hospitals, a sample of thirteen (13) were selected, that is, Fort Portal, Gulu, Jinja, Lira, Masaka, Mbale, Mbarara, Mubende, Moroto, Arua, Kabale, Hoima and Soroti. Naguru Regional referral hospital was excluded because it was not fully functional during FY 2011/12, one of the financial years under review.

2.1.2 Data Collection MethodsThe data collection methods used to obtain audit evidence for the audit were:

• Document review: The team reviewed policy guidelines from the Ministry of Health and annual health sector performance reports to obtain an insight into the operations of hospitals. Previous studies on hospital efficiency were also reviewed to ascertain similar characteristics that were incorporated in the report.

• Interviews: Interviews were conducted with officials of MOH, management and staff of RRHs and management of National Medical Stores (NMS) to seek clarification on the issues identified through data analysis.

• Physical inspections: Nine (9) RRHs were selected for inspection. The inspection was conducted to validate data and other information obtained from MOH and from document review.

• Questionnaires: These were sent to 4 RRHs which were not covered through physical inspection, namely: Arua, Kabale, Moroto and Hoima. However, only Kabale RRH responded to the questionnaire.

• Reference group discussion: A workshop was held with the responsible officials from the Ministry of Health, Directors of RRHs and Hospital administrators, in which findings were presented and discussed. Subsequently, their input was incorporated in the final audit report.

Data was collected from the Health Management Information System (DHIS-2) and corroborated with that from the 13 RRHs under review. Data on medicines and health supplies was further corroborated with that from (NMS) data records.

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2.1.3 Data Envelopment AnalysisData Envelopment Analysis (DEA) was used to assess the efficiency of each RRH. This was achieved by comparing the mix of inputs and outputs of each unit with those of all the other units.7 In this audit, the service units were the RRHs across the financial years 2011/2012, 2012/2013 and 2013/2014.

2.1.4 Data AnalysisFurther data analysis was carried out to explain the results of DEA. This involved ratio analysis, interpretation of performance indicators commonly used in health services, correlations and graphical comparisons. This analysis was used to provide explanations for the efficiency performance.

2.2 THEORETICAL FRAMEWORK OF DEADEA is a benchmarking technique which compares different entities called Decision Making Units (DMUs) considering resources used and services provided. A DMU could either be a firm or an organization, as in this case.8 In DEA analysis, efficiency refers to the success of the DMU in producing as large as possible output from a given set of inputs (output based) or using the least amount of resources to meet a target in production (input based). The technique identifies the most efficient units or best practice units and the inefficient units in which real efficiency improvements are possible. In the context of health, the DMU is the referral hospital and the technical efficiency can be described as producing a given level of health service outputs with the least health system inputs.

Efficiency can be assessed using a number of analysis tools such as ratio analysis, regression analysis, unit cost measurement, Stochastic Frontier analysis. Most studies on efficiency of hospitals have used Data Envelopment Analysis. This is mainly due to the fact that hospitals have an array of inputs and outputs that would render most methodologies ineffective.

The DEA model is a model that makes it possible to determine the presence and amount of inefficiency within each RRH. This information can thus be used by management to aid policy decision-making and resource allocation. (Further illustration of DEA is in Appendix III)

2.2.1 Previous StudiesDEA has been widely used to measure the efficiency of hospitals and a number of efficiency studies from different countries have been published. A review of these previous studies on hospitals revealed common traits which have been summarized in Appendix IV.

Most of these studies considered “beds” and “human resource” as inputs and, “outpatient services” and “inpatient services” as outputs. The most common indicator used to capture the quality of health service was mortality rate. Most studies assumed both the Variable Returns to Scale (VRS) and Constant returns to Scale (CRS).

7Sherman, H.D.; Zhu, J.; 2006; Service Productivity Management: Improving Service Performance using Data Envelopment Analysis, p508The DEA framework was introduced by Farrell(1957) and extended to situations with multiple inputs and outputs by Charnes, Cooper and Rhodes (1978), Measuring the efficiency of decision making units, CCR 1978 (page 429)

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9L. O’Neill et al., 2008, “A Cross-National Comaprison and Taxonomy of DEA-based Hospital Efficiency Studies”, p172, Socio-Economic Planning Sciences 42 (2008) 158–18910ANC= 1st and 4th Antenatal Care visits; MCH= Maternal and Child Health contacts; FP= Family Planning visits.The multiplicative factors against each of the outputs in the equation of SUO were generated by the MOH.

2.2.2 The Data SetThe dataset includes thirteen (13) RRHs for the three (3) financial years 2011/2012, 2012/2013 and 2013/2014. It was sourced from the Health Management Information System (DHIS-2) under the management of the Ministry of Health. HMIS data was used because it is the recommended data source for the health sector due to its reliability. The audit also obtained data from the RRHs.

For each hospital, the dataset included number of health workers, beds, diagnostic equipment, diagnostic tests, outpatient attendance, admissions, deliveries, hospital deaths, still births, live births, immunization data, ANC visits, standard unit of output, drug expenditure and other operating costs. These were discussed with the RRH directors to agree on what they considered key inputs and outputs of the RRH.

2.2.3 Model SpecificationThe input and output variables were chosen based on discussions with the RRHs, the hospital production process and on the commonly used variables in previous similar research studies on efficiency of hospitals as explained above.

Input VariablesThe input variables used in our preferred model included:

a) Health workers: These were chosen because they are directly involved in the provision of health services to patients. Furthermore, the wage bill of RRHs constitutes about two thirds of their total operating cost. Health worker category included medical professionals (medical officers, specialists and consultants), nursing staff, midwifery staff, dental professionals, allied health professionals.

b) Beds: This is commonly chosen in hospital studies as a proxy for capital investment and hospital size9.

c) Drug expenditure: This represents the treatment given to both the inpatients and outpatients. It constitutes the actual expenditure on essential medicines and health supplies.

Output Variablesa) Standard unit of Output (SUO): This is a composite output measure converting

all outputs of the RRH into outpatient equivalents. SUO total = [(Inpatients x15)+ (Outpatients x1) + (Deliveries x5) + (Immunizations x0.2) + (ANC/MCH/FP1 x0.5)]10. It is based on earlier work of cost comparisons and is used by the MoH in the Annual Health Sector Performance reports to make a uniform and fair comparison of outputs across hospitals that have varying capacities.

Furthermore, SUO captures the different types of patient care services provided by the RRHs such as outpatient services, inpatient services, maternity services, and prevention and rehabilitation services.

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b) Hospital deaths: This variable was used as a rough measure of the quality of health care provided by the RRHs. It is assumed that the more deaths a hospital encounters, the lower the quality of its services. This same parameter was used in previous studies as a quality measure as discussed earlier.

Table 2: Summary statistics for the variables of the preferred model perfinancial year 2011/12

Health Workers Beds

Drugs (UGX mil) SUO Hospital Deaths

Mean 172 278 851 412,385 241

SD 43 95 317 127,873 135

Minimum 97 120 329 188,681 90

Maximum 251 429 1356 609,384 578

2012/13

Health Workers Beds


Mean 172 319 1057 503,599 249

SD 43 92 276 176,885 257

Minimum 97 150 556 225,951 56

Maximum 251 447 1591 858,116 962

2013/14

Health Workers Beds


Mean 186 321 895 524,750 209

SD 58 88 226 158,569 212

Minimum 69 170 379 206,090 62

Maximum 310 447 1254 885,840 893

Source: OAG Analysis of data from RRHs

The mean and standard deviation serve to show that the quantity of each input and output generally varies amongst the RRHs and from one year to another. The only exceptions are health workers and beds which remain fairly constant on a year-on-year basis. The aforementioned variation necessitated that the efficiency analysis be carried out separately for each year in order to obtain unbiased results.

2.2.4 Sensitivity AnalysisA sensitivity analysis was carried out using four models in order to assess the credibility of the results and the comprehensiveness of the variables. The input and output variables used for each model were:

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Table 3: Different models in the sensitivity analysis

Model Inputs Outputs

Preferred Model Beds

Health Workers

Drugs

Standard Unit of Output

Hospital Deaths

Model 1 Beds

Health Workers

Drugs

Adjusted Standard Unit of Output*

Model 2 Beds

Health Workers

Drugs


Average Length of Stay

Model 3 Beds

Health Workers

Drugs


Model 4 Beds

All Staff

Drugs


Hospital Deaths

*SUO adjusted for floor admissions

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3CHAPTER THREE

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CHAPTER THREE

SYSTEMS AND PROCESS DESCRIPTION

3.1 PROCESS DESCRIPTION

3.1.1 BudgetingThe User department/unit of the RRH generates priorities and the Head of Department or unit presents them to Top Management which serves as a Budget Committee. The Top management develops work plans and budgets which are presented to the Hospital Management Board, which is the link to the community served by the respective referral. The budget is presented to the Ministry of Health for consideration. However, sometimes the Ministry has its own priorities as per government policies. Feedback is then given to the respective players by the top management.

Budgeting for medicines and other health suppliesIndicative planning figures (IPFs) are set and presented to RRHs as ceilings for expenditures on medicines and other health supplies. Procurement plans are developed based on these ceilings and sent to NMS which has the mandate to procure and distribute medicines and other health supplies to all government health units in the country. NMS then develops its own procurement plan for drugs by amalgamating procurement plans for all the government health units. Funds for these items are sent directly to NMS for general procurement and deliveries made to health units based on a predetermined schedule.

3.1.2 Outpatient serviceWhen patients arrive at the Outpatients Department (OPD), their personal details are registered by the records officer. They are directed to the clinician or the dentist. The patient’s complaint is then considered and the patient is sent to the laboratory where the lab attendant carries out the required tests and sends the patient, with the results, back to the clinician. Based on the results, the clinician makes a diagnosis and gives the patient a prescription or recommends them for admission. The clinician may send a patient to a consultant or one of the specialized clinics such as Tuberculosis, Diabetes, if they need a specialized service. The patient receives the prescribed drugs from the pharmacy.

3.1.3 Inpatient serviceWards receive patients from the Outpatients Department, referrals from other hospitals and patients from their homes. All patients are received by the ward in-charge or any medical staff on duty, depending on the different shifts. Each patient has a personal file which is referred to on admission and where necessary, tests are done. Different wards have different procedures for treating their patients, for example: in the surgical ward, a Complete Blood Count (CBC) and X-ray is done prior to operation. In the maternity ward, mothers are examined: those in latent labour admitted in the maternity ward, and those in established labour admitted in the labour suite. Expectant mothers with other complications, such as: pregnancy-induced hypertension, malaria are also admitted and monitored. Referrals and other complications are handled by the specialized doctors.

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3.1.4 Procurement and movement of drugs

Figure 1: Process for Procurement and Movement of drugs in Hospitals.

NMS delivers thedrugs (2 monthscycle) which areverified by the

store keeper andrecorded on the

stock cards.

Orders submitedto NMS (on a 2months cycle)

3.2 ROLES AND RESPONSIBILITIES OF KEY PLAYERSRegional referral hospitals operate within an institutional framework of which the most important stakeholders are:

ENTITY/PLAYER KEY ROLES AND RESPONSIBILITIES

Ministry of Health (MoH) • Is responsible for all matters relating to national health. It is responsible for policy formulation, setting standards and guidelines used in hospital day to day operations, resource mobilization, capacity building, technical supervision, monitoring and evaluation as well as overall regulation.

Department of Clinical services

• Is involved in the management of referral hospitals by setting the standards for what activities, equipment and infrastructure should be present at the referral hospitals.

CHAPTER ONE

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Quality Assurance Department

• Organizes teams from amongst the Ministry staff which carry out monitoring and supervision at the RRHs on a quarterly basis, and prepare reports which are discussed in joint review meetings held at the Ministry.

Ministry of Finance, Planning and Economic Development

• The Ministry is responsible for resource mobilization and allocation.

• It coordinates other sectors regarding provision of guidelines for optimal use of resources, ensuring efficiency, effectiveness and accountability.

• MoFPED also conducts annual reviews of the utilisation of funds using Budget Monitoring and Accountability Unit (BMAU).

National Medical Stores • Supplies essential medicines and medical supplies to public health facilities in Uganda, including the referral hospitals.

• Takes orders for drugs and other medical supplies from the hospitals, processes these orders and delivers the drugs to the respective hospital premises.

Development Partners and Non-Government Organization (NGOs)

• These, together with other collaborating organisations, play a significant role of funding and building the capacity of RRHs.

Hospital management Board

• The Board oversees the overall activities of the hospitals.

Hospital Director • Ensures that there is effective service delivery in the hospital through monitoring the performance of health workers and gives necessary assistance and guidance.

• Submits timely performance reports and work plans in the subscribed format to stakeholders.

• Rewards or disciplines the staff in the hospital in accordance with the reward and sanctions framework for the Public Service as well as taking disciplinary action in accordance with the Government Standing Orders, Public Service Code of Conduct and Ethics.

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Human Resource Manager/Officer

• Processing and verifying information related to recruitment, salary changes, personnel statistics and job analysis;

• Drafting letters of appointments, promotion and confirmation;

• Collecting data and other vital statistics relating to recruitment and training;

• Handling staff relations and welfare matters

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4CHAPTER FOUR

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CHAPTER FOUR

FINDINGS AND RECOMMENDATIONSThis chapter presents the efficiency-score results of the preferred model and the sensitivity analysis carried out. Conclusions, recommendations and other issues affecting performance of RRHs are also detailed thereafter.

4.1 RESULTS

4.1.1 Efficiency Scores of RRHsTable 3 presents the calculated annual efficiency scores for the different RRHs during the chosen period. The score required to be a benchmark hospital is 100%. Any score below 100% suggests an input saving potential given the level of outputs produced by the RRH in that particular year.

Table 4: Annual percentage efficiency scores per RRH for the periods 2011/12 - 13/14

RRH 2011/12 2012/13 2013/14

MBALE 100 100 100

MOROTO 100 100 100

MUBENDE 100 100 100

MASAKA 100 100 100

HOIMA 100 100 100

SOROTI 100 85 99

FORT PORTAL 100 85 90

GULU 100 69 77

ARUA 85 71 75

JINJA 67 69 83

KABALE 78 84 91

LIRA 99 84 93

MBARARA 89 83 78

Number of inefficient RRHs 5 8 8

Average efficiency (%) 94 87 91

Average inefficiency12 (%) 6 13 9

Source: DEA analysis using on-front software of inputs and outputs of the preferred model.

12Inefficiency score (%) is computed as 100% minus the efficiency score.

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For example, the efficiency score for Mbarara RRH of 83% in 2012 implies that it is possible to reduce its inputs by 17% and maintain its current level of outputs. By doing so, Mbarara RRH will become 100% efficient. For further illustration, consider the total recurrent expenditure of Mbarara RRH in 2012/2013 of UGX 4,528,189,274. This RRH has the potential to reduce its annual recurrent expenditure by UGX 769,792,176.58 while delivering the same level of output in terms of SUO. Details of the saving potential per RRH on recurrent expenditure for FY 2012/13 are shown in Appendix V.

From Table 4 above, the average inefficiency score varied between 6% and 13% over the three-year period and approximately 50% of the RRHs were inefficient. Although there was an improvement in the average inefficiency score between 2012/13 and 2013/2014, there was still a considerable variation in inefficiency scores among the RRHs from 1% to 33%.

The sensitivity analysis conducted to ascertain the behaviour of the model due to changes in the mix of the inputs and outputs did not show much change in the score and rankings of the RRHs as shown in Appendix VI. This further emphasizes the comprehensiveness of the input and output variables used and the credibility of the preferred model.

Management ResponseThe efficiency results from the DEA model should be interpreted with caution and in the context of the health care system as higher level health facilities such as regional referral hospitals can appear inefficient, for example, because of relatively longer stays due to patient mix, staff skill mix and staff cost associated with specialists. However, this may be an indication of the effectiveness of the health system in referring individuals with serious health conditions to better equipped health facilities.

Audit Comment Regional referral hospitals in Uganda are required to offer the same services as detailed in section 1.3.1 of this report (description of the audit area). They also employ the same categories of human resource who are paid based on the Government of Uganda salary structure at their various levels of specialisation.

The tool used to compute efficiency scores in this study assessed the use of inputs of a hospital relative to usage of the same inputs by counterpart hospitals.

The results are therefore reliable and showed a potential for improving efficiency in the RRHs by saving on the inputs currently used to produce outputs. At the individual hospital level, this saving potential ranged from 1% to 33. It implies that these RRHs have gaps that hindered the provision of the highest possible level of service. The saving potential of each RRH varies and may not be uniform across all inputs.

RecommendationCommittees should be instituted in the inefficient RRHs to re-examine their operational procedures with the view of identifying slacks in the utilisation of resources. This could be done by interacting with the efficient RRHs to ascertain the usage of inputs especially in the consistently efficient RRHs that is Mbale, Moroto, Mubende, Masaka and Hoima. Based on interviews, reviews of documentation and data analysis undertaken in the course of this study, the potential areas of interest could include but not limited to those identified in section 4.2 below.

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4.2 UTILISATION OF KEY INPUTSIn measuring the efficiency of RRHs, the audit analysed the use of key inputs, that is, medicines and other health supplies, health infrastructure and health workforce in the delivery of health services and how they impact on the efficiency of operations of RRHs. The following was observed:

4.2.1 Analysis of Medicines Management and Utilisation

a) Variances in Medicines Utilisation

RRHs committed to attaining value for money in the delivery of their outputs in the Ministerial Policy Statements by ensuring efficiency in utilisation of resources. Medicines and health supplies are an essential input in all RRHs. Analysis of the relationship between unit cost of drugs and the efficiency scores, showed that efficient hospitals had lower expenditures on medicine per unit of output. (Appendix VII (b)).

A comparison was made of the expenditures on medicines and health supplies with the standard unit of output to generate medicines utilized per unit of output as shown in Table 5 below. It was observed that the value of medicines used per unit of output ranged between UGX 995 to 2,417 (143% difference) in 2013/14; UGX1,190 to 3,590 (200% difference) in 2012/13; and UGX1,031 to 3,177 (208% difference) in 2011/12. Whereas, there is no standard average amount of the value of drugs consumed by each patient, a hospital spending less for each patient will be likely to treat more patients using a given expenditure on drugs. In this case, Mbale RRH was the best performing hospital since it spent the least amount on drugs to treat the equivalent of one outpatient. Kabale, Soroti, Mbarara and Arua performed lowest compared to other RRHs in drug utilisation. This affected their efficiency score as was illustrated in Table 4.

Table 5: Drug Expenditure per standard unit of output for each RRH over the period 2011/12-2013/14

RRH 2013/14 2012/13 2011/12

MBALE 995 1,190 1,031

HOIMA 1,366 2,105 1,660

LIRA 1,422 1,886 3,177

JINJA 1,547 2,320 2,927

FORT 1,679 1,771 1,779

MSKA 1,729 1,304 1,638

MBND 1,730 1,910 2,188

GULU 1,751 2,782 1,573

MRTO 1,842 2,465 1,744

ARUA 1,974 2,281 1,918

MBRA 2,094 2,454 2,681

SROTI 2,119 2,915 1,277

KABALE 2,417 3,590 2,699

AVERAGE 1,743 2,229 2,022

Source: OAG Analysis of annual expenditure on medicines and SUO.

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The high variation in utilisation of drugs for each unit of output was partly attributed to the extent of expiry of medicines and other health supplies at the affected hospitals and clinician preferences for expensive drugs over cheaper alternatives.

The difference expressed by the figures above is an indication of wide variations in the pattern of drug prescription and consumption across the RRHs and may, in part, account for differences in overall hospital efficiency. It also indicates the potential for savings in drugs expenditure after critical assessment of the economic consequences of how drugs are managed in hospitals.

Management responseThe variations could result from differences in levels of stock-outs of medicines across the RRHs in the country. Hospitals that see more patients compared to the available medicines and thus have to give prescriptions for the patients to source for the medicine outside the hospital may seem more efficient. Differences were also attributed to varying prescription patterns by specialists.

Audit Comment It is true that variations in medicines could result from differences in stock-out levels across the RRHs. That being the case, hospitals spending less on medicines for every unit of output would have a bigger need for medicines than those spending more. This implied that the budget for medicines was not allocated according to the outputs of the hospitals.

Recommendation•The Ministry of Health is advised to ensure that the budget allocated to hospitals

is based on the output of hospitals so that stock-outs do not affect the provision of services in hospitals.

•RRHs are advised to ensure that all clinicians adhere to treatment guidelines of the MOH while making prescriptions so that medicines supplied by NMS are well utilized. It is also recommended that a study on the stock-out levels of medicines be instituted in the RRHs to ascertain the impact on service delivery.

b) Expired and shortage of drugs

According to the Ministry of Health Ministerial Policy Statement, National Medical Stores (NMS) is supposed to procure and distribute essential medicines and health supplies in accordance with procurement plans for RRHs.

According to the RRH delivery schedule, NMS is supposed to deliver essential medicines after every two months which translate into six cycles in a year. The orders and delivery should be in line with the RRH procurement plan to curb the expiry and shortage of drugs in RRHs and ensure effective service delivery.

Inspections, interview and review of the stock cards made in 9 RRHs13 revealed that RRHs continued to have and accumulate expired and experience stock out of medicines over the 3 years under review.

Hospital managers attributed the expiry to changes in morbidity patterns, changes in treatment policies, delivery of drugs with a short shelf-life and the push system of supplies

13This is respect to all 9 RRHs visited by the audit team. There was no information provided by the 4 unvisited hospitals.

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delivery where NMS supplied items not ordered by the hospital while the shortage was due to NMS failure to deliver what is actually required. Analysis of drug deliveries indicated that NMS supplied more items towards the end of the year than at the beginning contrary to the procurement plan.

Whereas, expiry and shortage of drugs was partly attributed to the irregular deliveries of health supplies by NMS, in an interview with the NMS General Manager, it was noted that the expiry and shortage of the drugs in RRHs was also due to improper planning by the RRHs in their annual procurement plans. Whereas, hospitals are allowed a variance between order and plan of 20%, it was observed that all RRHs exceeded this allowance at time of ordering. This contributed to the stock outs of drugs.

In Mubende, it was noted that the RRH had eight stores dispersed across the hospital premises yet it only had one stores assistant in charge of all these stores. Furthermore, the stores assistant seldom conducted stock-taking exercises to confirm that balances of inventories on record physically existed. Without a proper procedure of taking inventory of the stores, the stores assistant could not identify and report any expired medicines and those medicines nearing expiry so that management could devise strategies to counter losses before expiry such as redistribution/donation of the medicines to other health units.

It was also observed that in the RRHs where physical counts were conducted, no reports were made to the accounting officer. As a result, the RRHs did not have the actual balances of medicines in their stores which further led to requisitioning for less or more than what was needed.

In Jinja, Mubende and Gulu, it was also observed that expired drugs were mixed with unexpired drugs. Whereas, this was attributed to lack of storage space, the team noted that this practice increased the probability of issuing expired drugs to users.

Management Comment

The MoH redistribution strategy and the improvement in the hospital quantification capacity, computerization of stores and the continued use of the pull system of EMHS from NMS would progressively reduce both levels of expired medicines and stock-outs as coordination in the health systems improved.

Audit Comment Expired items represented wastage of resources as they were purchased using funds that could be put to other areas of operation. They also take up space in the stores and more funds are required to ensure their safe destruction.

Recommendations• Stock taking exercises should be emphasized. This would enable the hospitals

keep track of near expiries, stock outs and thus be a basis for planning.

• The MoH should expedite the development of a system for redistribution of medicines and coordination between various players in the health system. RRHs should strengthen the tracking system of consumption patterns of medicines and other health supplies so that expected future orders do not materially differ from current plans.

• The hospitals should prioritize the construction of consolidated stores to ease the distribution of drugs to different units and stock taking.

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4.2.2 Infrastructure Usage

a) Beds

According to the Annual Health Sector Performance Reports of 2012/13 and 2013/14, bed utilisation is assessed using indicators such as bed occupancy rate and average length of stay.

i) Bed occupancy rate

The bed occupancy rate is an indicator of the average proportion of beds in the hospital which are occupied by patients in a day. A bed occupancy rate of 100% would imply that all the hospital beds were occupied by patients on a daily basis. Hospitals with BOR between 80% and 90% are considered to be operating optimally.14 Through interviews with the Directors of RRHs, it was established that this provides an allowance for emergency admissions. Coupled with a moderate length of stay, an optimal BOR would ensure the readiness of the hospital to take in more admissions. The bed occupancy rate varied among the RRHs as shown in the Table 6 below.

Table 6: Bed occupancy rates, Average Length of Stay and Floor admissions per RRH in the period 2011-2014

BOR ALOS FLOOR ADMISSIONS

YEAR 11/12 12/13 13/14 11/12 12/13 13/14 11/12 12/13 13/14

ARUA 65% 78% 75% 4 4 5 0 0 0

FORT PORTAL

84% 70% 86% 5 4 5 0 0 0

GULU 51% 58% 57% 5 6 5 0 0 0

HOIMA 117% 97% 77% 7. 5 4 40 0 0

JINJA 61% 66% 68% 6 4 5 0 0 0

KABALE 76% 75% 80% 6 6 6 0 0 0

LIRA 56% 73% 75% 5 5 5 0 0 0

MASAKA 235% 90% 81% 12 3 4 445 0 0

MBALE 77% 116% 74% 3 3 2 0 67 0

MBARARA 90% 99% 75% 5 4 4 0 0 0

MOROTO 104% 133% 134% 6 6 8 6 49 55

MUBENDE 116% 98% 119% 4 4 5 19 0 33

SOROTI 111% 104% 105% 5 5 4 14 11 12

Source: OAG Analysis admission data of RRHs obtained from DHIS 2

From Table 6 above, bed occupancy rates over the 3 years ranged from 51% to 235%.

A bed occupancy rate of below 80% implies that a hospital has many unutilized beds. For instance; it was noted that in Lira and Jinja, there were 16 beds and 13 beds respectively in their Intensive Care Units that were underutilized. This partially contributed to their low bed occupancy rates. Inspection of the store in Gulu RRH revealed 20 unutilised beds.

14Annual Health sector performance report 2013/14, page 53.

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High bed occupancy rates (that is above 100%) were caused by a huge influx of patients due to operational weaknesses in Health Centre IIs, IIIs and IVs. One such weakness was absenteeism of health workers, prompting a large number of patients to seek health services from the referral hospital for conditions which these lower health centres would have been capable of handling. For example, an interview with a midwife at Mbale RRH revealed that expectant mothers travel long distances from the neighbouring districts seeking the services of a midwife because of lack of midwives at the Health Centre IIIs or IVs.

Furthermore, from document review15, absenteeism rates of health centres IIs to IVs in the financial year 2011/12 also contributed to the high bed occupancy rates in RRH. Table 7 below shows the absenteeism rates of health workers at the various health centres during 2011/12.

Table 7: Absenteeism Rates for Health Workers at Health Centres in 2011/12

Facility Absenteeism rate

Health Centre II 25%

Health Centre III 30%

Health Centre IV 50%

Source: Annual Health Sector Performance Report, 2012-2013, p35

Audit CommentThe RRHs with a bed occupancy rate above 100% may have a low preparedness for emergency admissions. In addition, it diminished the quality of health services provided by the hospital arising from floor admissions. Through a review and analysis of patient days and available beds over the three years under review, we noted that six of the thirteen RRHs experienced floor admissions ranging from an average of 6 to 445 patients per day over the review period as shown in Table 6. Discussions with Hospital Directors revealed that the floor admissions increase the risk of patient to patient infections therefore prolonging their recovery and stay at the hospital.

ii) Average Length of Stay

Analysis of Data shows that the average length of stay of patients affects the performance of RRHs in delivering inpatient services. RRHs with a higher average length of stay tend to have fewer admissions yet the number of available beds remains unchanged (Figure 2 below refers). For example, the hospitals which had ALOS of 3 days reported admissions over 40,000 on average, while an average of only 10,000 admissions were reported where the ALOS was 8 days. This is because if inpatients are admitted for long periods, fewer beds will be available to accommodate new ones.

15Ministry of Health, Annual Health Sector Performance Report, 2012-2013, p35

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Figure 2: Graph showing the Average Admissions Vs Average Length of Stay.

Source: OAG Analysis

From Table 6 above, audit noted that four (4) RRHs such as Arua, Kabale, Moroto and Mubende showed no improvement in their ALOS over the three-year period i.e. their ALOS was increasing.

It was noted that one of the causes of a high average length of stay in RRHs is the shortage of medical specialists. From interviews with the Hospital management16, it was noted that where there were fewer medical specialists such as medical officers- special grade, consultants, and senior consultants, the average length of stay tends to be high because patients suffering acute illnesses spend extra days admitted in the hospital, waiting in line to receive treatment from the few available specialists.

This was confirmed by a comparison of the number of medical professionals in a RRH and its average length of stay (Figure 3 below refers). The average number of medical specialists across the RRHs is 8. Moroto and Kabale which reported average length of stay above 5 days had fewer medical specialists than the average of 8. Masaka, Mbarara, Soroti and Jinja which had an average length of stay below 5 days were found to have more medical professionals than the average of 8.

Figure 3: Graph showing the relationship between medical specialists and ALOS in 2013/14


16Interview notes, Hospital Administrators, Mbale and Soroti RRH

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b) Idle Infrastructure

Infrastructure is considered a key focus and a priority intervention in health system strengthening.17 In addition, the National Committee on Medical Equipment (NACME) Standard Equipment list 2009 prepared by the Ministry of Health sets out the type and quantity of equipment required by a RRH.18

Efficiency is achieved when the available resource inputs are applied in a way that maximises the desired output. Although health infrastructure is a key input of RRHs, it was noted that some of the infrastructure in RRHs was lying idle and/or under-utilised.

i) ICU Facilities in jinja and Lira RRHsFor example, inspections and interviews in Jinja and Lira RRHs revealed that Jinja RRH which ran a 13-bed Intensive Care unit only used 6 of the beds, leaving 7 beds idle in the unit while Lira RRH had not utilized its 16-bed ICU since FY 2012/13. The Hospital Directors of Jinja and Lira RRHs explained that more nurses would have to be deployed as each bed required at least 2 full time nurses to the unit to ensure full utilisation of the unit without compromising the quality of care. The unit would also require full time doctors and an anaesthesiologist. In Lira RRH, management explained that the ICU had not been commissioned and that its underutilisation was also due to the absence of an oxygen plant. However, audit noted that the ICU facility was completed in the FY 2012/13 and that Jinja RRH, which had no oxygen plant, had partially utilized its ICU. It was also observed that the oxygen plant had not been planned for.

With the current ICU bed capacity in Uganda of 61 in all public and private hospitals, 23 unutilized ICU beds in Jinja and Lira represents a wasted resource. It is estimated that about 10 critically ill patients were deprived of ICU admission daily and as a result succumbed to their illnesses19.

ii) Idle beds in Gulu RRH Inspection of the main store at Gulu RRH revealed that 20 mattresses, 20 pillows and 20 beds had been kept in the stores for more than one year as shown in Picture 1 below. The stock cards indicated that these items had been acquired by the hospital in 2013 but had never been handed over to any ward for usage.

Gulu RRH management explained that the mattresses were a donation at a time when the hospital had enough mattresses and all the beds commonly used had mattresses. The store keeper further explained that the mattresses could not be distributed without protective plastic mattress covers as they would easily be soiled by patients. The audit team however, attributed this to poor planning as these covers were not planned for in the financial years 2012/13 and 2013/14.

It was also noted that in 2011/12, the bed occupancy rate of Gulu RRH was below 100% and there were no floor admissions. This goes to show that no proper needs assessment was carried out before procuring these items.

Lira faced a similar challenge with 15 beds stacked up in their store for over a year.

iii) Imaging Equipment in Mbale RRH In Mbale RRH, imaging equipment donated by the Japan government had been idle for part of the FY 2013/2014. Interview with the principal hospital administrator revealed that

17Ministry of Health: Health Sector Quality improvement Framework and strategic plan 2010/11-2014/1518NACME Standard Equipment list 200919National Intensive Care Unit bed capacity and ICU patient characteristics in a low income county – Research notes. Arthur Kwizera, Martin Dunser, Jane Nakibuuka (page 2)

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the equipment was not repaired promptly because the spare parts and technical repair skills were not available on the Ugandan market.

iv) Idle Equipment in Mubende RRH In Mubende RRH, inspection of the stores established that two slit lamps, four oxygen therapy apparatus machines and one operating cold light unit which was supplied by Uganda Health Systems Strengthening Project (UHSSP) have been idle for 1 year (since 2013).

Picture 1: Idle Equipment in Gulu and Mubende Regional Referral Hospitals

Picture 1

Gulu RRH: Mattresses lying idle in the stores

Mubende RRH: Idle equipment in store

Source: OAG photo

Management responseSome of the equipment was acquired through donations and not procured by the RRHs. The donated mattresses in Gulu were received at a time when the hospital had an adequate stock of mattresses and kept them as buffer stock. All the commonly used beds have mattresses. Consideration was not made for additional requirements of the ICU in Jinja namely: presence of an anaesthesiologist, specialised nurses and doctors, a darkroom and maintenance funds.

Audit Comment Any unutilised equipment (whether donated or procured by the RRH) represents an idle resource. The money spent on the purchase of these items, estimated at United States dollars (US$77,200 in total (as shown in table 9 below) could have been put to procurement of more pressing equipment in the hospital such as diagnostic equipment. In addition, such capital assets being left idle in stores could depreciate before the hospital derives the intended benefits.

Table 8: Quantity and Value of Idle Equipment found in 5 RRHs

RRH IDLE EQUIPMENT VALUE (USD)

Jinja ICU beds [6] 6,000

Lira ICU beds [16]ICU Monitors [3]Examination lights [12]Beds

16,00019,5006,0007,500

Gulu Beds and mattresses [20] 10,000

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RRH IDLE EQUIPMENT VALUE (USD)

Mbale Imaging Equipment Unknown

Mubende Slit lamps [2]Oxygen therapy apparatus machine [4]Operating cold light unit [1]

6,0003,2003,000

Total value of idle equipment 77,200

Source: Physical inspections and interview notes in jinja, Lira, Gulu, Mbale and Mubende RRHs.

NB: The values were obtained from the NACME equipment checklist provided by MOH.

c) Utilisation of X-ray and Ultrasound Machines

RRHs are committed to attaining value for money in the delivery of their outputs by ensuring efficient utilisation of resources. Carrying out diagnostic testing and examinations for both outpatients and inpatient services is a key output of RRHs as spelled out in the Ministerial Policy Statements for MoH.

Analysis of data relating to utilisation of X-ray and ultra sound machines (only functional machines for FY 2013/14) revealed that the RRHs exhibited big differences in the number of examinations conducted per machine per year. For X-ray machines, the number ranged between 887 in Arua to 8,782 in Masaka (as shown in Table 10 below) while usage of ultra sound scans ranged between 629 images per scanner per year in Kabale to 6,309 in Gulu as detailed in Table 11 below.

It was also observed that a number of X-ray machines and ultra sound scanners were non-functional and this further limited the output of these vital equipment.

The low performance of hospital equipment was mainly due to lack of routine and proper maintenance. Hospital managers in response attributed this to the lack of bio medical engineers and high costs of repairing the equipment, for instance, according to Jinja RRH, the maintenance of the En-Visor ultra sound machine and the repairs of the Duo-Diagnostic big x-ray machine requires not less than UGX 15 million, and without a medical equipment maintenance fund, it is a challenge to maintain and repair the radiology and imaging machines.

Management of Fort Portal RRH attributed the low usage of the x-ray and ultrasound machines to stock-outs of the supplies, such as reagents and films required for the operation of this diagnostic equipment.

Table 9: Number of X-ray images produced per machine for the Financial Year 2013/14

RRH X-RAY EXAMINATIONS

NO. OF FUNCTIONAL MACHINES

USAGE PER X-RAY MACHINE

MASAKA 8,782 1 8,782

KABALE 8,112 1 8,112

LIRA 7,868 1 7,868

MBALE 3,891 1 3,891

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RRH X-RAY EXAMINATIONS


USAGE PER X-RAY MACHINE

MBARARA 3,385 1 3,385

MUBENDE 3,355 1 3,355

FORT 6,610 2 3,305

JINJA 3,037 1 3,037

MOROTO 2,172 1 2,172

HOIMA 3,476 2 1,738

SOROTI 2,783 2 1,392

ARUA 887 1 887

GULU - -

AVERAGE 3,994

Source: MOH resource centre.

Table 10: Number of ultra sound images produced per scanner for the Financial Year 2013/14

RRH ULTRA SOUND EXAMINATIONS


USAGE PER ULTRASOUND MACHINE

GULU 6,309 1 6309

MBALE 4,689 1 4,689

MBARARA 4,429 1 4,429

JINJA 4,005 1 4005

LIRA 5,783 2 2892

ARUA 5442 2 2721

FORT PORTAL 5278 2 2639

SOROTI 8917 4 2229

MOROTO 1747 1 1747

MUBENDE 1491 1 1491

HOIMA 1361 1 1361

KABALE 629 1 629

MASAKA N/A N/A N/AAVERAGE 2928

Source: MOH resource centre

Management responseOne of the machines in Fort Portal was a mobile x-ray for limb fractures and its outputs were not expected to be the same as the main digital x-ray. Similarly the second ultrasound machine was acquired toward end of 2013/14. The demand for services was high but x-ray and ultrasound has been one of the areas where supplies have not been consistently delivered.

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Audit Comment Whereas, mobile x-ray machines were expected to conduct less x-ray examination, as was the case in Fort Portal, the analysis as shown in the Table 9 above indicated that availability of additional machines was not commensurate to need. For example, Masaka and Hoima which had the highest numbers of x-ray examinations conducted had only one x-ray machine while Soroti and Hoima with much lower numbers of examinations had 2 machines each.

Recommendations• The District Directors of Health Services at the districts should address the

operational weaknesses in the Health centre II, III and IVs such as absenteeism, lack of medicines among others, which results in the RRHs being overstretched.

• Shortage of health workers should be addressed by putting in place mechanisms that would attract and retain these professionals to the RRHs.

• RRHs with unutilised and underutilised equipment should consider redistributing them to other health units that would put these items to better use.

• Lira RRH is advised to expedite the commissioning of the ICU and benchmark from Jinja RRH on the alternative sources of oxygen in the absence of an oxygen plant.

4.2.3 StaffingRRHs are mandated to provide specialized services such as Obstetrics and Gynaecology, Surgery, Paediatrics, Medicine, Psychiatry, Ear Nose and Throat (ENT), Ophthalmology, dentistry, intensive care, radiology, pathology, higher level surgical and medical services training and research in addition to general health care services20. In order to meet this mandate, they are required, in coordination with Health Service Commission, to recruit highly specialized personnel in the various areas. Furthermore, WHO recommended a patient: doctor ratio is 800:1.21

However through interviews with the hospital directors and administrators and analysis of the approved staffing structures, it was noted that all RRHs have not recruited all the specialized staff to deliver the services. At the time of the audit, most of RRHs visited had not achieved required number of consultants as per the established structure to handle the specialized services of the RRHs as shown in table 11 below.

Table 11: Staffing Situation of Medical Consultants per RRH in 2013/14

RRH ESTABLISHED FILLED GAP % NOT FILLED

GULU 13 1 12 92

ARUA 16 5 11 68

FORT PORTAL 9 4 5 55

HOIMA 12 3 9 75

JINJA 15 12 3 20

KABALE 16 4 12 81

20Ministry of Health National Hospital Policy-201421National Development Plan, 2010/11-2014/15

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RRH ESTABLISHED FILLED GAP % NOT FILLED

LIRA 17 1 15 88

MASAKA

MBALE 15 10 5 33

MBARARA 0

MOROTO 13 0 13 100

MUBENDE 12 2 10 83

SOROTI 14 8 6 42

TOTAL 152 51 101 66

Source: RRHs staffing structures.

Moroto had the worst case scenario with no consultant, followed by Gulu with only one consultant who was doubling as the Hospital Director, followed by Lira and Mubende.

RRHs are staffed according to staffing norms approved by the Health Service Commission. The staffing levels in some areas do not enable RRHs to fulfil their mandate of providing specialized service. The staffing situation in the hospitals is inadequate and there is wide variance across all RRHs.

Through document review of the annual health sector performance report 2012/13, it was revealed that the ratio of patients to clinicians was high in RRHs and varied from one RRH to another. The average doctor-patient ratio per year in RRHs was 12440:1 implying one doctor for 34 patients per day while clinician- patient ratio was 10652:1 annually implying one clinician for 29 patients.

In an interview with the management of each RRH, the situation was attributed to failure by the hospital to retain health workers due lack of accommodation, and remoteness of some referral hospitals.

Interviews with ministry officials confirmed the assertion that geographical location of some referral hospitals affected their ability to attract health workers.

As a result, there was distributive inefficiency leading to some referral hospitals having to refer patients to other referral hospital for specialized services. For example; Kabale, Fort Portal, Masaka and Mbale Regional Hospitals referred some special cases to Mbarara RRH for services like CT scan, renal dialysis, neurosurgeon, paediatric surgery. In addition, lack of adequate staff has led to referrals to the National Referral Hospital and this has further resulted in the congestion and handling of cases at National Referral Hospital which cases could be handled by the RRHs. The process of referrals is costly and in some cases patients lose their lives in the process of reaching the health facility to which they have been referred.

Management responseStaffing needs for RRHs have not been adjusted to meet the growth of the hospitals and in some cases; to adapt with the transformation from District General hospitals to Regional Referral hospitals. There is also no standard staffing structure provided to RRHs by the MOH.

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Audit Comment Lack of specialised staff limits the ability of RRHs to execute their mandate of offering specialised services.

Recommendations• The MOH is advised to develop staffing structures suitable for the needs of

RRHs.

OVERALL AUDIT CONCLUSIONThe results of the efficiency study of the operations of RRHs using the data envelopment analysis technique have shown that 50% of the RRHs were relatively efficient in the utilization of their resources. The remaining inefficient hospitals exhibited potential for improvements if appropriate interventions were made to address the slacks in the utilization of the key inputs such as medicines, infrastructure, /equipment and human resource.

With reduced inefficiency, RRHs stand to reap significant input savings from their activities. This would ensure improvements in the coverage and quality of health services.

Admissions Patients who undergo a hospital’s formal admission process and may be either an overnight-stay patient or a same-day patient.

Allocative efficiency This occurs when there is an optimal distribution of services, taking into account consumers’ preferences

Antenatal Care The health care given to a pregnant woman and her unborn baby throughout a pregnancy.

Autoclave A pressure chamber used to sterilize equipment and supplies by subjecting them to high pressure saturated steam.

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GLOSSARY OF TERMS

Average Length of Stay (ALOS)

The average number of days that patients spend in hospital. It is generally measured by dividing the total patient days by the number of admissions or discharges.

Bed capacity The number of beds available in the hospital for inpatient admissions.

Bed Occupancy Rate The number of patient days divided by the number of available hospital beds multiplied by the number of days in a year.

CT scan A Computed Tomography (CT) scan is an imaging medical equipment that uses x-rays and digital computer technology to obtain detailed images of internal organs.

Diagnostic equipment A device or substance used for the analysis or detection of diseases or other medical conditions. Examples include: X-ray machine, CT scan, ultrasound machine

Distributive efficiency This occurs when services are consumed by those who need them most and is concerned with an equitable distribution of resources.

Efficiency This means getting the most from available resources. It is concerned with the relationship between resources employed and outputs delivered in terms of quantity, quality and timing.

Hospital Manager This report has used this to mean any member of the hospital administration representing the top management of the hospital, for example, hospital director, hospital administrators, heads of department

Inpatient A patient who stays in a hospital while under treatment.

Maternal mortality Maternal mortality is the death of a woman while pregnant or within 42 days of termination of pregnancy, from any cause related to or aggravated by the pregnancy or its management but not from accidental or incidental causes.

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Maternal Mortality rate Maternal mortality rate is the number of maternal deaths in a population divided by the number of women of reproductive age, usually expressed per 1,000 women.

Outpatient A patient who receives medical treatment without being admitted to a hospital.

Patient days The total number of days stayed by all inpatients during a year.

Standard Unit of Output The SUO is a composite measure of outputs that allows for a fair comparison of volumes of output of hospitals that have varying capacities in providing the different types of patient care services. The standard unit of output attempts to attribute the final outputs of a hospital a relative weight based on previous cost analyses taking the outpatient contact as the standard of reference. The SUO converts all outputs to outpatient equivalents.

Technical efficiency This occurs when a firm is producing the maximum output from the minimum quantity of inputs, such as labour, capital and technology.

Waiting Time The time from when a patient arrives at the hospital to the time of being attended to by a health worker.

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APPENDICES

APPENDIX I: DETAILS OF INTERVIEWS CONDUCTED

INTERVIEWEE OBjECTIVE OF THE INTERVIEW/MEETING

Director General Health services – MOH

To introduce the team to the DG and obtain an overview of the role of the ministry in the operations of the RRHs

Commissioner – Clinical Services, MoH

The team was to obtain knowledge on the policies and guidelines given to the RRHs by the ministry. Team also sought to understand the preliminary information on services offered by RRHs.

Assistant commissioner – MOH resource centre

To establish the availability, accuracy and completeness of RRH data held by the ministry. The interview also enabled the team access all data on inputs and outputs.

HMIS officials at the resource centre MOH

To obtain data on inputs, outputs and other indicators on health.

Principle Finance Officer – Planning Department, MoH

To understand the ministry’s role in RRHs.

To understand the general structure and functioning of RRHs.

To get guidance on which ministry departments and documents would provide the information needed for the efficiency audit

Principal Medical Officer- Curative Services, MoH

The purpose of the meeting was to obtain answers to a number of questions that would guide the team in planning the audit.

Hospital Directors – 9 RRH The purpose of the meeting was to understand the operation and management of Gulu RRH

Human Resource Officers The purpose of the interview was to complete the part of the Field work questionnaire relating to Health workforce.

Principal Hospital Administrator – 9 RRH

The purpose of the interview was to complete the part of the Field work questionnaire relating to Health Infrastructure.

OPD and IPD staff members To obtain information about the process of handling patients in the OPD and challenges faces.

Stores and Pharmacy Dept – 9 RRHs.

Obtain information on the management of stores, the procurement and handling of drugs with in the hospital.

NMS Management To collaborate information and assertion from RRHs relating to drugs.

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AP

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APPENDIX III: DETAILS OF DEA THEORETICAL FRAMEWORK.

Illustration of the DEA model

Assuming five hospitals (A, B, C, D & E) with two inputs (for example doctors and money spent on drugs). The following illustrates their usage of the inputs.

A

D

Drug expenditure

In the analysis an input based model is used. That is, the model used assumes that hospitals have little control over varying their outputs than their inputs. Units (A, B, C, D)uses the least amount of resources to produce a given level of output. Combining (envelope) these hospitals makes up what in economics is called an isoquant, or best practice frontier. Since A, B, C and D are on the isoquant the assumption is that the isoquant represents all possible combinations of minimum inputs that can be used to produce a given level of output. It is therefore not possible to reduce the inputs and at the same time produce the given level of output. Turning the focus to hospital E it is obvious that hospital E could reduce the amount of Doctors and Drugs and still be able to produce a given amount of output. Hence E can be considered to be inefficient. When measuring the efficiency we make use of the line between O and E as the direction for potential input savings. The input saving potential is hence represented by the distance between E and E*. Thus in order to become efficient hospital Ecan reduce its inputs to level.

The technical efficiency (TE) scores are computed by comparing the distance between the origin and E with the distance from the origin and E*: T.E = ||OE*||/||OE||. The efficiency score obtained is interpret as the potential reduction in resources. For example, of the efficiency score for hospital E is 0.7 only 70% of the currant resource use is necessary. Only using 70% if E’s input place unit E where E* is located. Multiplying E’s resources use with 0.7 is the same as claiming that the potential is an input reduction with 30%. This implies that in order for hospital E to be efficient, it must save up to 30% (i.e. 100% minus 70%) of their current inputs while still producing the same level of output.

Returns to ScaleReturns to scale (RTS) explains the behaviour of the rate of increase in outputs relative to the associated increase in the input. In the long run all inputs are variable and subject to change due to a given increase in size (scale). A constant return to scale (CRS) implies that a double increase in inputs results in a double increase in the outputs. Production units strive to attain a constant RTS in the long run and therefore this method is applicable where decision making units aim to attain efficiency in the long term.

Variable returns to scale (VRS) implies that a double increase in the inputs results in a more than or less than double increase in the outputs. In the short run, this method is more applicable.

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APPENDIX IV: SUMMARY OF PREVIOUS DEA STUDIES ON HOSPITALS

AUTHORS NAME OF STUDY

NUMBER OF HOSPITALS

VARIABLES RETURNS TO SCALE

Ministry of Health Uganda

Efficiency analysis of Health facilities in Uganda. 2011

All RRHs, General Hospitals and Health centres.

Inputs; Doctors, Nurses, other health staff, support staff, expenditure on medicines, non – wage expenditure.Outputs; OPD, inpatients, deliveries, HCT counselling, ART clients, PMTCT clients.

CRS, IRS, DRS.

Dorold Barnum

Measuring Hospital efficiency with Data Envelopment Analysis

87 community Hospitals

Inputs Staff (Employees)Staffed bedsOutputs Annual patient Annual outpatient

Jan.P. Clement and Valdmans 2012

An Analysis of Hospital Outcomes and Efficiency with a DEA model of output congestion.

25 Inputs FTE registered NursesFTE Licensed practical NursesStaffed bedsOutputsBirths Outpatient surgeriesEmergency room visits Outpatient visitsCase mix adjusted admissionsMortality rate

Gary D Ferrier and Julie S. Trivit

Incorporating quality into the measurement of hospital efficiency; A double DEA approach -2012

1074 Inputs BedsFTE RNFTE LPNoutputsInpatient daysOutpatient daysInpatient and outpatient Surgeries

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NUMBER OF HOSPITALS


Andrew LindenSouth Africa

Measuring Hospital Efficiency using DEA-2013

138 Inputs FTE RNMedical doctorsSpecialistsActive bedsStaffed bedsNumber of non-nursing medical and dental staffDrugs Capital chargeOutputs OPD attendancesNo of birthsSurgeriesEmergency room visitsAdmissions Acute discharge

Both constant and variable return to scale

Joses M. Kirigia

A performance method for hospitals: the case of Municipal Hospitals in Angola

28 public municipal Hospitals

Inputs Doctors Nurses Drugs and suppliesBeds Outputs OutpatientAntenatal visitsInpatient admissions

Both constant and variable return to scale

James Akazili and Martin Adjuik

Using DEA to measure the extent of technical efficiency of public health centres in Ghana

54 CRS and VRS

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NUMBER OF HOSPITALS


Joses M. Kirigia

Measurement of technical efficiency of public Hospitals in Kenya: using DEA

54 Inputs.Doctors Pharmacist Clinicians Nurses Admin staffTechnicians Drugs Maintenance Beds Out putsOPD casual visitsSpecial care visitsInpatient departmentMaternity admissionsPaediatrics ward admissions

CRS and VRS

EyobZere, Thomas Mbeeli et al

Technical efficiency of district Hospitals: Evidence from Namibia using DEA.

30 Inputs Recurrent expenditureBeds Nursing staff outputsOutpatient visitsInpatient days

Constant Return to Scale

Felix Masiye, Joses M. Kirigia et al

Efficient management of Health centres Human Resource in Zambia.

20 Inputs Clinical officersNo of NursesOther staffoutputsOutreach servicesNo of visitsImmunisation

CRS and VRS

Yang & Wu Zeng

The trade-off between efficiency and quality in the hospital production

70 Inputs; Beds, doctors, nurses, administrative staff and other staff.Outputs; outpatient visits and inpatient visits.Quality; Mortality rate and Average length of stay

VRS and CRS

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APPENDIX V: ILLUSTRATION OF THE POTENTIAL SAVING ON RECURRENT EXPENDITURE PER RRH IN 2012/13

RRH* RECURRENT EXPENDITURE for FY 2012/13 ( UGX)

POTENTIAL SAVING (%)

POTENTIAL SAVING (UGX)

ARUA 3,673,907,486 29 1,065,433,171

FORT PORTAL 4,306,786,485 15 646,017,972

GULU 3,369,615,055 31 1,044,580,667

JINJA 4,542,151,566 31 1,408,066,985

KABALE 2,669,549,373 16 427,127,899

LIRA 3,002,901,291 16 480,464,206

MBARARA 4,528,189,274 17 769,792,176

SOROTI 3,317,110,385 15 497,566,557

TOTAL SAVING 6,339,049,633

*Excluding the RRHs which scored 100% in 2012/13.

Source: OAG Analysis of the efficiency scores (potential saving = 100% - efficiency score)

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APPENDIX VI: SENSITIVITY ANALYSIS

Sensitivity analysis was carried out using four models. The input and output variables of each model are:

Table 12: Different models in the sensitivity analysis

Model Inputs Outputs

Preferred Model BedsHealth WorkersDrugs

Standard Unit of OutputHospital Deaths

Model 1 BedsHealth WorkersDrugs

Adjusted Standard Unit of Output*


Standard Unit of OutputAverage Length of Stay



Model 4 BedsAll StaffDrugs

Standard Unit of OutputHospital Deaths

*SUO adjusted for floor admissions

Table 15: Efficiency Scores for each RRH under each model for the period 2011-2014

RRH MODEL 1

2013/14 2012/13 2011/12

ARUA14 77% 71% 91%

FORT14 90% 85% 100%

GULU14 78% 69% 100%

HOIMA14 100% 100% 100%

JINJA14 85% 69% 74%

KABAL14 98% 85% 79%

LIRA14 93% 84% 100%

MSKA14 100% 100% 73%

MBALE14 100% 87% 100%

MBRA14 78% 83% 100%

MRTO14 100% 100% 100%

MBND14 100% 100% 100%

SROTI14 100% 83% 100%

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MODEL 2

2013/14 2012/13 2011/12

ARUA14 77% 71% 91%

FORT14 90% 85% 100%

GULU14 78% 69% 100%

HOIMA14 100% 100% 100%

JINJA14 85% 69% 74%

KABAL14 98% 85% 79%

LIRA14 93% 84% 100%

MSKA14 100% 100% 73%

MBALE14 100% 87% 100%

MBRA14 78% 83% 100%

MRTO14 100% 100% 100%

MBND14 100% 100% 100%

SROTI14 100% 83% 100%

MODEL 3

2013/14 2012/13 2011/12

RUA12 75% 71% 85%

FORT12 90% 85% 93%

GULU12 77% 68% 97%

HOIMA12 100% 100% 100%

JINJA12 83% 69% 67%

KABAL12 89% 84% 78%

LIRA12 93% 84% 90%

MSKA12 100% 100% 100%

MBALE12 100% 100% 100%

MBRA12 78% 83% 89%

MRTO12 100% 100% 100%

MBND12 100% 100% 100%

SROTI12 99% 85% 100%

MODEL 4

2013/14 2012/13 2011/12

ARUA14 97% 76% 82%

FORT14 88% 94% 100%

GULU14 83% 100% 100%

HOIMA14 100% 100% 85%

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JINJA14 100% 76% 68%

KABAL14 100% 87% 59%

LIRA14 88% 94% 100%

MSKA14 99% 100% 100%

MBALE14 100% 100% 100%

MBRA14 80% 84% 86%

MRTO14 100% 100% 100%

MBND14 100% 100% 100%

SROTI14 100% 100% 100%


a) Model 1This model uses the same variables as the preferred model but applies floor admissions as a quality measure rather than hospital deaths. This is because floor admissions were thought to be an indicator of quality of health care as suggested by the Hospital directors. The average efficiency scores changes lightly from the preferred model because most of the hospitals report few or no floor admissions. Of interest are Masaka and Mbale RRH which report the highest number of floor admissions in 2011/12 (Masaka) and in 2012/13 (Mbale) resulting in a drop in their average efficiency scores from 100% to 91% and 96% respectively.

b) Model 2This model uses the same variables as the preferred model but applies average length of stay as a quality measure rather than hospital deaths. The average scores generally remain the same for all the RRHs with only marginal changes of 1%-3% for three RRHs from the preferred model results. This model therefore, does not offer unique information.

c) Model 3This model uses the same variables as the preferred model but excludes hospital deaths, therefore leaving quality measures out of the model. There are slight changes in the average efficiency scores of four RRHs while the considerable change is in Soroti RRH which goes from 95% to 100% efficiency. However, this model has not been chosen because disregarding quality results in omitted variable bias as argued by Carey and Burgess (1999)22.

d) Model 4 This model uses the same variables as the preferred model but replaces health workers with total number of staff, therefore incorporating administrative and support staff in the model. This changes the average efficiency score of five RRHs. However, this model has not been chosen because the administrative and support staff are not directly involved in delivering the health service to patients.

22Ferrier, D. et al, 2012, “Incorporating Quality into the Measurement of Hospital Efficiency: A Double DEA Approach”, p338.

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APPENDIX VII: GRAPHS AND TABLES

a) Graphs showing the comparison between Budget or Orders and Deliveries of Medicines and health supplies of 5 selected RRHs

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b) Graphs showing the relationship between unit cost expenditure on medicines and the efficiency scores (E.S) for the RRH

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c) Number of medical specialists and the average length of stay per RRH in 2013/14

RRH ALOS 2013/2014 NO. OF MEDICAL SPECIALISTS

MOROTO 8 0

GULU 5 3

HOIMA 4 4

ARUA 5 5

KABALE 6 6

LIRA 5 6

MUBENDE 5 6

MBALE 2 9

FORT PORTAL 5 10

MASAKA 4 11

SOROTI 4 13

JINJA 5 15

MBRA 4 19

MEAN 5 8

Source: Ministry of Health - Resource Centre and OAG analysis

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d) Maternal Mortality Rate per RRH for the financial years 2012/13 and 2013/14

RRH 2012/13 (per 100,000 live births)

2013/14 (per 100,000 live births)

ARUA 429 656

FORT PORTAL 695 542

GULU 119 375

HOIMA 509 641

JINJA 304 515

KABALE 76 151

LIRA 191 308

MASAKA 519 380

MBALE 301 230

MBARARA 310 374

MOROTO 201 571

MUBENDE 602 916

SOROTI 498 420

AVERAGE 366 468

Source: OAG Analysis of Maternal death and live births.

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OFFICE OF THE AUDITOR GENERALOFFICE OF THE AUDITOR GENERAL

P.O. Box 7083, Kampala.Tel. +256 414 344 340 Fax: +256 417 336 000

E-mail: [email protected],go.ug

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