Balancing efficiency of health services and equity of access in remote areas in Greece

Data envelopment analysis (DEA) was used to investigate the efficiency of a set of small-scaled Greek hospitals known as hospital-health centers (HHCs). These facilities naturally provide primary and secondary care but are also expected to function as health centers addressing mostly preventive medicine, hygiene and other public health issues. They are located in remote rural areas and serve the relatively small local populations. This study aimed to obtain insight on their productive efficiency in light of their particular role. The sample consisted of 17 from the 18 units existing in the Greek NHS. Variables chosen to characterize production were numbers of doctors, nurses and beds as inputs, and admissions, outpatient visits and preventive medical services as outputs. The DEA model was input oriented, allowed for constant returns to scale and units were ranked according to a benchmarking approach. Analyses were performed with and without the preventive medicine variable and the results demonstrated technical inefficiencies 26.77 and 25.13%, respectively. Location appeared to affect performance, with remote units, e.g. on small islands, more inefficient. This raises the question if correcting reduced efficiency compromises equity of service access for highly dependent populations. Moreover, we observed superior performance of units additionally offering preventive medical services. This generates another question as to the role these facilities should play in our currently changing health care system.     

Supporting operational decision making

The collection and processing of information is a source of power. This fact is true especially in the health care industry. The apparent lack of information related to operational decisions in the health care industry is cause for concern. Data envelopment analysis (DEA) provides information regarding efficiency of resource utilization. This article reports on the use of DEA to measure relative technical efficiency of nursing units and the level of association between efficiency scores and the presence of selected operational characteristics. We found a statistically significant association between efficiency and two of the selected characteristics. Although nursing units are used to illustrate the application of the technique, DEA can be applied to any operational unit of a health care organization. However, we conclude that information systems and a minimum data set are essential to optimizing utilization of a such techniques.     

Assessing the efficiency of rural health centres in Burkina Faso: an application of Data Envelopment Analysis

Background  Effective health care provision benefits from the support of measurement techniques. Contrary to the situation in industrialised countries efficiency analyses in the health care sector in Africa are a very recent phenomenon. Hardly any of the existing studies was conducted at the level of primary care. Aim  The purpose of this study was twofold: (1) to evaluate the relative efficiency of health centres in rural Burkina Faso and (2) to investigate reasons for inefficient performance. Methods  Data Envelopment Analysis (DEA) was applied. To account for the situation in that country, the output-oriented approach was used in connection with different returns to scale assumptions. To identify the spatial effect of the catchment area on efficiency the Tobit model was applied. Results  According to constant returns to scale, 14 health centres were relatively efficient. The DEA projections suggest that the inefficient units were too big to be efficient. Tobit regression showed that the relatively efficient health centres are located close to villages in their catchment area. Conclusions  For ethical reasons it is not appropriate to try to improve the efficiency of health centres by closing some of them. Their efficiency can be improved and lives can be saved if access to health centres is enhanced. Funding: This study was supported by a research grant of the German Research Foundation (Deutsche Forschungsgemeinschaft).     

Institutional arrangements and efficiency of health care delivery systems

This study examined the efficiency of health care delivery systems in 24 OECD countries. Practicing physicians, practicing nurses, inpatient beds, and pharmaceuticals were considered as inputs to treat populations of various age groups. Data envelopment analysis (DEA) was utilized to calculate efficiency. We also calculated input efficiency that should be helpful in determining excess number of physicians, nurses, inpatient beds, and pharmaceuticals consumed. Institutional arrangements affect efficiency: public-contract and public-integrated countries are more efficient than public-reimbursement countries. Countries in which physicians are paid in wages and salaries and countries with capitation have higher efficiency than fee-for-service countries. Countries in which a primary care physician acts as a gatekeeper are also more efficient than countries without gatekeepers.     

Output congestion leads to compromised care in Peruvian public hospital neonatal units

Peru is moving toward a universal health insurance system, and it is facing important challenges in the provision of public health services. As more citizens gain access to health insurance, the flow of patients exceeds the capacity of public hospitals to provide care with quality. In this study we explore the relationship between technical efficiency and patient safety events in neonatal care units of Peru’s public hospitals. We use Data Envelope Analysis (DEA) with output congestion to assess the association between technical efficiency and patient safety events. We study 35 neonatal care units of public hospitals in Peru’s Social Security Health System, and identify two undesirable (risk-adjusted) safety outcomes: neonatal mortality and near-miss neonatal mortality. We found that for about half of hospital’s neonatal care units, technical efficiency is affected by output congestion. For those hospitals, patient safety is being compromised by receiving too many patients. Our results are consistent with public reports indicating that hospitals in the Peru’s Social Security Health System are overcrowded, affecting efficiency and jeopardizing quality of care. We found that most congested hospitals are located in the capital city and suburban areas, and are more likely to be hospitals with the lowest and the highest level of care. Our results call for improvements in the patient referral system and capacity expansion.     

Case-mix adjustment and efficiency measurement

AIMS: The importance of using valid case-mix systems in long-term care is addressed by comparing the predictive power of different case-mix models, and by applying them in the calculation of technical efficiency scores of care units. METHODS: To construct different case-mix models a statistical clustering technique (Automatic Interaction Detection) was used. Technical efficiency score were calculated using data envelopment analysis (DEA). RESULTS: The Resource Utilization Groups (RUG-III/22) classification explained 39% of resident specific cost, compared with 16% for a functional dependency scale in the Finnish patient information system HILMO. CONCLUSION: When assessing the economic performance of long-term care units it is important to pay attention to the predictive validity of the case-mix measure to be used. The choice of case-mix measure significantly affected how units were rated in efficiency.     

The efficiency of the delivery of neonatal care in the UK

BACKGROUND: A recent paper in Journal of Public Health Medicine (O'Neill et al., 2000; 22(1): 108-115) used regression modelling to determine the average costs of neonatal care services for a sample of 49 units in the United Kingdom in 1990-1991, and concluded that economies of scale were present in the sample as a whole. Although this form of modelling is useful, analysis of the efficiency of production for individual units is also important. METHODS: Data envelopment analysis (DEA) was used to analyse the data set published by O'Neil et al., to determine technical efficiency of neonatal units, measuring efficiency compared with a benchmark efficient frontier, and estimating economies of scale for each unit. Potential cost savings if units were to operate efficiently are estimated. RESULTS: There is evidence of substantial levels of technical inefficiency. Economies of scale varied between units, with increasing returns in the 36 inefficient units, and mainly constant returns in the 13 efficient units. This suggests that the presence of technical inefficiency was as important as scale inefficiencies. Total cost savings, if all units were operating efficiently, are estimated at ?10.4 million, equivalent to 10 extra units producing 57,000 additional days of care. CONCLUSIONS: DEA is a technique of great potential value in analysing the efficiency of health care production. As well as inefficiencies in the production of neonatal care in the United Kingdom due to differences in the scale of production, there appears to have been considerable technical inefficiency, which was not due to differences in case mix. The potential cost savings from efficiency gains are large.     

基于数据包络分析法的手术科室运营效率探讨

目的对手术科室运营效率进行分析,提出后续资源配置方案。方法以某三甲医院为研究对象,选取神经内科、耳鼻喉科、骨科、口腔科等13个手术科室的资源投入产出相关数据,采用数据包络分析法对各科室运营效率进行评价。结果确定了各手术科室医疗资源投入产出指标。经分析,神经外科需优先增加医生数量,控制医疗费用;胰腺外科需优先增加医生数量;骨科需控制医疗费用;心胸外科建议优先增加护士和床位。结论采用数据包络分析法对各手术科室运营效率进行评价具有可行性。可通过调整医院资源配置,提升手术科室运营效率,缓解“住院难”问题。但未来需加强信息化建设,提高数据采集准确性。     

Relative efficiency in rural primary health care: an application of data envelopment analysis.

This study applied data envelopment analysis (DEA) to the evaluation of rural primary health care programs, which are known to be very heterogeneous. DEA is a mathematical programming technique that optimizes the relative efficiency ratio of current inputs over current outputs for each decision-making unit (DMU). It produces a summary scalar efficiency ratio for each DMU and identifies the amount of inefficiency. The data came from the National Evaluation of Rural Primary Health Care Programs. Despite the demands of the software used for homogeneous units and nonzero values, the efficiency analysis was useful to the evaluation. It assessed multiple inputs and multiple outputs simultaneously, and identified directly those units that are performing efficiently or inefficiently when compared to specific peer programs. This then allowed us to compare this efficient-inefficient classification with other data, first, to verify the classification and, second, to assist with the evaluation. DEA can contribute to the evaluation of heterogeneous health programs, especially when used in conjunction with other methods of analysis.     

Evaluation of resource utilization efficiency in obstetrics and gynecology units in China: A three-stage data envelopment analysis of the Shanxi province

In China, health care resources for expectant mothers and children are still not utilized to full efficiency, with health requirements still not being met. The purpose of this study is to critically examine the efficiency of gynecology and obstetrics hospital (OB/GYN) units in Shanxi province of China, with the overarching objective of exploring methods for improving their efficiency. We employ the three-stage data envelopment analysis (DEA) model to measure the efficiency of 134 OB/GYN units in Shanxi. The results show that the technical efficiency and scale efficiency scores of the sample units were low (0.48 and 0.54, respectively). The efficiency of the OB/GYN units varies by region, city, and county and by type of unit. We conclude that the main reason for the low efficiency of OB/GYN units in Shanxi province lies in the unreasonable scale. The government should, therefore, allocate health resources more reasonably, improving the efficiency of different regions, cities, and counties, as well as different types of OB/GYN units.     

Comparison of apparent efficiency of haemodialysis satellite units in England and Wales using data envelopment analysis

OBJECTIVES: To expand care for chronic haemodialysis (HD) patients throughout England and Wales by studying two aspects of service delivery that are important: to identify relative performance of haemodialysis satellite units (HDSUs), and understand the factors that influence the performance. As a first step toward these aspects, this work reports a study of apparent comparative efficiency in the delivery of HDSUs and demonstrates the potential of data envelopment analysis (DEA). METHODS: DEA was applied to data obtained from a national survey of the organizational structures and processes of delivering care at HDSUs in England and Wales. RESULTS: DEA was found to be a judicious approach for performance assessment of HDSUs, although valid results depend on appropriate model specification and quality of data available. The available data were not of sufficient comprehensiveness or quality to produce definitive results but suggested that overall efficiency could improve; these data suggested by as much as 10% overall (mean efficiency score 90%) and variably within the sample (46 [65%] that HDSUs were potentially inefficient, the lowest unit scoring 38%). CONCLUSIONS: Addressing questions raised by comparative inefficiency could help plans to improve capacity to deal with the growing demand for HD delivered in HDSUs. The application was an important start and needs to be followed by further research to establish model validity and obtain authoritative results.     

Technical and scale efficiency in public and private Irish nursing homes – a bootstrap DEA approach

This article provides methodological and empirical insights into the estimation of technical efficiency in the nursing home sector. Focusing on long-stay care and using primary data, we examine technical and scale efficiency in 39 public and 73 private Irish nursing homes by applying an input-oriented data envelopment analysis (DEA). We employ robust bootstrap methods to validate our nonparametric DEA scores and to integrate the effects of potential determinants in estimating the efficiencies. Both the homogenous and two-stage double bootstrap procedures are used to obtain confidence intervals for the bias-corrected DEA scores. Importantly, the application of the double bootstrap approach affords true DEA technical efficiency scores after adjusting for the effects of ownership, size, case-mix, and other determinants such as location, and quality. Based on our DEA results for variable returns to scale technology, the average technical efficiency score is 62 %, and the mean scale efficiency is 88 %, with nearly all units operating on the increasing returns to scale part of the production frontier. Moreover, based on the double bootstrap results, Irish nursing homes are less technically efficient, and more scale efficient than the conventional DEA estimates suggest. Regarding the efficiency determinants, in terms of ownership, we find that private facilities are less efficient than the public units. Furthermore, the size of the nursing home has a positive effect, and this reinforces our finding that Irish homes produce at increasing returns to scale. Also, notably, we find that a tendency towards quality improvements can lead to poorer technical efficiency performance.     

Benchmarking physician performance, part 2

Part 1 of this article (January-February 2006) reviewed ways of measuring the work of physicians through methods such as data envelopment analysis (DEA) and relative value units (RVUs). These techniques provide insights into: 1. Who are the best-performing physicians? 2. Who are the underperforming physicians? 3. How can underperforming physicians improve? 4. What are the underperformers' performance targets? 5. How do you deal with full- and part-time physicians in a university setting? Part 2 compares the performance of 16 primary care physicians in the same medical specialty using DEA efficiency scores. DEA is capable of modeling multiple criteria and automatically determines the relative weights of each performance measure. This research also provides a preliminary framework for how work measurement and DEA can be used as a basis for a medical team or physician compensation system.     

Technical efficiency of healthcare systems in African countries: An application based on data envelopment analysis

AimThis study aimed to measure the healthcare system efficiency of 36 African countries and to compare efficiency levels between countries.MethodData envelopment analysis (DEA) was used to evaluate efficiency. The input variables employed within the scope of DEA consisted of the proportion of total health expenditures in the gross domestic product (HE); the number of physicians (PHY), nurses (NUR) and hospital beds (BN) per 1000 people; the unemployment rate (UN); and the Gini coefficient (Gini). The study's output variables were life expectancy at birth and 1/(infant mortality rate). After DEA, the variables affecting the performance of national healthcare systems were identified using a Tobit regression model.ResultsAccording to DEA results, 21 (58.33%) of 36 African healthcare systems were found to be efficient. Among the efficient countries, Senegal was the country most referenced for inefficient countries. According to the Tobit regression analysis results, the number of nurses per 1000 people and Gini coefficient variables statistically significantly affected the inefficiency of national healthcare systems.ConclusionThis study's results suggest that in order to achieve the same health outcomes, national healthcare systems need to use public and private health resources more effectively and efficiently. By assessing the efficiency of countries’ healthcare systems and health services through international comparison, effectiveness and efficiency can be ensured within these systems.     

中国卫生资源配置效率DEA和SFA组合分析

目的 应用科学、客观和较全面的评价方法对中国卫生资源配置效率进行研究,为卫生事业管理科学化提供依据。方法 采用数据包络分析和随机前沿分析,分别对2004-2013年间中国卫生资源配置的技术效率和成本效率进行评价分析,找出影响2种效率的因素。结果 2004-2013年,中国卫生资源配置技术效率不断提高,规模报酬趋于稳定,平均技术效率值为0.997,技术有效率为50%;中国卫生资源配置成本效率差异较大,平均成本效率值仅为0.690,有4个自变量（卫生人员数、诊疗人次、入院人数和平均住院日）对总成本具有负影响。结论 政府相关部门应当重视效率测算,合理解决中国卫生资源配置中存在的问题,加强科学化管理。     

Assessing efficiency in the UK breast screening programme: does size of screening unit make a difference?

The UK breast screening programme (UK BSP) is organised into a large number of individual screening units. Decision makers need to ensure these units are producing efficiently, particularly as the programme is anticipated to expand. Data envelopment analysis (DEA) was applied to investigate: the relative efficiency of screening units; the impact of screening unit size on efficiency; and how individual units could improve. Sixty-four screening units were categorised into 33 large and 31 small. Data were collected using a national survey and routinely collected data. The overall median efficiency score was 91%, 39 units were inefficient. Variation in efficiency scores was wide. Large units had a median efficiency score of 100% and 12 units were inefficient. Smaller units had a median efficiency score of 95% and 19 were inefficient. This difference was not statistically significant (Mann-Whitney, P=0.076). Forty-two percent of large units and 21% of small units were operating at constant returns to scale (mean difference 0.20, 95% CI: 0.15-0.43). Although there is no systematic difference in efficiency by size of screening unit there are inefficiencies in both large and small units and there is scope for many individual units to improve their use of current resources. It will be necessary for decision-makers to examine the practices of individual screening units before considering options for how best to improve their resource use. DEA can help to identify feasible options.     

天津市医疗卫生资源配置公平性及效率评价

目的　对天津市2010—2020年医疗卫生资源配置的公平性及效率进行分析评价,为实现配置公平与效率统一提供参考。方法　运用基尼系数、泰尔指数分析公平性,运用数据包络分析评价效率。结果　2010—2020年天津市卫生机构、床位、执业（助理）医师和注册护士的公平性总体较好,但卫生机构的基尼系数上升,注册护士的基尼系数相对较高。医疗卫生资源配置主要表现为区域间差异,卫生机构的组间贡献率高达76.51%。医疗卫生资源配置效率呈现“有效 - 无效”的态势,纯技术效率制约综合效率。结论　通过增量配置和存量优化向环城区和远郊区输送医疗卫生资源。新增床位向老年人口增长较为集中的地区、病床使用率高的卫生机构倾斜。纵向整合医疗卫生资源配置,推动区域定位差异化发展。     

Benchmarking physician performance, Part 1

The performance of 16 primary care physicians in the same medical specialty and university clinic is compared using data envelopment analysis (DEA) efficiency scores. DEA is capable of modeling multiple criteria and automatically determines the relative weights of each performance measure. In this research, the performance measures include physician work relative value units (RVUs) as an input variable and patient satisfaction and total billable charges as the two output variables. The results provide insights into: 1. Who are the best-performing physicians? 2. Who are the underperforming physicians? 3. How can underperforming physicians improve? 4. What are the underperformers' performance targets? 5. How do you deal with full- and part-time physicians in a university setting? This research also provides a preliminary framework for how work measurement and DEA analysis can be used as a basis for a medical team or physician compensation system.