EFFICIENCY MEASURMENT OF PUBLIC SECTOR HOSPITALS IN UTTARAKHAND THROUGH DEA TECHNIQUE

Abstract

Uttarakhand, the 27th state of India, attained its statehood on November 9, 2000. It consists of thirteen districts and is culturally divided into two regions: Garhwal and Kumaon. Out of thirteen districts, two districts namely Haridwar and Udham Singh Nagar are in the plain region and two districts namely Dehradun and Nanital are partially covered by plain areas, while the rest area of the state is fully hilly. A large part of it is hilly and thinly populated where public hospitals are the main source of healthcare services; while in densely populated plain region, people have better access to private healthcare services. On an average, per capita public expenditure on health in Uttarakhand has been higher than the national average, while the reverse is true in the case of per capita private expenditure on health. Since public resources at the disposal of the state government are limited and have competitive uses, it becomes imperative to make their efficient use so that maximum social welfare may be achieved. Uttarakhand has an extensive network of public health institutions. It has 2 women & child welfare centers, 1765 women & child welfare sub-centers, 84 main centers, 250 additional primary health centers (PHCs), 55 community health centers (CHCs), 322 allopathic dispensaries, 39 rural female hospitals, 107 homeopathic dispensaries, 540 ayurvedic hospitals, 5 unani hospitals, 18 tuberculosis hospitals, 24 tehsil/district level post-mortem centers and 36 district / base / combined hospitals [27]. To cater to specific diseases, the State owns 14 T.B. hospitals, 23 blood banks, 3 leprosy hospitals, 9 urban leprosy centers and 7 urban family welfare centers. Only one private medical college and 2 government ayurvedic medical colleges are positioned in the State. However, there exists a wide disparity in the public healthcare infrastructure across districts and regions. For instant, 60% of government hospital beds are situated only in four districts, namely, Pauri, Almora, Dehradun and Nanital. The State also faces a shortage of training institutions and public health management experts. It also suffers from insufficiency of medical and paramedical staff and their willingness to work in the inaccessible areas. Out of total 6143 sanctioned positions of doctors, 1799 are vacant. Public sector hospitals play a significant role in the overall development of a nation’s economy. In the developing countries like India, public hospitals are the backbone of the iv healthcare system. Hospitals efficiency is more difficult to evaluate than manufacturing business efficiency because it is difficult to choose the input-output variables for efficiency evaluation. More sophisticated analytical tools are required to evaluate the efficiency of service sectors, such as, public healthcare sector. Data Envelopment Analysis (DEA) happens to be appropriate for such evaluation. It identifies the best performing decision making units (DMUs) without requiring prior information of input and output prices or specification of the technologies. It can handle multiple inputs and outputs and does not require any assumption of a functional form relating inputs to outputs. Thus, it is well suited for comparative performance analysis of public sector hospitals. Public sector hospitals, which provide un-priced services outside the market mechanism, bristle with the conceptual difficulty of such a precise delimitation of inputs and outputs. The problem becomes more acute in the absence of relevant data pertaining to the inputs and outputs. As such, this difficulty is partially bypassed by some performance measurement techniques which do provide scope for testing alternative input and output definitions using different combinations of inputs and outputs. One approach towards this end has been to examine the performance status of public hospitals on the basis of which policy decisions on the future course of action could be taken. It is in this context that this study applies DEA to measure the technical and scale efficiencies of public hospitals of Uttarakhand with a view to identify inefficient hospitals and input reduction (output augmentation) required to make them efficient. By critical examination of the available literature, it is found that DEA based studies dealing with the relative efficiency of public sector hospitals in India are extremely limited. The present study attempts to assess the performance of the public sector hospitals of Uttarakhand State through this technique. The CCR and BCC models are applied to determine the efficiencies of public sector hospitals. The study also measures the impact of various available background variables on the efficiency using a Tobit regression model. Sensitivity analysis is conducted to identify the outliers on the frontier and verify the robustness of the efficiency scores. Super efficiency models are also applied to rank the efficient hospitals. A non-oriented slack based model (SBM) is also applied to measure the efficiencies of the hospitals. The basic DEA models cannot assess the impact of slacks on efficiency scores. Also the results obtained from these models show that many multipliers have zero value which indicates that the corresponding variables (inputs/outputs) have not been fully utilized in the assessment of v the efficiency scores. To overcome this problem, new slack model (NSM) is applied to the data of 27 public sector hospitals of Uttarakhand. Time series data for the period 2001 to 2011 have been used to assess the growth trends and efficiency patterns of the hospitals. The data are collected from the Directorate of Medical Health and Family Welfare, Government of Uttarakhand, Dehradun for the period from 2001 to 2011. We estimate the production correspondence between three inputs and four outputs, as per the availability of the data. We consider number of beds, number of doctors and number of paramedical staff (PMS) as input variables and number of out-door patients (OPD), number of indoor patients (IPD), number of major surgery and number of minor surgery as output variables for the assessment of productivity and efficiency in the hospitals. The main objectives of the study are to: i. analyse the growth trends and efficiency pattern of the public hospitals; ii. measure the relative efficiencies of the public hospitals of Uttarakhand; iii. measure the effect of several background variables on the performance of the hospitals; iv. identify use of excess input and deficient output for the inefficient hospitals; v. verify the robustness of the efficiencies of the hospitals; vi. measure the super efficiency scores of efficient hospitals; and vii. assess the total factor productivity changes, technical efficiency and technical changes in the hospitals. The chapter-wise summary of the thesis is as follows: Chapter 1 is introductory in nature. It deals with the aspects of performance measurement, statement of the problem, objectives, scope, and limitations of the study. This chapter also discusses briefly about the DEA techniques used to assess the efficiency and productivity. Chapter 2 is devoted to the review of literature on theme. DEA and MPI based studies on the health sectors in India and abroad along with some other relevant studies have been reviewed. Chapter 3 shows the advancement in DEA techniques from the basic models to the new DEA based models. This chapter presents the basic (CCR and BCC) models, AR model, and DEA slack-based models, such as, Additive model, Two-stage model, SBM model, SA model, NSM model, and DEA models with non-discretionary and categorical variables. vi Chapter 4 presents the efficiency evaluation of the public sector hospitals of Uttarakhand. This chapter presents a cross-sectional analysis of the public hospitals of the state for the calendar year 2011. Tobit regression and sensitivity analysis have also been carried out to identify the effect of background variables and robustness of the efficiency scores. Chapter 5 deals with a non-oriented “slack based model” (SBM) of DEA to evaluate the efficiency of hospitals. This model allows managers to work on both inputs and outputs to achieve efficiency. Generally, in case of public hospitals it is difficult to choose the orientation (input or output) for the evaluation of efficiencies. It is not admirable to reduce input levels or increase output levels regarding public sector hospitals. So, in this chapter, a non-oriented and non-radial model known as SBM-DEA model has been used. Chapter 6 deals with a new slack model (NSM) of DEA to evaluate the efficiency with the actual impact of slacks on the efficiency scores. This chapter also presents the super efficiencies of the hospitals and ranks of the efficient hospitals. Chapter 7 deals with theoretical aspects of the Malmquist Productivity Index (MPI) and assesses the total factor productivity (TFP) change, technical efficiency change and technical changes that have taken place in public hospitals for the period 2001 to 2011.. It also examines the reasons of low productivity in the public hospitals. The last chapter presents a summary of findings, conclusions and recommendations for the policy considerations along with some suggestions for the future research.