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CHAPTER 2

A SURVEY OF LITERATURE

2.1 Introduction

This chapter presents a brief survey of literature i.e. the various studies conducted on the

public and the private healthcare sector and on the efficiency of the healthcare sector i.e.

hospitals. Before reviewing the literature, there is a brief discussion on the concept of health

and the health sector and the system of healthcare provision in India. Consequently, the

various studies in the field of public and private health sector in India are highlighted. It is

often argued that healthcare institutions are not expected to be efficient, as they do not adhere

to neo-classical firm optimization behavior. Hence, there is a dearth of literature in India as

far as efficiency of the health sector is concerned. However, given the vast amount of

resources that goes towards funding such institutions, there is a great and growing interest in

examining efficiency in hospitals with the driving force for such concern being value for

money.

Therefore, we try to understand in this chapter the concept of efficiency and its relevance for

the health sector. We try to understand the different concepts of efficiency and review the

literature abroad and in India as far as studies conducted in the field of efficiency in the

health sector using Data Envelopment Analysis (DEA) approach.

Recently, the demand for better quality healthcare services is rising. Accordingly, the medical

costs have increased tremendously, which build a sharp contrast with very limited

government resources and fund that could be allocated to cope with this challenge. Increasing

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healthcare costs has been one of the most hotly debated policy issues in developed and

developing countries in recent years. In many countries, public pressure and executive

interest for cost control have led to various studies of the organizational causes of excess

resource utilization. This has led the governments to seek new approaches to confront these

critical issues as healthcare is important at an individual as well as societal level.

Section 2.2 in the chapter discusses about health and healthcare; section 2.3 gives picture

about the provision of healthcare in India; section 2.4 gives details about the various studies

done on public and private health in India; section 2.5 deals with the concept of efficiency, its

importance, types and demand for efficiency analysis in health; section 2.6 deals with

hospital efficiency, methods of measuring hospital efficiency and Data Envelopment

Analysis Approach to measure efficiency of hospitals and finally, section 2.7 reviews various

studies done abroad and in India on efficiency of healthcare institutions i.e. hospitals and

section 2.8 deals with the summary of this chapter.

2.2 The Concepts of Health and Healthcare

The English word "health" comes from the Old English word hale, meaning "wholeness, a

being whole, sound or well." During the Ottawa Charter for Health Promotion in 1986, the

WHO said that health is: "A resource for everyday life, not the objective of living. Health is a

positive concept emphasizing social and personal resources, as well as physical capacities."

Healthcare is the diagnosis, treatment, and prevention of disease, illness, injury, and other

physical and mental impairments in humans. Healthcare is delivered by practitioners in

medicine, chiropractic, dentistry, nursing, pharmacy, allied health, and other care providers. It

31

refers to the work done in providing primary care, secondary care and tertiary care, as well as

in public health. Access to healthcare varies across countries, groups and individuals, largely

influenced by social and economic conditions as well as the health policies in place.

Primary care is the term for the healthcare services which play a role in the local community.

Secondary care is the healthcare services provided by medical specialists and other health

professionals who generally do not have first contact with patients, for example,

cardiologists, urologists and dermatologists. It includes acute care: necessary treatment for a

short period of time for a brief but serious illness, injury or other health condition, such as in

a hospital emergency department. It also includes skilled attendance during childbirth,

intensive care, and medical imaging services. The "secondary care" is sometimes used

synonymously with "hospital care". However many secondary care providers do not

necessarily work in hospitals, such as psychiatrists, clinical psychologists, occupational

therapists or physiotherapists, and some primary care services are delivered within hospitals.

Depending on the organization and policies of the national health system, patients may be

required to see a primary care provider for a referral before they can access secondary care.

Tertiary care is specialized consultative healthcare, usually for inpatients and on referral from

a primary or secondary health professional, in a facility that has personnel and facilities for

advanced medical investigation and treatment, such as a tertiary referral hospital. Examples

of tertiary care services are cancer management, neurosurgery, cardiac surgery, plastic

surgery, treatment for severe burns, advanced neonatology services, palliative, and other

complex medical and surgical interventions.

According to the World Health Organization (WHO), a well-functioning healthcare system

requires a robust financing mechanism; a well-trained and adequately-paid workforce;

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reliable information on which to base decisions and policies; and well maintained facilities

and logistics to deliver quality medicines and technologies. Healthcare forms a significant

part of a country's economy. Healthcare is conventionally regarded as an important

determinant in promoting the general health and well-being of people around the world. An

example of this is the worldwide eradication of smallpox in 1980—declared by the WHO as

the first disease in human history to be completely eliminated by deliberate healthcare

interventions (WHO, 2010).

Health and healthcare need to be distinguished from each other for no better reason than that

the former is often incorrectly seen as a direct function of the latter. Heath is clearly not the

mere absence of disease. Good Health confers on a person or a group freedom from illness

and the ability to realize one's potential. Health is therefore, best understood as the

indispensable basis for defining a person's sense of well being. The health of population is a

distinct key issue in public policy discourse in every mature society often determining the

deployment of huge society. They include its cultural understanding of ill health and well-

being, extent of socio-economic disparities, reach of health services, quality and costs of care

and current bio-medical understanding about health and illness.

Healthcare covers not merely medical care but also all aspects of preventive care too. Nor can

it be limited to care rendered by or financed out of public expenditure within the government

sector alone but must include incentives and disincentives for self-care and care paid for by

private citizens to the private sector to get over ill health.

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2.3 Provision of Healthcare in India

In, India, provision of healthcare services is complex. It is provided mainly by the public and

private sector. The public sector provides health services through the central government,

state governments, municipal corporations and other local bodies. The private health sector

consists of the 'not-for-profit' and ‗for-profit' health sector.

Historically the Indian commitment to health development has been guided by two principles.

The first principle was state responsibility for healthcare and the second (after independence)

was free medical care for all (and not merely to those unable to pay). However, the state

failed in its responsibilities on the basis of both the principles which had the following

repercussions.

The first set of consequences was inadequate priority to public health, poor investment in

safe water and sanitation and to the neglect of the key role of personal hygiene in good

health, culminating in the persistence of diseases like Cholera.

The second set of consequences pertains to substantially unrealized goals of National Health

Policy (NHP) 1983 due to funding difficulties from compression of public expenditures and

from organizational inadequacies. The ambitious and far reaching National Population Policy

(NPP) 2000 goals and strategies have however been formulated on that edifice in the hope

that the gaps and the inadequacies of NHP 1983 would be removed by purposeful action.

Without being too defensive or critical about its past failures, the rural health structure should

be strengthened and funded and managed efficiently in all States by 2005. This can trigger

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many changes over the next twenty years in neglected aspects or rural health and of

vulnerable segments.

The third set of consequences appears to be the inability to develop and integrate plural

systems of medicine and the failure to assign practical roles to the private sector and to assign

public duties for private professionals.

To set right these gaps there is a need to redefine the state's role keeping the focus on equity.

But, during the last decade there has been an abrupt switch to market based governance styles

and much influential advocacy to reduce the state role in health in order to enforce overall

compression of public expenditure and reduce fiscal deficits. People have therefore, been

forced to switch between weak public services and expensive private provision or at the limit

forego care entirely except in life threatening situations, in such cases sliding into

indebtedness.

Health status of any population is not only the record of mortality and its morbidity profile.

But, it is also a record of its resilience based on mutual solidarity and indigenous traditions of

self-care - assets normally invisible to the planner and the professional. Such resilience can

be enriched with the state retaining a strategic directional role for the good health of all its

citizens in accordance with the constitutional mandate. However, due to the weakness of the

public sector it has been overridden by the private sector in recent times.

The private sector involvement over the last several decades has become widespread. But, it

has remained stubbornly urban with polyclinics, nursing homes and hospitals proliferating

often through doctor entrepreneurs. Standards in some of the mushrooming private hospitals

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are truly world class. But, given the commodification of medical care as part of business

plans it has not been possible to regulate the quality, accountability and fairness in care

through criteria for accreditation, accountable record keeping etc. (Srinivasan, 2004).

Thus, in the absence of a state- funded health infrastructure providing free care, citizens have

no option but to seek out private facilities. As a result, we have a burgeoning private

healthcare sector, unregulated and often exploitative (Ananthakrishnan, 2008). Therefore, it is

imperative to undertake a review of various studies done on public as well as private sector in

health to understand the twin sectors in an empirical way.

2.4 Various Studies Done on the Public and the Private Healthcare in India

Mahapatra and Berman conducted two studies based on secondary data of 108 secondary

level public hospitals in Andhra Pradesh. The first study looked at the utilization and

productivity, the second study dealt with the performance service-mix ratios (Mahapatra and

Berman 1990 and 1992).

Kakade, Narendra‘s (1998) study explores the distribution of health services in the urban

slums of Bombay. The findings of the study are that there is an overall decrease in the

expenditure on health by Bombay Municipal Corporation (BMC). The major part of the

expenditure is on big hospitals i.e. teaching hospitals rather than dispensaries and healthcare

centers. Of this, a large proportion is spent on establishment than on diet or other equipments

for patients. BMC pays more attention to the curative services than preventive care.

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The sharp growth of the private health sector towards the end of the sixties was prompted by

several factors: the falling state-spending for health, the increasing number of medical

personnel who could not find adequate employment in the health institutions, a growing

middle class dissatisfaction with public sector and willingness to pay to the private sector.

The poor and middle class people who are the major public hospital users also show a

preference for private providers in the first instance and come to public hospital only when

their conditions get serious or their finances are low. Therefore, they accept whatever care

they get. On one side inadequate public health facilities and on other side sickness and

disease make them resort to the private sector with no other alternative left. This leads to the

dubious money making practices of private hospitals like-unnecessary investigations and

irrational therapies. Even though there is not much pressure on the public hospitals to be

quality conscious, this aspect has to be stressed or else, they will be overtaken by the private

sector. The public systems work in an inefficient manner thereby making people resort to

private clinics. Right from the time a patient queues up for registration as an outpatient or an

in-patient, to getting a bed and other diagnostic facilities, medical attention etc., a huge

investment of time and money is needed which is unaffordable for the poor.

In Mumbai city in Maharashtra, in spite of having better healthcare services as compared to

rest of the country, residents of Mumbai do not have proper access to healthcare services as

32% of the ailments remain untreated (Nandraj, etal, 2001). A sizeable proportion of

deliveries are still home deliveries (NFHS-II-9%; RCH survey-7%). All these surveys show

that the public health sector in Mumbai was providing healthcare to less than 20% of the

population. Inconvenient location and timing were cited as the main reasons for not utilizing

these services (CORT, 2000; Nandraj, etal, 2001).

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While the public health infrastructure is not so impressive, there are weaknesses in its

provision of facilities for mothers and infants and the special needs of newborn babies are

also not adequately recognized or addressed. Several interrelated factors are responsible for

this weakness. Tertiary hospitals tend to be overburdened as sources of routine prenatal and

delivery care, maternity homes specifically oriented to the management of routine deliveries

are underused; there is limited or no provision of prenatal and postnatal care at health posts,

inter-sectoral linkages are weak and patterns of referral between institutions have not yet

been systematized, there is lack of standardization of clinical and administrative protocols,

particularly in terms of coherence across a range of health care institutions, case provider

efficiency and morale are low and the coverage of home-based care and home visit systems

for the vulnerable new born is poor (Fernandez and Osrin, 2006).

As per estimates, hospitalization rates in private sector in urban and rural India are higher at

62% and 58% respectively (NSSO, 2006). Empirical evidence has been suggestive of failure

of public sector as one of the prime reasons for growth of the private sector in India

(Chatterjee, 2008).

Therefore, people turn to the private sector. A number of studies have been conducted on the

private healthcare sector.

To examine the utilization pattern in the healthcare a number of studies are done by

organizations such as National Sample Survey Organization (NSSO), Foundation for

Research in Community Health (FRCH), Kerala Shastra Sahitya Parishad (KSSP) and

National Council of Applied Economic Research (NCAER).

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These studies have revealed that around 60 to 80 percent of people utilize private health

facilities in the country in both rural and urban areas1.

Medico Friend Circle conducted a public survey in Mumbai to understand patient‘s

experiences views and perceptions of the private health care system. The findings bring out

various aspects of the private practitioners functioning in terms of waiting period, treatment

provided, reasonability of charges, among others (Medico Friend Circle, 1990).

Another Study on ―Improving the Performance of Reference Health Centre‖, a case study of

Urban Health Centre (UHC), Dharavi, Bombay (1991) was undertaken by Department of

Health Studies. The findings showed that overall utilization of UHC was low for all services

as people preferred to use private services of healthcare.

A study was conducted on private hospitals and nursing homes (Nandraj, 1992) to find out

the conditions of private nursing homes/ hospitals in the city of Bombay to find out the

functioning of private nursing homes/hospitals. The nursing homes/hospitals were selected on

a random sample basis from each of the wards in the Eastern zone of Bombay.

The study found that fifty percent of the nursing homes are either in a poorly maintained

building or they are in dilapidated condition. A seventh of them are run from sheds or left in

slums.

__________________________________________________________________________________________________

1These studies are NSSO, 1987, Duggal, R. Amin, S. 1989, Kannan, K. P., etal, 1991, NCAER, 1992, George, A, etal.

39

Most of the nursing homes are congested, lack adequate space. The passages are congested,

and entrances are narrow and crowded. Seventy-seven percent do not have scrubbing rooms.

Less than a third has qualified nurses. Seventy-seven percent of the nursing homes that have

an Operation Theatre did not have a sterilization room while 66.7% did not have a generator.

None of the nursing homes incinerate infectious waste material but instead dump it in

municipal bins. None of them keep proper records of diseases.

A study was conducted in urban and rural Rajasthan (Cedric and Misra, 1993) to study the

utilization, regulation, costs and quality in private hospitals in Rajasthan. The study area

covered five districts of Rajasthan; they were Jaipur, Jodhpur, Udaipur, Ajmer and Bharatpur.

The 5 districts cover around 60% of the total private hospitals in Rajasthan. A general survey

was conducted in the 5 districts to assess the profile of different hospitals. A total of 25

hospitals with a single facility and some hospitals with less than 20 indoor beds were selected

as the sample. One interview schedule was used to assess the profiles of hospitals and a

second schedule was used to interview the patients and their attendants. This schedule was

designed to collect information about the socio-economic background of the patient,

treatment cost, perception of the respondent about healthcare services and other related

information.

The study brought out the following facts-

A total of 313 patients were surveyed. Of these, three fourths of the patients belonged to the

poor economic strata. Around 48.28% of the patients accounted for malaria and 24.14% for

tuberculosis. The main reason they went to the private hospital was the better healthcare

services there and non-availability of government health services. It showed that 29.71% of

the respondents found the services provided by the private hospitals to be good. It was found

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that 74.1% visited the private hospital directly to receive healthcare services. Only 21.7%

were found to go to the public hospitals.

People were not fully convinced or satisfied with the fees charged by the private healthcare

services. They found the charges to be high and irrational. Around 44.73% found the charges

reasonable, 29.71% found it comparatively high and 14.70% very high. They also felt that

unnecessary surgery and tests were on the rise because of which patients had to borrow and

take loans. Around 47.28% borrowed money for their treatment, 10.86% took loans. This

shows that the major proportion of patients belong to the poor economic strata.

Through this study it becomes clear that the private health sector is more accessible and

popular even with those who cannot afford it. However, it is found that the private health

sector in its present unregulated form does not favor the low-income groups since they suffer

from a heavy economic burden due to high treatment costs. The reason the poor are forced to

go to the private hospitals is the non-availability of government medical services, better

quality of services and easy access. Unless certain minimum reforms are undertaken to ensure

good service by the government, the poor will be forced to go to the private hospitals and get

exploited, thus leading to the increase in their economic burden.

A listing of heath establishments and practitioners in Ahmednagar district, Maharashtra, was

done by Foundation for Research in Community Health (FRCH) in 1993.This study

identified a total of 3060 doctors in the district belonging to all systems of medicines and

92% of them were found to be practicing in the private sector (including a very small

percentage in the voluntary sector). Of the total doctors identified 51% were in urban areas

and the rest in rural areas.

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Nanda and Baru (1993) conducted a study to know the trends, characteristics and services

offered by the private medical sector in Delhi. This study provides insights into the

heterogeneity in provisioning of services and plurality in utilization patterns. The

heterogeneity and haphazard growth of the private sector clearly points to the need for some

planning, which would include registration and regulation.

Another study was conducted in rural Maharashtra (Nandraj and Duggal,1997) that focused

on the physical standards of Nursing Homes (NHs) and Hospitals. For this a socio-

economically average district (as per the CMIE index), Satara, was thus selected. A sample of

53 medical practitioners and 49 NHs/hospitals was drawn from the underdeveloped Patan and

the highly developed Karad tehsils. The tools used were a structured interview schedule along

with an observation schedule and a checklist for equipment. The study revealed the following

facts:

The Medical Practitioners:

One-fourth of practitioners are unqualified. Amongst the qualified, only 40% are

allopaths while 52.5% are from Indian Systems and 7.5% practice homeopathy. Yet

79% of all practitioners in the sample were found practicing allopathy.

62% of all practitioners kept no medical record of their patients. 38% kept some

record that consisted mostly of medicines administered and charges to be recovered

from patients. Thus, instead of being an actual medical record, it was more of a trade

or a business record! Fittingly, such record is maintained in diaries and notebooks

rather than on the medical record sheets.

The study also found that much of the basic medical equipment was conspicuous by

their absence in the clinic of many practitioners.

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The hospitals and nursing homes:

Over 80% of them were established in the 1980s and 1990s. 91.8% of them were

individual proprietorships. 80% of hospitals were run by doctor-owners and without

assistance from any other doctor. Average bed strength was 11.

More than 90% doctors running hospitals were males.

Only 71.5% of doctors owning hospitals were trained in allopathy.

Only three qualified nurses were found in 49 hospitals studied. Unqualified women,

who were paid very low salaries, made up for the rest of the nursing staff.

Almost all of the hospitals and nursing homes provided general medical care. In

addition, 55% provided maternity and gynecological services and 16% general

surgery. Only 2% of hospitals were treating emergency cases and only 18% had

facility for pathological examination.

None of these hospitals were registered with any health authority.

A quarter of them had uninterrupted power supply and of them, 24% had installed a

generator. Only three fourths of them had a telephone and none had an ambulance.

In only 28%, the area of consulting room was adequate. In 65%, there was no screen,

curtain, or a separate room for examination of patients. A wash basin with tap was

available in 59% of the hospitals, and of these in 49% there was no water available in

the wash basin.

In only 6% of the hospitals, the space per bed was adequate. The bed sheets and

pillows were found to be dirty, in more than 50% of the hospitals,

Most of them 71% had an Operation Theatre (OT), but only 11% of them had an

adequate area. 39% had a shadow-less lamp, 10% had Electrocardiography (ECG)

facility and only 65% had sterilizer.

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In those providing obstetrics and gynecological services, nearly a quarter did not have

basic equipment. 52% had an oxygen cylinder, 74% had a delivery table and 81% had

a suction machine.

In those providing surgical services, 39% had an X-ray machine, 56% had an oxygen

cylinder, 39% had an electro-coterie unit and none had a boyle‘s apparatus.

The study shows that the perception of high quality healthcare in private sector is a fallacy, at

least in terms of the physical and medical standards. It also makes a strong case for regulating

the private sector for improving standards.

Another study by Bhat (1999) indicated that most of the state governments face the problem

of shrinking budgetary support and thus find it difficult to provide and expand health

facilities and thus cater to the health needs of the people. To overcome this problem, several

state governments are trying to involve private sector in public healthcare activities and to

work jointly. This is done in the hope that private sector involvement would bring investment

into the health sector and would provide health services to the people. The study however,

concludes that in our country, the public-private initiatives are in a premature state.

In another study, conducted in the city of Mumbai (Duggal, 2004), reasons for preference of

private sector facility included proximity, quality of care and convenient timing.

Affordability was a leading factor for selection of public healthcare facility. However, on

internal comparison of the data elicited that, 64.5% of users of private sector hospitals

considered them affordable, while only 10.8% of the users of public healthcare facilities,

considered public sector hospitals affordable.

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With private sector omnipresent across urban and rural India, it continues to be preferred

compared to the public sector (National Commission on Macroeconomics and Health, 2004).

Further, as per the report of the NCMH, the cost of care in private sector is about 2.2 to 24.3

times higher but still it continues to be preferred, indicating the affordability is secondary to

accessibility and availability.

In a study to understand health seeking behavior of semi-urban population (Patel, etal, 2010),

it was observed that 62% of the households preferred private healthcare facility. The reasons

for avoiding government facility, though the services were free of cost included long waiting

time, facility located at a distance, inadequate facilities, unclean premises, harsh behavior of

the staff and low faith in government doctors. Among those preferring public sector hospitals,

the leading reasons include free availability services (73.33%) and close location of facilities

(68.33%). Interestingly, quality of medical care is not considered to be the criterion for

selection of public or private sector facilities.

Another study (Pinto and Udwadia, 2010) cited reasons like poor quality with a general lack

of trust in government services, lack of attention offered to patients, long waits, poor hygiene,

suspected quality of drugs and lack of privacy, for non preference of public sector hospital.

Only a nominal portion (3%) considered free services as a reason for preference of public

sector.

A study on private health sector in Maharashtra on private hospitals emphasize on the need

for maintenance of standards in private hospitals and the awareness of private health

providers regarding Bombay Nursing Home Registration Act (BNHRA) and accreditation

aspects ( Bhate-Deosthali and Khatri, 2011).

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As one can observe from the above studies, that in India, especially in the urban areas, the

private health sector is perhaps the dominant player. Therefore, it is all the more relevant to

assess its efficiency. Since there no studies conducted till date, on examining the efficiency of

private hospitals we make an attempt to study efficiency of private hospitals in Mumbai by

taking a sample of hospitals from different municipal zones of Mumbai. To begin with, let us

first try to define the concept of efficiency, analyze the importance and types of efficiency,

and look at why efficiency measurement is important, what are the various methods to

measure efficiency and why this research has used non- parametric approach to measure

efficiency.

2.5 What is Efficiency and Why is it Important?

Efficiency is defined as the ratio of outputs to the resources (inputs) used. One way to

increase efficiency is to decrease the level of resources (inputs) and investments and/or

increase the production (output). However, healthcare is a sector in which human factor is the

most critical issue.

Efficiency has been the subject of research in a wide range of production activity. It is

expressed as a percentage which can be calculated as the ratio of total output to total input

under specified conditions. Efficiency analysis has always been linked to the relative

difficulty encountered in assessing the performance of Decision-Making Units (DMUs) to

find its weakness so that subsequent improvements can be made.

Thus, efficiency which could be related to the performance of the processes is one of the

main concerns of the organizations. It is therefore, important to measure and perform

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continuous improvement in the efficiency of the processes. This is also valid for the health

services as in all others.

In today‘s dynamic and rapidly changing socio-economic conditions, all institutions have to

search and find ways for continuous improvement. As a service business, healthcare

institutions have followed the similar goals with other organizations for achieving

performance improvements. In recent years, efficiency has been one of the most important

issues for hospitals which used limited resources for maximum value (Chu, etal, 2003).

The World Health Report 2000 called attention to the importance of efficiency in all

functions of a health system and in ultimately achieving the goals of health improvement,

responsiveness and fairness in financing. Technical efficiency refers to the extent that

resources are being wasted. It measures the degree of producing the maximum amount of

outputs from a given amount of inputs or, conversely, using the minimum amount of inputs to

produce a given output. Examples of inefficiencies are excessive hospital length of stay,

over-prescribing, over-staffing, over-use of branded generic drugs and wastage of stock. It

has thus, been analogized to a ―torn rice sack‖ as resources are wasted due to inefficiencies in

the system. Measurement of efficiency is especially relevant in settings constrained by scarce

resources given the recent economic downturn and escalating healthcare costs; it allows a

system to produce more and better in terms of both quality and quantity.

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2.5.1 Macro Efficiency and Micro Efficiency in Healthcare

A micro-system in healthcare delivery can be defined as a small group of people who work

together on a regular basis to provide care to discrete subpopulations of patients. It has

clinical and business aims, linked processes, and shared information environment and

produces performance outcomes. They evolve over time and are (often) embedded in larger

organizations. Microsystems are the building blocks that come together to form Macro-

organizations (Huber, 2006). Finally, the community, market and the social policy system

impact healthcare and provide systems of care. It is necessary to promote efficiency, both

from macro and micro perspectives, to provide necessary and proper healthcare and to ensure

sustainability of the system.

Below, we discuss how to realize macro efficiency that achieves an appropriate level of

medical expenses, how to curb the growth of total medical expenses, and how to improve

micro efficiency, which is efficiency of resource allocation. The former imposes budgetary

constraints on the entire healthcare system, while the latter demands optimization of the

allocation of medical resources under such constraints. It is worth emphasizing that these are

complementary to each other; efficient resource distribution facilitates management of the

total medical expenses. It goes without saying that in addition to efficiency, fairness is

essential. Fairness includes a fair cost burden as well as fair access to healthcare.

Thus, from the above we can conclude that individual levels of promoting health are

commonly referred to as micro perspective whereas those community-based efforts are

known as macro issues that relate to changing social support and community norms or laws

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to positively affect health. To best serve the health of citizens, a combination of both micro

and macro efforts must be used ( Evans, etal, 2008).

In the context of the healthcare system, a distinction is made between micro efficiency and

macro efficiency. The former represents the realization of technical efficiency (the maximum

production with the prescribed inputs). The shortage of socially important medical services,

such as the shortage of doctors is an issue that must be remedied by an improvement in micro

efficiency.

On the other hand, macro efficiency strives for appropriateness of the overall level of medical

expenses in relation to an economic scale (the GDP) and its sustainability (a long-term

balance between fiscal revenue and expenditure). It represents allocative efficiency

(allocation of resources according to needs and minimization of expenses), within the

framework of the prescribed constraints of resources (the total medical expenses available).

As long as the market mechanism functions ideally, the choices made by each economic unit,

such as households or enterprises at a micro level, and the allocation of resources, quantity of

production and consumption within the price mechanism, should be at an appropriate scale,

and therefore sustainable (feasible), from a macro economy perspective. However,

information available to medical institutions and insurers/insured (patients) is asymmetrical.

In these circumstances of a divergence between benefits and burden, there is no guarantee

that total medical expenses are sufficient to meet the needs of citizens. This is because

asymmetrical information is likely to boost physician-induced demands and a disparity

between benefits and burden may induce patients to get over-treated; which is better known

as the problem of moral hazard in Economics.

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Some consider that if the government behaves rationally and with a long-term perspective, it

would be trying to autonomously curb the total amount of healthcare benefits. To make the

healthcare system sustainable and meet the tight constraints in the government‘s budget,

including social security funds, management of the aggregate amount is not necessary in

principle. However, the government cannot, in reality, be that rational and it has no

knowledge, in advance, of the means of achieving an appropriate level of medical expenses.

As a matter of course, the scale of resources that the economy should invest as a whole into

healthcare services, being the ratio of appropriate medical expenses to GDP will entail a

value judgment and require social consensus. Such asymmetric information can be corrected

by-

1. Promoting information disclosure which will enable actual medical services to be

compared with standard medical services. It is, however, difficult for individual patients to

collect and analyze information on medical practice that requires advanced professional

knowledge. It is for this reason that an insurer‘s monitoring ability as an agent of the insured

needs to be strengthened.

2. Decentralization that provides medical institutions, insurers and local governments with

authority to distribute medical resources, so as to meet the needs of regions and patients, will

contribute to an improvement in micro efficiency. This is because decentralization allows

various insurers and local governments to discover the best measures by experimenting with,

and making a comparative assessment of, various policies, including specialization of

functions and cooperation among medical institutions, health promotion, medical fee

schedules, evaluation methods of medical institutions, etc.(Motohiro Sato,2008).

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Micro-efficient allocation of medical resources cannot be planned by the state or by

bureaucracy. It is necessary to use a trial-and-error approach to improve micro efficiency, but

macro efficiency is not necessarily guaranteed in its course. To take an example, let us

suppose the case of the governments adopting a policy to promote competition among

medical institutions. In this case, if physician-induced demands are aroused or competition in

quality, not price, i.e. the purchase of expensive medical equipment such as Magnetic

Resonance Imaging (MRI), occurs in circumstances where asymmetry of information

remains uncorrected, medical expenses may even increase. Demands for medical services do

not necessarily reflect the proper needs of the public. In a scenario where finances of the state

and local governments investing public funds in the medical service are declining,

management of total medical expenses (management of the ratio of public medical expenses

to GDP, or management of the growth rate, etc.) from a macro perspective, is the second-best

measure to ensure sustainability of the system and equity between generations {OECD

(1995), Schutz and Van de Ven (2005)}.

The economic reforms process that was set in motion in India since 1991 changed the entire

health scenario. As a part of the policy reforms process, role of the state is likely to reduce in

many investment areas including health. However, health being part of the social sectors of

the economy may have its own public good characteristics; making it necessary to move in

this direction in a calibrated way. Also a number of questions are being raised like: Have the

people of the country accepted privatization in the healthcare sector? In terms of affordability

and acceptability, is the private medical care a good substitute for the public health care

management? These are the issues to be tackled with and therefore it becomes inevitable to

understand the health sector efficiency in India (Kadekodi, etal, 2009).

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2.5.2 Types of Efficiency

Efficiency is the success of the hospital in using its resources to produce output. The recent

history of microeconomic efficiency began in 1950 with Koopmans, who was the first to

formally define technical efficiency. Debru (1951) first measured efficiency whereas Farrell

(1957) defined a simple measure of firm efficiency that could account for multiple inputs

within the context of technical, allocative (price) and overall (productive) efficiency. Farrell's

definition of the efficient firm is "its success in producing as large as possible an output from

a given set of inputs." Farrell introduces the efficient production function as a special case of

the traditional (Paretian) production function, defined as "the output that a perfectly efficient

firm could obtain from any given combination of inputs."

Farrell distinguishes between technical, price and overall (productive) efficiency. Technical

efficiency is defined as a firm's success in producing maximum output from a given set of

inputs, i.e., producing on the "technical frontier." Price efficiency is defined as the firm's

success in choosing an optimal set of inputs, i.e., the set that would minimize cost if the firm

were producing on the technical frontier. Overall efficiency (commonly known as productive

efficiency) is the product of price and technical efficiency. Technical and price inefficiency

each imply overall inefficiency as defined by Farrell .

Farrell's definition of productive efficiency was inspired by Koopmans' work on "activity

analysis," and his measure of technical efficiency is similar to Debreu's "coefficient of

resource utilization." The novelty of Farrell's approach is that his efficiency measure

explicitly allows the inclusion of multiple inputs and outputs, whereas previous work (e.g.,

52

index numbers) was often limited to single inputs or outputs (e.g., the average productivity of

labor).

The figure below shows the classic framework by Farrell which makes it possible to

decompose overall efficiency into technical and allocative (price) efficiency. Consider the

case of a simple output (Y) that is produced by using two inputs (X1, X2). Under the

assumption that the production function Y = f (X1, X2) is linearly homogeneous, the efficient

unit isoquant, Y=1, shows all technically efficient combinations. In the figure, P represents a

firm, hospital, etc., that also produces at Y=1, but uses higher levels of inputs, and is

therefore less efficient in a technical sense. The magnitude of the technical efficiency can be

expressed as the ratio between optimal and actual resource use (OR/OP). By taking into

account the iso cost line (representing relative factor prices), we can identify allocative

efficiency. Any point on the line Y=1 has technical efficiency, but only Q receives technical

efficiency at minimum cost. Allocative (price) efficiency can be expressed as the ratio

between minimum and actual cost (OS/OR), and overall efficiency is the product of technical

and allocative efficiency.

53

FIGURE 2.1: TECHNICAL, ALLOCATIVE AND OVERALL EFFICIENCY

Source: Farrell MJ, 1957.

Yet another classification on efficiency given by economists discusses; Pareto efficiency,

Kaldor-Hicks efficiency and X efficiency. Pareto efficiency and Kaldor-Hicks efficiency are

more philosophical concepts.

The term ‗Pareto efficiency‘ is named after Vilfredo Pareto, an Italian statistician and

economist who used this term in his research of income distribution and economic efficiency.

Given an alternative allocation for individuals, an allocation shift from one individual to

another can make the former better without worsening the later. This is often called a Pareto

optimization or Pareto improvement.

54

The Kaldor-Hicks efficiency, named after Nickolas Kaldor and John Hicks, is another

concept of economic efficiency that starts as an explanation of the limitation of unrealistic

Pareto efficiency. Kaldor and Hicks‘s concept of efficiency is more applicable to normal

environment with less restricted criteria.

X-efficiency, in contrast, is a more practical and measurable concept. For example,

Leibenstein‘s X-efficiency means that if a company produces the maximum output, given

available input resources such as workers, and machinery and technology, it is called X-

efficiency.

2.5.3 The Demand for Efficiency Analysis in Healthcare

The demand for healthcare is likely to occur unexpectedly. Healthcare purchasers have a

serious information difficulty when negotiating contracts with providers. Efficiency analysis

can therefore help purchasers to understand better the performance of their local providers

relative to best practice, and introduces an element of ‗yardstick competition‘ into the

purchasing function (Schleifer, 1985). Likewise, even in non-competitive healthcare systems,

providers have a natural interest in seeking out best practice and identifying scope for

improvement.

The international explosion of interest in measuring the inputs, activities and outcomes of

health systems can be attributed to heightened concerns with the costs of health care,

increased demands for public accountability and improved capabilities for measuring

performance (Smith, 2002). Broadly speaking the policy maker‘s notion of efficiency can be

thought of as the extent to which objectives are achieved in relation to the resources

55

consumed. There might also be some consideration of external circumstances that affect the

ability of the system to achieve its objectives. This beguilingly simple notion of efficiency is

analogous to the economist‘s concept of cost-effectiveness or the accountant‘s concept of

value for money. The potential consumers for measures of efficiency include governments,

regulators, healthcare purchasers, healthcare providers and the general public.

Finally, there are increasing demands for offering the general public reliable information

about the performance of its national and local health systems, and of individual providers

(Atkinson, 2005).

There are numerous conceptual and practical issues to be clarified when seeking to

understand an empirical analysis of efficiency in healthcare. To clarify the concept once

again, an organization‘s efficiency is considered to be the ratio of the value of outputs it

produces to the value of inputs it consumes. The figure 2.2 summarizes the principles

underlying this view point.

FIGURE 2.2: THE NAIVE MODEL OF ORGANIZATIONAL PERFORMANCE

Source: Jacobs R, 2006.

Output-1 Input-1

Health

Care

Organization

Benefits

X

Output-2 Costs

X

Input-2

Output-3 Input-3

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In competitive industries the physical output of the organization is usually a traded product.

However, defining the outputs of the healthcare sector is particularly challenging. Health is a

complex concept for which there has been no readily available valuation, and there is no

market for health in the conventional sense. In the context of efficiency analysis, two

fundamental issues need to be considered. How should the outputs of the healthcare sector be

defined? And what value should be attached to these outputs?

Defining outputs of the health sector is problematic because healthcare is rarely demanded

for its own sake. Rather demand derives from the belief that healthcare outputs should

properly be defined in terms of the health outcomes produced. However, rarely do

organizations collect routine information about what health outcomes they produce. More

commonly the analyst is forced to rely on comparing healthcare organizations in terms of the

quantity and type of activities they undertake.

The input side of efficiency analysis is usually considered less problematic than the output

side. Physical inputs can often be measured more accurately than outputs, or can be

summarized in the form of a measure of costs. The efficiency model then becomes a cost

function. However, a single measure of costs takes a long term perspective considering that

organizations can freely adopt an optimal mix of capital and labor. It may also be important

to consider a short-term perspective in which certain aspects of the input mix are considered

beyond the control of the organization. In this case, it is necessary to disaggregate the inputs

to some extent in order to capture the different input mixes that organizations have inherited.

In particular, disaggregation of labor and capital may be required.

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Labor inputs:

They can usually be measured with some degree of accuracy, often disaggregated by skill

level. Labor inputs are measured in either physical units (hours of labor) or costs of labor. In

certain circumstances, the analyst may need to resort to a single measure of inputs, in the

form of total costs.

Capital inputs:

Incorporating measures of capital into the efficiency analysis is more challenging. Measures

of capital are often very rudimentary, and even misleading. For example, accounting

measures of the depreciation of the physical stock usually offer little meaningful indication of

capital consumed.

Indeed, in practice, analysts may have to resort to very crude measures; for example, the

number of hospital beds or floor space as a proxy for physical capital. Besides, a central issue

in the treatment of capital is the extent to which short run or long run efficiency is under

scrutiny. In the short run, it makes sense for organizations to make full use of the

infrastructure investments. So, for example, short run efficiency should be judged in the light

of the capital configuration that a hospital has available. Yet, in the longer run one might

expect the hospital to reconfigure its capital resources when this can bring about efficiency

improvements.

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2.6 The Concept of Hospital Efficiency and the Need to Focus on Measuring Hospital

Efficiency

In the Farrell (1957) framework, a hospital is judged to be technically efficient if it is

operating on the best practice production frontier in its hospital industry. In the original

Farrell framework, the entire observations on given sample is assumed to have access to same

technology.

Efficiency measurement represents a first step towards the evaluation of a well-coordinated

healthcare system, and constitutes one of the basic means of audit for the rational distribution

of human and economic resources. Over the past two decades, efficiency measurement has

been one of the most intensely explored areas of health services research. The measurement

of efficiency in the health sector is complicated by the nature of production process.

Measurement of the ideal output-improved health status-is difficult, both conceptually and

empirically (Grosskopf and Valdmanis, 1987). Complications arise from the fact that health

status is a function of many variables, many of which are exogenous to the health sector-for

example household income, education, and intra-household decisions.

Magnussen (1996) stated that measuring technical efficiency allows us to compare hospitals

in terms of their real use of inputs and outputs rather than costs or profits. A hospital is said to

be technically efficient if an increase in an output requires a decrease in at least one other

output, or an increase in at least one input. Alternatively, a reduction in any input must

require an increase in at least one other input or a decrease in at least one output. On the other

hand, allocative efficiency occurs when inputs or outputs are put to their best possible uses in

the economy so that no further gains in output or welfare are possible.

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To measure hospital‘s efficiency, the hospital‘s output(s) must be identified. There are many

potential measurements for a hospital‘s outputs such as number of cases treated, number of

procedures performed, and number of patient days, bed turnover, and bed occupancy, among

others. A single output or combination of outputs can be used depending on the objectives of

the hospital and on the level of measurement activities.

Problems of hospital efficiency are faced by all groups of countries: high and middle income

countries; Eastern Europe and the Former Soviet Union (FSU); and low income countries.

Although they have obvious differences there are also considerable similarities in the

problems they face and the solutions to them.

The differences reflect not only per capita health expenditure and variations in disease burden

but include cultural and historical influences on funding and services delivery. The

similarities, and hence the ability to look internationally for solutions to problems, are:

the continuing imbalance between resources (especially finance) and demand –

whatever the per capita spend - fuelled by population size and age, new technology

and greater public expectations;

the need to shift limited resources to more cost effective interventions in the

ambulatory care or primary care settings;

changes in medical technology which mean that patients typically stay a shorter time

in hospital, and hence that throughput per bed can increase and

Above all, the realization that within the hospital sector there are enormous efficiency

gains to be made, which would allow considerable increases in both the quality and

quantity of service delivery for the same or less expenditure.

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‗Hospital‘ is an economic institution with a social role in the community. The hospitals in the

healthcare system have fundamentally altered over the years. It has received attention due to

the central role played in the healthcare system. It has not only continued to concentrate on

human, technical and physical capital but has also consumed a major proportion of healthcare

budgets in many countries. For example, spending on hospital services to the total health

expenditure of 13 OECD countries range from the highest of 67.6 percent of Norway to the

lowest of 29.8 percent of Poland in 2001 (OECD, 2004). A high income or a good education

yield little satisfaction to the chronically sick. And, at the extreme, ill health that leads to

death will make all other sources of satisfaction irrelevant. It is not surprising therefore, that

throughout the world considerable resources have been devoted to the maintenance and

preservation of health.

Cost of providing healthcare services is very important under the scarce resources of health

sector in developing countries like India. The national average expenditure on hospital and

dispensaries was around 43.99 percent (1950/51) in India to 15.76 percent (2003/04) which

shows there has been considerable reduction in state expenditure for health. Hence, there is a

need to analyze whether the share of health sector resources used by the hospitals are

economically efficient. Kirigia, etal, (2008) state that in the context of hospitals, efficiency

means providing maximum services out of obtainable resources or minimizing the use of

available resources to produce a given level of services.

In recent times, there is growing importance towards the private healthcare providers in India

(Bhatt, 1993; Mathiyazhagan, 2003).This trend has brought into the forefront to analyze the

performance of hospitals since state expenditures on health are declining consistently.

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2.6.1 Methods of Measuring Efficiency of Hospitals

In recent years efficiency has become one of the most attractive work areas of healthcare

management literature. Some authors argue that hospitals are profit organizations while some

others do not agree with them (White and Ozcan, 1996). Hospitals whether are economic

organizations or not (Ferrier and Valdmanis, 2004), have limited resources to gain maximum

value like all other organizations (Watcharasriroj and Tang, 2004).

Studies on efficiency mostly focus on the issue of maximum gain with limited resources

(Sorkis and Talloru, 2002).One of the frequently raised issues on these studies is the efficient

use of resources and controlling the costs. Thus, the interest on hospital efficiency has

increased because of the desire to control the increasing costs. Accordingly, hospital

resources and their processes became critical and, as a result, the number of studies done on

the hospital sector has increased in recent years.

Regression analysis, ratio analysis and non-parametric techniques were applied to analyze

hospital efficiency in the previous studies (Ferrari and Valdmanis, 2004). In recent times,

Data Envelopment Analysis (DEA) technique is popular in evaluating hospital efficiency

because it is applicable to the multiple input-output that is essential for the nature of a

healthcare system (Hollingsworth, etal, 1999). It is one of the most applied techniques for

evaluating hospital efficiency (Linna, etal 2006; Bakar, etal 2010).

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2.6.2 Data Envelopment Analysis (DEA) Approach to Measure Efficiency of Hospitals

Charnes and Cooper (1985) describe a non- parametric approach for institutions like

hospitals, banks etc. to measure efficiency and the technique is known as Data Envelopment

Analysis (DEA). DEA calculates the efficiency of a given organization in a group relative to

the best performing organization in that group. These individual units analyzed are also

referred to as decision making units (DMUs) in DEA. The DMUs for which efficiency scores

are measured can be a whole agency such as hospitals, banks or units within organizations

such as separate wards in a hospital.

By providing the observed efficiencies of individual organizations, DEA helps to identify

efficient organizations benchmarks towards which performance can be targeted by the

inefficient ones. The actual levels of input use or output production of efficient organizations

(or a combination of efficient organizations) can serve as specific targets for less efficient

organizations, while the processes of benchmark organizations can be promulgated for the

information of managers of organizations aiming to improve performance.

DEA uses Linear Programming (LP) methods to establish the frontier from sample data. The

efficiency is then measured relative to the efficiency of all others in the sample, subject to the

restriction that all DMUs lie on or below the frontier (Bjurek, etal, 1990). This is achieved by

solving a series of LP problems.

This method is generally preferred for efficiency analysis in non-profit sector such as health

institutions where, according to (Coelli, etal, 1998):

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Random noise is less of a problem

Multi-product output production is relevant

Price data are difficult to find

Setting behavior assumptions such as profit maximization or cost minimization as

done with the cost/production function method described above is difficult.

However, there are limitations of this method too.

2.6.3 Reasons for using DEA Approach to Measure Efficiency in this Research Study

An efficiency measurement technique in general consists of four classes: Parametric, Non-

parametric, Deterministic, and Stochastic. This study focuses on non-parametric DEA

technique of efficiency measurement. Measurement of efficiency of any organization like

hospital that uses multiple inputs and generates multiple outputs is complex and comparisons

across units are difficult. DEA is basically a linear programming technique used for

measuring the relative performance of organizational units where the presence of multiple

inputs and outputs makes comparisons difficult. DEA involves identification of units, which

in relative sense use the inputs for the given outputs in the most optimal manner. DEA uses

this information to construct efficiency frontier over the data of available organization units.

DEA uses this efficient frontier to calculate the efficiencies of the other organization units

that do not fall on efficient frontier and provide information on which units are not using

inputs efficiently. Thus, this research study has also used DEA technique to measure

efficiency of private hospitals.

Below, we review the studies on efficiency of hospitals done abroad with the use of DEA

approach.

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2.7 Review of Hospital Efficiency Studies

A. Studies done on an International level using DEA Approach

In this section a review of studies done to measure efficiency of hospitals in different

countries in different time frames is provided. The Data Envelopment Analysis (DEA)

technique has been extensively used in Asia, the America and Western Europe to shed light

on the efficiency of various aspects of national health systems.

Sherman (1984) wrote one of the founding articles on efficiency utilizing the DEA

methodology on U.S. hospitals. He examined teaching hospitals and included nurses and

interns trained as well as patient days as outputs. He compared results of traditional ratio and

regression analysis as well as DEA. He found that DEA is a useful tool for the evaluation of

resources among health care organizations and can lead towards improved hospital efficiency

and reductions in health care costs. He suggested that DEA technique can overcome

limitations of traditional ratio and regression analysis and provide a more comprehensive

measure of hospital efficiency.

The DEA technique was first used to study hospital production by Banker, Conrad and

Strauss (1986) in North Carolina. Grosskopf and Valdmanis (1987) examined 22 public

hospitals and 60 private not-for profit hospitals in California. They used DEA method and

found that the two classes of hospitals to be facing distinct production frontiers with public

hospitals being more efficient overall.

Valdmanis (1990) applied the DEA method to a group of hospitals in Michigan and found

that government-owned hospitals were more efficient. This might be due to the fact that an

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imperfect adjustment is made for the quality of output and patient day rather than admission

are generally used to measure output. The other surprising result is that for profit hospitals

tend to be disproportionately represented among highly inefficient hospitals (Ozcan, 1992)

and are inefficient compared to not-for-profit hospitals when output is measured by inpatient

discharges.

Ozcan and Bannick (1994) used DEA to study trends in efficiency in defense hospitals from

1998-1999 using 124 military hospitals and data from the American Hospital Association

Annual Survey. In a 1995 study, these authors also compared defense hospitals efficiency

with that of Veteran Administration hospitals efficiency (n=284) using 1989 data. These

studies were conducted at the strategic level under a different operational paradigm, prior to

the large-scale adoption of managed care.

Fare, etal, (1994) published a paper evaluating productivity change in Swedish hospitals

during the period from 1970 to 1985. They employed DEA Malmquist output based

productivity index. However, cost consideration was questionable as hospitals (specially the

public ones) are not originally intended to maximize revenue. As cost factors were not

considered thoroughly in the research, results showed that productivity is decreasing. Such

illumination of the cost-expensive revenue factors may make the results biased. Similar to

cost, the consideration of quality factors which are usually ignored is another reason that may

indicate that such results can be biased.

Parkin and Hollingsworth (1997) used constant returns to scale DEA model to measure

efficiency of 75 Scottish acute care hospitals. They used an input vector consisting of three

capital and three labor variables and output vector consisting of four categories of inpatient

66

discharges as well as emergency attendances and outpatient attendances. They found the rank

correlation to range from 0.69 to 0.96.

Study done by Harris (1997) used DEA to examine the technical efficiencies of 573 Turkish

acute general hospitals. Inputs of number of beds, number of primary care physicians, and

number of specialists, and how they are used to produce outputs of inpatient discharges,

outpatient visits, and surgical operations, are examined. Results illustrate that less than 10%

of Turkish acute general hospitals operate efficiently compared to their counterparts.

Inefficient, compared to efficient hospitals, on average utilize 32% more specialists, 47%

more primary care physicians, and have 119% more staffed bed capacity. They also produce

on average less output. Particularly, 13% less outpatient visits, 16% inpatient hospitalization,

and 57% less surgical procedures. Additionally, the validity of DEA was illustrated by

comparing it to the ratio analysis method; no discernible differences in the results were

found.

Linna, etal, (1998) investigated the development of hospital cost efficiency and productivity

in Finland by comparing both parametric and non-parametric panel models. The parametric

panel methods has used Stochastic Frontier Analysis (SFA) model with a time varying

inefficiency component. The non-parametric panel methods used various DEA models to

calculate efficiency scores and the Malmquist productivity index. Linna‘s main objective in

undertaking study was to determine if the use of panel data model would improve the

estimates of individual efficiency scores compared to earlier cross-sectional analyses. The

author found that results using panel data suggested that a reduction in inefficiency will

reduce total hospital costs by between 1 and 1.2 billion Finnish Marks annually. The results

further indicated that the choice of modeling approach does not affect the results. SFA and

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DEA models were both able to reveal that productivity progress in 1988-1994 was due to

both the exogenous rate of technical change and to the effect of time-varying efficiency. The

author found that SFA and DEA methods produce different average efficiency scores.

Nevertheless, he concluded that non-parametric and parametric methods used together with

panel data provide a sufficiently clear understanding of the development of efficiency in

hospital production to justify future studies of frontier models in healthcare.

Another study by Chang (1998) combines DEA with regression analysis to evaluate the

efficiency of central government-owned hospitals in Taiwan over the five fiscal years

between 1990 and 1994. Efficiency is first estimated using DEA with the choice of inputs and

outputs being specific to hospital operations. A multiple regression model is then employed

in which the efficiency score obtained from the DEA computations is used as the dependent

variable, and a number of hospital operating characteristics are chosen as the independent

variables. The results indicate that the scope of services and proportion of retired veteran

patients are negatively and significantly associated with efficiency, whereas occupancy is

positively and significantly associated with efficiency. Furthermore, the results also show that

hospital efficiency has improved over time during the periods studied. Given the

contemporary focus on concerns regarding efficiency in healthcare; the results provide an

indication that inter-temporal efficiency gains are attainable in the healthcare sector in

anticipation of the implementation of the National Health Insurance Program.

Puig-Junoy (1998) compared the technical efficiency of healthcare in OECD countries

between 1960 and 1990. He found that overall, technical efficiency improved over time,

mostly as a result of improved scale efficiency. The OECD countries consistently improved

in pure technical efficiency (estimated efficiency score was 91%).

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McKillop, etal, (1999) estimated the technical efficiency of 23 acute hospitals in Northern

Ireland from 1986 to 1992 using DEA. All the 23 acute hospitals were categorized into small,

medium and large (based on total number of inpatients and outpatients). The efficiency

estimates are used to investigate whether the empirical evidence supports the current

rationalization policy for hospital provision in Northern Ireland. Non-parametric DEA

analysis is used to measure the efficiency of larger and smaller hospitals relative to best

practice. The results cautiously support the current policy of expanding larger hospitals and

restructuring/closing smaller hospitals, but also indicate that the expansion of large hospitals

may not yield substantial efficiency gains.

Andrew (2001) presented a survey paper on DEA techniques usage in healthcare systems in

US till 1999. The paper discussed some of the difficulties in using productivities‘

measurements to evaluate hospitals productivity such as those mentioned earlier. Other

factors include the difficulty to measure some factors specially those that are related to

quality attributes. Other difficulties also include defining the right input and output factors. In

some cases, a model or an attribute can be used as an input or an attribute together.

Kirigia, etal, (2001) study used DEA approach for 155 primary health care clinics in

Kwazulu-Natal province in South Africa and found 70% of them to be technically inefficient.

Giuffrida and Gravelle (2001) examined the performance of British Family Health Service

Authorities (FHSAs) in the periods 1993-1994 and 1994-1995. They applied various methods

and showed that the average efficiencies computed using DEA were similar to those resulting

from the regression-based methods and were within the ranges of stochastic frontier models.

Kirigia (2002) study also assessed the technical efficiency of 54 public hospitals using the

DEA application in Kenya. He found that 26% (14) of the hospitals were technically

69

inefficient. The study singled out the inefficient hospitals and provided the magnitudes of

specific input reductions or output needed to attain technical efficiency.

Biorn, Hagen and Iversen (2002) measured technical efficiency of hospitals in Norway using

DEA. They find that there was a large improvement in efficiency in the first year after the

reform of the funding system.

Zavras, etal, (2002) study of 133 healthcare centers in Greece in 1999 using input-based DEA

indicated that medium sized centers were relatively more efficient than larger and smaller

units.

Coppola (2003) conducted a DEA study of 78 military medical facilities in army, navy and

air force using 1998-2002 data in US. In his study he selected the following input variables:

costs, number of beds, number of service offered. For output variables, he used surgical visit,

ambulatory patient visit, emergency visits, and live births. The study concluded that air force

facilities were slightly more efficient followed by army and then navy facilities.

Butler, etal, (2003) tried to work on studying the impact of variables‘ changes on inefficient

DMUs in Michigan hospitals. The variables used in the study include: number of beds, total

services, and number of technical employees are as inputs and total number of inpatients,

number of surgeries, and number of handled operations in the emergency room as outputs.

Another study by Stanford‘s (2004) examined the performance of 107 Alabama hospitals by

using DEA in the treatment of acute myocardial infarction patients. It also examined the

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clinical efficiency and quality of care. Cross efficiencies were used to improve the efficiency

discrimination between hospitals.

In Asia, Hu and Huang (2004) produced the first study of medical centers and regional

hospitals in Taiwan. Data on 80 centers in 2001 were collected and subjected to input-based

DEA. The 5-input/4-output estimation results revealed high pure technical efficiency (92.7%)

as well as scale efficiency (96.5%), resulting in an overall technical efficiency of 89.5% for

the whole sample.

On the other hand, in Kenya 32 public health centers were found to be quite inefficient

(Kirigia, etal, 2004). Their average technical efficiency score was 65% while the average

scales efficiency score was 70%.

Using different outputs, a later DEA study by Retzlaff-Roberts, Chang and Robin (2004)

computed both input-oriented and output-oriented variable returns to scale in 27 OECD

countries. The results for 1998 indicated that13 of the 27 countries were efficient regardless

of which approach was adopted. In absolute terms, the output-oriented approach suggested

that infant mortality could be improved by 14.5 percent and life expectancy by 2.1 percent,

on average. However, adopting the input-oriented approach, 14.0 percent of inputs could

have been saved if infant mortality were the target output, while 21.0 percent of inputs could

have been saved if life expectancy were the target output.

Renner, etal, (2005) study in Sierra Leone revealed that 59% of the 37 peripheral health units

in Pujehun district were technically inefficient.

71

A pilot study by Osei, etal, (2005) of 21 public health centers and 21 hospitals was carried

out in 2000 in Ghana. The results showed that 18% of the health centers were technically

inefficient.

Bates (2006) used data envelopment analysis and multiple regression analysis to examine

empirically the impact of various market-structure elements on the technical efficiency of the

hospital services industry in various metropolitan areas of the United States. Market-structure

elements include the degree of rivalry among hospitals, extent of Health Maintenance

Organizations (HMO) activity, and health insurer concentration. The DEA results showed the

typical hospital services industry experienced 11 percent inefficiency in 1999. Moreover,

multiple regression analysis indicated the level of technical efficiency varied directly across

metropolitan hospital services industries in response to greater HMO activity and private

health insurer concentration in the state. The regression analysis suggested the degree of

rivalry among hospitals had no marginal effect on technical efficiency at the industry level.

With slightly different input and output mixes, Kontodimopoulos, Nanos, and Niakas (2006)

estimated the efficiency scores of 17 hospital health centers in Greece in 2003. The overall

average efficiency estimates were quite similar to those of Zavras etal (2002), and the results

suggested that the health centers required only 73 percent of the inputs currently applied to

produce the existing levels of outputs.

Zere, etal, (2006) measured technical efficiency of district hospitals in Namibia using Data

Envelopment Analysis. The findings suggest the presence of substantial degree of pure

technical and scale inefficiency. The average technical efficiency level during the given

period was less than 75%. Less than half of the hospitals included in the study were located

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on the technically efficient frontier. Increasing returns to scale is observed to be the

predominant form of scale inefficiency.

Masiye (2007) did technical efficiency study using DEA in Zambia for 20 hospitals. The

study revealed average efficiency of 64% implying that the 17 inefficient hospitals could

lower their cost by 36% and still achieve their current levels of output.

Barros, etal, (2008) analyzed the efficiency and productivity growth for a sample number of

Portuguese hospitals by observing technological and efficiency changes. The research used

DEA and Malmquist productivity index. A directional distance function is introduced to

measure the smallest changes of inputs and outputs in a given direction by defining a

reference or goal point to be achieved after performing the frontier approach. They conclude

that Portuguese hospitals experienced very weak productivity growth and low incidence of

technological change in the period 1997-2004.

Osei, etal, (2008) tried to measure the technical and scale efficiency for 84 hospitals and

health centers in Ghana and gives directions that help decision-makers for an effective

management in the health sector. The study divided inputs into the following broad

categories: personnel, materials, and capital. The output is divided into maternal and child

health care visits, deliveries and inpatient discharges. The study used CRS (i.e. Constant

Returns to Scale) and VRS (i.e. Variable Returns to Scale) models to assess the efficiency of

the selected hospitals. Measuring efficiency of the DMUs is calculated in three steps; first,

the efficiency was estimated through CRS and second, through VRS. Third, scale efficiency

was obtained by dividing each hospital's CRS efficiency score by its VRS efficiency score.

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Harfouche (2008) used DEA to evaluate the impact of changes in the hospital management

model in the technical efficiency level. The study concluded that the new public enterprise

hospitals were more efficient than the traditionally managed hospitals.

Kirigia, etal, (2010) presented a research paper to evaluate hospitals efficiency in Benin using

DEA. The study includes data for five years from 2003 to 2007. Results showed that a large

percent of hospitals are inefficient. Results showed that the size of the hospital is an

important factor in assessing its productivity.

The next section deals with studies done on efficiency of hospitals using DEA in India. There

are very few studies in Indian context, irrespective of numerous studies available at the

international levels that have been reviewed above.

B. Studies Done in India Using the DEA Approach

In India there is dearth of literature as very few studies are done on efficiency of hospitals

using DEA analysis. However, after a thorough review of literature, a few studies that are

conducted in India are presented below.

A study was conducted by Razz, Samandri (2001) of privately funded quality healthcare LV

Prasad Eye Institute (LVPEI) and Ophthalmologic Institute in Hyderabad, India using DEA

framework. The success of LVPEI in terms of efficiency as brought out by DEA can be

attributed to close attentions to three areas of health administration – fiscal solvency,

programmatic focus and quality management. Detailed financial audits and policy studies are

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conducted annually to implement standards for cost contentment and maximize the institute‘s

efficiency.

LVPIE‘s reputation for delivery of high quality care enhances its ability to raise funds and

foster new initiatives. The institute‘s strong clinical program is accompanied by successful

research, rehabilitation & outreach programs. In order to standardize care, the institute

adopted protocols, clinical guidelines and mechanisms of internal review before any patients

were seen. Clearly defined standards of practice set it apart from other medical institutions,

including long standing private and public ophthalmologic hospitals in Hyderabad.

Patients were assured of a systematic and equitable method of care and contributors were

assured that their donations would be well utilized. The secret to the success of the institute

lies in its patient oriented, multilayered approach to self-evaluation and to the active

implementation of corrective majors.

For instance, to evaluate its effectiveness LVPEI uses quality improvement majors, including

patient surveys, post operative outcome studies and service utilization reviews. The

development of quality assessment is supported at the highest levels of administration and is

the basis of the institutes policies and ‗Culture of Accountability.‘ This is just the type of

internal accountability and regulation that the Operations Evaluation Department (OED)

believes is the necessity ‗if the private sector will continue to serve the public health goals in

India.‘ (World Bank, 2000).

LVPEI‘s active program of quality management, its academic commitment and pragmatic

relevance to the needs of its community should be modularized to produce similarly viable

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healthcare establishments especially in a heavily populated country like India where both

public and private sectors are inevitable part for any policy making. The LVPEI stands as an

illustration for quality healthcare institutions and to actualize the principles of equity,

efficiency and efficacy.

Another successful study was conducted by Bhat, etal, in 2001 using DEA for district

hospitals and grant-in –aid hospitals in Gujarat state. The study makes an attempt to provide

an overview of the general status of the healthcare services provided by hospitals in the state

of Gujarat in terms of their technical and allocative efficiency. One of the two thrusts behind

addressing the issue of efficiency was to take stock of the state of healthcare services (in

terms of efficiency) provided by grant-in-aid hospitals and district hospitals in Gujarat. The

motivation behind addressing the efficiency issue is to provide empirical analysis of

government‘s policy to provide grants to not-for-profit making institutions which in turn

provide hospital care in the state. The study addresses the issue whether grant-in-aid hospitals

are relatively more efficient than public hospitals.

This comparison between Grant-in-aid hospitals (GHs) and District hospitals (DHs) in terms

of their efficiency has been of interest to many researchers in countries other than India, and

no consensus has been reached so far as to which category is more efficient. The relative

efficiency of government and not-for profit sector has been reviewed in this study.

The efficiency score of 85% for DH indicates that on an average the hospitals could increase

the output using the same level of resources or reduce the input usage or input costs by 15 per

cent to deliver the same amount of healthcare. The efficiency score of 89% for GHs indicates

that on an average the hospitals could increase the output using the same level of resources or

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reduce the input usage or input costs by 11 per cent to deliver the same amount of healthcare.

The finding of the study suggests that the efficiency variations are significant within district

hospitals than within the grant-in-aid institutions. The overall efficiency levels of grant-in-aid

institutions are higher than the district level hospitals. The grant-in-institutions are relatively

more efficient than the district hospitals.

Mathiyazhgan in (2006) highlights the cost efficiency using DEA of public and private

hospitals in Karnataka state in India. This is estimated through the parametric and non-

parametric methods by using the Hospitals Facility Survey (2004) in Karnataka state. The

findings indicate that the choice of econometric approach did not make any significant

difference in the results and they are robust. The analysis infers that (a) hospitals (both

public and private together in the analysis ) are cost inefficient in the state, which is due to

technical and allocative system of resources of the hospitals (b)the private hospitals appear

relatively less inefficient than the public hospitals (c) the main determinants of the technical

and allocative inefficiencies of the public hospitals are due to inappropriate interventions of

inpatient days care, share of medical personnel, beds capacity, quality indices and choice of

the locations while in the case of private hospitals, it relates only to beds capacity and quality

indices.

The study focused on the hospital cost function and analysis of scale economies as it is

supposed to provide useful insights to policy makers in 3 ways viz: hospital budgeting,

assessment of hospital efficiency and assessment of efficiency by different health

interventions (Adams, etal, 2003).

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Efficiency of hospitals in Karnataka was measured using Stochastic Frontier Analysis (SFA)

and Data Envelopment Analysis (DEA) which indicated that private hospitals have not only

been technologically efficient but also efficient in allocation of resources in terms of inpatient

days, outpatient visits and share of medical personnel as compared to public hospitals.

2.8 Summary

In recent years, the issue of efficiency in relation to the hospital costs has been analyzed by

the improved methodological frameworks such as Data Envelopment Analysis (DEA)

{Magnussen (1996), Linna (1998) and Kirigia (2010)}. There were evidences of significantly

decreased productivity among hospitals and also large variations in efficiency between

different hospitals. The World Health Report 2000 made an assessment of the effectiveness

of healthcare delivery by rankings based comparison of the productive efficiency of the

healthcare systems of 191 countries (WHO, 2000). However, most studies of hospital

efficiency have been criticized for not having measured output or even case mix

appropriately (Linna, 1998).

It is well- known and clear from the above basic understanding that there is a scarcity of

resources in the health sector. At the same time, there is a growing need and demand for

quality health services for all, particularly in light of growing and aging populations and

increasing diversity and complexity of diseases. The pursuit of efficiency and equity in

resource allocation and use is accepted as a major goal of health systems among policy

makers. Hence, it is necessary to undertake the study of efficiency in the functioning of

hospitals which can help to achieve the following objectives:

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a. Examine how efficiently hospitals (be it any public, private not for profit and private for

profit) deliver healthcare services;

b. Compare efficiency of public, private not for profit and private for profit hospitals;

c. Compare costs and outputs between different hospitals and

d. Develop hospital efficiency indicators.

Even though efficiency is accorded a central place in the health policies of most countries, in

practice much remains to be done. The dearth of literature on hospital efficiency studies in

India may perhaps indicate that in practice not much attention is given to efficiency by

healthcare administrators. Much of the attention of policymakers and health system

researchers seem to be focused on health sector reforms, prominent of which is the

mobilization of additional resources for healthcare through user fees and other modalities of

financing.

However, before examining the efficiency of hospitals, it is essential to know at the first

place and understand the situation of both public and private healthcare in the Indian context.

This will serve as a foundation for our further research focusing on the study of efficiency in

the private hospitals in the city of Mumbai which play a pivotal role in providing health

services to the people in recent times.