structural reforms and health equity: a comparison of nss surveys, 1986 ... · a comparison of nss...

Structural Reforms and Health Equity: A Comparison of NSS Surveys, 1986-87 and 1995-96Author(s): Gita Sen, Aditi Iyer, Asha GeorgeSource: Economic and Political Weekly, Vol. 37, No. 14 (Apr. 6-12, 2002), pp. 1342-1352Published by: Economic and Political WeeklyStable URL: http://www.jstor.org/stable/4411960 .Accessed: 25/04/2011 04:38

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Structural Reforms and Health Equity A Comparison of NSS Surveys, 1986-87 and 1995-96

Preliminary results of an analysis of data sets on morbidity and health care utilisation from two NSS surveys in the 1980s and 1990s together with empirical results of other studies

points the worsening of class-based inequalities in access to health services for both men and women. While gender inequity, particularly in untreated morbidity, appears to have

remained severe, also seen is a relative worsening of access for poor men over this period, even though in absolute terms men are better off than poor women.

GITA SEN, ADIT IYER, ASHA GORGE

A ssessing the magnitude, direction, and impact of changes in the health

1A sector in India during the 1990s is complex. Not only has there been a multi- plicity of changes at the micro and macro levels affecting aspects ranging from health financing to health-related behaviour, but the data are fragmentary and disparate in their reliability and scope. Analysts to date have therefore tended to address partial aspects and have often had to hypothesise rather than confirm. The data with the widest coverage are two surveys of morbidity and utilisation of health care by the National Sample Survey (NSS) in the mid- 1980s and 1990s. The report of the second NSS survey has only become available since 1998, and has not been much com- mented on as yet.

Our concern in this paper is to use some of the data from these surveys, together with the empirical results of other studies to put forward some preliminary results of significant changes that appear to have occurred in the 1990s, especially in relation to the question of health equity.

Health Equity in Period of Reform

Dimensions of Equity

Gender and economic class are two major dimensions of socio-economic inequality and injustice.2 While each of these dimensions interacts with and crosscuts the other, they are by no means congruent in terms of how they work or in their effects. Each therefore has to be analysed both sepa- rately and in relation to the other in order to obtain a fuller picture of the causes or consequences of inequality.

The gap between rural and urban areas

in terms of development resources and services is also striking, and has persisted despite half a century of development efforts after independence. In the health sector, this has meant that urban areas and economically developed regions have at- tracted a larger share of health institutions, qualified doctors and health workers, than warranted by their share in the total population [Duggal et al 1995a; Nandraj and Duggal 1997; Sule 1999].

Gender Biases

The government's approach to the pro- vision of public health services has paid little attention until very recently3 to the need to systematically tackle gender biases at the household and community levels. At the same time, the prevalence of gender biases in access to nutrition and health care, working to the detriment of girls and women has long been known [Das Gupta 1987]. Women all too often suffer ill health silently, particularly when it is related to sexuality orreproduction [Bang etal 1989]. While there are considerable variations in this regard across states within the country, gender bias is significant in all but a few areas.

Such biases remained significant, as attested by the NSS survey in 1986-87 [NSSO 1992]. Table 1 (Col 1, Col 4) shows that in 1986-87, untreated morbidity was 15-21 per cent higher among women and girls. This figure does not include the reservoir of untreated sexual and reproductive illness that neither the NSS survey of 1986-87 nor that of 1995-96 was able to capture.4

Morbidity rates as such were not very different between rural men and women in 1986-87, but were higher for urban women than for men. However, the reporting of

female morbidity is particularly sensitive to study methodologies and techniques of data collection. It would appear that the full extent of women's morbidity becomes evident only when women are addressed one-to-one by women researchers/inter- viewers after initial rapport building.

Women through long years of socialisation, reinforced by competing demands on their time and energy, often do not acknowledge their own health problems. Chronic backache and persis- tent weakness are but two examples from a long list that also includes reproductive problems and mental stress, among other health conditions [Madhiwalla et al 2000; Bhatia and Cleland 1995; Bang et al 1989]. A recent district-level study of women's ailments and health seeking [Madhiwalla et al 2000] showed that careful gender- sensitive probing increased reporting of morbidity by 124 per cent. We can therefore conclude that the rates of female morbidity, as elicited in the NSS surveys, are probably gross underestimates of the full extent of women's illness. Since an illness that is not acknowledged is unlikely to be treated, this probably means that women's untreated morbidity is also underestimated. Gender bias is also reported in the way health service providers treat women [Koenig and Khan 2000].

Economic Class Differentials

Just as gender bias has been an inherent part of the health-related behaviour of households, economic class differentials in the use of health services have also been striking. These differentials affect the amount of treatment that households get and how much they spend on it. Table 2 (Col 1, Col 3) provides evidence for the failure of the health system in this regard.

1342 Economic and Political Weekly April 6, 2002

The NSS surveys provide data tabulated across the monthly per capita expenditure (MPCE) fractiles of households. Using MPCE as a rough proxy for economic class,5 we use the gradient across fractiles as a simple measure of the extent of inequality. The NSS survey shows a positive class gradient for morbidity rates in the rural areas, but neither the rural nor the urban slope is significantly different from zero. Findings of positive gradients for morbidity are not, however, peculiar to the NSS surveys alone. A positive gradient means that the better-off have higher morbidity than the poor. This holds a fortiori for women in the NSS survey, as the inequality in reported morbidity among women was greater than among men. Positive gradients for morbidity fly in the face of common sense understanding of the probability of ill-health given the differences in nutrition levels, anaemia, and environmental and occupational conditions between the poor and the rich.

However, district level studies often show morbidity rates to be positively associated with socio-economic status [Duggal with Amin 1989; George et al 1997]. But does this reflect more illness amongst the rich, or a reporting bias against the poor who may not be able or willing to acknowledge their own ill-health?

Those who believe the latter to be true point out that the need for and access to health services reflects a process with multiple stages. At its core lies a health concern that may not always be recognised. Once a problem is identified and recognised as a need, social dynamics within households and communities endorse or con- strain health-seeking behaviour. At a third level lie questions of the availability, quality and affordability of care. It is only when all these 'gateways' are crossed that morbidity is nearly certain to be reported [Chatterjee 1988].

In addition to the problem of morbidity reporting, the class gradient for untreated morbidity was highly significant and negative in both rural and urban areas in 1986- 87. This means that the poor were less likely to get treated for their illnesses than the rich. The extent of inequality among women in this regard was even worse than among men in both rural and urban areas. Indeed almost the entire urban class differential in untreated morbidity was due to differences among women; the class gradient among urban males was not significantly different from zero. Furthermore, when they did get treatment, the poortended

to spend less on both outpatient and in- patient care (as shown by the positive and highly significant gradients) than the better off.

The discussion in this section shows that, at least until the mid- 1980s, the health service system had not done away with either class or gender inequity in access. Untreated morbidity had both an economic class gradient and significant gender inequality even without the inclusion of untreated reproductive ill health. Further- more, the class differences among women in terms of untreated morbidity were higher than among men. Qualitative and micro-

survey evidence corroborates some of these findings from the large-scale NSS survey [Das et al 1982; Khan et al 1982]. They point to a pattern of pre-existing gender and class inequity in access to health care in the public and private sectors, as well as to the resources needed to cover health care costs.

Health Care Use: Public-Private Mix

The demand for services from the private health care sector can be highly inelastic in the absence of a functioning

Table 1: Gender Differences in Rates of Morbidity and Untreated Morbidity: All-ndia

Rural Urban Per Cent Per Cent

1986-96 1995-96 Change 1986-96 1995-96 Change Col 1 Col 2 Col 3 Col 4 Col 5 Col 6

Morbidity rates (No of ailing persons per 1,000 people)# Male 64 83 30 30 79 163 Female 63 87 38 33 88 167 Total 64 85 33 31 83 168 F/M ratio 0.98 1.05 6 1.10 1.11 1

Untreated morbidity rates' (no of untreated persons per 1,000 ailing people) Male 172.4 162 -6 98.1 90 -8 Female 198.0 184 -7 118.9 97 -18 Total 184.8 173 -6 108.6 93 -14 F/M Ratio 1.15 1.14 -1 1.21 1.08 -11

Notes: * 1986-87: Untreated morbidity=(100,000-rate of treated morbidity)/100. 1995-96: Untreated morbidity=(1000-rate of treated morbidity). The morbidity rates for 1995-96 (with a 30-day recall period) are estimates by the NSS (NSSO 1998:18-19). NSS1995-96 (30 days) = NSS1995-96 (15 days) + PPC (15 days) where PPC is the number of persons reporting any ailment (acute or non acute) during the 15-day recall period. Calculated ratios in the table are slightly lowerthan the NSS estimated because of non-availability of PPC for non-acute ailments.

Sources: NSSO 1992, Statement 10, p 65; Statement 11, p 66. NSSO 1998, Source Tables: 1.2 and 9.2, p A-21, A-53, A-126, A-158; Source Table 8.2, A-46, A-151.

Table 2: Class Gradients by Gender in Morbidity, Untreated Morbidity and Costs of Care: All-India

(Gradients)

Rural Urban 1986-87 1995-96 1986-87 1995-96

Col 1 Col 2 Col 3 Col 4

Morbidity rates (No per 1,000 persons) Male 1.25 8.82" -0.18 5.00** Female 2.29 10.82** 0.79 6.64** Total 1.82 9.61** 0.25 5.68**

Untreated morbidity rates (No per 1,000 ailing persons) Male -13.44** -26.50** -0.04 -15.04 Female -24.47** -22.82** -15.79* -20.25** Total -18.74** -24.75* -8.27* -17.57*

Average expenditure on hospitalisation (in Rupees) Male na 889.89* na 1437.40* Female na 532.39* na 1245.60* Total 42.50** 736.86* 143.37** 1354.40'

Average expenditure on outpatient care (in Rupees) Male na 20.21** na 26.39** Female na 19.96** na 25.46** Total 5.17* 20.11 9.83** 26.04**

Notes: 1 NA - Not Available 2 The gradients have been estimated by fitting trend lines for the variable across different

fractiles of monthly per capita consumption expenditure. 3 * implies significance at 5 per cent level; ** implies significance at 1 per cent level.

Sources: NSSO 1992, Statement 10, p 65; Statement 11, p 66; Table 5.00, p S-418; Table 11.00, p S-516. NSSO 1998, Source Tables: 1.2 and 9.2, pp A-21, A-53, A-126, A-158; Table 8.2, pp A-46, A-151; Table 19, pp A-92, A-197; Table 22.2, pp A-103, A-208.

Economic and Political Weekly April 6, 2002 1343

public health system as a base. Unless people have an alternative, they may be compelled to pay high prices or be forced to opt out of health services altogether. The consequences of opting out are increased burden of untreated morbidity, and in terms of the often hidden cost of women's time and labour as the health care providers of first and last resort. Public services therefore play a critical role in the health of the poor and especially for poor women.

A well-functioning public health system not only assures effective services to those at the lower ends of the socio-economic hierarchy, but can also set a ceiling for , rices and a norm for quality in the private sector. It can therefore be a major anchor for equity overall in the health service system. Inter-state comparisons within India appear to confirm this as states with better public health services have lower prices in the private sector [Krishnan 1995]. A study of public hospitals in seven sub- Saharan African countries found that although curative health spending was not well targeted, it was still progressive. The subsidy that did reach the poor constituted a larger proportion of their household expenditure compared to the rich [Castro- Leal et al 2000].

Tables 3 and 4 show the public-private mix of utilisation of outpatient and in- patient services based on the mid-1980s NSS survey. Table 3 (Col 1, Col 3) shows that by the mid-1980s, over 70 per cent of outpatient care was in the private sector, the bulk being provided by private doctors. This was true in both rural and urban areas. However, Table 4 (Col 1, Col 3) shows that the public sector still accounted for 60 per cent of all in-patient care, the bulk being provided by public hospitals in rural and urban areas.

Table 5 (Col 1, Col 4) shows that the cost6 differential (as measured by average expenditure) between private and public outpatient care was only 5 per cent in rural services and 8 per cent in urban services.7 Given that the NSS survey did not include a range of costs such as bribes, tips, etc, that are known to be rampant in the public sector, one can safely conclude that there was practically no cost difference between public and private outpatient services. In these circumstances, patients appear to have gone overwhelmingly to the private sector.

On the other hand, the cost difference between private and public in-patient care was much higher. Average expenditure incurred on in-patient care in rural private

hospitals was 129 per cent more than in public hospitals and in urban private hospitals 213 per cent more expensive than in public hospitals. The two tables together point to the fact that, where private costs

were relatively higher, the share of the private sector was lower. This may explain why public hospitals continued to be more popular than private hospitals for in- patient care in the 1980s.

Table 3: Public-Private Sector Use for Outpatient Care: All-India (Percentage distribution)

Rural Urban 1986-87 1995-96 1986-87 1995-96


Share of Public Sector 25.6 19.0 27.2 19.0 Public hospital 17.7 11.0 22.6 15.0 PHC/CHC* 4.9 6.0 1.2 1.0 Public dispensary 2.6 2.0 1.8 2.0 ESI doctor** 0.4 0.0 1.6 1.0

Share of Private Sector 74.5 80.0 72.9 81.0 Private hospital 15.2 12.0 16.2 16.0 Nursing home 0.8 3.0 1.2 2.0 Charitable institution 0.4 0.0 0.8 1.0 Private doctor 53.0 55.0 51.8 55.0 Others 5.2 10.0 2.9 7.0

Total 100.1 99.0 100.0 100.0

Notes: * PHC - Primary Health Centre, CHC - Community Health Centre. * ESI - Employees State Insurance.

Sources: NSSO 1992, Statements 13R and 13U, pp 67-68, Statement 2R and 2U, pp 53-54. NSSO 1998, Table 4.10, p 22; Table 4.16, p 28.

Table 4: Public-Private Sector Use for Inpatient Care: All-India (Percentage distribution)

Rural Urban 1986-87 1995-96 1986-87 1995-96


Share of public sector 59.7 45.2 60.3 43.1 Public hospital 55.4 39.9 59.5 41.8 PHC/CHC* 4.3 4.8 0.8 0.9 Public dispensary 0.5 0.4 ESI doctor*

Share of private sector 40.3 54.7 39.7 56.9 Private hospital 32.0 41.9 29.6 41.0 Nursing home 4.9 8.0 7.0 11.1 Charitable Institution 1.7 4.0 1.9 4.2 Private doctor Others 1.7 0.8 1.2 0.6

Total 100.0 99.9 100.0 100.0

Notes: * PHC - Primary Health Centre, CHC - Community Health Centre. * ESI - Employees State Insurance. Sources: NSSO 1992, Statements 13R and 13U, pp 67-68, Statement 2R and 2U, pp 53-54.

NSSO 1998, Table 4.10, p 22; Table 4.16, p 28.

Table 5: Average Expenditure on medical Care: All-India, 1995-96 (Rs per illness episode/hospitalisation)

Rural Urban Urban:Rural Ratio* 1986-87 1995-96 Per Cent 1986-87 1995-96 Per Cent 1986-87 1995-96

Col 1 Col 2 Change Col 4 Col 5 Change Col 7 Col 8 Col 3 Col 6

Outpatient care Public sector 73 129 77 74 166 124 1.01 1.29 Private sector 77 186 142 80 200 150 1.04 1.08 Total 76 176 132 79 194 146 1.04 1.10

Private:Public ratio@ 1.05 1.44 1.08 1.20 Inpatient care

Public sector 320 2080 549 385 2195 470 1.20 1.06 Private sector 733 4300 486 1206 5344 343 1.64 1.24 Total 597 3202 436 933 3921 320 1.56 1.22

Private:Public ratio@ 2.29 2.07 3.13 2.43

Notes: @Measures the private-public differential in average expenditure. 'Measures the urban-rural differential in average expenditure.

Sources: NSSO 1992, Source Table 11.00, p S-516, Statement 6, p 59. NSSO 1998, Table 4.19, p 32; Table 4.21, p 33.


The published survey data for 1986-87 allow us to explore the economic class implications only for in-patient care, and also do not provide corresponding gender breakdowns of the data. While the gradients across the MPCE fractiles for both public hospitals and PHCs in rural and urban areas were negative, and the gradient for private hospitals was positive, none of these gradients was statistically significant. On balance, the gradient for hospital use was near zero indicating relatively low economic class inequality in overall utilisation for in-patient care in both rural and urban areas in 1986-87.

To sum up, in 1986-87, while patients increasingly resorted to the private sector for outpatient services, public hospitals were still the dominant providers of in- patient care especially for the poor. Although this varied considerably across states, public hospitals provided an important alternative to the private sector and at significantly lower cost. Also there was little class inequality in the extent of hospitalisation for in-patient care.

Privatisation and Deregulation in 1990s

Despite its continuing importance for in- patient care, the public sector was beset with quality problems by the late 1980s. These problems continued in the 1990s. Availability of hospitals and health centres continued to favour cities and developed villages [ICMR 1988, 1991]. The referral system was poorly developed in most states. Rural health centres tended to be poorly supported with essential drugs [Phadke et al 1995], equipment, facilities [ICMR 1991] and professional medical staff, particularly those with specialist degrees (CBHI various years). Lower level func- tionaries - especially auxiliary nurse midwives - were burdened with excessive responsibilities, many of which they were unable to fulfil due to inadequate training, unsupportive on-the-job supervision as well as their own social vulnerability [Iyer and Jesani 1999].

These weaknesses of the public health system were due to an inadequate resource base as well as managerial inefficiencies and distortions caused by the excessive focus of the family planning programme on contraceptive method-specific targets, incentives and disincentives. The share of health in the government's (combined centre and states) revenue expenditure declined after the 1980s and especially in

the first half of the 1990s [Duggal et al 1995a]. Between 1990-91 and 1994-95, the real value of government (centre and states) health expenditures stagnated at around Rs 33 per capita. Thereafter, there was a modest increase, but no significant infusion of funds until 1998 (computed from data compiled by CEHAT).

Cost recovery schemes in public hospitals were introduced after the 1980s to augment finances and to induce greater 'efficiency' in resource use and quality of care. In the 1980s, a few states like Rajasthan and West Bengal formally introduced charges for diagnostic facilities and other services [Purohit and Siddiqui 1995; Bhat 2000]. In the 1990s, several others followed suit.

A review of user fee strategies in Gujarat, Madhya Pradesh, Orissa, Rajasthan and West Bengal [Bhat 2000] showed that they do not contribute more than 2 per cent to hospital budgets. More important, the impact on utilisation, especially by the poor, is not known except through anec- dotal evidence, even though a mounting body of international evidence shows that user fees can be highly regressive [Reddy and Vandemoortele 1996].

Growing Impetus for Privatisation

Although 1991 is typically bracketed as the year in which India formally launched reforms aimed at greater deregulation, liberalisation and privatisation, the health sector had already begun to move in this direction from the 1980s. During the 1990s, the impetus for these changes grew.

The declining share of public hospitals and dispensaries in public health expenditures since the 1980s [Duggal et al 1995b] coincided with growing state support for private hospitals and privatisation. In the 1980s, the large private hospitals that sprang up in metropolitan cities were actually registered as public trusts to take advan- tage of tax exemptions [Jesani with Ananthraman 1993]. This further skewed the urban bias in health resources docu- mented earlier. In the 1990s, a number of corporate hospitals8 sprung up on land allotted to them by the government in prime urban locations, in exchange for their providing a proportion of their services free to the poor [Baru 2000]. There is increasing evidence of non-compliance with this condition by major private hospitals. Moreover, as corporate hospitals have come to set the standard for medical technology and interventions, there is

reason to believe that they have contri- buted to the increases in health costs that are clearly evident in the mid-1990s NSS survey.

The 1990s also saw the privatisation of public health institutions and specific involvement of private providers in the public health system. For instance, the Punjab Health Systems Corporation was set up bringing 150 public hospitals under its purview [Gill 1996]. In some places, privatisation meant contracting the services of private bodies for non-medical essential services (like laundry, equipment maintenance, catering, media campaigns) in government hospitals [Bhatia and Mills 1997; Bennett and Muraleedharan 2000]. In others, it led to contracting the services of private specialists and hospitals for first referral services [Purohit and Mohan 1996]. In other instances, retail outlets and private practitioners were enlisted to market con- traceptives. Private practitioners were also oriented and trained for rational management of priority health problems and national programmes [Gill et al 1997]. Finally, the government also set up autono- mous societies to facilitate easier disburse- ment of funds and to operationalise programmes like the AIDS control, blind- ness control and reproductive and child health programmes [Bennett and Muraleedharan 2000].

On the whole, some of the collaborative initiatives between the public and private sectors are innovative and could possibly improve quality and access. However, a lot would depend on how well these collaborations are regulated and to what extent they seek to address the needs of patients, especially those who are poor. For instance, corporatisation may improve managerial efficiency, but may not solve the problem of access in remote areas. Contracting may help to improve the availability of services, but the standards of care and standardisation of charges would have to be addressed, as also the question of accountability to the patients using government facilities. Similarly, the qualifications of private practitioners, their prescribing practices and charges for treatment would also need to be carefully re- viewed to ensure quality of care and equity.

These are important issues because many of the quality-related problems in the private sector stem from an inadequate system of regulation.9 There is enough evidence to show that private hospitals and nursing homes have non-uniform -at times, grossly deficient - physical and process standards


[Nandraj and Duggal 1997; Muraleedharan 1999]. Practitioners, particularly those in the private sector, tend to prescribe in- appropriate or unnecessary drugs [Phadke et al 1995] which needlessly increase the cost of treatment. 'Cross practice', meaning qualified doctors selectively practising another system of medicine for which they have not been trained, is quite rampant too among private practitioners, especially in rural areas [Nandraj and Duggal 1997]. Knowledge about the side effects and prices of drugs is unreliable and variable,10 and 'cut practice', meaning kickbacks from specialists, laboratory and radiological facilities to referring general practitioners, prompt unnecessary tests and specialist consultations. All consumers, both the poor and the better off are potentially affected by these problems. But the poor have fewer resources to circumvent them or to challenge health practitioners or institutions on their own. Inequity thus gets locked in.

Deregulation of Drugs

Systematic deregulation of the pricing of drugs ha had a crucial bearing on the quality and costs of health care in the 1990s. Until the late 1960s, virtually no regulations governed the pharmaceutical industry that was dominated by transnational corporations [Bidwai 1995]. In the 1970s, the government passed the Indian Patents Act,1l a Drug (Price Control) Order, and constituted a committee that called for major changes12 in the working of the drug industry [Hathi Committee, GOI 1975].12 This committee provided the inspiration for the Drug Policy of 1978 although its more radical recommenda- tions never saw the light of day.

Since the Hathi Committee's report in 1975, two Drug Policy statements and several Drug Price Control Orders have been passed. Each of these further liberalised the scope of price control in terms of the number of drugs that are included and the extent to which the government can control the import, reten- tion and common sale prices of bulk drugs, as well as the retail and ceiling prices of scheduled formulations. In 1970, all drugs were under price control. In 1979, this number came down to 347; in 1987, it was 163; and by 1995, it was brought.down to a mere 76 [Rane 1998].

One of the major reasons why the government failed to adequately regulate the prices and production of drugs is overt and covert resistance from the drug industry, com-

prised initially of transnational corporations, and later including Indian firms and wholesale and retail traders. A second reason is that policies governing the pharmaceutical industry come under the purview of the ministry of chemicals and fertilizers and not the ministry of health. Hence the drug industry has been directly affected by changes occurring in India's overall industrial policy. The effects of general industrial deregulation began to be felt in the 1980s [Bidwai 1995] and these continued and accelerated in the 1990s. In the absence of a regulatory list of essential drugs, the market is flooded with irrational and expensive drugs. The non-adoption of generic names has also led to excessive branding and differential pricing which consumers are in no position to assess.

The impact of the liberalisation of the drug industry is starkly evident in spiralling costs of drugs since the 1980s. An analysis of drug prices between 1980 and 1995 revealed a 197 per cent increase overall for 778 drugs selected for study. The sharpest increases were evident in the prices of imported drugs, those that en- joyed a near monopoly as well as those used for long-term treatment. The prices of 'inessential' drugs and irrational com- binations also increased [Rane 1996].

II Health Inequity in the 1990s How have utilisation patterns been af-

fected by privatisation in the health sector? Among those who sought outpatient care in 1995-96, more than 80 per cent did so in the private sector (Table 3, Col 2, Col 4). This represents a further increase in the already dominant share of the private sector in outpatient care. What is also striking is the fall in public sector utilisation even in poorer states like Rajasthan, Assam, Orissa, and Madhya Pradesh [Iyer and Sen 2000]. The increase in utilisation of the private sector and the decline in the public sector are not, however, uniform across sub- categories. The bulk of the decline in public sector utilisation for outpatient services has been in the public hospitals whose share in rural areas fell from 17.7 to 11 per cent of the total, and from 22.6 to 15 per cent in the urban areas between the two NSS survey periods. In rural areas, the share of private hospitals also declined while the share of PHCs/CHCs in the public sector, and of nursing homes, private doctors, and 'others' in the private sector

increased. To the extent that lower level institutions such as PHCs and CHCs are picking up some of the patients who earlier would have gone without a referral directly to a hospital, this may be a trend in the direction of greater effiency of use of public sector institutions. However, clearly not all of the decline in the public hospitals was due to such shifts.

Furthermore, while there has been a small increase in hospitalisations in urban areas, there has been a sharp drop in rural areas from 28 per 1000 ailing persons in 1986-87 to just 13 per 1000 in 1995-96 [NSSO 1998:25]. The general public- private mix for in-patient care is significantly different from the mid-1980s when the public sector was still dominant (Table 4, Col 2, Col 4). In 1995-96,55 and 57 per cent respectively of those who were hospitalised went to private sector institutions in rural and urban areas respectively compared to 40 per cent in 1986- 87. The private sector clearly became the dominant provider of in-patient care during the decade. This may be partly linked to a narrowing of the cost gap between the public and private sectors as we argue in the next sub-section.

Figure 1 shows significant changes to- wards grater economic class inequality in utilisation of health facilities by in- patients in the mid- 1990s. In the rural areas the class gradient for in-patient use of public hospitals which was insignificant in the mid-1980s, has turned positive and statistically significant. This means that even public hospitals came to be used more by the better off in the 1990s. Although PHC use has not become significantly unequal, the gradient for private hospitals, nursing homes and charitable institutions, which was already positive, has become steeper and statistically significant. The overall gradient for hospital use has gone from near zero (indicating not too much inequality overall) to a highly significant positive number. In the urban areas, inequality in the use of public facilities did not woren significantly but inequality in the use of private hospitals, nursing homes and even charitable institutions did.

Some of this increase in inequality in the utilisation of hospital facilities may be the result of attempts by both public and private health institutions to attract more paying customers who can cross-subsidise services to the poor. The pressure on institutions to do this has certainly increased in the climate of fiscal stringency preva-


Figure 1A: Class Gradients for In-patient Care by Facility: All-India, Rural, 1986-96

In-patients in Public Hospitals - Rural In-patients in PHCs - Rural Fractile Distribution 19 87,1995-96 Fracte Distribution: 1966-87, 1995-96

30 30 - y -1.2929x + 19.457

' 20 . 5 20 -_

- ' -- " 1o Q-

0 ,-'-' --, -,-,-.... ,0 ,-,-,-- , - ,-. 0 to 10 to 20 to 40 to 60 to 80 to 90 to 0 to 10 to 20 to 40 to 60 to 80 to 90 to 10 20 40 60 80 90 100 10 20 40 60 80 90 100

MPCE Fractiles MPCE Fractiles -- --. 1986-87 1995-97 - - - - -1986-87 --- 1995-97

Linear (1995-97) - - - - Linear (1986-87) Linear (1995-97) - - - - Linear (1986-87) 1986-87:-0.61 1995-96: 3.11* 1986-87:-1.29 1995-96:0.93

In-patients in Private Hospitals - Rural In-patients in Nursing Homes - Rural Fractile Distribution: 1986-87, 1995-96 Fractile Distribution: 1986-87, 1995-96

40 -40 a) 0

30 y-0.815a4x+11.024 > Jg ' y = 1.0893x + 9.9286

- 20 -A=81 . 20 - - . - - .... ---'-:- .-'

S 10- * - .* - 10- *-y- :. . y 5.6393x - 8.2571 a. .3786x - 3.2286 0 0

0 to 10 to 20 to 40 to 60 to 80 to 90 to Oto 10to 20 to 40 to 6to o 80 to 90 to 10 20 40 60 80 90 100 10 20 40 60 80 90 100

MPCE Fractiles MPCE Fracties ----- ?1986-87 --- 1995-97 ....- 1986-87 --- 1995-97 - - - - Linear (1986-87) - Linear (1995-97) - - - - Linear (1986-87) - Linear (1995-97)

1986-87:0.82 1995-96: 5.64** 1986-87:1.09 1995-96: 4.38**

In-patients in Charitable Institutions - Rural in-patients in all Hospitals - Rural Fractile Distribution: 1986-87, 1995-96 Fractile Distribution: 1986-87, 1995-96

30 40 y =0.5582x + 12.053

.? 20, g 30- y = -0.0796x + 14.604 c20 20

- ) - 20-

10 a. ? y= 3.0357x + 2.1429 CL 10 - 0 *4.1429x - 2.274 - .

Q - 10 ' '

O to 10to 20 to 40 to 60 to 80 to 90 to 0 to 10 to 20 to 40 to 60 to 80 to 90 to 10 20 40 60 80 . 90 100 10 20 40 60 80 90 100

-.- -.1986-87 ---- 1995-97 - - -- - 1986-87 ----1995-97 - Linear (1995-97) - - - - Linear (1986-87) - - - - Linear (1986-87) - Linear (1995-97)

1986-87:0.56 1995-96: 3.04* 1986-87: -0.08 1995-96: 4.14** Notes: * Implies significance at 5 per cent level. **

Implies significance at 1 per cent level.

lent in the 1990s. This would not be a problem if it made it more possible in fact for hospitals to offer in-patient services to the poor. However, the steep fall in total rural hospitalisation rates mentioned earlier, combined with increased usage by the better off suggests instead that the poor are being squeezed out.

Utilisation of the private sector is often directly related to the purchasing power of households [Sundar 1995; George et al 1997; NSSO 1998]. Debilitated public health institutions may not only have a negative impact on utilisation by the poor, but may also severely impact women's access to and utilisation of care. National

and state level studies indicate that inequalities within households mediate the distribution of benefits to certain groups. Significantly lower sums of money are spent on the treatment of women and girl children in the household for both in-patient and outpatient care [Das Gupta 1987; Sundar 1995; NSSO 1998].

For women, considerations like affordability, time, work, distances to be trav- elled and faith in the abilities of the health provider determine their access to and utilisation of care [Gupte et al 1999; Shatrugna et al 1993]. These considerations are not mutually exclusive. A group of rin women in a drought-prone area of

Maharashtra, for instance, spoke of dis- tance and time in terms of the money they would have to pay for transport or lose as wages [Gupte et al 1999]. Another study in Haryana showed that the presence of public health care facilities had a positive impact on women's utilisation of care [Rajeshwari 1996] because that entailed fewer demands on household resources.

Table 6 shows the genderwise class gradients for in-patient care by types of rural and urban institutional facilities in the mid-1990s. Such data were not available in the 1986-87 survey. The table shows significant inequality in the use of


Figure 1B: Class Gradients for In-patient Care by Facility: All-India, Urban, 1986-96

In-patients in Public Hospitals - Urban In-patients in PHCs - Urban Fractile Distribution: 1986-87, 1995-96 Fractile Distribution: 1986-87, 1995-96

401 30

- 40 2 Y0 Y= -1.5139x + 20.341 y =-1.2836x + 19.42

S 30 - .... X 20 - -

_ X 20 2

10 1'--1921 ~ 10 a. yy=0.3464x+ 12.9 1.25x 19 0 - I

0 to 10to 20 to 40 to 60 to 80 to 90 to to 10 to 20 to 40 to 60 to 80 to 90 to 10 20 40 6010 20 40 60 80 90 100

MPCE Fractiles MPCE Fractiles -- -.-- 1986-87 - 1995-97 ----- -1986-87 -* 1995-97

- Linear (1995-97) - - - -Linear (1986-87) - Linear (1995-97) - Linear (1986-87) 1986-87:-1.51 1995-96:0.35 1986-87: -1.28 1995-96: -1.25

In-patients in Private Hospitals - Urban In-patients in Nursing Homes - Urban Fractile Distribution: 1986-87,1995-96

40- 40

C) 30 - 30 y6 30 m 0 y 0= .1557x + 13.663 .C '-u X0y = 0.9736x + 10.39 S 20 --- 20

a 10 ' CL^^sLo.c LL~*-- 10

3.8857x - 1.2571 y = 3.4357x + 0.5429

0O O 0 to 10 to 20 to 40 to 60 to 80 to 90 to to 10to 20 to 40 to 60 to 80 to 90 to 10 20 40 60 80 90 100 10 20 40 60 80 90 100

MPCE Fractiles MPCE Fractiles - - -- - 1986-87 -- 1995-97 - - --- 1986-87 - 1995-97 - - - - Linear (1986-87) Linear (1995-97) - - - - Linear (1986-87) Linear (1995-97)

1986-87:0.16 1995-96: 3.44** 1986-87:0.97 1995-96: 3.89**

In-patients in Charitable Institutions - Urban In-patients in all Hospitals - Urban Fractile Distribution: 1986-87, 1995-96 Fractile Distribution: 1986-87,1995-96

40 40

30 y = -0.9846x + 18.224 30 y = -0.8104x +17.527

2 0 - 2 0 - = 10 --9=^---.-----------------------.O-l-----------------------10 .--.

0 to 10 to 20 to 40 to 60 to 80 to 90 to Oto 10to 20 to 40 to 60 to 80 to 90 to 10 20 40 60 80 90 100 10 20 40 60 80 90 100

- - ---.1986-87 -- 1995-97 - - -- 1986-87 ---- 1995-97

Linear (1995-97) - - - - Linear (1986-87) - -. - Linear (1986-87) - Linear (1995-97)

1986-87: -0.98 1995-96: 3.28* 1986-87: -0.81 1995-96:2.11

Notes: * Implies significance at 5 per cent level. ** Implies significance at 1 per cent level.

facilities (except PHCs and urban public hospitals) for both women and men.

Cost of Care

Compared to the mid-1980s, the costs of both outpatient and in-patient care have risen in rural and urban areas.13 Table 5 (Cols 3, 6, 7-8) shows that between 1986-87 and 1995-96 outpatient costs per illness episode in rural areas went up by 142 per cent in the private sector, and 77 percent in the public sector. In urban areas, private outpatient costs increased by 150 per cent compared to 124 per cent in the public sector. The urban-rural price differ-

ential for outpatient care rose from 1.04 in 1986-87 to 1.10 in 1995-96.

The trends in the costs of in-patient care between 1986 and 1996 are more dra- matic. Average costs spiralled by 436 per cent in rural and by 320 per cent in urban areas. This significantly larger rise in rural areas has resulted in a narrowing of the urban-rural expenditure differential from 1.56 to 1.22. The spiralling costs of in-patient care were also particularly evident in institutions in the public sector in contrast to the private sector in both rural and urban areas. There are opposing trends in the private-public cost ratio for outpatient and in-patient care (Table 5,

Cols 1-2, 4-5). Between 1986-87 and 1995-96, private-public cost ratio for

outpatient care increased from 1.05 to 1.44 in rural areas and from 1.08 to 1.20 in urban areas. For in-patient care in contrast, the private - public cost ratio actually fell from 2.29 to 2.07 in rural areas and from 3.13 to 2.43 in urban areas.

While the costs of all care went up significantly during the period, it is worth

noting that the cost of private outpatient care and of public in-patient care went up in comparative terms. In a sense this is a kind of 'double-whammy' for the poor since private outpatient care was not much more expensive than public care earlier,


and public in-patient care used to be much less costly compared to private care. It may also partly explain the relative increase in the share of the private sector in in-patient care, as the public sector becomes more costly in relative terms.

Lending added support to this argument is the fact that in 1995-96, hospitalisation costs to the poor in government hospitals were significantly higher than in other hospitals in the rural areas (NSSO 1998: Table 20). The average total expenditure per hospitalisation in the so-called 'free' wards of the government hospitals was more than 20 per cent higher than in other hospitals. The cost in the 'paying general' wards was about the same.

A major contributor to rising costs of outpatient and in-patient care is the esca- lation of drug prices already discussed. The rise in the cost for drugs is a result not only of increases in the actual prices of drugs, but is also affected by the prescribing practices of private practitioners who tend to substitute older drugs that may be as effective and less inexpensive with newer, more expensive drugs.

Taken together, rises in the costs of all types of care impose heavy burdens on people, especially those with few means. Prabhu et al (1995) showed that the proportion of household spending on treatment by the poorest income groups in five major states had already risen sharply between 1961 and 1987, and was higher than the average health expenditure for all income groups. District surveys in Maharashtra and Madhya Pradesh during the late 1980s and early 1990s also showed that expenditure on health as a proportion of total household consumption expenditure was higher among groups belonging to the lower socio-economic classes [Duggal with Amin 1989; George et al 1997].

On the basis of these findings, one could hypothesise that the cost of accessing health care may have had a range of possible impacts in the 1990s. These could include cutbacks on other areas of social consumption like food which itself directly impacts on health status; increased indebtedness especially among the poor; growing untreated morbidity, and greater gender and possibly age biases in health seeking behaviour. The first two of these outcomes were evidenced by a community-level study of the impact of structural adjustment on poor households in Rajasthan [ASTHA 1998]. Costs and affordability also cru- cially determine women's access to care, especially in poorer groups. In the face of

rising costs of care, it is likely that women may find it increasingly difficult to access formal care and may experience recurring untreated morbidity.

Untreated Morbidity

As we saw earlier, the quality of the morbidity data in the NSS surveys leaves a lot to be desired. Both the overall rates and the rates for women are suspiciously low when compared to community-level studies. Smaller studies report significantly higher rates of untreated morbidity. They also show that non-treatment tends to be highest in the reproductive age groups [Madhiwalla et al 2000]. Despite this caveat, the NSS data on untreated morbidity point to some trends that bear further investigation.

The mid-1990s survey shows rising morbidity rates for both women and men possibly due to better counting (Table 1, Col 2, Col 5). Untreated morbidity as such, both rural and urban, continued to be significantly higher for women. In 1995-96, the female to male ratio in untreated rural morbidity was practically unchanged at 1.14, while the urban ratio had fallen somewhat to 1.08. Somewhat surprisingly, untreated morbidity rates are lower overall than in the mid-1980s. This aggregate fall however conceals absolute increases in untreated morbidity in the bottom MPCE fractiles in both rural and urban areas. This is particularly sharp for men, while the

pattern for women is more mixed across the fractiles.

The surveys show that the rates of untreated morbidity among men showed substantial increases between 1986 and 1996 in the lowest fractile groups. In the lower most fractile, the rates went up by as much as 39 and 61 per cent in rural and urban areas respectively. In the next lowest fractile, the rates of increase were to the extent of 20 and 18 per cent. The trend begins to get reversed in the middle fractiles and this gets heightened in the top most group where rates actually fell by 17 to 18 per cent [Iyer and Sen 2000]. Since morbidity rates appear to be undercounted among the poor, the decline in untreated morbidity among the rich has led to the observed fall in the rate overall.

There is also greater inequality across economic classes as evidenced by increases in the gradients for the extent of untreated morbidity and expenditure on outpatient and in-patient care (Table 2). Figure 2 shows, that the class gradients for untreated morbidity have become significantly worse for both men and women in urban areas; there appears to have been little change in the class gradient for rural women. The worsening of the class gradient appears to have been sharper for men in both rural and urban areas.

The suspicion that health care is becoming increasingly difficult for the poorer classes to access is borne out by the reasons

Table 6: Class Gradients by Gender for In-Patient Care by Facility: All-India, 1995-96

Health Care Facility Rural Urban Male Female Male Female

Public hospitals 3.23* 2.95* 0.60 0.08 PHCs 1.40 0.58 1.19 -3.58* Private hospitals 5.71** 5.53** 3.63** 3.23** Nursing homes 4.68** 3.99** 3.85** 3.90** Charitable institutions 3.59* 2.48* 3.64** 2.82 All hospitals 4.33** 3.92** 2.26* 1.91

Source: NSSO 1998, Source Table: 12, p A-65, A-170.

Table 7: Reasons for No Treatment: All-India, 1986-96 (Percentage)

Rural Urban 1986-87 1995-96 1986-87 1995-96


Reasons for no treatment No medical facility 3 9 0 1 No faith in medicine 2 4 2 5 Long waiting 0 1 1 1 Financial reasons 15 24 10 21 Illness not "serious" 75 52 81 60 Other reasons 5 10 6 12 Total 100 99 100 101

Source: NSSO 1998, Table 4.9, p 21.


Figure 2: Class Gradients by Gender for Untreated Morbidity: All-India, 1986-96

Rates of Untreated Morbidity - Rural India 1986-96 Rates of Untreated Morbidity - Urban India 1986-96 0300 -

50 ~-~250

50 --------------------, ___________50 - y=-8.2721x + 144.18

50 0 0 to 10 to 20 to 40 to 60 to 80 to 90 to 0 to 10 to 20 to 40 to 60 to 80 to 90 to t 20 to 40 to 60 to 0 to

10 20 10 20 40 60 80 90 100 - - -- -- 1986-87 -- 1995-96 - - -- - 1986-87 * 1995-9 - - - - Linear (1986-87) - Linear (1995-96) - - - - Linear (1986-87) - Linear (1995-96)

1986-87:-18.74** 1995-96: -24.75** 1986-87: -8.27* 1995-96:-17.57*

Rates of Untreated Morbidity - Rural India Rates of Untreated Morbidity - Urban India Male Rates: 1986-96 300 Male Rates: 1986-96

300 -30

250 - y= -26.5x + 278.86 200 200 - ,

200

1oo " -:- -50 _

:_ 200 --?- -. -^ ""^r^ t^^-150- y=-15.036x + 158 150 - y= -13.436x+218.36 - - -

550 50 y= -0.0389x+ 102.15 0 -0 5

0 to 10 to 20 to 40 to 60 to 80 to 90 to Oto 10 to 20 to 40 to 60 to 80 to 90 to 10 20 40 60 80 90 100 10 20 40 60 80 90 100

---- 1986-87 -* 1995-96 - --- 1986-87 -* 1995-96 - - - Linear (1986-87)- Linear (1995-96) Linear (1995-96) - - - - Linear (1986-87)

1986-87:-13.44** 1995-96: -26.5** 1986-87:-0.04 1995-96:-15.04

Rates of Untreated Morbidity - Rural India Rates of Untreated Morbidity - Urban India Female Rates: 1986-96 Female Rates: 1986-96

300 - 300 250 - y = -22.821x + 282.71 3 250

'i 200 -- - 200 100 150 - y= 24.466x+2825 + 1 85.71 o 1 00 Y =24'466x + 288.26 o

n 50- a5 50 - X 50 y =-15.786x + 182.78

0 to 10 to 20 to 40 to 60 to 80 to 90 to0 to 20 to 40 to 60 to 80 to 90 to 10 20 40 60 80 90 10010 20 40 60 80 90 100

MPCE Fractiles MPCE Fractiles - ----. 1986-87 --1995-96 -- -*--1986-87 - 1995-96 - - - - Linear (1986-87) Linear (1995-96)- Linear (1995-96) - - - - Linear (1986-87)

1986-87: -24.47** 1995-96: -22.82** 1986-87:-15.79* 1995-96: -20.25**

Notes: * Implies significance at 5 per cent level. ** Implies significance at 1 per cent level.

that were offered forno treatment (Table 7). Compared to 1986-87, the proportion of those who were unable to access care because of 'financial reasons' went up significantly in both rural and urban areas as did the proportion who said that there was no medical facility available. Correspondingly, the proportion of those who did not consider their health problems to be 'serious' enough went down considerably.

Conclusion

The subject of health equity is a complex one with multiple determinants and various levels and dimensions. In this paper we have focused on equity by gender and

economic class in access to health services. We have also looked at how this has changed in the light of recent changes in health policy and the health system in India. Although we suspect that morbidity in general, and particularly for poor men and possibly all women, is undercounted in the NSS surveys, and despite the fact that data by economic class and gender are incomplete, this analysis shows some disturbing trends.

No one would seriously argue that health services were equitable in the country prior to the decade of the 1990s. Gender and economic class inequities were already severe. Despite attempts to develop a wide- ranging set of institutions and to provide a floor of basic services through the public

system in order to meet the goals of affordable and accessible health care for all, the reality was rather different. Public health services were poor in terms of access and quality. As a result, by the 1980s the bulk of health expenditure was out-of-pocket, and a largely unregulated private sector in health was becoming increasingly dominant. Gender and class inequity in access and cost continued to be severe. Never- theless the public sector, and especially public hospitals, did act to provide an important if inadequate alternative, especially for the poor.

Key changes during the last decade have however worked to erode health equity even further. These have included further deregulation of drug production and prices,


deterioration in public hospitals combined with growing subsidies to private hospitals, and a range of other privatisation measures with mixed and at present un- certain effects.

In this paper we have seen that, by the mid-1990s, the private sector had become dominant in terms of both outpatient and in-patient services, and that the average cost of all care (and particularly of in-patient care) has gone up significantly. Although the extent of untreated morbidity overall appears to have declined, this may be partly a sta- tistical artifact resulting from under- counting of morbidity among the poor and declines in untreated morbidity among the rich. Untreated illness among the poor has clearly increased. Inequity by economic class appears to have worsened, and the divide between rich and poor in terms of untreated illness and expenditures on health services, as well in the use of both public and private health care institutions, has grown.

Thus class-based inequalities in access to health services have clearly worsened for both men and women. Gender inequity, particularly in untreated morbidity, remains severe. However, the change in the class gradients for both untreated morbidity and hospital utilisation has been somewhat sharper for men. This relative worsening of access for poor men, even though they continue in absolute terms to be better off than poor women, may imply that poor households are now really stretched to the breaking point in terms of access and affordability of health services. It may reflect the worst kind of 'catching up' in terms of gender equality. [IS

Notes 1 For reasons of poor comparability, we have not

used the NCAER survey in our analysis [Sundar 19951.

2 Caste is obviously another major dimension of inequality. The NSS survey for the mid- 1990s provides some basic caste-related data but comparative data for the mid-1980s is not available . The caste data for the mid-1990s is difficult to interpret, and hence we have not discussed this further in this paper.

3 Some change in mindsets appears to have occurred after the International Conference on Population and Development in Cairo in 1994, but actual change on the ground is small.

4 Both surveys correctly decided that normal pregnancy and childbirth should not be treated as illness. NSS (1986-87) also excluded expenditures related to abortions and miscarriages. The later survey was meant to include complications around pregnancy and

childbirth but how well it did so is not clear. Neither survey made a special attempt to ensure that information on reproductive ill-health was

systematically collected from women. 5 There is a growing literature in high-income

countries showing that the economic class of male and female household members may not be the same because of differences in control over and access to income and other social support systems. The NSS data do not allow us however to explore such distinctions here. Other salient methodological features of the surveys are described in Annex 1 of Sen et al

(forthcoming 2002). A copy of this Annex could also be obtained by contacting the authors at [email protected].

6 Treatment costs comprise medical fees, and the cost of drugs, diagnostic facilities, institutional care and travel to the health facility. There would also be opportunity costs in terms of wages lost and hidden costs such as tips and bribes. The same absolute level of costs has a relatively higher burden on the poor and on disadvantaged women, as they have less security and control over their resources.

7 These comparisons do not take into account the possibility that patients may go to public and private services for different sets of health problems which may be intrinsically different in terms of cost.

8 The key players in the promotion of these

hospitals were equipment, pharmaceutical, health insurance and software corporations [Baru 2000].

9 The government's role in regulating the location and quality of private health services has been minimal. The absence of comprehensive legislation or regulation over their functioning has meant no standardisation or assurance of quality, or affordable pricing of such care.

10 Medical practitioners receive their 'continuing education' from medical representatives of pharmaceutical companies who tend to focus on urban doctors who prescribe more

frequently. This leads to a highly skewed distribution of information.

11 The act disallowed product patents, granted patents for processes for 5-7 years and introduced compulsory licensing in the public interest.

12 These include the call for a changeover from brand names to generic names, for the state to take complete responsibility for supporting research to develop new drugs, for a phased imposition of bans on the import of bulk drugs and for related measures to encourage indigenous manufacturing.

13 These figures have not been deflated for changes in inflation because of the difficulties in identifying and constructing an appropriate price deflator. However the implicit price deflator for the GDP during the 1990s grew at 8.6 per cent per year [World Bank 2000: Table 11]. If the costs of health services had simply kept up with this rate of inflation, costs in the mid-1990s would have been around 230 per cent of what they were a decade earlier. As can be seen, while the increases in costs of outpatient care were less than this, cost

increases for in-patient care were considerably higher.

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