Pattern of Morbidity, Health Service Utilisation and Cost ...shodhganga.inflibnet.ac.in/bitstream/10603/18184/13/13_chapter 5.p… · Simply put, a rich person may identify a relatively

Chapter V

Pattern of Morbidity, Health Service

Utilisation and Cost of Treatment

among Urban Poor: A Case Study of

Selected Slums in Delhi

The financial burden of health care is a universal issue, cutting across socio-economic

co-ordinates of households. However, health has ofter been perceived as a luxury

good 1• The perception of illness in general and severity of illness in particular has

been found to be affected by socio-economic, physiological and even psychological

characteristics of an individual. This therefore mea.'"ls that the definition of ailment is

not universal. Simply put, a rich person may identify a relatively minor indisposition

as ailment and go for treatment, while the poor might perceive an ailment only when

it is work-disabling in nature. Their subsequent choice of service providers is often in

conformity with their respective financial status. The resultant burden of illness

therefore is inherently asymmetrical as far as its nature and origins are concerned. If

we incorporate the largely urban elite specific instances of life-style diseases and

cosmetic surgeries catering to aesthetic makeovers, the issue of asymmetry only gains

further credence. This should remove any doubt whatsoever about the group that

deserves special attention when we discuss economic burden of illness. It has to be

the poor, who often continue to bear the burden of illness, long after it has been cured.

5.1: Urban Poverty in India

The United Nations estimates that the world's urban population has been growing at a

rate of 1.8 per cent annually and will soon leave behind the overall global population

1 A "luxury good" is a good for which demand incn::!s-.~ more than proportionally as income rises, in

contrast to a "necessity good" for which demand increases less than proportionally as income rises.

Thus luxury goods have a high income elasticity of demand.

growth rate of l percent (United Nations 2005). In fact, beginning 2007, more than

half of the world's population is living in cities, for the first time in history.

Developing countries like India have contributed significantly to this spmt in city

dwellers thanks to the existing rural-urban divide, in almost every aspect of economic

development. Though it is highly contentious whether the quality of life of the urban

dweller in general and the urban poor in particular, is better in a city vis-a-vis his

rural counterpart, it has in no way stymied the rapid urbanization that India has been

witnessing in recent times. 27.8 percent (Census 2001) of the country's population

live in urban areas. Though lower than the Asian average, the absolute number of

people in urban cities and towns has gone up substantially. With over 575 million

people, India will have 41 percent of its population living in cities and towns by 2030

from the present level of 286 million (United Nations 2005)

The poor constitute a sizeable proportion of our cities and towns. As per the latest

poverty figures2 released by the Planning Conm1ission of India, 25.7 per cent of the

urban inhabitants were poor i.e. they did not possess enough income to acquire a basic

minimum level of calorie based nutrition. An important dimension of urban poverty is

the status of dwelling or housing. It might be safely presumed that a substantial share

of the urban poor resides in the slums and squatter settlements that have become an

integral part of the vibrant urban economy of India. The 2001 Census enumerated

40.3 million persons comprising 22.6 percent of the total urban population in slums

(Office of the Registrar General and Census Commissioner, 2005). This is a definite

underestimate since the census enumerated slum population only in cities/towns

haying a total population of 50,000 and above, as per 1991 census. Also, the census

considered only registered slum settlements and hence ignored illegal and unlisted

slums, unrecognized squatter settlements, people living in pavements, construction

sights etc. Poor people live in slums which are overcrowded, often polluted and lack

basic civic amenities like clean drinking water and sanitation. Most of them are

involved in informal sector activities where there is constant threat of eviction,

removal, confiscation of goods and almost non-existent social security cover. A

2 Based on National Sample Sun-ey data of the latest quinquinnial round ( 61" Round) on consumption expenditure.

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substantial portion of the benefits provided by public agencies are cornered by middle

and upper income households.

Poverty in urban areas is critically influenced by labour markets. Very often incomes

are too low to purchase what is needed for long-tern1 survival and advancement

because of lack of employment opportunities, low wages and/or low returns from

informal vending or other forms of self employment. Urban households are required

to purchase essential goods and services like water, sanitation, housing, transport,

health care and even education from the market. Low pay, lack of assets and ill health

leading to further depletion of assets reduces their purchasing power and consequently

the mentioned essential goods and services prove to be way beyond their means. In

view of this cycle of lack of employment opportunities, low wages and incomes and

the inability to procure essential services from the market, households are vulnerable

to crises. With the lack of basic services, health crises in particular are widely

prevalent. Development experts and agencies concerned about poverty generally

focus on mr::U development. While the significance of rural poverty cannot be

underplayed especially in a country like India, there is a need for a better

understanding of the nature and causes of urban poverty and the underestimation of its

magnitude (Environment &Urbanization Brief, 2005).

Prevalence of the alarming phenomenon of economic burden of illness is invariant of

the place of residence of the poor households - rural or urban. However, it might be

contended that the extent and severity of the burden of disease is more in the case of

the urban poor vis-a-vis his rural counterpart. Apart from the higher cost of living and

an extremely competitive informal job market, the burden of disease among the urban

poor is enhanced, thanks to unhygienic living conditions, deplorable status of basic

necessities like water and sanitation, increased exposure to accidents and poor

environmental condition that increases the vulnerability to indispositions and hence

the economic burden. High rate of growth of urban population and consequent

increase in population residing in slums has lead to over straining of infrastructure

and deterioration in public health and wide inequalities in accessing services. Such

hostile circumstances coupled with the lack of social network and fall back options,

arguably ieads them to the "medical poverty trap".

119

5.2 The Case Study of Urban Slum: Rationale, Design and a Statistical

Summary

In order to estimate the economic burden of illness among the urban poor, a total of

150 households with at least one history of ail~ent during specified recall periods

were selected from two slums in South Delhi. The first slum viz. Vasant Vihar Coolie

Camp is a non-notified jhuggi-jhonpri colony located awkwardly close to the up

market Priya Complex, one of the busiest commercial establishments in South Delhi.

The second, Kusumpur Pahari is a notified slum, located in interior Vasant Kunj,

adjacent to a residential block consisting of Government quarters.

The rationale behind the selection of these slums arises from the fact that South Delhi

hosts two of the largest public health institutions in India viz. the All Indian Institute

of Medical Science (AIIMS) and the Safdarjang Hospital that caters to patients not

only from Delhi and its neighbours but from the whole of India and even abroad.

Again, the selected slums are situated at a distance of 7-10 kms from these institutions

which can hardly be termed as proximal, especially when the case in question is that

of a medical emergency involving the poor. Presumably, these observations do have a

bearing on the health care utilisation pattern of the slum dwellers. So in a way, the

selected sample brings in an element of randomness in the choice of medical provider

which again has a direct bearing on the financial burden of treatment.

While there is rarely any doubt regarding the service provider (public or private) that

suits the pockets of the urban poor, the randomness in choice of service provider is

further enhanced when we consider some other factors like presence of private health

institutions in the vicinity and their rates, the quality/efficacy and quantity of services

provided by both types of service providers, the general health awareness level of the

household, the occupational pattern and hence presence or absence of any formal

health insurance, etc.

5.2.1. Design of the Case Study

We proceeded to estimate the economic burden of illness among the urban poor by

canvassing a questionnaire designed to elicit responses on the type of morbidity, cost

120

(direct as well as indirect) of treatment as well as the coping mechanisms adopted to

finance the same. Responses were collected from 150 households with a history of

ailment within a brief recall period (365 days for inpatient treatment and 30 days for

outpatient treatment). Thus, this was a case of non-probabilistic purposive sampling3

whereby the detailed questionnaire was canvassed only to the households with

ailment. The methodology adopted for selection of the sample was as follows. Firstly,

a complete house listing of the slums were obtained from the local councilor in case

of Kusumpur Pahadi and from an NGO working on matemal health issues in the

Coolie Camp slum. Both the slums were found to be demarcated into blocks (5 in case

of Kusumpur Pahadi and 2 in case of Coolie Camp) for administrative purposes. As is

often the case, the blocks were different from each other in tem1s of the places of

origin of the residing households. For example, Block A in Kusumpur Pahadi largely

consisted of people from Haryana. Secondly, a total of 44 and 40 households were

randomly identified from each block for Kusumpur Pahadi and Coolie Camp

respectively, which had a case of treated ailment within the specified recall period.

Thus in effect, 300 households with ailments i.e. 220 from Kusumpur Pahadi and 80

from Coolie Camp were isolated and numbered. Thirdly, every odd numbered

household out of these 300 households were selected for canvassing of the full

questionnaire. So finally we had 150 households, 40 from the smaller Coolie Camp

and 110 from the larger Kusumpur Pahadi, with at least one history of ailment, who

were approached to divulge details on general household characteristics as well as

specific infonnation on the type of morbidity, health service utilisation and treatment

cost.

The details of the sample are given in Table 5.1. The cllfi'"erit Chapter and the next is

based on the information on morbidity and health care services collected through this

questionnaire that has been provided as . an Appendix to this chapter. As far as

possible, efforts were made to collect information relating to ailments of each

household member from the member themselves. But in spite of the best efforts, some

3 The reason was that Delhi displayed a very low incidence of morbidity (around 1.6 percent) as per the

60'h round of NSS. Purposive sampling can be very useful for situations where we need to reach a

targeted sample (households with ailments, in this case) quickly and where sampling for

proportionality is not the primary concern. With a purposive sample, we are likely to get the opinions

of our target population, but we are also likely to overweight subgroups in our population that are

more readily accessible.

121

other person of the household might have provided this information, especially for the

children and the aged persons in the household

Table 5.1: Description ofthe Sample

Coolie Camp Kusumpur Pahadi All

No. of Households surveyed 40 110 150

No. of individuals surveyed 207 664 871

No. of Ailment cases treated as Inpatient 14 39 53

No. of Ailment cases treated as Outpatient 47 Ill 158

Source: Est1mated from data collected from the case study

5.2.2 A Description of the Slums

The non-notified jhuggi-jhonpri colony at Coolie Camp, Vasant Vihar is built on land

owned by the Delhi Development Authority. The slum hosts approximately 350

households mostly from the neighbouring states of Uttar Pradesh and Rajasthan. The

slum is located along a nullah fed by sewerage from the nearby commercial and

residential establishments. The major problem for the inhabitants of this colony has

been the access to water. There are just two taps with a very infrequent supply, for the

entire slum. Supplementary arrangements of water tankers arrive at odd hours when

the male members of the household are at work. It is often not possible for women to

carry filled jerry-cans of water into their jhuggi from the main road where the tanker

is parked. Many of the jhuggis are of the unserviceable kutcha variety and measures

six by six feet, roughly. There is no toilet and the inhabitants defecate in the forest

nearby. The community toilet that had been built ceased to function due to lack of

maintenance. The drains inside the slum are open kutcha and filthy. Although there is

electricity in all the jhuggis the slum dwellers complain of disproportionately high

meter (newly installed) readings. The nearest private hospital, doctor or chemist shop

is located within a distance of 1.5 km. However the nearest government hospital or

health centre is relatively far from the slum.

Situated alongside the remnants of the endangered Delhi Ridge Area around Vasant

Kunj, Kusumpur Pahadi is a slum cluster more in the form of an urban village. It has a

population of more than twenty thousand. The settlement came into being almost 35

to 40 years back and ironically, the first settlers were labourers who built the Jawahar

Lal Nehru University. The inhabitants are more diverse vis-a-vis the Coolie Camp,

122

having settled from UP, Punjab, Haryana and MP, Himachal Pradesh, Bihar and even

West Bengal. There exists substantial disparity in access to basic services especially

water and very alanningly the division is along the lines of political leaning,

economic status and even place of domicile. However there exists a pucca motorable

road within the slum that allows for water tankers among other vehicles to serve the

farthest corner of the colony. Majority of the houses are of the serviceable kutcha

variety but without own toilet. Drainage within the clusters is of open kutcha type.

The slum is self sufficient as far as services such as provision store, chemist shop,

grocery shop, stationery shop, jewellery shop, tea stalls etc is concerned. However

medical facility available within the slum is of a rather dubious nature. There are a

number of shady clinics run by the "Bangali Daaktar"s who reportedly charge meagre

amounts and are not adequately trained in medicine. The slum dwellers are aware of

the limitations, inefficacies and in certain cases fatality of the treatment offered by

these men. Still they approach them since the direct cost and opportunity cost incurred

on treatment from their fonnal counterpmis is often high and burdensome. However,

the dearth of genuine medical facility, public or private has also allowed entry points

to some NGO's who are doing a commendable job in this area.

5.2.3 A Statistical Summary of the Sample

The households have been living in the selected slums for 18 years on an average and

a majority (95 per cent) of them have migrated from the rural areas of a different

state, predominantly a neighbouring one. The average and modal household size was

5.66 and 5 respectively. The mean age of the respondents was 23 while 4.5 per cent of

the total population was aged i.e, more than 60 years old. 48 per cent of the sample

population was females while almost 3 per cent were infants (less than equal to one

year of age). The married accounted for around 41 per cent of the population while 4

per cent were widowed or divorced. A look into their general educational level

suggests that 30 per cent of the sample were illiterate. Majority (10 per cent) of the

literate respondents quit studies after the fifth standard. However, there were very few

instances of "no-where'"' children and not a single reported case of child labour within

the selected sample. Their economic condition notwithstanding, most of the children

in the school going age were found to attend schools. Out of the 871 individuals

4 Defined as children who neither go to school nor engaged in economic activity.

123

surveyed, 303 (around 35 per cent) were currently employed, 58 per cent of whom

worked as daily wage earners. Only 14 per cent of the working populations were

salaried employees. Table Y.A.lin the appendix presents the percentage distribution

of the sample surveyed across age-group, gender, general educational level and

occupational status for the two slums.

Table V.A.2 in the appendix presents the descriptive statistics on the economic

conditions of the households surveyed. Data was collected on the monthly income of

the main earner as well as the total consumption expenditure of the household. A

considerable difference between these two variables indicates the existence of

multiple income sources for many of the households, if not all. The median of the

income variables is consistently lower than the average implying the presence of

outliers at the upper end of the income ladder. A distribution of the

households/individuals across expenditure classes show that the lower two income

classes accounted for almost 70 per cent .of the sample and a majority of the sample

households belonged to the per capita expenditure class of Rs 500 to Rs I 000.

Incidentally this class contains the official urban poverty line for the state of Delhi

which is Rs. 612.91 (Press Release, Planning Commission of India, March 2007).

Precisely, only 36 percent of the individuals in the sample were found to have a

monthly per capita income less than the official pove11y line for urban Delhi.

Academic debates regarding poverty lines notwithstanding, a visit to these slums and

a study of living standard of the inhabitants are bound to raise serious doubts

regarding official poverty measurements.

5.3: Morbidity Patterns among Urban Poor: Results from the Case

Study

The subsequent sections are based on the enquiry on morbidity and health care

conducted during the survey of the slums. The enquiry covered the curative aspects of

general health care and also the utilisation of health care services, together with the

expenditure incurred by the households for availing these services. The following

sections present the survey results relating to all these aspects viz., the utilisation of

the curative health care services, morbidity profile of the population, separately for

124

hospitalised and non-hospitalised treatment of ailments together with the estimates of

expenditure incmred for treatment of ailments. We categorise morbidity as per NSS

(60111 Round) definitions:

A. Non-hospitalised Ailment: Stands for any deviation from the state of physical

and mental well-being that may not cause any necessity of hospitalisation,

confinement to bed or restricted activity. The treatment of ailment might have

been received a outpatient of a hospital or clinic, public or private.

Reference/Recall period of30 days.

B. Hospitalisation: One was considered hospitalised if one had availed of medical

services as an indoor patient in any hospital. Reference/Recall period of 365

days.

The discussion starts with an exploration of the pattern of morbidity among the

selected slum households. Here inpatient and outpatient cases are considered together

and their distribution is displayed across certain relevant socio-economic and

demographic variables. Next, the morbidity pattern is examined separately for

inpatient and outpatient cases across nature of ailments and type of service providers.

Sections 5.4 onwards deal with the issue of expenditure on treatment, across a couple

of economic indicators pertaining to the household as well as type of ailment and

source of treatment.

Table 5.2 shows the percentage distribution of ailments treated either as outpatient or

as inpatient of a hospital across certain demographic and economic attributes. The

prime objective is to explore the presence of any pattern in the morbidity reported by

this randomly selected sample consisting of 150 households. The attributes chosen are

age-group, relation to household head, educational status, occupational status and

economic status of the ailing individual. There were 61 cases of treated ailments from

Coolie Camp and 150 cases from Kusumpur Pahadi.

125

Table 5.2: Distribution of Ailment Episodes (Inpatient+ Outpatient) bv Individual Characteristics

Coolie Camp Kusumpur Pahadi All

Male Female All Male Female All Male Female All

Age-Group

Less than equals I 5.56 13.00 8.20 5.80 1.23 3.33 5.70 3.80 4.70

2 to 4 16.67 10.00 14.75 13.04 7.41 10.00 14.30 8.50 11.40

5 to 14 16.67 12.00 14.75 17.39 14.81 16.00 17.10 14.20 15.60

15 to 24 5.56 21.00 11.48 17.39 20.99 19.33 13.30 20.80 17.10

25 to 39 25.00 32.00 27.87 18.84 32.10 26.00 21.00 32.10 26.50

40 to 59 22.22 8.00 16.39 21.74 16.05 18.67 21.90 14.20 18.00

More than equals 60 8.33 4.00 6.56 5.80 7.41 6.67 6.70 6.60 6.60

All 100 100 100 100 100 100 100 100 100

Relation to Household Male Female All Male Female All Male Female All

Head

Household head 47.22 4.00 29.51 34.78 3.70 18.00 39.05 3.77 21.33

Spouse of household head 44.00 18.03 43.21 23.33 0.00 43.40 21.80

Married child 2.78 4.00 3.28 5.80 2.47 4.00 4.76 2.83 3.79

Spouse of married child 4.00 1.64 9.88 5.33 0.00 8.49 4.27

Unmarried child 30.56 44.00 36.07 47.83 24.69 35.33 41.90 29.25 35.55

Grandchild 13.89 8.20 7.25 9.88 8.67 9.52 7.55 8.53

Father/mother (in law) 2.78 1.64 1.45 4.94 3.33 1.90 3.77 2.84

Brother/sister (in law) 2.78 1.64 2.90 1.23 2.00 2.86 0.94 1.90

All 100 100 100 100 100 100 100 100 100

Educational Status Male Female All Male Female All Male Female All

Not of school going age 16.67 20.00 18.03 23.19 12.35 17.33 20.95 14.15 17.54

Illiterate or without formal 25.00 40.00 31.15 24.64 43.21 34.67 24.76 42.45 33.65

schooling

Up to primary 27.78 20.00 24.59 10.14 20.99 16.00 16.19 20.75 18.48

Up to secondary 25.00 12.00 19.67 36.23 19.75 27.33 32.38 17.92 25.12

Higher secondary and above 5.56 8.00 6.56 5.80 3.70 4.67 5.71 4.72 5.21

All 100 100 100 100 100 100 100 100 100 - . Source. Eshmated from data collected from the case study

The highest cases of ailments were registered for the age group 25 - 39. It might be

recalled that these are apparently the most productive years in the life of an

individual. As such, the costs associated with treatment, both direct and indirect,

might be of greater significance. More than half of the ailment cases among females

within the slums were accounted for by the age groups I 5 - 24 and 25- 39. This was

primarily due to gastro-intestinal diseases and childbirth although a substantial

126

proportion of deliveries in the urban slums occur at home. Unmarried children

registered the highest cases of treated ailments followed by the household head and

his/her spouse respectively.

Table 5.3:

Occupational Status

Distribution of Ailment Episodes (Inpatient+ Outpatient) by Economic

Characteristics of the Individual

Coolie Camp Kusumpur Pahadi All

Male Female All Male Female All Male Femal

e

All

Not working 44.44 72.00 55.74 52.17 69.14 61.33 49.52 69.81 59.72

Salaried 2.78 1.64 8.70 6.17 7.33 6.67 4.72 5.69

Wage earner 30.56 8.00 21.31 30.43 8.64 18.67 30.48 8.49 19.43

Shop/trade/business 2.78 .r ····.-· • 1.64 0.95 0.00 0.47

Self-employed 16.67 9.84 8.70 1.23 4.67 I 1.43 0.94 6.16

Domestic servant 20.00 8.20 13.58 7.33 0.00 15.09 7.58

Pensioner 2.78 1.64 1.23 0.67 0.95 0.94 0.95

All 100 100 100 100 100 100 100 100 100

Consumption Expenditure Quintifes

I 16.67 8.00 13.11 13.24 30.38 22.45 14.42 25.00 19.71

II 5.56 16.00 9.84 23.53 13.92 18.37 17.31 14.42 15.87

III 22.22 8.00 16.39 30.88 24.05 27.21 27.88 20.19 24.04

IV 22.22 20.00 21.31 17.65 18.99 18.37 19.23 19.23 19.23

v 33.33 48.00 39.34 14.71 12.66 13.61 21.15 21.15 21.15

All 100 100 100 100 100 100 100 100 100

Source: Estimated from data collected from the case study

The distributions of cases of ailment across educational and econom1c categories

show that a majority of them in both the slums were illiterate. The nom1ally

observable positive education gradient in illness perception and treatment was not

evident among the slum dwellers. Intuitively, this seems reasonable since the poor

generally opt for treatment once the ailment is work disabling in nature or too severe

to bear. Hence more than perception, it is the enormity of the external manifestations

of the ailment that determine treatment seeking. Among occupation groups, the "not

working" population had the highest share of ailments. Apart from the unemployed,

this group also includes the individuals who haven't attained working age. The wage­

earners accounted for almost 20 per cent of total cases of morbidity. Thus, even if

they succeed in dealing with uncertain work and inadequate wage, physical

vulnerability often robs them of their only asset - labour. The last few rows present

127

I

;

the consumption expenditure quintile wise distribution of the hospitalisation cases.

The figures do not display any noticeable pattern that suggests the presence of an

income gradient in illness perception and consequent treatment. The following two

sections discuss the distribution of ailments across nature of ailment categories and

type <;>f service providers, followed by the patterns in treatment cost separately for

inpatient and outpatient cases within the slum households.

5.3.1 Cases of Treatment as Inpatient in 365 days preceding the Day of Survey

In all there were 53 cases of hospitalisation in the 365 days preceding the survey. Out

of them 14 (8 males and 6 females) cases were from Coolie Camp while 39 (23 males

and 16 females) were from Kusumpur Pahadi. Table 5.4 presents the distribution of

the hospitalisation cases in the two slums across ailment categories and source of

treatment. The number of such cases being very few, it is more meaningful to analyse

the distribution taking the two slums together. Hence the last three columns of Table

5.4 fonn the basis of the following discussion.

Interestingly, while the point of first consultation had been predominantly a private

doctor/institution, government institutions had a major share of hospitalisation

thereafter. Personal communication with the respondents reveal that among the cases

admitted in a private hospital there were many who first approached a public hospital.

However they were disillusioned by the long waiting time, callousness and rude

behaviour of the staff, absence of medicines and equipments etc. in a public hospital

and had to reve11 to a more expensive but less time consuming option. Under ideal

conditions they would definitely prefer a public hospital for inpatient treatment given

the relatively lower cost of treatment. But again the burden of indirect costs in tern1s

of the man days lost of the ailing as well as his attendant is potentially much higher in

case of public hospitals. It might be hypothesized therefore that for the urban poor the

burden of indirect costs of illness ·is more debilitating than that of the direct costs

which can be managed through available coping mechanisms such as borrowing. That

is precisely the reason why in spite of such meagre income, almost 44 per cent of the

inpatients were treated in private hospitals.

128

Table 5.4: Percentage distribution of hospitalised ailment cases bv treatment source and nature of

ailment

Coolie Camp Kusumpur Pahadi Total

Male Female All Male ' female All Male Female

Whom first consulted

Public 62.5 33.3 50.0 39.1 37.5 38.5 45.2 36.4

Pvt. Registered 37.5 66.7 50.0 56.5 62.5 59.0 51.6 63.6

Pvt. Unregistered 0.0 0.0 0.0 4.3 0.0 2.6 3.2 0.0

All 100 100 100 100 100 100 100 100

Type of Hospital

Government 87.5 33.3 64.3 52.2 56.3 53.8 61.3 50.0

Private 12.5 66.7 35.7 47.8 43.8 46.2 38.7 50.0

All 100 100 100 100 100 100 100 100

Ailment Category

Accident and injury 37.5 16.7 28.6 26.! 6.3 17.9 29 9.1

Cardiological 12.5 0 7.1 8.7 0 5.1 9.7 0

Fever/ENT/Anaemia!Generalised 0 0 0 13 6.3 10.2 9.7 4.5

Weakness

Gastro-intestinal 12.5 33.3 21.4 21.7 I 43.8 30.8 19.4 40.9 I Gynaecological and obstetric 0 50 21.4 0 ' i2.5 I 5.1 0 22.7

Tuberculosis 25 0 14.3 4.3 6.3 5.1 9.7 4.5

Others 12.5 0 7.1 25.9 25.2 25.8 22.5 18

All 100 100 100 100 100 100 100 100

Source: Esttmated from data collected !Tom the case study

*Others include ophthalmological, orthopaedic, respiratory, nephrological, neurological and skin diseases.

The disease w1se break up of hospitalisation cases show that gastroenterological

disorders were the major cause followed by accident and injury. This result holds no

surprise given the unsanitary and often inhuman conditions prevailing in an urban

slum. Meagre income and large families make an impa<:t on the quantity and even

quality of food and water consumed and as such diseases like diarrhoea, gastritis,

typhoid, cholera, jaundice etc. are rampant in the colonies. In addition to this, the

universal problem of alcoholism among men contributes to their health status. One of

the reasons behind so many cases of accidents and injury is that of unattended

children oweing to working parents. Gynaecological cases (including childbirth) and

diseases of the nervous system were the oLlJer rwo prevalent reasons for

hospitalisation. However the most alanning case was that of tuberculosis that

accounted for almost 8 per cent of all the hospitalis.arion cases. TB is one of the

leading causes of mortality in India killing 2 persons every three minute, nearly 1,000

129

All

41.5

56.6

1.9

100

56.6

43.4

100

20.8

5.7

7.6

28.3

9.4

7.5

20.8

100

every day (Directorate General of Health Services, MOHFW). India's DOTS (Directly

Observed Treatment, Short course) programme is the fastest expanding programme,

and the largest in the world in ten11S of patients initiated on treatment, placing more

than 100,000 patients on treatment every month. No doubt proper public intervention

can go a long way in detecting and curing this dreaded epidemic that has been found

to infect the poor disproportionately.

5.3.2 Cases of Treatment as Outpatient in 30 days preceding the Day of Survey

Next we turn to the slightly more interesting case of morbidity that does not require

inpatient treatment. It is more interesting because treatment seeking in this case is not

automati"c or inevitable. Apart from the severity of indisposition a host of other socio­

economic considerations determine an individual's treatment seeking behaviour. For

that matter even the severity of ailment is a subjective perception that might vary

across class, gender, social norms, geographical location, level of education,

occupational flexibility, economic affiuence etc. While these can be generally

classified as demand side factors, the presence or absence of adequate medical

facilities in the vicinity do constitute the supply side factor that affect health seeking

behaviour. The 61 'st round of the National Sample Survey reports "ailment not

considered serious" accounting for 50 per cent of the cases of untreated ailment spells

in urban India. The encouraging part is that such cases constituted 60 per cent of

untreated ailments in the preceding NSS round (52'nd). However since we are

concerned with economic burden of illness, the issue of untreated ailment though

extremely important is a digression.

We therefore focus on the cases of treated morbidity within the sample. The recall

period for morbidity without hospitalisation was one month. There were 158 cases of

ailments in the month preceding the survey- 47 cases from Coolie Camp and Ill

cases from Kusumpur Pahadi.

130

Table 5.5: Percentage distribution of non-hospitalised ailment cases by treatment source and nature of

ailment

Coolie Camp Kusumpur Pahadi Total

Male Female All Male Female All Male Female

Source of Treatment

Public 21.4 10.5 17.0 10~9 10.8 10.8 14.9 10.7

Private Registered 71.4 68.4 70.2 65.2 80.0 73.9 67.6 77.4

Private Unregistered 7.1 21.1 12.8 23.9 9.2 15.3 17.6 11.9

All 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Ailment Category

Accident and injury 3.6 0.0 2.1 8.7 0.0 3.6 6.8 0.0

Anaemia and generalized 0.0 5.3 2.1 0.0 9.2 5.4 0.0 8.3

weakness I Cardiological 0.0 5.3 2.1 6.5 4.6 5.4 4.1 4.8

Fever and ENT infection 39.3 36.8 38.3 21.7 18.5 19.8 28.4 22.6

Gastro-intestinal 25.0 10.5 19.1 21.7 24.6 23.4 23.0 21.4

Gynaecological and ~<etric 0.0 10.5 4.3 0.0 4.6 2.7 0.0 6.0

Nervous system 0.0 I 0.0 0.0 6.5 4.6 5.4 4.1 3.6

Ophthalmological disorder • 0.0 0.0 0.0 2.2 0.0 0.9 1.4 0.0

Orthopaedic 7.1 10.5 8.5 2.2 9.2 6.3 4.1 9.5

Respiratory including asthma 10.7 15.8 12.8 17.4 4.6 9.9 14.9 7.1

Skin disease and infection 14.3 0.0 8.5 10.9 3.1 6.3 12.2 2.4

Tuberculosis 0.0 5.3 2.1 0.0 3.1 1.8 0.0 3.6

Others 0.0 0.0 0.0 2.2 13.8 9.0 1.4 10.7

All 100 100 100 100 100 100 100 100 -

Source: Estimated from data collected from the case study

*Just one case ofhospitalisation was reported under these ailment categories

People displayed a marked preference for private sources of treatment. In about 80 per

cent of the cases a private doctor was approached for treatment. This is in contrast to

the cases of hospitalisation where people generally preferred a public hospital though

the first consultation might have been with a private source. The most appalling

finding however is that almost 15 per cent of the ailing sample opted for treatment

from an unregistered private practitioner. These are none other than "quacks", locally

known as the "bangali daaktar" who are quite conspicuous within the slums. They

attract a lot of patients oweing to their locational utility and low charges which would

be made clear in the following section on expenditure. The direct as well as the

indirect cost associated with treatment from the fonnal counterparts is so high that the

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All

12.7

72.8

14.6

100.0

3.2

4.4

4.4

25.3

22.2

3.2

3.8

0.6

7.0

10.8

7.0

1.9

6.3

100

slum dwellers are compelled to opt for treatment, which by their own admission, is of

dubious quality. The status of and the lack of confidence on public institutions is

amply demonstrated by the fact that as low as 12 per cent of the ailing individuals

opted for that mode of treatment. Fever, gastro-intestinal diseases and respiratory

diseases including asthma were the three major causes, together constituting around

60 per cent of all ailments.

The present discussion identifies the pattern of morbidity within the selected slum

households and its variation across socio-economic and demographic traits. The

principle objective of the study being the analysis of economic burden amorig the

urban poor, we now focus on the cost of treatment incurred by these households and

explore the variations, separately for inpatient and outpatient cases. Components of

medical expenditure included fees for doctors/surgeons, other specialists, cost of

medicines, diagnostic tests, bed charges (for inpatients only), attendant charges,

expenditure on physiotherapy, personal medical appliances, food, blood, oxygen

cylinder etc., ambulance services and expenditure not reported elsewhere5. Associated

expenditure on hospitalisation included transport cost other than ambulance, lodging

charges of escort(s) and others. In most of the cases the respondent failed to

remember the expenditure incurred under detailed heads. However they could recall

with considerable certainty, the total expenditure on hospitalisation.

5.4 Direct Cost of Treatment

Inpatient

The average duration of stay in a hospital was 13 days. The median total expenditure,

which in the current case is a better measure of central tendency, was fount to be Rs.

6100 per treated case as an inpatient of a hospital. Table 5.6 presents the descriptive

statistics on expenditure figures disaggregated by slum. It reveals that both medical

and associated and hence total expenditure was higher for the smaller Coolie Camp

vis-a-vis the Kusumpur Pahadi slum. The maximum expenditure (50,000) incurred on

hospitalisation however was from the Kusumpur Pahadi slum. This was the case of a

5 ·E'tpenditure not reported elsewhere' refers to a lump sum payment for a number of goods and

services taken together which the respondent is unable to categorically recall.

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23 year old boy who met with a dreadful road accident in which his ann was severed

from the body. He was admitted at the AIIMS and stayed there for 22 days. The

family hails from Uttaranchal and owns two stationery shops in the slum. They could

survive the crisis on account of their moderately comfortable financial position and a

good social network.

Table 5.6: Descriptive statistics of expenditure (in Rs.) on hospitalisation across the slums

Medical Expenditure Associated Expenditure Total Expenditure

Slum Min Max Med Avg Min Max Med Avg Min Max Med Avg

Coolie 1037 1000 22000 7000 9523 0 3000 500 850 1450 23000 8500

Camp(l4) 3

Kusumpur 600 50000 5000 7874 0 5000 100 358 800 50000 6000 8232

Pahadi(39)

All (53) 600 50000 6000 8287 0 5000 200 481 800 50000 6100 8767

Source: Estimated from data collected from the case study Min- Minimum, Max- Maximum, Med- Median, Avg- Average

A more interesting picture emerges when we compare inpatient expenditure by type

of hospital and ailment categories. As might be anticipated, the average expenditure

on private inpatient treatment was higher than that in a public hospitaL

Gynaecological and obstetric ailments proved to be the most expenstve to treat

followed by accidents and injury. Surprisingly the average treatment cost of

tuberculosis was considerably high notwithstanding the huge amount of public

expenditure being channeled in the anti-TB programme by the government.

Table 5. 7: Average hospitalisation expenditure (in Rs.) by source of treatment and nature of ailment.

Medical Associated

Expenditure Expenditure Total Expenditure

Type Of Ailments Median Mean Median Mean Median Mean

Accident and injury 7000 12818 200 445 8000 13264

Cardiological 4000 8500 300 1767 4300 10267

Fever/ENT/Anaemia!Generalised Weakness 4250 4625 525 263 4775 2444

Gastro-intestinal 3500 4771 0 93 3500 4864

Gynaecological and obstetric 17000 13000 1000 1100 20000 14100

Tuberculosis 6250 5950 400 738 7400 6688

Others 5000 8209 100 364 6500 8573

Type Of Hospital Median Mean Median Mean Median Mean

Government 4500 7427 200 447 4750 7873

Private 7050 9459 O· 527 7400 9986

All 6000 8287 200 481 6100 8767

Source: Estimated from data collected from the case study

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Table 5.8 presents the average expenditure on inpatient treatment across occupation of

the main earner and monthly per capita expenditure quintiles of the affected

households. The distribution of hospitalisation expenditure across occupational

categories of the main earner in the household shows that the self employed registered

the maximum average expenditure on inpatient treatment although the highest number

of inpatient cases occurred among the wage earning households. There was no

discernable pattern in the expenditure class wise variation of hospitalisation

expenditure. This can be attributed to the unavoidability of the type of expenditure we

are discussing.

Table 5.8: Average hospitalisation expenditure (in Rs.) across occupation category and expenditure

guintile

Medical Expenditure Associated Expenditure Total Expenditure

Occupation of the Main Earner Median Mean Median Mean Median Mean

Salaried 5500 7575 0 275 6000 7850

Wage earner 6000 7423 200 632 6200 8055

Shop/trade/business • 50000 50000 0 0 50000 50000

Self-employed 7000 9700 200 540 8500 10240

Domestic help .7000 7550 100 125 7200 7675

Pensioner 4000 3833 0 0 4000 3833

Expenditure quintiles Median Mean Median Mean Median Mean

I 5000 6313 200 431 5750 6744

II 7500 10789 200 1078 7500 I 1867

Ill 5000 6391 100 591 5000 6982

IV 7000 10629 75 246 7250 10875

v 4500 7025 150 238 4650 7263

All 6000 8287 200 481 6100 8767

Source: Esllmated from data collected from the case study

*There was just one case of hospitalisation among the mentioned group which incurred exceptionally high cost because of the nature and gravity of the ailment as has been discussed in the text.

Outpatient

In this section we discuss m detail the direct cost of treatment of non-hospitalised

ailments and its variation across sample subgroups. The average and median

expenditure on treatment for the entire sample were Rs. 615 and Rs. 305 respectively.

Medical expenditure and total expenditure on outpatient treatment was considerably

higher for the Coolie Camp as compared to Kusumpur Pahadi. The average associated

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expenditure incurred mostly on account of transport amounted toRs. 43 per capita per

month.

Table 5.9: Descriptive statistics of expenditure (in Rs.) on non-hospitalised treatment across the slums

Medical Expenditure Associated Expenditure Total Expenditure

Slum Min Max Med Avg Min Max Med Avg Min Max Med Avg

CoolieCamp(l4) 0 3000 300 490 0 500 0 43 50 3000 350 533

Kusumpur Pahadi(39) 0 4300 300 608 0 500 0 42 30 4800 300 651

All 0 4300 300 573 0 500 0 43 30 4800 305 615

Source: Estrmated from data collected from the case study Min- Minimum, Max- Maximum, Med- Median, Avg- Average

Table 5.10: Average expenditure (in Rs.) on non-hospitalised treatment by source of treatment and

nature of ailment.

Associated Medical Expenditure

Expenditure Total Expenditure

Ailment type Mean Median Mean Median Mean Median

Accident and injury 1512 1000 40 0 1552 1200

Anaemia and generalized weakness 404 465 0 0 404 465

Cardiological 697 500 3 0 700 500

Fever and ENT infection 243 198 10 0 252 198

Gastro-intestinal 887 450 69 0 956 500

Gynaecological and obstetric 612 300 40 0 652 300

Nervous system 517 500 115 75 632 550

Ophthalmological disorder * 100 100 50 50 150 150

Orthopaedic 960 260 75 100 1035 460

Respiratory including asthma 446 500 41 0 486 500

Skin disease and infection 308 200 40 50 348 300

T ubercu losi s 400 500 133 100 533 700

Others 551 425 40 0 591 475

Source of Treatment

Public 174 200 88 75 262 245

Private Registered 741 500 43 0 785 500

Private Unregistered 78 80 0 0 78 80

All 573 300 43 0 615 305

Source: Est• mated from data collected from the case study

*Just one case of hospitalisation was reported under these ailment categories

A disease specific summary of treatment cost shows that persons with accidents and

injury incurred the highest average expenditure followed by tuberculosis and diseases

of the nervous system. The most common ailment i.e., fever and ENT infection

accounted for an average cost of Rs. 252. The fact that a visit to a quack ("private

135

unregistered" formally) costs around Rs. 80 on an average probably explains why the

urban poor opt for treatment of such dubious quality, in spite of being aware of the

often limited efficacy of the medicines sold by these units. Though even this amount

corresponds to a days eaming of a casual labourer, the coiTesponding figures for the

registered private and even the public counterparts are much higher.

Table 5.11: Average expenditure (in Rs.) on non-hospitalised treatment across occupation category and

expenditure guintile

Medical Expenditure Associated Expenditure Total Expenditure

Occupation of Main Earner Mean Median Mean Median Mean Median

Salaried 744 500 38 0 782 500

Wage eamer 547 300 39 0 586 300

Shop/trade/business 233 100 100 0 333 300

Self-employed 329 230 50 25 379 325

Domestic servant 487 110 42 25 528 160

Pensioner 950 800 133 0 1083 800

Expenditure quintiles Mean Median Mean Median Mean Median

I 526 300 41 0 567 300

II 656 375 38 0 693 425

Ill 384 250 34 0 417 300

IV 706 250 67 0 773 300

v 669 450 39 0 708 450

All 573 300 43 0 615 305

Source: Estimated from data collected from the case study

Table 5.11 presents the disaggregated picture of the cost incurred on treatment as

outpatients across occupational category of the main earner of the affected household

and monthly per capita expenditure quintile. The median expenditure was highest for

the pensioners followed by the salaried. Though the average expenditure on outpatient

treatment does demonstrate a slightly positive gradient across expenditure quintiles,

the median expenditure however is not found to possess such a trait.

5.5 Indirect Cost of Illness

By indirect cost we mean foregone income due to days spent in indisposition as well

as days spent in attending to the indisposed. The question on workdays lost by the

ailing as well as the attendant was posed to all the households with history of ailment.

The results are presented in the following tables. Here we consider collectively the

136

cases of inpatient and outpatient. Hence the reference period here 1s an illness

episode.

Table 5.12: Indirect cost of illness (hospitalised+ non-hospitalised) within the sample

Statistic Ailing Attendant

Days Lost Income Loss Days Lost Income Loss

Mean 35 2877 9 858

Median 20 1500 7 600

Std. Deviation 40 3530 7 702

Minimum 2 133 I 67

Maximum 220 18333 30 3000

Source: Eshmated from data collected !Tom the case study

On an average an ailing individual lost 35 working days owemg to ailments of

varying intensity and type. The average income loss per illness episode amounted to

Rs. 2877. The median values for the same were 20 days and Rs. 1500. The number of

days lost due to ailment varied from 2 to 220 depending on whether the treatment was

undertaken as an inpatient or outpatient. Attending to the ailing member of the

household also involved loss of substantial income. The income loss varied from Rs.

67 to Rs. 3000 with an average of Rs 858. Most of the studies on health financing

tend to ignore the indirect cost of illness, especially that of the attendant.

Notwithstanding the several methodological issues that are bound to arise with the

measurement of indirect cost, the current analysis gives us a fair idea of why an

illness episode is more debilitating than it seems, to a poor household.

5.6: Conclusion

This chapter therefore makes a detailed analysis of morbidity, health service

utilisation and treatment cost of the urban poor on the basis of a case study of two

slums in South Delhi. There are certain significant observations that might essentially

have a bearing on the economic burden of illness. Firstly, the major share of ailment

cases occurred for the highly productive age group 25 to 39. Secondly, among those

working, the casual wage labourers were the most vulnerable occupational group in

terms of morbidity prevalence. Thirdly, the lower three income quintiles accounted

for almost sixty percent of all ailment cases. Fourthly, gastro-intestinal diseases

emerge as the major ailment among the sample of urban poor dwelling in slums.

137

These results were consistent for inpatient and outpatient treatment alike. Fifthly,

while people preferred the public hospital for inpatient treatment, for ailments of

relatively lesser intensity, they avoided a public source. This is in spite of the costs

being much higher in a private source. However, they have been found to adopt a

hazardous alternative of seeking treatment from unqualified doctors within the slum.

Sixthly, the high indirect cost of illness might be preventing the ailing poor to seek

treatment from a public hospital or dispensary as the whole process is admittedly time

consuming. These observations are informative enough to establish a story about the

health-poverty nexus. In the next chapter however, we try to provide sufficient

analytical and technical evidence in support of the existence of the "medical poverty

trap" among the urban poor.

138