Health insurance coverage and its associated factors amongst households of an urban village in Delhi

ABSTRACT

Context:

Urban poor households mostly comprising of migrants from small towns and villages are prone to residing in overcrowded, unplanned settlements, bearing a higher risk of healthcare ailments and expenditure. There is a need to assess health insurance amongst them to better understand insurance coverage, as well as their experience and attitude towards it.

Aims:

To find out the prevalence of health insurance and its associated factors amongst households of an urban village in Delhi.

Settings and Design:

A cross-sectional study amongst households that have been residing for the last year in an urban village of Delhi.

Methods and Material:

This 18-month duration study was carried out in an urban village of Delhi, where a sample size of 188 was calculated based on a study conducted in Dakshina Kannada, and households were selected using systematic random sampling. A pre-designed, pre-tested, semi-structured, and interviewer-administered questionnaire was used in Hindi to elicit and record relevant information.

Statistical analysis used:

Data was recorded and coded in MS Excel, and analysis was done using licensed IBM SPSS v. 26. Tables were generated for relevant data, and cross-tables were used to assess statistical association with Chi-square or Fisher’s Exact tests, as required. Multivariate logistic regression was applied to the variables found to have a statistically significant association in cross-tables (P < 0.05).

Results:

Almost sixty percent of study households had no health insurance coverage, while 39.4% of households had some degree of health insurance, and only 53 (28.2%) had complete health insurance coverage of all household members.

Conclusions:

Only 28.2% of households in the urban village of Aliganj, Delhi, are covered under health insurance.

Introduction

Globally, because of healthcare expenses, 100 million people are pushed into extreme poverty every year.[1] In India National Statistical Office (NSO) surveys reported that 55 million people were propelled into poverty because of out-of-pocket health expenditure during the 1994–2014 period. Out of this, nearly 38 million incurred Catastrophic health expenditure. Further, National Health Accounts Estimates have highlighted that out-of-pocket expenditure (OOPE) accounted for 63.2% of Current Health Expenditure for the year 2016–17, which is one of the highest in the world.[2]

This also reflects the minuscule government spending on healthcare, which the public must compensate for by spending more from their pockets for healthcare. In such a scenario, it becomes important to protect the population against the economically debilitating effects of healthcare costs. This is also the aim of Sustainable Development Goals (SDG) target 3.8, which other than to promote the coverage of essential health services, also emphasises decreasing the proportion of the population with significant household expenditure on health as a share of total household expenditure or income (SDG Target 3.8.2).[3]

India healthcare system has multiple forms of health insurance coverages, including state run health insurance schemes, such as Central Government Health Scheme (CGHS) and Employees State Insurance Scheme (ESIS), which are available for working people; Employer-based schemes provided by public sector organizations such as railways, defence and security forces, mining sectors, and others by offering medical services and benefits to the employee and their dependents; Central government has its flagship Pradhan Mantri Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (PM-JAY) for the rural and urban poor households providing an umbrella cover of 5 lakh rupees. India also has a burgeoning market of Private insurance companies that offer medical care insurance of various kinds through individual subscriptions. For those working in the informal sector, community-based schemes, Non-Governmental Organization (NGO) provided, and government-sponsored subsidized schemes are also there. In a few of these insurance schemes entire expenditure is borne by the insuring organization, while some have reimbursement provisions post health expenditure. Some cover the entire gamut of health conditions, while a few depend on a subscription model only.

Despite having a variety of health insurance model in India, as per the 75^th National Sample Survey Household Social Consumption data, only 14% of the rural population and 19% of the urban population have any form of health insurance coverage, and reimbursements of healthcare costs vary from 4.4% in rural to 16.8% in urban.[4]

The reason could be limited scope of state-run health insurance in terms of population that can be covered, high cost, and low reimbursement rate of private insurance providers, along with the lack of awareness, and low confidence towards health insurance, etc.

There have been only a few studies assessing health insurance and these factors amongst the urban poor.[5,6,7] To date, there is a paucity of research studying the health insurance available to households of an urban poor locality comprehensively.

Against this background, the current study was planned among the households of an urban village – a special setting characterized by unplanned and haphazard settlements, overcrowding, and poor sanitation – with the objective to find out the prevalence of health insurance and its associated factors amongst households of an urban village in Delhi.

Materials and Methods

This cross-sectional study was conducted over an 18-month period between 2019-2020 to determine health insurance coverage and its associated factors amongst households of an urban village in Delhi.

The cross-sectional study was carried out over a period of 18 months in a setting of an urban village in Aliganj, Delhi. An urban village is an unauthorized and/or unplanned settlement, where many homes have been constructed in an unplanned, haphazard manner, resulting in overcrowding, and where residential and commercial properties exist together without clear demarcation.[8] Aliganj, catering to a population of approximately six thousand inhabitants, mainly comprises of migrants from other states and villages.

The study included all households residing for >1 year in the area and had a sample size of 188 households estimated using a statistical formula, based on a study done in urban households of Dakshina Kannada by Tiwari et al.[9]

To select the participant households, systematic random sampling was used. A sampling frame having 1,668 households was adapted for systematic random sampling from a preexisting socio-demographic data of Aliganj. The first house was chosen using a random number between 1 and 9, and from then on, every subsequent house was selected by adding a sampling interval of 9. When a household selected by the above process was found locked or not having the head of household, at least 3 consecutive visits were made to contact.

Definitions

Household

A household was defined as a group of persons normally living together and taking food from a common kitchen. In a house inhabited by multiple families, a household was identified by the number of kitchens or Chulah.[10]

Head of household

The one who made all the major decisions of the household.

Study tool

A pre-designed, semi-structured questionnaire was prepared in English and then translated into Hindi. The questionnaire was pre-tested on 10 percent of the sample size in a population of a similar area, Pilanji, Delhi, before the study. Participants were interviewed to elicit relevant information regarding socio-demographic profile, health insurance, and its associated factors.

The above information was collected from the head of household for all the members of that household. Whenever possible, hospital bills, Below Poverty Line (BPL) card, etc., were checked to verify the information provided. Socio-economic status was calculated as per the revised Kuppuswamy Scale, 2019.

Statistical methods

Data entry was done in Microsoft Excel spreadsheets using variable coding. Data were verified by double entry and proofreading. Data cleaning and analysis were done using licensed IBM SPSS v. 26 (Chicago, Illinois, USA). All the variables were analysed using descriptive statistics to calculate frequency, mean, range, etc., Bivariate analysis was done to determine the association between the presence of health insurance and socio-demographic variables. Statistical tests of significance for the difference between proportions, i.e. the Chi-square test and Fisher’s exact test, were applied, and the calculated results were considered significant at a P value < 0.05.

Ethical issues

Each eligible subject was explicitly informed about the purpose of the study by the investigator, and informed consent was obtained before inclusion. Approval from the Institutional Ethical Committee was obtained before the start of the study. Privacy of subjects and confidentiality of information were maintained, and this was also explained to the subjects before inclusion.

Results

The present study was conducted in 188 households of an urban village of Delhi in 2020, wherein the heads of the households were interviewed for the study.

The study found the mean age of the head of the households in the study was 41.5 years (S.D. ±11.3), with 177 (94.1%) households’ heads being males, and most of the households (174; 92.5%) Hindu by religion. Out of 188 heads of households, 22 (11.7%) were unemployed, and the rest had some kind of employment.

The median number of members a family had was 4, and the majority (147; 78.2%) of the households had a nuclear family. As per the Modified Kuppuswamy Scale, revised for 2019, 59 (31.4%) of the study households belonged to the upper-middle socio-economic class, rest 129 (68.6%) to the lower socio-economic class. Eighty percent (151) of the households resided in rented accommodations. Seventy-nine (42.0%) households had members from vulnerable groups like children less than five years old, pregnant women and the geriatric.

Amongst the study households, only 53 (28.2%) households had complete health insurance coverage, meaning all the members were covered under one or more health insurance; the rest of the households were either partially covered (21, 11.2%) or not covered at all (114, 60.6%).

Of those 74 households who had any kind of health insurance, irrespective of complete or incomplete, the majority of the households had the Employees’ State Insurance scheme, private health insurance, and the PMJAY scheme. The source of information regarding health insurance amongst these was mostly the place of work (51, 68.9%) or friends and family (21, 28.4%). More than half (43, 58.1%) of households had monthly insurance payments for health insurance, the rest had annual, one-time, free, or they were not aware of the payments, as they were not directly involved in paying.

Those who did not have any kind of health insurance, the reasons were lack of awareness (67; 49.6%), lack of money (59; 43.7%), and 8 (5.9%) households did not feel health insurance is important, and rest 10 (7.4%) households had other reasons for not having health insurance like prior bad experience with insurance, old age, presence of morbidities which excluded them from health insurance policies, and lack of time to explore health insurance [Table 1].

Table 1.

Distribution of study households according to health insurance coverage (n=188)

	Number (%)
1. Coverage by any health insurance scheme
Complete coverage of the household	53 (28.2)
Partial coverage of the household	21 (11.2)
No coverage of the household	114 (60.6)
2. Name of the scheme (n=74)*
Employee’s State Insurance scheme	32 (43.2)
Private Insurance scheme	20 (27.0)
Pradhan Mantri Jan Arogya Yojana	11 (14.9)
Central Government Insurance Scheme	9 (12.2)
State Government Insurance Scheme	6 (8.1)
3. Ever used the insurance by anyone in the household (n=74)
Yes	21 (28.4)
No	53 (71.6)
4. Source of information about health insurance (n=74)*
Place of work	51 (68.9)
Friends and family	21 (28.4)
Other sources	15 (20.3)
5. Frequency of insurance payments (n=74)*
Monthly	43 (58.1)
Annually	15 (20.3)
Once payment	10 (13.5)
Free	5 (6.8)
Not aware	3 (4.1)
6. Reasons for partial or no health insurance coverage (n=135)*
Not aware	67 (49.6)
Lack of money	59 (43.7)
Not important	8 (5.9)
Others	10 (7.4)

*Not mutually exclusive

Almost two-thirds of the households (89, 65.9%) who did not have health insurance were interested in buying it, while the rest were either not interested or were not sure. Those who wanted to buy health insurance were interested as it can protect health expenditure, any sudden illness expenditure, or the possibility of receiving better quality of healthcare.

Of those who were not interested in buying any health insurance, the reasons cited were mainly lack of money (14; 46.7%), lack of knowledge about it (5; 16.7%), lack of any disease (5; 16.7%), perception of lack of any benefit from it (6; 20.0%), and other reasons including young age (1; 3.34%), no confidence in government schemes (1; 3.34%), prior bad experience, lack of surety of future residences (1; 3.34%), and too old an age for health insurance (1; 3.34%).

Those households who wanted to buy it, 74 (83.1%) households wanted coverage for medicines, 67 (75.3%) households wished to have hospitalization coverage, 60 (67.4%) for investigation costs, 47 (52.8%) for outpatient care, same number for accident coverage, and 43 (48.3%) households for severe diseases.

Of the 89 households who did not have health insurance and were interested, they were willing to bear the mean annual insurance cost of INR 9,066.4 (S.D. ±17,916.9), with a median of INR 3,000 [Table 2].

Table 2.

Distribution of households according to their attitude towards buying health insurance coverage (n=135)

	Number (%)
1. Interest in buying health insurance
Yes	89 (65.9)
No	30 (22.2)
Not sure	16 (11.9)
2. Reasons for interest (n=89)*
Protection against expenditure	62 (69.7)
Protection against sudden illness	24 (27.0)
Better care	6 (6.7)
3. Reasons for no interest (n=30)*
No money	14 (46.7)
No idea about it	5 (16.7)
No disease	5 (16.7)
No benefit	6 (20.0)
Other	4 (13.4)
4. What must be covered by health insurance (n=89)*
Medicines	74 (83.1)
Hospitalization	67 (75.3)
Investigations	60 (67.4)
Outpatient care	47 (52.8)
Accidents	47 (52.8)
Severe diseases	43 (48.3)
5. Amount willing to pay annually (INR) (n=89)
0–1000	32 (36.5)
1001–5000	21 (23.6)
5001–10000	14 (15.7)
10,001–20,000	16 (18.0)
>20,000	7 (7.9)

*Not mutually exclusive. Mean=INR 9,066.4±17,916.9; Median: INR 3,000, IQR: INR 11,000

The study found a statistically significant association (P < 0.05) of health insurance with socio-economic status, with a Odds’ ratio of 4.1 (CI: 1.94 – 8.7) on multivariate logistic regression All the 11 (100%) BPL households had at least one household member covered under any health insurance, against only 63 (35.6%) of non-BPL holder households having health insurance, and the association was found to be statistically significant (P < 0.05) [Table 3].

Table 3.

Association between socio-demographic characteristics of the head of the household and health insurance coverage amongst study households (n=188)

	Health Insurance coverage		Total Number (%) 188 (100)	P
	Present Number (%) 74 (39.4)	Absent Number (%) 114 (60.6)
Age (in completed years)
<60	70 (40.2)	104 (59.8)	174 (100)	0.39*
≥60	4 (28.6)	10 (71.4)	14 (100)
Sex
Male	72 (40.7)	105 (59.3)	177 (100)	0.20**
Female	2 (18.2)	9 (81.8)	11 (100)
Religion
Hindu	71 (40.8)	103 (59.2)	174 (100)	0.15*
Others	3 (21.4)	11 (78.6)	14 (100)
Education
Illiterate	3 (20.0)	12 (80.0)	15 (100)	0.11*
Literate	71 (41.0)	102 (59.0)	173 (100)
Occupation
Unemployed	10 (45.5)	12 (54.5)	22 (100)	0.53*
Gainfully employed	64 (38.6)	102 (61.4)	166 (100)
Number of family members
≤4	48 (38.7)	76 (61.3)	124 (100)	0.80*
>4	26 (40.6)	38 (59.4)	64 (100)
Socio-economic status
Middle	56 (47.9)	61 (52.1)	117 (100)	0.02*
Lower	18 (25.4)	53 (74.6)	71 (100)
Type of family
Nuclear	57 (38.8)	90 (61.2)	147 (100)	0.76*
Joint	17 (41.5)	24 (58.5)	41 (100)
House ownership
Rent	55 (36.4)	96 (63.6)	151 (100)	0.09*
Owned	19 (51.4)	18 (48.6)	37 (100)
Caste
General	36 (39.1)	56 (60.9)	92 (100)	0.96*
Other Backward Castes	24 (40.7)	35 (59.3)	59 (100)
Schedules castes and tribes	14 (37.8)	23 (62.2)	37 (100)
BPL cardholder
Yes	11 (100.0)	0 (0.0)	11 (100)	0.01**
No	63 (35.6)	114 (60.6)	177 (100)
Ration card holder
Yes	12 (32.4)	25 (67.6)	37 (100)	0.34*
No	62 (41.1)	89 (58.9)	151 (100)
State of origin
Delhi	19 (50.0)	19 (50.0)	38 (100)	0.13*
Other states	55 (36.7)	95 (63.3)	150 (100)
Vulnerable groups
Yes	35 (44.3)	44 (55.7)	79 (100)	0.38*
No	39 (35.8)	70 (64.2)	109 (100)

*Chi-square test. **Fisher Exact test. Bold values indicate statistically significant P values

Discussion

The current study found that 39.4% of the households had some degree of health insurance coverage. NSO survey 75^th round, HSC data on Health (India, 2019), on the other hand, reported that 14% of the rural population and 19% of the urban population had health expenditure coverage.[4] The higher coverage in our study could be due to the presence of better workplace regulations in Delhi and better access to health insurance policies, and NSO aggregating country-wide data. Likewise, Prinja et al.[11] (India, 2019) in their study amongst the households of 8 districts of three states in India, i.e. Gujarat, Haryana, and Uttar Pradesh, reported the coverage of health insurance to be 20%. It was reported to be highest in Gujarat (25%), followed by Haryana (23%) and Uttar Pradesh (10%). This suggests that the urban migrant population employed in Delhi has better health insurance coverage, mainly provided by employers like ESIS, and further that Delhi has a robust healthcare system, which makes it easier to access health insurance policies. In another study by Madhukumar et al.[5] (Bangalore, Karnataka; 2012) to assess awareness level and willingness to join and pay for a health insurance policy in the rural population of Bangalore, they reported 22.7% of families had an insurance policy, but only 57.3% were fully insured, and the rest were partially insured. In our study, the health coverage was higher, and further, 71.6% of those households that had health insurance had complete coverage of all the members, which highlights the stark urban-rural divide in health insurance coverage in India.

Our study reported that only 28.4% of households had ever utilized the health insurance they had. This is much less than reported by Kusuma et al. (Delhi, 2018).[7] They found that 45% of the insurance holders had utilized the insurance. The likely reason for low utilization could be the presence of multiple public healthcare facilities in the vicinity of the study area, along with the loss of time and wages involved in accessing far-distant ESI hospitals, as also reported by Kusuma et al.[7] The same reasons could justify other studies having better utilization rates.[5,6]

Almost half (49.6%) of the respondents who did not have health insurance did not know about it in our study. The study by Kusuma et al. (Delhi, 2018) reported that though 98.3% of the respondents said they were aware of health insurance, only 50.2% knew what it does, which is congruent with our findings.[7] In 2012 a study by Madhukumar et al.[5] (Bangalore, Karnataka; 2012) to assess awareness level and willingness to join and pay for a health insurance policy in the rural population, reported only 35.3% of the households had heard of health insurance, which resonated with the current study. They further reported that the major deterrents to health insurance subscription were low household income or uncertainty of income, lack of reliability on insurance, friends or relatives not having any insurance, not having adequate knowledge regarding its benefits (16%), not feeling the need (29%); which also resonate with the reasons reported in the current study for unwillingness to buy health insurance. This highlights the need for better assurance of health insurance reimbursement and ease of exercising health insurance in India, to improve the confidence amongst the poor households.

The source of information regarding health insurance was majorly (68.9%) place of work, then friends and family, or other sources like village men, insurance agents, banks, etc., On the contrary, Madhukumar et al. (Bangalore, Karnataka; 2012) study found the source of information about health insurance to be mostly TV ads, newspapers, and from health workers visiting their houses.[5] Our population comprises of migrant urban poor population which could justify the major source being their workplace, where they get social security benefits.

The expectations from health insurance have been congruent everywhere. In the current study, the households mainly wanted coverage for medicines, hospitalization coverage and investigations. In the study by Madhukumar et al.[5] (Bangalore, Karnataka; 2012) families wanted hospitalization, major and minor surgeries, and deliveries to be included in the insurance coverage. Some of them wanted total healthcare, that is, they wanted OPD charges and doctor charges to be covered or reimbursed. This is in tandem with OOPE being incurred mainly on medicines and inpatient care everywhere in India.[4]

In the current study, the mean amount of expenditure the households were willing to bear for health insurance was INR 9,066.4 (S.D. ±17,916.9), with a median of INR 3,000. The only other study to assess the same reported the willingness to pay a premium of Rs 1000 to Rs 1500.[5] As that Madhukumar et al. (Bangalore, Karnataka; 2012) study reflects almost a decade-old prices and primarily rural population, the difference could be justified.[5]

Madhukumar et al.[5] (Bangalore, Karnataka; 2012) also reported that most of the farming families in their study were willing to pay the premium on a half-yearly basis or every year, and those involved in manual or daily wages were willing to pay per month, depending on their monthly income. This reflects the choices of the households in our study, which mainly comprised migrant poor households employed in low-income jobs, as they preferred monthly premiums for health insurance.

The current study found a statistically significant association between middle socioeconomic status households and health insurance in comparison to lower socioeconomic status households (P < 0.05). Further, having a BPL card was also found to have a statistically significant association with health insurance (P < 0.05). Similar findings were reported by Prinja et al.[11] (India, 2019), where they reported health insurance was higher for BPL families.

Though the prevalence of health insurance coverage was limited in the current population, there was limited utilization and a lack of awareness about insurance. Interestingly, the study could elicit the expectation as well as willingness to pay for health insurance in the urban poor households, which highlights the unmet need for health insurance coverage amongst the urban poor.

The study shows that there is an immediate need for health insurance coverage for the urban poor households to protect them from the poverty health trap. Schemes like Ayushman Bharat PM-JAY of the Government of India should be extended to accommodate more fractions of urban poor households, along with other group insurance schemes to protect employees.

Half (49.6%) of the households were not covered under any health insurance scheme because of a lack of awareness. Mass campaigns to generate awareness about health insurance amongst the urban poor are required, along with providing simple and clear information about terms and conditions and components covered by health insurance. The awareness campaign should also include guidance on how to avail health insurance during times of need, as 71.6% of those who had health insurance reported not utilizing it.

Conclusion

The households of an urban village of Aliganj, Delhi, have low health insurance coverage (28.2%). The study advocates for the better and assured health protective mechanisms to achieve Universal health coverage and protect the urban poor from massive health expenditure.

Strengths

The study has the unique setting of studying protective mechanisms against health expenditure during the COVID-19 pandemic. There is a paucity of literature on health insurance and its associated factors in the urban population, which the current study tried to fill.

Limitations

The current study was conducted only in one urban village of Delhi, and hence, the findings of the study cannot be extrapolated to other areas of the country.

List of Abbreviations

Abbreviation	Definition
NSO	National Statistical Office
ESIS	Employee’s State Insurance scheme
PMJAY	Pradhan Mantri Jan Arogya Yojana

Conflicts of interest

There are no conflicts of interest.

Funding Statement

Nil.