phd thesis on health insurance in india

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• v.11(12); 2021

Original research

Impact of public-funded health insurances in india on health care utilisation and financial risk protection: a systematic review, bhageerathy reshmi.

1 Department of Health Information Management, Manipal College of Health Professions, Manipal Academy of Higher Education (MAHE), Manipal, Karnataka, India

Bhaskaran Unnikrishnan

2 Department of Community Medicine, Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, Karnataka, India

3 Department of Health Information, Public Health Evidence South Asia, Prasanna School of Public Health, Manipal Academy of Higher Education (MAHE), Manipal, Karnataka, India

Shradha S Parsekar

Ratheebhai vijayamma.

4 Manipal Institute of Communication, MAHE, Manipal, Karnataka, India

Bhumika Tumkur Venkatesh

Associated data.

bmjopen-2021-050077supp001.pdf

Data are available upon reasonable request. All data relevant to the study are included in the article or uploaded as supplementary information. The datasets used and/or analysed during the current study are available from the corresponding author on request.

Universal Health Coverage aims to address the challenges posed by healthcare inequalities and inequities by increasing the accessibility and affordability of healthcare for the entire population. This review provides information related to impact of public-funded health insurance (PFHI) on financial risk protection and utilisation of healthcare.

Systematic review.

Data sources

Medline (via PubMed, Web of Science), Scopus, Social Science Research Network and 3ie impact evaluation repository were searched from their inception until 15 July 2020, for English-language publications.

Eligibility criteria

Studies giving information about the different PFHI in India, irrespective of population groups (above 18 years), were included. Cross-sectional studies with comparison, impact evaluations, difference-in-difference design based on before and after implementation of the scheme, pre–post, experimental trials and quasi-randomised trials were eligible for inclusion.

Data extraction and synthesis

Data extraction was performed by three reviewers independently. Due to heterogeneity in population and study design, statistical pooling was not possible; therefore, narrative synthesis was performed.

Utilisation of healthcare, willingness-to-pay (WTP), out-of-pocket expenditure (including outpatient and inpatient), catastrophic health expenditure and impoverishment.

The impact of PFHI on financial risk protection reports no conclusive evidence to suggest that the schemes had any impact on financial protection. The impact of PFHIs such as Rashtriya Swasthy Bima Yojana, Vajpayee Arogyashree and Pradhan Mantri Jan Arogya Yojana showed increased access and utilisation of healthcare services. There is a lack of evidence to conclude on WTP an additional amount to the existing monthly financial contribution.

Different central and state PFHIs increased the utilisation of healthcare services by the beneficiaries, but there was no conclusive evidence for reduction in financial risk protection of the beneficiaries.

Registration

Not registered.

Strengths and limitations of this study

• Inclusion of all kinds of empirical evidence to answer the research question about impact of public-funded health insurance (PFHI) schemes in India.
• This is one of the very few reviews that has used a systematic methodology to provide latest evidence on the impact of the newly launched Pradhan Mantri Jan Arogya Yojana scheme in India.
• Choice of quality appraisal tool, due to unavailability of other tools for this kind of study, was a limitation.
• Multiple PFHI (state-specific and central) schemes in India (with different benefit packages) and modifications in the schemes due to changes in central/state governments led to high data heterogeneity.
• Due to heterogeneity in data, we could not provide the pooled estimate via meta-analysis. However, results were explained via a narrative synthesis.

Introduction

India has a complex and mixed healthcare framework with presence of parallel public and private healthcare systems. 1 2 There is a stark difference in government spending on both public and private healthcare. 3 Health policies in India have been guided by the principle of equity with prioritising the needs of the poor and underprivileged. 4 Out-of-pocket expenditure (OOPE) for health is one of the important factors while addressing the inequities in healthcare, and in India, it is an important source of healthcare financing. It is estimated that, in India, around 71% of the healthcare spending is met by OOPE. This not only is an immediate financial burden to the poor households but also pushes the households into a never-ending poverty trap. 5 Health-related OOPE poses a threat to the principle of financial risk protection and adds to the unaffordability and inaccessibility of healthcare for the poor. High OOPE also leads to catastrophic health expenditure (CHE), which is the increase in healthcare payment by a household, beyond the threshold, where the threshold is defined as the household’s income or capacity to pay. This is further divided into catastrophe 1, where healthcare OOPE exceeds by 10% of the household’s consumption expenditure, and catastrophe 2, if OOPE exceeds to more than 40% of the household’s non-food expenditure. The increase in OOPE affects the rural population marginally more than the urban population and the effect of OOPE is more pronounced among the people living below the poverty line (BPL) than those above the poverty line (APL), as BPL people are pushed more into poverty than APL, due to the high OOPE, when measured via the increase in poverty head counts. 5

Over the years, government of India has rolled out different initiatives to address the healthcare-related inequities in India. The public healthcare system was revised and reframed as the National Rural Health Mission in 2005, later restructured as National Health Mission in 2014. 5 6 Other initiatives like Janani Suraksha Yojana and the public funded health insurance (PFHI) schemes such as Rashtriya Swasthya Bima Yojana (RSBY) were also introduced to address the health inequalities, improve health outcomes and provide financial risk protection. 6 Many states sponsored health insurance (HI) schemes, viz., the Vajpayee Arogyashree Scheme (VAS) by Karnataka, Comprehensive Health Insurance Scheme (CHIS) by Kerala and Chief Minister Health Insurance Scheme (CMHIS) by Tamil Nadu, which have been introduced for ensuring financial protection of the vulnerable population.

Challenges posed by healthcare inequalities and inequities like OOPE can also be addressed via the Universal Health Coverage (UHC). The UHC, as defined by the WHO, means that all people and communities can use the promotive, preventive, curative, rehabilitative and palliative health services they need, of sufficient quality to be effective, while also ensuring that the use of these services does not expose the user to financial hardship. The UHC aims towards increasing the accessibility and affordability of healthcare for the entire population. The definition of UHC is embodied in its three objectives, that is, equity, quality and financial protection. 7

The twelfth 5-year plan of the government of India acknowledges the importance of UHC as it introduces a work plan for achieving UHC for the 1.3 billion population of the country. The agenda for this plan is based on the principle of providing affordable, accessible and good quality healthcare with financial protection to the people of the country. 8 The provision of UHC has been included in the National Health Policy of India (2017). To achieve the UHC, government of India announced the ‘Ayushman Bharat’ programme in 2018 with two initiatives, that is, (a) Health and Wellness center and (b) National health protection scheme —Pradhan Mantri Jan Arogya Yojana (PMJAY), that is intended to cover around 500 million beneficiaries (from vulnerable families) and is intended to cover up to Indian National Rupees (INR) 500 000 per family, per year, for secondary and tertiary hospitalisation. 9

The addition of PMJAY scheme to the various existing PFHI (central and state) schemes aims to increase the UHC, by increasing the affordability and accessibility of good quality healthcare. It is important to assess whether these schemes (including PMJAY) have been proven to be effective in improving health outcomes and providing financial protection to the vulnerable population. Following the principles of UHC, willingness to pay (WTP) for a particular HI scheme can also be used as an indicator to assess the affordability and effectiveness of a scheme in providing good quality healthcare. Additionally, data on beneficiaries willing to pay more or contribute more for a HI scheme (viz., CGHS) indirectly provide information on their satisfaction with the services provided by the scheme, therefore, making it an indicator to assess effectiveness of the scheme. The previous systematic review 10 on assessing the effectiveness of PFHI schemes in India was conducted before complete rolling out of the PMJAY and, therefore, did not include findings on the effectiveness of the scheme (PMJAY). Also, this review 10 did not provide information on the WTP component of assessing impact of the HI schemes. The present review was, therefore, conducted with an aim to provide information related to effectiveness of the central and state-funded HI schemes (including the PMJAY scheme) via healthcare utilisation, WTP and financial risk protection of the beneficiaries. This review was planned to answer the following research question: (a) What is the impact of PFHI schemes on access and utilisation of healthcare, willingness-to-pay and financial risk protection in India?

This systematic review follows the methodology by Cochrane handbook for systematic review of interventions 11 and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist was used to report the review. 12

Criteria for including studies in the review

• Population: population group above 18 years of age enrolled in a PFHI scheme in India.
• Intervention: HI schemes funded by either central or state government, and that covers, range of services such as hospitalisation, out-patient charges, medicine costs, treatment procedures, etc. Different PFHI schemes in India, for example, RSBY, VAS, CMHIS and PMJAY were eligible to be included. Private or community-based HIs were not eligible to be included. Mixture of HIs was excluded provided a study carried out subgroup analysis for PFHIs.
• Comparison: comparison group comprises of people who did not receive any PFHI services.
• Outcomes: this review includes the following outcomes: (a) utilisation of healthcare, (b) WTP, (c) financial risk protection measured in terms of OOPE, CHE and impoverishment.
• Study design: cross-sectional studies with comparison, impact evaluations, difference-in-differences design based on before and after implementation of the scheme, pre–post design, experimental trials and quasi-randomised trials were eligible to be included.

Search methods for identification of studies

Electronic databases such as Medline (via PubMed, Web of Science), SCOPUS, Social Science Research Network and International Initiative for impact evaluation (3ie) repository were searched from their inception until 15 July 2020; however, only English publications, published in the last 10 years were considered. References and forward citations of the included studies were scanned through for any additional eligible studies. Keywords were identified before the initiation of the search. The initial search was carried out in PubMed ( online supplemental file 1 ) and was replicated in other databases. Search was conducted by a designated information scientist.

Supplementary data

Data collection.

Result of search strategy was imported to Endnote V.X7 reference manager software. Duplicates were removed and the unique citations were exported to Microsoft Excel spreadsheet for screening.

Selection of studies

Unique citations were subjected to title and abstract screening independently by two reviewers. Eligible abstracts of all the relevant studies as per the inclusion criteria were included for full-text screening (by BTV, ER and SSP) and relevant ones from these were included for analysis. Before initiating full-text screening, we tried to retrieve the full-text articles by contacting authors of the respective articles and the full texts that were not retrieved were excluded. Disagreements were resolved by discussion or by a third reviewer.

Data extraction

Data extraction was done (by ER, BTV, SSP) using a predesigned data extraction form. Information on variables such as bibliographic details (author names, publication year, journal name); study details (information about the objectives of the study and research question addressed); study setting (name of the state, rural/urban); participant characteristics (age, gender, socioeconomic status, occupation); intervention details (name and type of HI, mode of delivery of the HI, incentives given, healthcare services covered, time duration of seeking HI, any additional HIs); comparison details; outcome details (information about changes in accessibility of healthcare, utilisation of healthcare services, OOPE, WTP, health outcomes like morbidity and mortality, measurement of the outcomes, method used for measurement, time at which the outcome was measured) and study design details (type of study design and analysis) were extracted.

After pilot testing of the data extraction form, it was revised according to the modifications suggested by the team. Disagreements among the reviewers, during data extraction, were resolved by consensus, if still not resolved, third reviewer was approached for resolving the disagreements. Extracted data from all the included studies were cross-checked and independent extraction was done for one-third randomly selected studies.

Methodological quality

The methodological quality of the included studies was assessed using Effective Public Health Practice Project Quality Assessment Tool (EPHPP). 13 This tool assesses methodological quality of the quantitative studies based on questions under the following seven domains, that is, (a) selection bias, (b) study design, (c) confounders, (d) blinding, (e) data collection method, (f) withdrawals and dropouts, (g) intervention integrity and (h) analysis. Quality assessment using this scale was performed independently by reviewers in groups of two. After discussion, global rating for the scale was followed and studies were marked as (1) methodologically strong, if none of the domains had any weak rating, (2) moderate, if at least one domain was marked as weak and (3) weak, if two or more domains were marked as weak. Quality assessment was performed using Microsoft excel spreadsheet.

Data analysis

Due to heterogeneity in data, narrative synthesis was performed to answer the research question. The results are summarised based on outcomes and types of PFHIs. The effect measures of included studies such as mean difference or correlation coefficients with appropriate CI and/or p values are reported.

Public and patient involvement

We did not involve public or patient during the process of this review.

The literature search on electronic databases generated 555 citation yield, out of which 179 were duplicates. Additionally, 17 records were identified from forward and backward reference checking. After title and abstract screening of 393 citations, 157 were included for full-text screening, of which finally 25 articles were included for data synthesis. Schematic representation of the selection process is shown in figure 1 .

PRISMA flow diagram. PFHI, public-funded health insurance; PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses.

Characteristics of included studies

The summary of study characteristics is given in table 1 and the detailed characteristics of included studies are given in online supplemental file 1 .

Summary characteristics of included studies

Impact of PFHI on financial risk protection, utilisation of healthcare and WTP

This systematic review provides evidence on the impact of different PFHI schemes that have been operational in India. These schemes are funded by the central government, viz., RSBY, CGHS, Employee State Insurance Scheme, Swavlamban, Nirmaya-Disability Health Insurance Scheme and PMJAY and by the state governments like VAS (Karnataka), Rajiv Arogya Shree (Andhra Pradesh) and CHIS (Tamil Nadu). The eligibility criteria and benefits offered under each scheme vary according to different state governments. More information on these PFHI schemes is given in box 1 .

Central and state-sponsored PFHI schemes in India

Central-funded health insurance schemes

• Rashtriya Swasthya Bima Yojana—RSBY (2008) is a central-funded health insurance scheme in which 75% of the annual premium is provided by the central government and rest 25% by the state governments. In-patient expenditure of upto Indian National Rupees (INR) 30 000 per family per annum is insured for below poverty line families. Unorganised sector is also covered under this scheme.
• Prime Minister’s Jan Arogya Yojana—PMJAY (2018) is a fully government sponsored scheme, which provides a cover of INR 500 000 per family per year in government empanelled public and private hospitals of India, for secondary and tertiary-level hospitalisation. Vulnerable and below the poverty line (BPL) families are eligible to avail the services under this scheme.
• Central Government Health Scheme (1954) is eligible for central government employees and pensioners enrolled under the scheme. According to this scheme, inpatient services at the government empanelled hospitals, outpatient services including medicines, consultation by experts, maternity and child health services (family welfare) and medical consultation for alternative system of medicines are covered.
• Swavlamban (2015), this is a central-funded health insurance scheme for people with disabilities. Eligible population includes BPL and differently abled people with blindness, hearing impairment, leprosy-cured, locomotor disability, mental illness, etc. A sum of INR 200 000 per annum is covered and treatment of pre-existing illness is covered under the scheme.
• Nirmaya-Disability Health Insurance Scheme (2008), this central-funded health insurance scheme is specifically for people with Cerebral Palsy, autism, multiple disabilities and mental retardation. Services of upto INR 100 000 are covered under this scheme.
• Employee State insurance Scheme—Employee State Insurance Scheme(1952), this scheme is funded by the employers and staff contributions and is applicable to employees of factories and establishments drawing wages upto INR 15 000 a month. Under this scheme, a number of benefits to protect the employees or workers from illness, disability and death are paid to the beneficiaries. Benefits such as sickness benefit (70% of wages), temporary disablement benefit (90% of last wage), permanent disability benefit (90% of wage), maternity benefit (100% of wage), dependent benefit (90% of wage), INR 10000 to dependents for funeral expenses in case of death of the employees and other benefits like vocational and physical rehabilitation are given to the beneficiaries.

State government-funded health insurance schemes

• Aarogyasri Scheme (2007), this scheme is by the Telangana state and BPL families belonging to the state are eligible. Benefits include cashless transactions for treatment of extreme illness, for up to INR 200 000 per year, covered under the scheme.
• Ayushman Bharat—Mahatma Gandhi Rajasthan Swasthya Bima Yojana (2019), this scheme is by the government of Rajasthan and is formed by merging PMJAY scheme and Bhamashah Swasthya Bima Yojana. All the Rajasthani families belonging to BPL category are covered under this scheme. Under this scheme, an insured amount of INR 50 000and INR 450 000 are provided for secondary and tertiary illness, respectively.
• Chief Minister’s Comprehensive Health Insurance Scheme (2012), this is a state-funded HI scheme by government of Tamil Nadu. People belonging to families of less than INR 72 000 are annual earning or less and members of unorganised labour welfare boards, including their families are eligible. Services and benefits of up to INR 500 000 per family per year are covered under the scheme.
• Deen Dayal Swasthaya Seva Yojana (2016), by Goa government, for residents of Goa (residing for at least 5 years), central and state government employees already covered under other government health insurance benefits are eligible. Benefits include cashless inpatient services under government empanelled services. Annual coverage of upto INR 250 000 for a family of three and INR 400 000 for a family of four or more is given. Beneficiaries have to provide an annual premium of INR 200–300 to avail the benefits of the scheme.
• Dr YSR Aarogyasri Scheme (Formerly called Rajiv Arogyasri Community Health Insurance Scheme)−2007, by the Andhra Pradesh government, this scheme covers BPL families from Andhra Pradesh. Under this scheme, free end-to-end cashless services are provided for patients undergoing treatment for therapies listed by the network hospitals. Free outpatient assessments are done for patients not undergoing treatment under the sited therapies.
• Vajpayee Arogaya Shree (2009), this scheme is funded by the government of Karnataka and is applicable for BPL families from rural and urban areas of Karnataka. A total of INR 150 000 is reimbursed for services provided to five members of the beneficiary family, an extra sum of INR 50 000 per annum is provided in case-to-case basis.
• West Bengal Health for All Employees and Pensioners Cashless Medical Treatment Scheme (2014), previously known as ‘West Bengal Health Scheme’, by the government of West Bengal, this scheme is for West Bengal government employees, pensioners and their family members. Benefits include reimbursement for in-patient services in the state empaneled hospitals and outpatient services for 15 diseases mentioned in the scheme. Cashless medical treatment for up to INR 100 000 is provided for inpatient treatment.
• Yeshasvini co-operative farmer’s healthcare scheme (2003), by government of Karnataka, this scheme is for farmers who are members of the cooperative societies. According to this scheme, beneficiaries from the rural areas have to contribute INR 250 (for general category) and INR 50 (for SC/ST families) per annum. Beneficiaries from the urban areas have to contribute INR 710 (for general category) and INR 110 (for SC/ST) per annum. Benefits include inpatient services, discount rates for lab investigations, tests, outpatient services and medical emergency services due to mishaps during farming or any other agriculture related work.

Summary of the impact findings of RSBY and other PFHIs is given in tables 2 and 3 , respectively, and the detailed synthesis is provided in online supplemental file 1 .

Impact of RSBY on financial risk protection and healthcare utilisation

APL, Above poverty line; ATT, Average Treatment Effect on Treated; DID, Difference in Differences; NSSO, National Sample Survey Office; OOPE, out-of-pocket expenditure; PSM, Propensity Score Matching; RSBY, Rashtriya Swasthya Bima Yojana.

Impact of other public-funded health insurance (PFHI) schemes on financial risk protection and healthcare utilisation

OLS, Ordinary Least Squares.

Financial risk protection

Twenty-one studies measured financial risk protection, of which 17 were of strong methodological quality, 14–30 3 of moderate methodological quality 31–33 and 1 weak methodological quality. 34 Nine studies 14 16 18 19 23 25 30 32 34 reported the impact of RSBY alone on financial protection. Thirteen studies 15 17 20–22 24 26–29 31–33 provided information on the effect of different PFHI schemes (including state insurance schemes) on financial risk protection.

Three high methodological quality studies reported a reduction in in-patient OOPE for RSBY households; 14 18 30 however, the findings were not significant. One low methodological study stated that after implementation of RSBY in Maharashtra state, there was a significant increase in in-patient expenditure for both public and private healthcare. 32 RSBY did not have a significant effect on in-patient OOPE as a share of total health expenditure, this was reported by two good methodological studies. 16 19 The findings for the impact of RSBY on outpatient OOPE were mixed as out of five good methodological quality studies, two studies mentioned that RSBY led to a reduction in outpatient OOPE, 14 18 two studies reported that RSBY did not have any impact on the outpatient OOPE 16 30 and one study reported that the probability of incurring increased after implementation of RSBY. 19 It was reported that the RSBY households were less likely to incur CHE for outpatient care, in-patient care and overall CHE; 14 16 19 however, one high methodological quality study reported that there was no impact of RSBY on CHE. 25 All these findings were non-significant. The effect of RSBY on impoverishment was not clear as one study reported that RSBY had no effect on impoversihment, 16 whereas another study reported an increase in impoverishment among the Above Poverty Line (APL) housholds. 25

For other PFHI schemes, the findings for effect of HI schemes on financial risk protection were mixed. Three studies reported a reduction in OOPE for insured households, 20 21 26 whereas another study reported no effect on OOPE. 24 For households insured under VAS and RAS, no effect of these schemes was seen on OOPE. 17 One study reported a reduction in in-patient drug expenditure for RAS households; 15 however, other studies reported an increase in-patient household expenditure. 27 32 For CHIS in Tamil Nadu, one study reported no association of CHIS with size of OOPE 17 and another study reported an increase in OOPE in-patient expenditure. 33 It was reported that CHE was reduced for households enrolled under different PFHI schemes, 21 28 however, specifically for VAS, one study reported reduction in CHE, 31 and another study reported no association between CHE and insurance. 17 For CHIS and RAS, no association was reported for CHE and insurance schemes. 15 17 Enrolment in PMJAY did not decrease the OOPE or CHE of the enrolled households. 29

Due to mixed evidence reported for the impact of PFHI schemes on different financial risk protection parameters, it is not possible to conclude whether these schemes have proven to be beneficial in reducing financial risk of the beneficiaries. A summary of these findings is given in tables 2 and 3 .

Access and utilisation of health services

Overall, 16 studies assessed the impact of PFHI on access and utilisation of health services ( tables 2 and 3 ). The HI programmes were RSBY, 14 16 23 26 27 30 32 35 VAS 36 37 RAS, 17 27 32 CHIS 20 21 24 26 33 and PMJAY. 29 Of the 16 studies, 13 studies 14 16 17 20 21 23 24 26 27 29 30 36 37 were assessed to be of strong methodological quality, 32 33 2 were assessed as of moderate quality and 35 1 was rated as weak quality. The analysis that was carried out majorly to look at the impact was logistic regression, profit models and other types. The outcomes that were reported include reporting of illness or morbidity, hospitalisation rate, outpatient care and in-patient care utilisation, duration of hospitalisation and utilisation of hospital services. Findings demonstrated increased access, utilisation of healthcare (both in rural and urban areas) and hospitalisation for RSBY. 14 16 23 26 27 30 32 35 For other PFHI schemes like VAS, RAS and CHIS, an increase in utilisation of healthcare and in-patient outpatient services was reported. 20 21 24 26 32 33 36 37 No significant difference in healthcare utilisation was reported for PMJAY beneficiaries. 29

Willingness-to-pay

A high methodological study 38 reported WTP for the insurance scheme. A majority (71 per cent) of CGHS beneficiaries considered that their current contribution was low and were willing to contribute more. Only 28 per cent Ex-servicemen Contributory Health Scheme beneficiaries were willing to pay an additional monthly financial contribution for better quality healthcare under the schemes. In comparison to higher employment grade beneficiaries, the CGHS beneficiaries from low employment grade were more willing to pay an additional amount to the existing monthly financial contribution.

This review identified and provided information on the impact of different PFHI schemes (operational in India) on healthcare utilisation, WTP and financial risk protection of the beneficiaries. It was observed that although the utilisation of healthcare services via in-patient and outpatient visits increased for insured beneficiaries, there was inconclusive evidence on the impact of different PFHII schemes on financial risk protection.

Our findings report that there is no conclusive evidence to suggest that RSBY reduced the OOPE and CHE or had an impact on financial risk protection. For other PFHIs including the state-sponsored PFHIs, viz., RAS, VAS and CHIS, the findings suggest a mixed impact of these schemes on OOPE, CHE and impoverishment, leading to inconclusive evidence for financial risk protection. Our findings are similar to another systematic review, 10 which reported lack of substantial evidence for reduction in OOPE or improvement in financial risk protection by PFHI schemes in India.

For financial risk protection, varying results, from different studies for the same PFHI scheme, resulted in mixed findings for this outcome. Therefore, it was a challenge to pool evidence together and conclude on the impact of PFHI schemes on financial risk protection. One of the plausible reasons for this can be the different study designs and analysis methods used by different studies to assess the impact of financial risk protection. Also, difference in benefits packages and implementation of the scheme by various successive governments might have resulted in these mixed findings for this outcome.

One of the reasons for studies reporting no substantial impact of RSBY on financial risk protection can be the limited insurance cover, for example, INR 30 000 annually under RSBY. As the utilisation of healthcare and hospitalisation under RSBY has increased over the years, 10 it is possible that beneficiaries would have been hospitalised for hospital services of more than INR 30 000, leading to additional OOP payment. Hospitalisation for services not offered by the RSBY package and denial of hospitalisation by the empaneled hospitals has also led to an increase in OOPE. 39 Another reason for the negligible impact of RSBY in reducing OOPE, as reported in some of the studies, can be the operational or functional error of the scheme. An important component of the scheme is the insurance companies, which are responsible for enrolling beneficiaries, empaneling hospitals, processing claims and reimbursing money. Delayed reimbursement from the insurance companies leads to hospitals asking beneficiaries to buy medicines and other consumables from outside, which results in high OOPE. Additionally, as there is no incentive for the insurance companies to keep a check on the OOPE payments, hospitals might charge patients or deny reimbursement of money on trivial grounds, leading to high OOPE. 39 Another reason could be (which is based on personal experience of authors) to get an appointment for the surgery in empenelled hospitals, beneficiaries of the PFHIs usually wait for a longer period of time. Therefore, to avoid the delay in treatment, beneficiaries have to resort to OOP.

The impact of PFHIs (other than RSBY) including the state-sponsored schemes was reported to be mixed and inconclusive, similar to another systematic review that reported lack of substantial evidence of impact on OOPE for PFHI operational in low and middle-income countries (LMICs). 40 Additionally, as the functioning of any PFHI scheme depends on the governance, different governance structures and demographic profiles of the states would have led to heterogeneity in results. Poor impact of different PFHIs on financial risk protection (reported in some of the studies) can be attributed to similar factors that affect RSBY, that is, low coverage or benefits offered by the schemes leading to OOPE and CHE even for insured beneficiaries and interference or reimbursement issues due to functioning of insurance companies or ‘trusts’.

This systematic review is the first one that has focused on the impact of PMJAY. Our findings suggest that there is a lack of evidence related to the impact of PMJAY, as only one study reported the poor impact of PMJAY on reduction in OOPE and financial risk protection. The reasons for poor impact can be similar as experienced by the earlier PFHIs schemes that is, problem of ‘double billing’, private providers monopoly and administrative problems. As PMJAY is a relatively new scheme, more evidence is needed to conclude on its impact. Additionally, as the only study included in the review was specifically for the state of Chhattisgarh, availability of evidence from other states is needed to summarise the impact of this scheme.

According to our review, there was an increase in incidence of outpatient and in-patient visits and the utilisation of medical services, however, the healthcare utilisation rate differed between states. The utilisation rate increased both among rural and urban areas for the RSBY and VAS. However, there was one study that assessed healthcare utilisation for PMJAY, and the results reported no significant increase in utilisation of healthcare by the PMJAY enrolees. One plausible reason for these results could be the lack of awareness regarding PMJAY, as it is a relatively new scheme. It is not justified to conclude based on a single study, and at the same time, it is important to look into various other aspects, due to which the results of the PMJAY are insignificant in increasing healthcare utilisation. The healthcare utilisation rate was assessed in terms of reporting morbidity, hospitalisation, utilisation of inpatient and outpatient services.

Overall, majority of the evidence suggests that implementation of PFHI has increased hospitalisation and the utilisation of outpatient care. Our findings are consistent with other systematic reviews, 10 40 that is, PFHIs had a positive influence on utilisation of healthcare and hospitalisation in India and other LMICs. Although there is substantial evidence on the impact of PFHI on healthcare utilisation, more rigorous evaluation studies are required to evaluate the impact of health insurance schemes and especially the newly launched PMJAY.

It was reported that although the participants were willing to pay more, the findings for WTP are inconclusive, because the evidence is generated from a single study and the focus of the insurance was limited.

Strengths and limitations

Our review is the first comprehensive review, which has summarised the impact of PFHI schemes in India (including the new scheme of PMJAY under the Ayushman Bharat) on utilisation of healthcare and financial risk protection. One of the limitations of the review is the choice of quality assessment tool used for critical appraisal of included studies due to absence of any other valid tool for secondary data analysis. Responses to some of the questions and individual domain ratings for the EPHPP tool were subjective, although, before finalising the rating, we had a substantial discussion on every domain rating score. Additionally, the tool is used to assess quality of all the quantitative studies, which makes it very vague. Also, due to heterogeneity in methods, population and types of insurances, we could not perform meta-analysis.

Implications of practice and research

Our systematic review has vast policy and practice implications. Since UHC is one of the important components to achieve the sustainable development goals, the role of PFHI becomes even more important in providing equitable and affordable healthcare access to everyone. Financial risk protection is one of the key components of any PFHI scheme that ensures affordable healthcare for everyone. Poor impact of PFHIs on financial risk protection also indicates failure of the PFHI schemes. More research on PFHIs, especially PMJAY and its effect on financial risk protection and healthcare utilisation, are needed as this scheme is an important component of the Ayushman Bharat scheme under the UHC. Similarly, future studies can consider studying the effect of some of the state-funded insurances such as by the government of Goa and West Bengal, which also includes APL households, for which, currently, there is no evidence.

State and central governments could consider including APL households, especially middle-income group under the purview of PMJAY. There should be mechanisms to check corruption in the process of PFHI enrolment and focus could be provided to ease out the administrative difficulties faced by people at the time of claiming insurance. Future research in form of rigorous qualitative research, formative evaluations and process evaluations should be directed towards the reasons for the failure of different PFHIs in improving financial risk protection of the beneficiaries and demand-side and supply-side barriers to implementation and uptake of PFHI. Research reporting reasons for failure of the PFHIs, in improving financial protection, will help in revising and modifying the functioning and implementation of the PFHI schemes for benefit of the consumers.

PFHI schemes, viz, RSBY, VAS, RAS and CHIS have been operational in India since 2008. These schemes have been impactful in increasing healthcare utilisation in terms of outpatient and in-patient care in both rural and urban areas. However, evidence related to financial risk protection was mixed and inconclusive. The new scheme of Pradhan Mantri Jan Arogya Yojana or PMJAY has incorporated administrative and strategic changes, which were based on the shortcomings of earlier PFHIs, viz., provision of a 24-hour inquiry helpline and increased coverage of healthcare services and benefit package. However, limited evidence available on the impact of PMJAY suggests no improvement in healthcare utilisation and financial risk protection of the beneficiaries. Future research on the impact of PMJAY and reasons for failure of other PFHIs on financial risk protection need to be explored.

Supplementary Material

Acknowledgments.

We acknowledge PHRI-RESEARCH grant by Public Health Foundation of India, with the financial support of Department of Science and Technology to partially support authors to carry out this research. We would like to acknowledge the technical support provided by Public Health Evidence South Asia (PHESA), Prasanna School of Public Health (PSPH), Manipal Academy of Higher Education (MAHE), Manipal. We would like to thank Dr. Jisha B Krishnan, Research Assistant, PHESA, PSPH, MAHE, Manipal for supporting us in the title/abstract screening and quality assessment of the included studies and Dr. Vijay Shree Dhyani, Research Assistant, PHESA, PSPH, MAHE, Manipal, for supporting us in title abstract screening.

Twitter: @ParsekarShrads

Contributors: RB is the guarantor of the review. BTV, ER, RB and SSP conceptualised the topic. RV developed search strategy and conducted the search. SSP carried out title/abstract screening and BTV, ER, SSP carried out full text screening. BTV, ER and SSP extracted first round of data extraction, analysed and synthesised the data for the review. Extracted data from all the included studies was cross-checked and independent extraction was done for one third randomly selected studies by BTV, ER, SSP. Quality assessment was performed by BTV, ER, SSP. BTV, ER, SSP drafted the first version of report, which was further edited by RB, BTV, ER, RV, BU and SSP. All the authors read, provided feedback and approved the final report.

Funding: The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests: None declared.

Provenance and peer review: Not commissioned; externally peer reviewed.

Supplemental material: This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

Data availability statement

Ethics statements, patient consent for publication.

Not applicable.

Ethics approval

This study does not involve human participants.

Health insurance sector in India: an analysis of its performance

Vilakshan - XIMB Journal of Management

ISSN : 0973-1954

Article publication date: 30 November 2020

Issue publication date: 16 December 2020

Health insurance is one of the major contributors of growth of general insurance industry in India. It alone accounts for around 29% of total general insurance premium income earned in India. The growth of this sector is important from the perspective of overall growth of general insurance Industry. At the same time, problems in this sector are also many which are affecting its performance.

Design/methodology/approach

The paper provides an understanding on performance of health insurance sector in India. This study attempts to find out how much claims and commission and management expenses it has to incur to earn certain amount of premium. Methodology used for the study is regression analysis to establish relationship between dependent variable (Profit/Loss) and independent variable (Health Insurance Premium earned).

Findings of the study indicate that there is significant relationship between earned premium and underwriting loss. There has been increase of premium earnings which instead of increasing profit for the sector in fact has increased underwriting loss over the years. The earnings of the sector is growing at compounded annual growth rate of 27% still it is unable to earn underwriting profit.

Originality/value

This study is self-driven based on secondary data obtained from insurance regulatory and development authority site.

• Health insurance premium
• Management expenses
• Insurance regulatory and development authority
• Underwriting loss
• Compound annual growth rate

Dutta, M.M. (2020), "Health insurance sector in India: an analysis of its performance", Vilakshan - XIMB Journal of Management , Vol. 17 No. 1/2, pp. 97-109. https://doi.org/10.1108/XJM-07-2020-0021

Emerald Publishing Limited

Copyright © 2020, Madan Mohan Dutta.

Published in Vilakshan - XIMB Journal of Management . Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence maybe seen at http://creativecommons.org/licences/by/4.0/legalcode

1. Introduction

1.1 meaning of insurance.

Insurance is a contract between two parties where by one party agrees to undertake the risk of the other in exchange for consideration known as premium and promises to indemnify the party on happening of an uncertain event. The great advantage of insurance is that it spreads the risk of a few people over a large group of people exposed to risk of similar type.

Insurance has been identified as a sunrise sector by the financial planners of India. The insurance industry has lot of potential to grow, penetrate and service the masses of India. Insurance is all about protection. An insured needs two types of protection life and non-life. General insurance industry deals with non-life protection of the insured of which health insurance is a part.

1.2 Meaning of health insurance

Health insurance is a part of general insurance which contributes about 29% of premium amongst all other sectors of general insurance. But problems in this sector are many which is the driving force behind this study. This study will help the insurance companies to understand their performance and the quantum of losses that this sector is making over the years.

A plan that covers or shares the expenses associated with health care can be described as health insurance. These plans fall into commercial health insurance, which is provided by government, private and stand-alone health insurance companies.

Health insurance in India typically pays for only inpatient hospitalization and for treatment at hospitals in India. Outpatient services are not payable under health policies in India. The first health policy in India was Mediclaim Policy. In 2000, the Government of India liberalized insurance and allowed private players into the insurance sector. The advent of private insurers in India saw the introduction of many innovative products like family floater plans, critical illness plans, hospital cash and top-up policies.

Health insurance in India is an emerging insurance sector after life and automobile insurance sector. Rise in middle class, higher hospitalization cost, expensive health care, digitization and increase in awareness level are some important drivers for the growth of health insurance market in India.

Lifestyle diseases are on the rise. A sedentary lifestyle has pervaded our being. There is lower physical labour today than earlier and there is no reason why this would not be the trend going forward. The implication is the advent of lifestyle chronic diseases such as cardiac problems and diabetes.

In the context of the Indian health insurance industry, one could look at it both ways. Mired by low penetration and negative consumer perception about its utility are affecting the prospect of this industry. The flipside though is that we have hardly scratched the surface of the opportunity that lies in the future. It is as if the glass is half full. Much remains to be conquered and even more remains to be accomplished.

Health insurance companies needs to be optimistic and have courage to bring in innovation in the areas of product, services and distribution system. Bring it to the fold as the safety net that smartly covers and craft a health insurance plan befitting the need of the customers.

1.3 Background of health insurance sector in India

India’s tryst with health insurance programme goes back to the late 1940s and early 1950s when the civil servants (Central Government Health Scheme) and formal sector workers (Employees’ State Insurance Scheme) were enrolled into a contributory but heavily subsidized health insurance programmes. As a consequence of liberalization of the economy since the early 1990s, the government opened up private sector (including health insurance) in 1999. This development threw open the possibility for higher income groups to access quality care from private tertiary care facilities. However, India in the past five years (since 2007) has witnessed a plethora of new initiatives, both by the central government and a host of state governments also entering the bandwagon of health insurance. One of the reasons for initiating such programs may be traced to the commitment of the governments in India to scale up public spending in health care.

1.4 The need for health insurance in India

1.4.1 lifestyles have changed..

Indians today suffer from high levels of stress. Long hours at work, little exercise, disregard for a healthy balanced diet and a consequent dependence on junk food have weakened our immune systems and put us at an increased risk of contracting illnesses.

1.4.2 Rare non-communicable diseases are now common.

Obesity, high blood pressure, strokes and heart attacks, which were earlier considered rare, now affect an increasing number of urban Indians.

1.4.3 Medical care is unbelievably expensive.

Medical breakthroughs have resulted in cures for dreaded diseases. These cures however are available only to a select few. This is because of high operating and treatment expenses.

1.4.4 Indirect costs add to the financial burden.

Indirect sources of expense like travel, boarding and lodging, and even temporary loss of income account for as much as 35% of the overall cost of treatment. These facts are overlooked when planning for medical expenses.

1.4.5 Incomplete financial planning.

Most of us have insured our home, vehicle, child’s education and even our retirement years. Ironically however we have not insured our health. We ignore the fact that illnesses strike without warning and seriously impact our finances and eat into our savings in the absence of a good health insurance or medical insurance plan.

1.5 Classification of health insurance plans in India

Health insurance plans in India today can be broadly classified into the following categories:

1.5.1 Hospitalization.

Hospitalization plans are indemnity plans that pay cost of hospitalization and medical costs of the insured subject to the sum insured. There is another type of hospitalization policy called a top-up policy . Top-up policies have a high deductible typically set a level of existing cover.

1.5.2 Family floater health insurance.

Family health insurance plan covers entire family in one health insurance plan. It works under assumption that not all member of a family will suffer from illness in one time.

1.5.3 Pre-existing disease cover plans.

It offers covers against disease that policyholder had before buying health policy. Pre-existing disease cover plans offers cover against pre-existing disease, e.g. diabetes, kidney failure and many more. After waiting for two to four years, it gives covers to the insured.

1.5.4 Senior citizen health insurance.

This type of health insurance plan is for older people in the family. It provides covers and protection from health issues during old age.

1.5.5 Maternity Health insurance.

Maternity health insurance ensures coverage for maternity and other additional expenses.

1.5.6 Hospital daily cash benefit plans.

Daily cash benefits are a defined benefit policy that pays a defined sum of money for every day of hospitalization.

1.5.7 Critical illness plans.

These are benefit-based policies which pay a lump sum amount on certain critical illnesses, e.g. heart attack, cancer and stroke.

1.5.8 Disease-specific special plans.

Some companies offer specially designed disease-specific plans such as Dengue Care and Corona Kavach policy.

1.6 Strength, weakness, opportunity and threat analysis of health insurance sector (SWOT analysis)

The strengths, weaknesses, opportunities and threats (SWOT) is a study undertaken to identify internal strengths and weaknesses as well as external opportunities and threats of the health insurance sector.

1.6.1 Strengths.

The growth trend of the health insurance sector is likely to be high due to rise in per capita income and emerging middle-income group in India. New products are being launched in this sector by different insurance companies which will help to satisfy customers need. Customers will be hugely benefited when cash less facility will be provided to all across the country by all the insurance companies.

1.6.2 Weaknesses.

The financial condition of this sector is weak due to low investment in this sector. The public sector insurance companies are still dominating this industry due to their greater infrastructure facilities. This sector is prone to high claim ratio and many false claims are also made.

1.6.3 Opportunities.

The possibility of future growth of this sector is high, as penetration in the rural sector is low. The improvement of technology and the use of internet facility are helping this sector to grow in magnitude and move towards environment-friendly paperless regime.

1.6.4 Threats.

The biggest threat of this sector lies in the change in the government regulations. The profitability of this sector is affected due to increasing expenses and claims. The economic slowdown and recession in the economy can affect growth of this sector adversely. The increasing losses and need for insurance might reach a point of no return where insurance companies may be compelled to decline an insurance policy.

1.7 Political economic socio cultural and technological analysis of health insurance sector (PEST analysis)

This analysis describes a framework of macro-environmental factors used as strategic tool for understanding business position, growth potential and direction for operations.

1.7.1 Political factors.

Service tax on premium on insurance policies is being increased by the government for past few years during budget. Government monopoly in this sector came to an end after insurance companies were opened up for private participation in the year 2000. Foreign players were allowed to enter into joint venture with their Indian counterpart with 26% holding and which was further increased to 49% in the year 2015.

1.7.2 Economic factors.

The gross savings of people in India have increased significantly thereby encouraging people to buy insurance policy to cover their risks. Insurance companies are fast becoming prominent players in the security market. As these companies have huge disposable income which they are investing in the security market.

1.7.3 Socio-cultural factors.

Increase in insurance knowledge is helping people to increase their awareness about the risk to be covered through insurance. Change in lifestyle is leading to increase in risk thereby giving an opportunity to insurance companies to innovate newer products. Societal benefit is derived by transfer of risk through insurance due to improved socio-cultural environment.

1.7.4 Technological factors.

Insurance companies deals in large database and maintaining it by the application of latest technology is huge gain for this sector. Technological advancement has helped insurance companies to sale their products through their electronic portals. This has made their task of providing service to the customers easier and faster.

2. Review of literature

After opening up of the insurance industry health insurance sector has become significant both from economic and social point of view and researchers have explored and probed these aspects.

Ellis et al. (2000) reviewed a variety of health insurance systems in India. It was revealed that there is a need for a competitive environment which can only happen with the opening up of the insurance sector. Aubu (2014) conducted a comparative study on public and private companies towards marketing of health insurance policies. Study revealed that private sector services evoked better response than that of public sector because of new strategies and technologies adopted by them. Nair (2019) has made a comparative study of the satisfaction level of health insurance claimants of public and private sector general insurance companies. It was revealed that majority of the respondents had claim of reimbursement nature through third party administrator. Satisfaction with respect to settlement of claim was found relatively higher for public sector than private sector. Devadasan et al. (2004) studied community health insurance to be an important intermediate step in the evolution of an equitable health financing mechanism in Europe and Japan. It was concluded that community health insurance programmes in India offer valuable lessons for its policy makers. Kumar (2009) examined the role of insurance in financing health care in India. It was found that insurance can be an important means of mobilizing resources, providing risk protection and health insurance facilities. But for this to happen, it will require systemic reforms of this sector from the end of the Government of India. Dror et al. (2006) studied about willingness among rural and poor persons in India to pay for their health insurance. Study revealed that insured persons were more willing to pay for their insurance than the uninsured persons. Jayaprakash (2007) examined to understand the hurdles preventing the people to purchase health insurance policies in the country and methods to reduce claims ratio in this sector. Yadav and Sudhakar (2017) studied personal factors influencing purchase decision of health insurance policies in India. It was found that factors such as awareness, tax benefit, financial security and risk coverage has significant influence on purchase decision of health insurance policy holders. Thomas (2017) examined health insurance in India from the perspective of consumer insights. It was found that consumers consider various aspects before choosing a health insurer like presence of a good hospital network, policy coverage and firm with wide product choice and responsive employees. Savita (2014) studied the reason for the decline of membership of micro health insurance in Karnataka. Major reason for this decline was lack of money, lack of clarity on the scheme and intra house-hold factors. However designing the scheme according to the need of the customer is the main challenge of the micro insurance sector. Shah (2017) analysed health insurance sector post liberalization in India. It was found that significant relationship exists between premiums collected and claims paid and demographic variables impacted policy holding status of the respondents. Binny and Gupta (2017) examined opportunities and challenges of health insurance in India. These opportunities are facilitating market players to expand their business and competitiveness in the market. But there are some structural problems faced by the companies such as high claim ratio and changing need of the customers which entails companies to innovate products for the satisfaction of the customers. Chatterjee et al. (2018) have studied health insurance sector in India. The premise of this paper was to study the current situation of the health-care insurance industry in India. It was observed that India is focusing more on short-term care of its citizens and must move from short-term to long-term care. Gambhir et al. (2019) studied out-patient coverage of private sector insurance in India. It was revealed that the share of the private health insurance companies has increased considerably, despite of the fact that health insurance is not a good deal. Chauhan (2019) examined medical underwriting and rating modalities in health insurance sector. It was revealed that while underwriting a health policy one has to keep in mind the various aspects of insured including lifestyle, occupation, health condition and habits. There have been substantial studies on health insurance done in India and abroad. But there has not been any work on performance of health insurance sector based on underwriting profit or loss.

3. Research gap

After extensive review of literature it is understood that there has not been substantial study on the performance of health insurance sector taking underwriting profit or loss into consideration. In spite of high rate of growth of earned premium, this sector is unable to make underwriting profit. This is mainly because growth of premium is more than compensated by claims incurred and commission and other expenses paid. Thereby leading to growth of underwriting loss over the years across the different insurance companies covered under both public and private sector. This unique feature of negative performance of this sector has not been studied so far in India.

4. Objectives

review health insurance scenario in India; and

study the performance of health insurance sector in India with respect to underwriting profit or loss by the application of regression analysis.

5. Research methodology

The study is based on secondary data sourced from the annual reports of Insurance Regulatory Development Authority (IRDA), various journals, research articles and websites. An attempt has been made to evaluate the performance of the health insurance sector in India. Appropriate research tools have been used as per the need and type of the study. The information so collected has been classified, tabulated and analysed as per the objectives of the study.

The data is based on a time period of 12 years ranging from 2006–2007 to 2018–2019.

Secondary data analysis has been done using regression of the form: Y =   a   +   b X

The research has used SPSS statistics software package for carrying out regression and for the various graphs Microsoft Excel software has been used.

5.1 The problem statement

It is taken to be a general assumption that whenever the premium increases the profit also increases. This determines that profits are actually dependent on the premium income. Hence, whenever the premium tends to increase, the profit made also supposed to increase.

The aim of the study is to find out whether the underwriting profit of the health insurance sector is increasing or there is an underwriting loss.

The problem statement is resolved by applying regression analysis between the premium earned and underwriting profit or loss incurred. It is assumed that if the underwriting profit increases along with the premium received, then the pattern forms a normal distribution and alternate hypothesis can be accepted and if this pattern of dependability is not found then the null hypothesis will be accepted stating that there is no relation between the premium and the underwriting loss or the underwriting profit by the sector. But what is happening in this sector is the increase in premium is leading to increase in underwriting loss. So premium is negatively impacting underwriting profit which is astonishing thing to happen and is the crux of the problem of this sector.

5.1.1 Underwriting profit/loss = net premium earned – (claim settled + commission and management expenses incurred).

Underwriting profit is a term used in the insurance industry to indicate earned premium remaining after claims have been settled and commission and administrative expenses have been paid. It excludes income from investment earned on premium held by the company. It is the profit generated by the insurance company in the normal course of its business.

5.2 Data analysis

Table 1 shows that health insurance premium increased from Rs.1910 crores in 2006–2007 to Rs. 33011 crores in 2018–2019. But claims incurred together with commission and management expenses have grown from Rs. 3349 crores to Rs. 40076 crores during the same period. So the claims and management expenses incurred together is more than the health insurance premium earned in all the years of our study thereby leading to underwriting loss.

Claim incurred shown above is the outcome of the risk covered against which premium is received and commission and management expenses are incurred to obtain contract of insurance. Both these expenses are important for insurance companies to generate new business as stiff competition exists in this sector since it was opened up in the year 2000.

Figure 1 depicts the relationship between health insurance premium earned and claims and management expenses incurred by the insurance companies of the health insurance sector for the period 2006–2007 to 2018–2019.

Bar chart between premiums earned and claims and management expenses incurred show that claims and management expenses together is higher than premium earned in all the years of the study thereby leading to losses. Claims, commission and management expenses are important factors leading to the sale of insurance policies thereby earning revenue for the insurance companies in the form of premium. But proper management of claims and commission and management expenses will help this sector to improve its performance.

Table 2 provides insight into the performance of health insurance sector in India. The growth of health insurance in India has been from Rs.1909 crores for the financial year 2006–2007 to Rs. 33011crores for the financial year 2018–2019. The growth percentage is 1629% i.e. growing at an average rate of 135% per annum. Compounded Annual Growth Rate (CAGR) is working out to be 27%.

From the same table, it can be inferred that health insurance sector is making underwriting loss in all the financial years. There is no specific trend can be seen, it has increased in some years and decreased in some other years. Here underwriting loss is calculated by deducting claims and commission and management expenses incurred from health insurance premium earned during these periods.

With every unit of increase in premium income the claims incurred together with commission and management expenses paid increased more than a unit. Thereby up setting the bottom line. So instead of earning profit due to better business through higher premium income, it has incurred losses.

Underwriting principles needs to be streamlined so that proper scrutiny of each policy is carried out so that performance of this sector improves.

It is seen from Figure 2 that there is stiff rise in premium earned over the years but claims and commission and management expenses incurred have also grown equally and together surpassed earned premium. So the net impact resulted in loss to this sector which can also be seen in the figure. It is also seen that loss is increasing over the years. So, increase in earnings of revenue in the form of premium is leading to increase in losses in this sector which is normally not seen in any other sectors.

But a time will come when commission and management expenses will stabilize through market forces to minimize underwriting losses. On the other hand, it will also require proper management of claims so that health insurance sector can come of this unprofitable period.

5.3 Interpretation of regression analysis

5.3.1 regression model..

Where Y = Dependent variable

X = Independent variablea = Intercept of the lineb = Slope of the line

5.3.2 Regression fit.

Here, Y is dependent variable (Underwriting Profit or Loss) which is to be predicted, X is the known independent variable (Health Insurance Premium earned) on which predictions are to be based and a and b are parameters, the value of which are to be determined ( Table 3 ). Y =   − 1028.737 − 0.226   X

5.3.3 Predictive ability of the model.

The value of R 2 = 0.866 which explains 86.6% relationship between health insurance premium earned and loss made by this sector ( Table 4 ). In other words, 13.4% of the total variation of the relationship has remained unexplained.

4.1 Regression coefficients ( Table 5 ).

H1.1 : β = 0 (No influence of Health Insurance Premium earned on Underwriting Profit or Loss made)

5.4.1.2 Alternative hypothesis.

H1.2 : β ≠ 0 (Health Insurance Premium earned influences underwriting Profit or Loss made by this sector)

The computed p -value at 95% confidence level is 0.000 which is less than 0.05. This is the confidence with which the alternative hypothesis is accepted and the null hypothesis is rejected. Thus regression equation shows that there is influence of health insurance premium earned on loss incurred by this sector.

The outcome obtained in this analysis is not what happens normally in the industry. With the increase of revenue income in the form of premium, it may lead to either profit or loss. But what is happening surprisingly here is that increase of revenue income is leading to increase of losses. So growth of premium income instead of influencing profit is actually influencing growth of losses.

6.1 Findings

The finding from the analysis is listed below:

The average growth of net premium for the health insurance has been around 135% per annum even then this sector is unable to earn underwriting profit.

The CAGR works out to around 27%. CAGR of 27% for insurance sector is considered to be very good rate of growth by any standard.

Along with high growth of premium, claims and commission and management expenses incurred in this sector have also grown substantially and together it surpassed in all the years of the study.

Thus, growth of claims and commission and management expenses incurred has more than compensated high rate of growth of health insurance premium earned. This resulted into underwriting loss that this sector is consistently making.

Astonishing findings has been higher rate of increase of premium earnings leading to higher rate of underwriting loss incurred over the years. Even though the sector is showing promise in terms of its revenue collection, but it is not enough to earn underwriting profit.

6.2 Recommendations

COVID 19 outbreak in India has led to a spike in health-care costs in the country. So, upward revision of premium charges must be considered to see bottom line improvement in this sector.

Immediate investigation of the claim is required. This will enable the insurers to curb unfair practice and dishonest means of making a claim which is rampant in this sector.

Health insurance market is not able to attract younger generation of the society. So entry age-based pricing might attract this group of customers. An individual insured at the age 30 and after 10 years of continuous coverage the premium will be less than the other individual buying a policy at the age of 40 for the first time.

6.3 Limitations and scope of future studies

The analysis of performance of health insurance sector in India taking underwriting profit into consideration is the only study of its kind in this sector. As a result, adequate literature on the subject was not available.

Health insurance and health care are part of medical care industry and are inter dependent with each other. So performance of health insurance sector can be better understood by taking health-care industry into consideration which is beyond the scope of the study.

This sector is consistently incurring losses. So, new ideas need to be incorporated to reduce losses if not making profits.

Opportunity of the insurance companies in this sector lies in establishing innovative product, services and distribution channels. So, continuous modification by the application of research is required to be undertaken.

Health insurance sector will take a massive hit, as tax benefit is going to be optional from this financial year. This can be a subject of study for the future.

6.4 Conclusion

This sector is prone to claims and its bottom line is always under tremendous pressure. In recent times, IRDA has taken bold step by increasing the premium rate of health insurance products. This will help in the growth of this sector.

With better technological expertise coming in from the foreign partners and involvement by the IRDA the health insurance sector in India must turn around and start to earn profit.

The COVID-19 pandemic is a challenge for the health insurance industry on various fronts at the same time it provides an opportunity to the insurers to fetch in new customers.

The main reason for high commission and management expense being cut-throat competition brought in after opening up of the insurance sector in the year 2000. So, new companies are offering higher incentives to the agents and brokers to penetrate into the market. This trend needs to be arrested as indirectly it is affecting profitability of this sector.

The study will richly contribute to the existing literature and help insurance companies to know about their performance and take necessary measures to rectify the situation.

Chart on health insurance premium earned and claims and management expenses paid

Chart on performance of health insurance sector in India

Data showing health insurance premium earned and claims and management expenses paid

. Dependent variable: Underwriting profit or loss;

. Predictors: (Constant), Health insurance premium earned

Aubu , R. ( 2014 ), “ Marketing of health insurance policies: a comparative study on public and private insurance companies in Chennai city ”, UGC Thesis, Shodgganga.inflibnet.ac.in .

Chatterjee , S. , Giri , A. and Bandyopadhyay , S.N. ( 2018 ), “ Health insurance sector in India: a study ”, Tech Vistas , Vol. 1 , pp. 105 - 115 .

Chauhan , V. ( 2019 ), “ Medical underwriting and rating modalities in health insurance ”, The Journal of Inssurance Institute of India , Vol. VI , pp. 14 - 18 .

Devadasan , N. , Ranson , K. , Damme , W.V. and Criel , B. ( 2004 ), “ Community health insurance in India: an overview ”, Health Policy , Vol. 29 No. 2 , pp. 133 - 172 .

Dror , D.M. , Radermacher , R. and Koren , R. ( 2006 ), “ Willingness to pay for health insurance among rural and poor persons: Field evidence form seven micro health insurance units in India ”, Health Policy , pp. 1 - 16 .

Ellis , R.P. , Alam , M. and Gupta , I. ( 2000 ), “ Health insurance in India: Prognosis and prospectus ”, Economic and Political Weekly , Vol. 35 No. 4 , pp. 207 - 217 .

Gambhir , R.S. , Malhi , R. , Khosla , S. , Singh , R. , Bhardwaj , A. and Kumar , M. ( 2019 ), “ Out-patient coverage: Private sector insurance in India ”, Journal of Family Medicine and Primary Care , Vol. 8 No. 3 , pp. 788 - 792 .

Gupta , D. and Gupta , M.B. ( 2017 ), “ Health insurance in India-Opportunities and challenges ”, International Journal of Latest Technology in Engineering, Management and Applied Science , Vol. 6 , pp. 36 - 43 .

Hand book on India Insurance Statistics revisited ( 2020 ), “ Insurance regulatory and development authority website ”, available at: www.irda.gov.in ( accessed 2 July 2020 ).

Jayaprakash , S. ( 2007 ), “ An explorative study on health insurance industry in India ”, UGC Thesis, Shodgganga.inflibnet.ac.in .

Kumar , A. ( 2009 ), “ Health insurance in India: is it the way forward? ”, World Health Statistics (WHO) , pp. 1 - 25 .

Nair , S. ( 2019 ), “ A comparative study of the satisfaction level of health insurance claimants of public and private sector general insurance companies ”, The Journal of Insurance Institute of India) , Vol. VI , pp. 33 - 42 .

Savita ( 2014 ), “ A qualitative analysis of declining membership in micro health insurance in Karmataka ”, SIES Journal of Management , Vol. 10 , pp. 12 - 21 .

Shah , A.Y.C. ( 2017 ), “ Analysis of health insurance sector post liberalisation in India ”, UGC Thesis, Shodgganga.inflibnet.ac.in .

Thomas , K.T. ( 2017 ), “ Health insurance in India: a study on consumer insight ”, IRDAI Journal , Vol. XV , pp. 25 - 31 .

Yadav , S.C. and Sudhakar , A. ( 2017 ), “ Personal factors influencing purchase decision making: a study of health insurance sector in India ”, BIMAQUEST , Vol. 17 , pp. 48 - 59 .

Further reading

Beri , G.C. ( 2010 ), Marketing Research , TATA McGraw Hill Education Private , New Delhi, ND .

Dutta , M.M. and Mitra , G. ( 2017 ), “ Performance of Indian automobile insurance sector ”, KINDLER , Vol. 17 , pp. 160 - 168 .

Majumdar , P.I. and Diwan , M.G. ( 2001 ), Principals of Insurance , Insurance Institute of India , Mumbai, MM .

Pai , V.A. and Diwan , M.G. ( 2001 ), “ Practice of general insurance ”, Insurance Institute of India , Mumbai, MM .

Shahi , A.K. and Gill , H.S. ( 2013 ), “ Origin, growth, pattern and trends: a study of Indian health insurance sector ”, IOSR Journal of Humanities and Social Science , Vol. 12 , pp. 1 - 9 .

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Measurement of Catastrophic Health Expenditure in India: A Systematic Review and Meta-Analysis

• Systematic Review
• Published: 10 May 2024

Cite this article

• Umenthala Srikanth Reddy   ORCID: orcid.org/0000-0002-1835-6959 1  

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Introduction

The escalating burden of catastrophic health expenditure (CHE) poses a significant threat to individuals and households in India, where out-of-pocket expenditure (OOP) constitutes a substantial portion of healthcare financing. With rising OOP in India, a proper measurement to track and monitor CHE due to health expenditure is of utmost important. This study focuses on synthesizing findings, understanding measurement variations, and estimating the pooled incidence of CHE by health services, reported diseases, and survey types.

Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, a thorough search strategy was employed across multiple databases, between 2010 and 2023. Inclusion criteria encompassed observational or interventional studies reporting CHE incidence, while exclusion criteria screened out studies with unclear definitions, pharmacy revenue-based spending, or non-representative health facility surveys. A meta-analysis, utilizing a random-effects model, assessed the pooled CHE incidence. Sensitivity analysis and subgroup analyses were conducted to explore heterogeneity.

Out of 501 initially relevant articles, 36 studies met inclusion criteria. The review identified significant variations in CHE measurements, with incidence ranging from 5.1% to 69.9%. Meta-analysis indicated the estimated incidence of CHE at a 10% threshold is 0.30 [0.25–0.35], indicating a significant prevalence of financial hardship due to health expenses. The pooled incidence is estimated by considering different sub-groups. No statistical differences were found between inpatient and outpatient CHE. However, disease-specific estimates were significantly higher (52%) compared to combined diseases (21%). Notably, surveys focusing on health reported higher CHE (33%) than consumption surveys (14%).

The study highlights the intricate challenges in measuring CHE, emphasizing variations in recall periods, components considered in out-of-pocket expenditure, and diverse methods for defining capacity to pay. Notably, the findings underscore the need for standardized definitions and measurements across studies. The lack of uniformity in reporting exacerbates the challenge of comparing and comprehensively understanding the financial burden on households.

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Bredenkamp C, Mendola M, Gragnolati M. Catastrophic and impoverishing effects of health expenditure: new evidence from the Western Balkans. Health Policy Plan. 2011;26:349–56. https://doi.org/10.1093/heapol/czq070 .

Article   PubMed   Google Scholar  

Joe W. Distressed financing of household out-of-pocket health care payments in India: incidence and correlates. Health Policy Plan. 2015;30:728–41. https://doi.org/10.1093/heapol/czu050 .

Xu K, Evans DB, Kawabata K, Zeramdini R, Klavus J, Murray CJL. Household catastrophic health expenditure: a multicountry analysis. Lancet. 2003;362:111–7. https://doi.org/10.1016/S0140-6736(03)13861-5 .

Wagstaff A, Flores G, Hsu J, Smitz MF, Chepynoga K, Buisman LR, et al. Progress on catastrophic health spending in 133 countries: a retrospective observational study. Lancet Glob Heal. 2018;6:e169–79. https://doi.org/10.1016/S2214-109X(17)30429-1 .

Article   Google Scholar  

Nandi A, Ashok A, Laxminarayan R. The socioeconomic and institutional determinants of participation in India’s health insurance scheme for the poor. PLoS ONE. 2013. https://doi.org/10.1371/journal.pone.0066296 .

Article   PubMed   PubMed Central   Google Scholar  

Raban MZ, Dandona R, Dandona L. Variations in catastrophic health expenditure estimates from household surveys in India. Bull World Health Organ. 2013;91:726–35. https://doi.org/10.2471/BLT.12.113100 .

Shukla V, Arora R. The economic cost of rising non-communicable diseases in India: a systematic literature review of methods and estimates. Appl Health Econ Health Policy. 2023. https://doi.org/10.1007/s40258-023-00822-8 .

Alam K, Mahal A. Economic impacts of health shocks on households in low and middle income countries: a review of the literature. Global Health. 2014. https://doi.org/10.1186/1744-8603-10-21 .

Harrer M, Cuijpers P, Furukawa TA, Ebert DD. Doing meta-analysis with R. 2021. https://doi.org/10.1201/9781003107347

Wang N. How to conduct a meta-analysis of proportions in R: a comprehensive tutorial. John Jay Coll Crim Justice. 2016. p. 1–63.

Higgins JPT, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002;21:1539–58. https://doi.org/10.1002/sim.1186 .

Pandey A, Ploubidis GB, Clarke L, Dandona L. Trends in catastrophic health expenditure in India: 1993 to 2014. Bull World Health Organ. 2018;96:18–28. https://doi.org/10.2471/BLT.17.191759 .

Yadav J, Menon GR, John D. Disease-specific out-of-pocket payments, catastrophic health expenditure and impoverishment effects in India: an analysis of national health survey data. Appl Health Econ Health Policy. 2021;19:769–82. https://doi.org/10.1007/s40258-021-00641-9 .

Sangar S, Dutt V, Thakur R. Economic burden, impoverishment, and coping mechanisms associated with out-of-pocket health expenditure in India: a disaggregated analysis at the state level. Int J Health Plann Manage. 2019;34:e301–13. https://doi.org/10.1002/hpm.2649 .

Nanda M, Sharma R. A comprehensive examination of the economic impact of out-of-pocket health expenditures in India. Health Policy Plan. 2023;38:926–38. https://doi.org/10.1093/heapol/czad050 .

Mohanty SK, Dwivedi LK. Addressing data and methodological limitations in estimating catastrophic health spending and impoverishment in India, 2004–18. Int J Equity Health. 2021;20:1–18. https://doi.org/10.1186/s12939-021-01421-6 .

Lee THJ, Saran I, Rao KD. Ageing in India: financial hardship from health expenditures. Int J Health Plan Manag. 2018;33:414–25. https://doi.org/10.1002/hpm.2478 .

Tripathy JP, Jagnoor J, Prasad BM, Ivers R. Cost of injury care in India: cross-sectional analysis of National Sample Survey 2014. Inj Prev. 2018;24:116–22. https://doi.org/10.1136/injuryprev-2017-042318 .

Article   CAS   PubMed   Google Scholar  

Mahal A, Karan A, Engelgau M. The economic implications of non-communicable disease for India. 2010.

Engelgau MM, Karan A, Mahal A. The economic impact of non-communicable diseases on households in India. Glob Health. 2012;8:9–12. https://doi.org/10.1186/1744-8603-8-9 .

Yadav J, John D, Allarakha S, Menon GR. Rising healthcare expenditure on tuberculosis: can India achieve the End TB goal? Trop Med Int Health. 2021;26:1256–75. https://doi.org/10.1111/tmi.13648 .

Mohanty SK, Sahoo U, Rashmi R. Old-age dependency and catastrophic health expenditure: evidence from Longitudinal Ageing Study in India. Int J Health Plan Manag. 2022;37:3148–71. https://doi.org/10.1002/hpm.3546 .

Rajasulochana SR, Kar SS. Economic burden associated with stroke in India: insights from national sample survey 2017–18. Expert Rev Pharmacoecon Outcomes Res. 2021;00:1–9. https://doi.org/10.1080/14737167.2021.1941883 .

Karan A, Farooqui HH, Hussain S, Hussain MA, Selvaraj S, Mathur MR. Multimorbidity, healthcare use and catastrophic health expenditure by households in India: a cross-section analysis of self-reported morbidity from national sample survey data 2017–18. BMC Health Serv Res. 2022;22:1–12. https://doi.org/10.1186/s12913-022-08509-x .

Verma VR, Kumar P, Dash U. Assessing the household economic burden of non-communicable diseases in India: evidence from repeated cross-sectional surveys. BMC Public Health. 2021;21:1–22. https://doi.org/10.1186/s12889-021-10828-3 .

Sriram S, Albadrani M. A study of catastrophic health expenditures in India—evidence from nationally representative survey data: 2014–2018. F1000Research 2022;11:2014–8. https://doi.org/10.12688/f1000research.75808.1 .

Madan J, Lönnroth K, Laokri S, Squire SB. What can dissaving tell us about catastrophic costs? Linear and logistic regression analysis of the relationship between patient costs and financial coping strategies adopted by tuberculosis patients in Bangladesh, Tanzania and Bangalore, India. BMC Health Serv Res. 2015;15:1–8. https://doi.org/10.1186/s12913-015-1138-z .

Behera S, Pradhan J. Uneven economic burden of noncommunicable diseases among Indian households: a comparative analysis. PLoS ONE. 2021;16:1–17. https://doi.org/10.1371/journal.pone.0260628 .

Article   CAS   Google Scholar  

Muniyandi M, Thomas BE, Karikalan N, Kannan T, Rajendran K, Saravanan B, et al. Association of tuberculosis with household catastrophic expenditure in South India. JAMA Netw Open. 2020;3:1–11. https://doi.org/10.1001/jamanetworkopen.2019.20973 .

Kastor A, Mohanty SK. Disease-specific out-of-pocket and catastrophic health expenditure on hospitalization in India: do Indian households face distress health financing? PLoS ONE. 2018;13:1–18. https://doi.org/10.1371/journal.pone.0196106 .

Maurya PK, Murali S, Jayaseelan V, Thulasingam M, Pandjatcharam J. Economic burden of cancer treatment in a region in South India: a cross sectional analytical study. Asian Pacific J Cancer Prev. 2021;22:3755–62. https://doi.org/10.31557/APJCP.2021.22.12.3755 .

Yadav J, Menon G, Agarwal A, John D. Burden of injuries and its associated hospitalization expenditure in India. Int J Inj Contr Saf Promot. 2021;28:153–61. https://doi.org/10.1080/17457300.2021.1879163 .

Mohanty SK, Agrawal NK, Mahapatra B, Choudhury D, Tuladhar S, Holmgren EV. Multidimensional poverty and catastrophic health spending in the mountainous regions of Myanmar, Nepal and India. Int J Equity Health. 2017;16:1–13. https://doi.org/10.1186/s12939-016-0514-6 .

Dwivedi R, Pradhan J, Athe R. Measuring catastrophe in paying for healthcare: a comparative methodological approach by using National Sample Survey. India Int J Health Plan Manag. 2021;36:1887–915. https://doi.org/10.1002/hpm.3272 .

Kumar K, Singh A, Kumar S, Ram F, Singh A, Ram U, et al. Socio-economic differentials in impoverishment effects of out-of-pocket health expenditure in China and India: evidence from WHO SAGE. PLoS ONE. 2015;10:1–19. https://doi.org/10.1371/journal.pone.0135051 .

Heijink R, Xu K, Saksana P, Evans D. Validity and Comparability of out-of- pocket health expenditure from household surveys: a review of the literature and current survey instruments. WHO Discuss Pap 2011. p. 1–30.

Mohanty SK, Kim R, Khan PK, Subramanian SV. Geographic variation in household and catastrophic health spending in India: assessing the relative importance of villages, districts, and states, 2011–2012. Milbank Q. 2018;96:167–206. https://doi.org/10.1111/1468-0009.12315 .

Pandey KR, Meltzer DO. Financial burden and impoverishment due to cardiovascular medications in low and middle income countries: an illustration from India. PLoS ONE. 2016;11:1–19. https://doi.org/10.1371/journal.pone.0155293 .

Yadav J, Allarakha S, Menon GR, John D, Nair S. Socioeconomic impact of hospitalization expenditure for treatment of noncommunicable diseases in India: a repeated cross-sectional analysis of national sample survey data, 2004 to 2018. Value Heal Reg Issues. 2021;24:199–213. https://doi.org/10.1016/j.vhri.2020.12.010 .

Karan A, Selvaraj S, Mahal A. Moving to universal coverage? Trends in the burden of out-of-pocket payments for health care across social groups in India, 1999–2000 to 2011–12. PLoS ONE. 2014;9:1999–2000. https://doi.org/10.1371/journal.pone.0105162 .

Gupta I, Joe W. Refining estimates of catastrophic healthcare expenditure: an application in the Indian context. Int J Health Care Finance Econ. 2013;13:157–72. https://doi.org/10.1007/s10754-013-9125-6 .

Xu K, Ravndal F, Evans DB, Carrin G. Assessing the reliability of household expenditure data: results of the World Health Survey. Health Policy (New York). 2009;91:297–305. https://doi.org/10.1016/j.healthpol.2009.01.002 .

Eze P, Lawani LO, Agu UJ, Acharya Y. Catastrophic health expenditure in sub-Saharan Africa: systematic review and meta-analysis. Bull World Health Organ. 2022;100:337-351J. https://doi.org/10.2471/BLT.21.287673 .

Clarke PM, Fiebig DG, Gerdtham UG. Optimal recall length in survey design. J Health Econ. 2008;27:1275–84. https://doi.org/10.1016/j.jhealeco.2008.05.012 .

Lu C, Chin B, Li G, Murray CJL. Limitations of methods for measuring out-of-pocket and catastrophic private health expenditures. Bull World Health Organ. 2009;87:238–44. https://doi.org/10.2471/BLT.08.054379 .

Kalita A, Carton-Rossen N, Joseph L, Chhetri D, Patel V. The barriers to universal health coverage in India and the strategies to address them: a key informant study. Ann Glob Heal. 2023;89:69. https://doi.org/10.5334/aogh.4120 .

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Acknowledgements

The team mentioned in the Methods section consists of three independent reviewers, Umenthla Srikanth Reddy, Adrita Banerjee, and Tapasya Raj, who extracted papers and data from the selected papers. The authors acknowledge the contribution of Adrita Banerjee, Tapasya Raj and Shreya Singh in editing the manuscript and providing valuable feedback. The author also acknowledges the journal editor for meticulously reviewing the manuscript, as well as the anonymous reviewers for their valuable suggestions and feedback.

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Reddy, U.S. Measurement of Catastrophic Health Expenditure in India: A Systematic Review and Meta-Analysis. Appl Health Econ Health Policy (2024). https://doi.org/10.1007/s40258-024-00885-1

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508
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