Abstract
India introduced a new healthcare scheme, the Pradhan Mantri Jan Arogya Yojana (PMJAY), in 2018, which has been in effect since 2019. This scheme aims to achieve universal health coverage and supports the catastrophic Out-of-Pocket Expenditure (OOPE) of below poverty line population in Indian states. This study assesses the impact of PMJAY in two selected districts of the Indian state of Bihar considering a sample of 324 respondents. Propensity score matching (PSM) and entropy balancing (EB) are two widely used methods to ensure the robustness of impact assessment exercises. The EB method is considered relatively robust and therefore, we use and compare both. The average effect of PMJAY on the beneficiaries using EB shows a significant rise in healthcare utilization; the values are 2.51, 0.79 and 0.36 for OPD visits, hospitalizations, and surgeries, respectively. Our sample consists of 22 percent PMJAY-beneficiaries. The findings highlight the scheme’s potential to improve healthcare access and outcomes for the vulnerable population. Beneficiaries have reported better post-hospitalization quality of life and are more likely to return to work regularly after treatment. These insights may assist policymakers in further improving their effectiveness by raising awareness among the eligible households, as there are still barriers to enrollment and information asymmetries with regard to utilization.
Acknowledgments
The authors thank participants at the 28th Asia Pacific Risk and Insurance Association 2024 Annual Meeting in National University of Laos, Vientiane, Laos (2024) and Global Conclave 2024 organized by Institute of Human Development, New Delhi, India (2024) for their constructive comments on an earlier version of this paper. The authors are responsible for any remaining errors in this manuscript and endorse that the research did not receive any research funding. The participation and presentation of the earlier version of the paper by the first author at the APRIA 2024 Annual Conference was possible because of the partial financial support from the Indian Council for Social Science Research (ICSSR).
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Research ethics: Not applicable.
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Informed consent: Not applicable.
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Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: The authors state no conflict of interest.
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Research funding: None declared.
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Data availability: Data can be shared upon reasonable request.

1. Household information
S. no. | Questions | Responses |
---|---|---|
1.1 | District | |
1.2 | Block | |
1.3 | Village | |
1.4 | Name of the household head | |
1.5 | Name of the respondent | |
1.6 | Is he/she the household head? | Yes – 01 |
No – 02 | ||
1.7 | Gender | Male – 01 |
Female – 02 | ||
1.8 | Education of household head | 1. Primary |
2. Secondary | ||
3. Higher secondary | ||
4. Graduate | ||
5. Postgraduate | ||
6. Not literate | ||
1.9 | Religion | 1. Hindu |
2. Muslim | ||
3. Christian | ||
4. Buddhist | ||
5. Sikh | ||
1.10 | Caste | 1. Upper caste |
2. OBC 1 | ||
3. OBC 2 | ||
4. SC | ||
5. ST | ||
6. Others…… |
S. no. | Questions | Responses |
---|---|---|
1.11 | Do you have ration card? | Yes – 01 |
No – 02 | ||
1.12 | In which category do you belong? | 1. APL |
2. BPL | ||
1.13 | Latrine system | Yes – 01 |
No – 02 | ||
1.14 | Drainage system | Yes – 01 |
No – 02 | ||
1.15 | Drinking water facility | Yes – 01 |
No – 02 | ||
1.16 | Distance of village from nearest hospital | Specify……… |
1.17 | Locality | 1. Urban |
2. Rural | ||
3. Peri-urban | ||
1.18 | Land holding (in Kattha) | Specify……… |
1.19 | Source of income | 1. Agriculture |
2. Casual labour | ||
3. Self-employment | ||
4. Formal sector job | ||
5. Others…… | ||
1.20 | Monthly consumption expenditure | 1. Up to Rs. 2,000 |
2. Rs. 2,000–5,000 | ||
3. Rs. 5,000–10,000 | ||
4. Above Rs. 10,000 | ||
1.21 | Total borrowings | |
1.22 | Source of borrowings | 1. Bank loan |
2. Co-operatives | ||
3. SHGs | ||
4. Money lenders | ||
5. Others | ||
1.23 | Assets purchased in the past 4 years | |
1.24 | Growth of income during past 4 years | |
1.25 | Assets sold in the past 4 years | |
1.26 | Do you have mobile phone with internet connectivity? | Yes – 01 |
No – 02 | ||
1.27 | Any member of your family hospitalized during Covid-19? | Yes – 01 |
No – 02 | ||
1.29 | Do you know about PM-JAY? | Yes – 01 |
No – 02 | ||
1.30 | Do you know the eligibility of this scheme? | Yes – 01 |
No – 02 | ||
1.31 | Is your family eligible? | Yes – 01 |
No – 02 | ||
1.32 | Is your family enrolled? | Yes – 01 |
No – 02 |
2. Demographic profile of household
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
Sl. no | Name | Relationship to head (code) | Age (code) |
Sex (code) |
Marital status (code) | Educational level (code) | Employment status (code) | Health status(code) |
1. Health status of households
Questions | Responses | |
---|---|---|
3.1 | How will you rate your health risk? | Extremely high – 01 |
High – 02 | ||
Average – 03 Low – 04 | ||
Extremely low – 05 | ||
3.2 | From which diseases are you suffering? | 1. Heart problem |
(Circle more than one if applicable) | 2. High BP | |
3. Diabetes | ||
4. Arthritis | ||
5. Disability diseases | ||
6. Respiratory | ||
7. Injury due to accident | ||
8. Thyroid | ||
9. Others……. | ||
3.3 | What is household average monthly medical | 1. Up to Rs 1,000 |
expenses? | 2. Rs 1,000–5,000 | |
3. Rs 5,000–10,000 | ||
4. Above Rs 10,000 | ||
3.4 | What preventive health care measures are you | 1. Disease screening |
undertaking? (Circle more than one if applicable) | 2. Identify risk factors for disease | |
3. Discuss tips for a healthy and balanced lifestyle | ||
4. Stay up to date with immunizations and boosters | ||
5. Regular exercise/yoga/walking |
Questions | Responses | |
---|---|---|
6. Washing hands with soap frequently | ||
7. Wearing helmet/car seat belt while driving | ||
8. Avoid smoking/alcohol | ||
9. Maintain weight | ||
10. Eating healthy food (fresh fruits and vegetables) | ||
3.5 | What is the source of financing your inpatient medical expenses? | 1. Free medical service by government |
2. Out of pocket expenditures | ||
3. Paid by employer/company | ||
4. Health insurance schemes | ||
5. Others (Specify) ………………. |
2. Awarenress about health insurance
Questions | 5 | 4 | 3 | 2 | 1 | |
---|---|---|---|---|---|---|
4.1 | I am aware of the benefits of health insurance | |||||
4.2 | I am aware of the general cost of health insurance premium | |||||
4.3 | I am aware of the health insurance claim procedure | |||||
4.4 | It is better to take a health insurance policy at a younger age | |||||
4.5 | Health insurance policies offered by non-life insurance companies usually last for a period of one year. | |||||
4.6 | I am aware that the Insurance Regulatory & Development Authority of India (IRDAI) is the insurance regulator for Health Insurance in India? | |||||
4.7 | I am aware that IRDA allows online issuance of HI policies | |||||
4.8 | Social health insurance schemes like Rashtriya Swasthya Bima Yojana (RSBY) and Ayushman Bharat help to create awareness regarding purchase of HI policy | |||||
4.9 | Rising social awareness about health care has positive influence on purchase decision of health insurance | |||||
4.10 | I am aware of the difference between life insurance and health insurance |
-
Note: Please give responses to the following questions on a scale of 5 to 1, where 5 = strongly agree, 4 = agree, 3 = neither agree nor disagree, 2 = disagree and 1 = strongly disagree.
3. Healthcare utilization
5.1 | Is any member of your household covered by a health insurance scheme? | Yes – 01 |
No – 02 |
If Yes, then answer the following questions.
5.2 | What type of health insurance plan do you have? | 1. Government sponsored health insurance scheme (Ayushman Bharat scheme) |
2. Employees state insurance Scheme | ||
3. Central government health insurance Scheme | ||
4. Medical Reimbursement from employer | ||
5. Health insurance from employer | ||
Private Voluntary Health Insurance | ||
6. Public company | ||
7. Private company | ||
8. Any other……………………………. | ||
5.3 | Which factor motivated you to buy health | 1. Advertisement |
insurance policy? | 2. Insurance agent | |
3. Internet | ||
4. Friends and relatives | ||
5. Others………………………(specify) | ||
5.4 | Name of the provider company | Specify……. |
5.5 | Total sum assured | Specify……. |
5.6 | Premium payable per annum | Specify……. |
5.7 | Frequency of OPD visits in a year | |
5.8 | Frequency of hospitalization visits in the last 4 years | Specify……. |
5.9 | Frequency of surgery in the past 4 years | Specify……. |
5.10 | Where did you get treatment? | 1. Public hospital |
2. Private hospital | ||
5.11 | What was the total cost of hospitalization? | Specify- - - - |
5.12 | What was the other cost (transportation, food etc.) | Specify- - - - |
5.13 | Did you claim your health insurance amount? | Yes – 01 |
No – 02 |
If No , then answer the following questions.
5.14 | Why you have not opted any health | 1. Low availability of funds |
insurance policy? | 2. Don’t feel the need for it | |
3. Lack of awareness | ||
4. Lack of reliability and flexibility | ||
5. Difficulty in availing services in hospital | ||
6. Cumbersome claim procedure |
6. Financial protection and satisfaction level
6.1 | Total inpatient expenses | |
6.2 | Borrowing in inpatient expenses (or surgery) | |
6.3 | Share of borrowing in expenses | |
6.4 | Post-surgery expenses | |
6.5 | Income lost as ratio of income | |
6.6 | Whether require post-surgery intervention? | Yes – 01 |
No – 02 | ||
6.7 | Whether life improved post-surgery? | Yes – 01 |
No – 02 | ||
6.8 | Whether work regularly post-surgery? | Yes – 01 |
No – 02 | ||
6.9 | Whether money saved? | Yes – 01 |
No – 02 | ||
6.10 | Satisfaction level from financial protection using health insurance? | 1. Excellent |
2. Good | ||
3. Average | ||
4. Poor |
Remarks (If any)
References
Abadie, A., and G. W. Imbens. 2006. “Large Sample Properties of Matching Estimators for Average Treatment Effects.” Econometrica 74 (1): 235–67. https://doi.org/10.1111/j.1468-0262.2006.00655.x.Search in Google Scholar
Acharya, A., S. Vellakkal, F. Taylor, E. Masset, A. Satija, M. Burke, et al.. 2013. “The Impact of Health Insurance Schemes for the Informal Sector in Low-And Middle-Income Countries: A Systematic Review.” The World Bank Research Observer 28 (2): 236–66. https://doi.org/10.1093/wbro/lks009.Search in Google Scholar
Aggarwal, A. 2010. “Impact Evaluation of India’s ‘Yeshasvini’ Community‐based Health Insurance Programme.” Health Economics 19 (S1): 5–35. https://doi.org/10.1002/hec.1605.Search in Google Scholar
Ahmed, S. 2024. “The Inequality in Healthcare Access in Bihar: Pattern and Determinants.” Arthaniti: Journal of Economic Theory and Practice: 09767479241254423. https://doi.org/10.1177/09767479241254423.Search in Google Scholar
Ahmed, S., and S. Mahapatro. 2023. “Inequality in Healthcare Access at the Intersection of Caste and Gender.” Contemporary Voice of Dalit 15 (1): 75–85. https://doi.org/10.1177/2455328x221142692.Search in Google Scholar
Amusa, L., T. Zewotir, and D. North. 2019. “Examination of Entropy Balancing Technique for Estimating Some Standard Measures of Treatment Effects: A Simulation Study.” Electronic Journal of Applied Statistical Analysis 12 (2): 491–507.Search in Google Scholar
Austin, P. C. 2011. “An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies.” Multivariate Behavioral Research 46 (3): 399–424. https://doi.org/10.1080/00273171.2011.568786.Search in Google Scholar
Austin, P. C., and E. A. Stuart. 2015. “Moving towards Best Practice when Using Inverse Probability of Treatment Weighting (IPTW) Using the Propensity Score to Estimate Causal Treatment Effects in Observational Studies.” Statistics in Medicine 34 (28): 3661–79. https://doi.org/10.1002/sim.6607.Search in Google Scholar
Bakx, P., O. O’Donnell, and E. Van Doorslaer. 2016. “Spending on Health Care in the Netherlands: Not Going So Dutch.” Fiscal Studies 37 (3–4): 593–625. https://doi.org/10.1111/j.1475-5890.2016.12114.Search in Google Scholar
Bauhoff, S., D. R. Hotchkiss, and O. Smith. 2011. “The Impact of Medical Insurance for the Poor in Georgia: A Regression Discontinuity Approach.” Health Economics 20 (11): 1362–78. https://doi.org/10.1002/hec.1673.Search in Google Scholar
Bergkvist, S., A. Wagstaff, A. Katyal, P. Singh, A. Samarth, and M. Rao. 2014. “What a Difference a State Makes: Health Reform in Andhra Pradesh.” World Bank Policy Research Working Paper, No. WPS6883. Washington: World Bank Group.10.1596/1813-9450-6883Search in Google Scholar
Biswas, S. 2024. “Can Mobile Financial Services Influence Financial Behaviour in India?” Indian Economic Journal: 00194662241265470. https://doi.org/10.1177/00194662241265470.Search in Google Scholar
Bittmann, F., A. Tekles, and L. Bornmann. 2021. “Applied Usage and Performance of Statistical Matching in Bibliometric: The Comparison of Milestone and Regular Papers with Multiple Measurements of Disruptiveness as an Empirical Example.” Quantitative Science Studies 2 (4): 1246–70. https://doi.org/10.1162/qss_a_00158.Search in Google Scholar
Choudhury, M., and P. Datta. 2020. “Health Insurance in Private Hospitals: Implications for Implementation of Ayushman Bharat.” Economic and Political Weekly 60 (17): 49–56.Search in Google Scholar
Chowdhury, S., and S. Mukherjee. 2019. “Can Ayushman Bharat National Health Protection Mission Protect the Health of India’s Poor?” Institute of Development Studies Kolkata, Occasional Paper, No. 64. Kolkata: Institute of Development Studies.Search in Google Scholar
Crivelli, L., and P. Salari. 2014. “The Inequity of the Swiss Health Care System Financing from a Federal State Perspective.” International Journal for Equity in Health 13: 1–13. https://doi.org/10.1186/1475-9276-13-17.Search in Google Scholar
Dash, U., V. R. Muraleedharan, and M. Rajesh. 2019. “Accessing Ayushman Bharat- Pradhan Mantri Jan Arogya Yojana (PM-JAY): A Case Study of Three States (Bihar, Haryana and Tamil Nadu).” Center for Technology and Policy Working Paper, IIT Madras.Search in Google Scholar
D’cruze, N. A. 2020. “Risky Insurance: The Pradhan Mantri Jan Arogya Yojana in Jharkhand.” Economic and Political Weekly 55 (45): 1–10.Search in Google Scholar
Dubey, S., S. Deshpande, L. Krishna, and S. Zadey. 2023. “Evolution of Government-Funded Health Insurance for Universal Health Coverage in India.” The Lancet Regional Health-Southeast Asia 13: 100180. https://doi.org/10.1016/j.lansea.2023.100180.Search in Google Scholar
Duggal, R., and S. K. Hooda. 2021. “COVID-19, Health Insurance and Access to Healthcare.” Economic and Political Weekly 53 (31): 10–2.Search in Google Scholar
Ecks, S. 2018. ““When the Government Changes, the Card Will Also Change”: Questioning Identity in Biometrie Smartcards for National Health Insurance (RSBY) in India.” Anthropologica 60 (1): 190–200. https://doi.org/10.3138/anth.60.1.t18.Search in Google Scholar
Ekman, B. 2007. “The Impact of Health Insurance on Outpatient Utilization and Expenditure: Evidence from One Middle-Income Country Using National Household Survey Data.” Health Research Policy and Systems 5 (1): 1–15. https://doi.org/10.1186/1478-4505-5-6.Search in Google Scholar
Elf, M., M. Flink, M. Nilsson, M. Tistad, L. von Koch, and C. Ytterberg. 2017. “The Case of Value-Based Healthcare for People Living with Complex Long-Term Conditions.” BMC Health Services Research 17 (24): 1–6. https://doi.org/10.1186/s12913-016-1957-6.Search in Google Scholar
Fan, V. Y., A. Karan, and A. Mahal. 2012. “State Health Insurance and Out-Of-Pocket Health Expenditures in Andhra Pradesh, India.” International Journal of Health Care Finance and Economics 12: 189–215. https://doi.org/10.1007/s10754-012-9110-5.Search in Google Scholar
Fiestas Navarrete, L., S. Ghislandi, D. Stuckler, and F. Tediosi. 2019. “Inequalities in the Benefits of National Health Insurance on Financial Protection from Out-Of-Pocket Payments and Access to Health Services: Cross-Sectional Evidence from Ghana.” Health Policy and Planning 34 (9): 694–705. https://doi.org/10.1093/heapol/czz093.Search in Google Scholar
Fong, C., and K. Imai. 2014. Covariate Balancing Propensity Score for General Treatment Regimes. Princeton Manuscript.Search in Google Scholar
Garg, S., K. K. Bebarta, and N. Tripathi. 2020. “Performance of India’s National Publicly Funded Health Insurance Scheme, Pradhan Mantri Jan Arogya Yojana (PMJAY), in Improving Access and Financial Protection for Hospital Care: Findings from Household Surveys in Chhattisgarh State.” BMC Public Health 20 (1): 949. https://doi.org/10.1186/s12889-020-09107-4.Search in Google Scholar
Gertler, P. J., S. Martinez, P. Premand, L. B. Rawlings, and C. M. Vermeersch. 2016. Impact Evaluation in Practice, 2nd ed. World Bank Publications.10.18235/0006529Search in Google Scholar
Ghosh, S. 2018. “Publicly Financed Health Insurance Schemes.” Economic and Political Weekly 53 (23): 16–8.Search in Google Scholar
Ghosh, S. M., and I. Qadeer. 2019. “Pradhan Mantri Jan Arogya Yojana: A Paper Tiger.” Social Change 49 (1): 136–43. https://doi.org/10.1177/0049085718821767.Search in Google Scholar
Gnawali, D. P., S. Pokhrel, A. Sié, M. Sanon, M. De Allegri, A. Souares, et al.. 2009. “The Effect of Community-Based Health Insurance on the Utilization of Modern Health Care Services: Evidence from Burkina Faso.” Health Policy 90 (2–3): 214–22. https://doi.org/10.1016/j.healthpol.2008.09.015.Search in Google Scholar
Gopichandran, V. 2019. “Ayushman Bharat National Health Protection Scheme: An Ethical Analysis.” Asian Bioethics Review 11 (1): 69–80. https://doi.org/10.1007/s41649-019-00083-5.Search in Google Scholar
Gowda, N. R., A. Hakim, G. Singh, A. Gupta, and D. K. Sharma. 2022. “The Experience of Patient and Implementation of the Landmark Scheme Ayushman Bharat (AB-PMJAY) of Government of India in a Tertiary Care Hospital.” Journal of Health Management 24 (4): 566–71. https://doi.org/10.1177/09720634221128082.Search in Google Scholar
Guarcello, M. A., R. A. Levine, J. Beemer, J. P. Frazee, M. A. Laumakis, and S. A. Schellenberg. 2017. “Balancing Student Success: Assessing Supplemental Instruction through Coarsened Exact Matching.” Technology, Knowledge and Learning 22 (3): 335–52. https://doi.org/10.1007/s10758-017-9317-0.Search in Google Scholar
Gupta, I., S. Chowdhury, A. Roy, and Ramandeep. 2020. “Ayushman Bharat-Costs and Finances of the Prime Minister’s Jan Arogya Yojana.” Economic and Political Weekly 55 (36): 56–64.Search in Google Scholar
Hainmueller, J. 2012. “Entropy Balancing for Causal Effects: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies.” Political Analysis 20 (1): 25–46. https://doi.org/10.1093/pan/mpr025.Search in Google Scholar
Hainmueller, J., and Y. Xu. 2013. “Ebalance: A Stata Package for Entropy Balancing.” Journal of Statistical Software 54 (7): 1–18. https://doi.org/10.18637/jss.v054.i07.Search in Google Scholar
Halpern, E. F. 2014. “Behind the Numbers: Inverse Probability Weighting.” Radiology 271 (3): 625–8. https://doi.org/10.1148/radiol.14140035.Search in Google Scholar
Hooda, S. K. 2015. “Health Insurance, Health Access and Financial Risk Protection.” Economic and Political Weekly 50 (50): 63–72.Search in Google Scholar
Hooda, S. K. 2020. “Penetration and Coverage of Government-Funded Health Insurance Schemes in India.” Clinical Epidemiology and Global Health 8 (4): 1017–33. https://doi.org/10.1016/j.cegh.2020.03.014.Search in Google Scholar
Iacus, S. M., G. King, and G. Porro. 2012. “Causal Inference without Balance Checking: Coarsened Exact Matching.” Political Analysis 20 (1): 1–24. https://doi.org/10.1093/pan/mpr013.Search in Google Scholar
Imai, K., and M. Ratkovic. 2014. “Covariate Balancing Propensity Score.” Journal of the Royal Statistical Society - Series B: Statistical Methodology 76 (1): 243–63. https://doi.org/10.1111/rssb.12027.Search in Google Scholar
Imbens, G. W., and J. M. Wooldridge. 2009. “Recent Developments in the Econometrics of Program Evaluation.” Journal of Economic Literature 47 (1): 5–86. https://doi.org/10.1257/jel.47.1.5.Search in Google Scholar
Indian Council of Medical Research, Public Health Foundation of India, & Institute for Health Metrics and Evaluation. 2017. “India: Health of the Nation’s States. The India State-Level Disease Burden Initiative. ICMR, PHFI, and IHME.” https://ora.ox.ac.uk/objects/uuid:1f44ac9f-a7bf-4a76-aa6a-4434a1dcc034.Search in Google Scholar
Joseph, J., D. H. Sankar, and D. Nambiar. 2021. “Empanelment of Health Care Facilities under Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (AB PM-JAY) in India.” PLoS One 16 (5): e0251814. https://doi.org/10.1371/journal.pone.0251814.Search in Google Scholar
Kalita, A., and K. Croke. 2023. “The Politics of Health Policy Agenda Setting in India: The Case of the PMJAY Program.” Health Systems and Reform 9 (1): 2229062. https://doi.org/10.1080/23288604.2023.2229062.Search in Google Scholar
Kamath, S., R. Kamath, and B. D’Souza. 2017. “An Assessment of the Public Healthcare Infrastructure Deficiency in a District of Bihar State of India.” Postgraduate Medical Journal 93 (1105): 710–1. https://doi.org/10.1136/postgradmedj-2017-135065.Search in Google Scholar
Kamath, R., V. Lakshmi, and H. Brand. 2022. “Health Index Scores and Health Insurance Coverage across India: A State Level Spatiotemporal Analysis.” Clinical Epidemiology and Global Health 18: 101185. https://doi.org/10.1016/j.cegh.2022.101185.Search in Google Scholar
Karan, A., W. Yip, and A. Mahal. 2017. “Extending Health Insurance to the Poor in India: An Impact Evaluation of Rashtriya Swasthya Bima Yojana on Out-Of-Pocket Spending for Healthcare.” Social Science & Medicine 181: 83–92. https://doi.org/10.1016/j.socscimed.2017.03.053.Search in Google Scholar
Katyal, A., P. V. Singh, S. Bergkvist, A. Samarth, and M. Rao. 2015. “Private Sector Participation in Delivering Tertiary Health Care: A Dichotomy of Access and Affordability across Two Indian States.” Health Policy and Planning 30 (1): 23–31. https://doi.org/10.1093/heapol/czu061.Search in Google Scholar
King, G., E. Gakidou, K. Imai, J. Lakin, R. T. Moore, C. Nall, et al.. 2009. “Public Policy for the Poor? A Randomised Assessment of the Mexican Universal Health Insurance Programme.” The Lancet 373 (9673): 1447–54. https://doi.org/10.1016/s0140-6736(09)60239-7.Search in Google Scholar
Kumari, R. 2016. “Regional Disparity in Uttar Pradesh and Bihar: A Disaggregated Level Analysis.” Journal of Social and Economic Development 18 (1): 121–46. https://doi.org/10.1007/s40847-016-0022-y.Search in Google Scholar
Kusi, A., K. S. Hansen, F. A. Asante, and U. Enemark. 2015. “Does the National Health Insurance Scheme Provide Financial Protection to Households in Ghana?” BMC Health Services Research 15: 1–12. https://doi.org/10.1186/s12913-015-0996-8.Search in Google Scholar
Kwon, S. 2009. “Thirty Years of National Health Insurance in South Korea: Lessons for Achieving Universal Health Care Coverage.” Health Policy and Planning 24 (1): 63–71. https://doi.org/10.1093/heapol/czn037.Search in Google Scholar
Larrain, N., and O. Groene. 2023. “Improving the Evaluation of an Integrated Healthcare System Using Entropy Balancing: Population Health Improvements in Gesundes Kinzigtal.” SSM-Population Health 22: 101371. https://doi.org/10.1016/j.ssmph.2023.101371.Search in Google Scholar
Malani, A., C. Kinnan, G. Conti, K. Imai, M. Miller, S. Swaminathan, et al.. 2024. “Evaluating and Pricing Health Insurance in Lower-Income Countries: A Field Experiment in India (No. w32239).” National Bureau of Economic Research.10.1920/wp.ifs.2024.3324Search in Google Scholar
Matschinger, H., D. Heider, and H. H. König. 2020. “A Comparison of Matching and Weighting Methods for Causal Inference Based on Routine Health Insurance Data, or: What to Do if an RCT Is Impossible.” Das Gesundheitswesen 82 (2): 139–50. https://doi.org/10.1055/a-1009-6634.Search in Google Scholar
Mensah, J., J. R. Oppong, and C. M. Schmidt. 2010. “Ghana’s National Health Insurance Scheme in the Context of the Health MDGs: An Empirical Evaluation Using Propensity Score Matching.” Health Economics 19 (1): 95–106. https://doi.org/10.1002/hec.1633.Search in Google Scholar
Miller, G., D. M. Pinto, and M. Vera-Hernández. 2009. High-powered Incentives in Developing Country Health Insurance: Evidence from Colombia’s Regimen Subsidiado. Cambridge: National Bureau of Economic Research.10.1920/re.ifs.2024.0551Search in Google Scholar
Ministry of Health and Family Welfare. 2021. National Family Health Survey (NFHS-5), 2019–21: Bihar. International Institute for Population Sciences (IIPS).Search in Google Scholar
Morgan, S. L., and C. Winship. 2015. Counterfactuals and Causal Inference: Methods and Principles for Social Research, 2nd ed. Cambridge University Press.10.1017/CBO9781107587991Search in Google Scholar
Morra-Imas, L., and C. Rist. 2009. The Road to Results: Designing and Conducting Effective Development Evaluations. World Bank Publications.10.1596/978-0-8213-7891-5Search in Google Scholar
Nay, O., S. Béjean, D. Benamouzig, H. Bergeron, P. Castel, and B. Ventelou. 2016. “Achieving Universal Health Coverage in France: Policy Reforms and the Challenge of Inequalities.” The Lancet 387 (10034): 2236–49. https://doi.org/10.1016/s0140-6736(16)00580-8.Search in Google Scholar
Nguyen, H. T., Y. Rajkotia, and H. Wang. 2011. “The Financial Protection Effect of Ghana National Health Insurance Scheme: Evidence from a Study in Two Rural Districts.” International Journal for Equity in Health 10: 1–12. https://doi.org/10.1186/1475-9276-10-4.Search in Google Scholar
NITI Aayog. 2020. Healthy States, Progressive India: Report on the Ranks of States and Union Territories. NITI Aayog. https://www.niti.gov.in.Search in Google Scholar
NITI Aayog. 2023. National Multidimensional Poverty Index: A Progress Review 2023. NITI Aayog. https://www.niti.gov.in.Search in Google Scholar
Nshakira-Rukundo, E., E. C. Mussa, N. Nshakira, N. Gerber, and J. von Braun. 2021. “Impact of Community-Based Health Insurance on Utilisation of Preventive Health Services in Rural Uganda: A Propensity Score Matching Approach.” International Journal of Health Economics and Management 21: 203–27. https://doi.org/10.1007/s10754-021-09294-6.Search in Google Scholar
Pandey, N., S. Jha, and V. Rai. 2021. “Ayushman Bharat: Service Adoption Challenges in Universal Healthcare System.” South Asian Journal of Business and Management Cases 10 (1): 35–49. https://doi.org/10.1177/2277977921991915.Search in Google Scholar
Parish, W. J., V. Keyes, C. Beadles, and A. Kandilov. 2018. “Using Entropy Balancing to Strengthen an Observational Cohort Study Design: Lessons Learned from an Evaluation of a Complex Multi-State Federal Demonstration.” Health Services & Outcomes Research Methodology 18: 17–46. https://doi.org/10.1007/s10742-017-0174-z.Search in Google Scholar
Parisi, D., S. Srivastava, D. Parmar, C. Strupat, S. Brenner, C. Walsh, et al.. 2023. “Awareness of India’s National Health Insurance Scheme (PM-JAY): A Cross-Sectional Study across Six States.” Health Policy and Planning 38 (3): 289–300. https://doi.org/10.1093/heapol/czac106.Search in Google Scholar
Parmar, D., C. Strupat, S. Srivastava, S. Brenner, D. Parisi, S. Ziegler, et al.. 2023. “Effects of the Indian National Health Insurance Scheme (PM-JAY) on Hospitalizations, Out-Of-Pocket Expenditures and Catastrophic Expenditures.” Health Systems and Reform 9 (1): 2227430. https://doi.org/10.1080/23288604.2023.2227430.Search in Google Scholar
Porecha, M. 2019. Inside Bihar’s Crumbling Health System, Nothing Has Changed. Businessline. https://www.thehindubusinessline.com/news/inside-biharscrumbling-health-system-nothing-has-changed/article28842861.ece.Search in Google Scholar
Prinja, S., A. S. Chauhan, A. Karan, G. Kaur, and R. Kumar. 2017. “Impact of Publicly Financed Health Insurance Schemes on Healthcare Utilization and Financial Risk Protection in India: A Systematic Review.” PLoS One 12 (2): e0170996. https://doi.org/10.1371/journal.pone.0170996.Search in Google Scholar
Robins, J. M., A. Rotnitzky, and L. P. Zhao. 1994. “Estimation of Regression Coefficients when Some Regressors Are Not Always Observed.” Journal of the American Statistical Association 89 (427): 846–66. https://doi.org/10.2307/2290910.Search in Google Scholar
Rosenbaum, P. R., and D. B. Rubin. 1983. “The Central Role of the Propensity Score in Observational Studies for Causal Effects.” Biometrika 70 (1): 41–55. https://doi.org/10.2307/2335942.Search in Google Scholar
Rosenbaum, P. R., and D. B. Rubin. 1984. “Reducing Bias in Observational Studies Using Sub Classification on the Propensity Score.” Journal of the American Statistical Association 79 (387): 516–24. https://doi.org/10.2307/2288398.Search in Google Scholar
Sancheti, P., S. G. Shastri, A. Krishnamurthy, G. G. Dayananda, P. K. Srinivas, M. Jayaprakash, et al.. 2023. “Utilization of Tuberculosis Healthcare Packages under Ayushman Bharat Pradhan Mantri Jan Arogya Yojana-Arogya Karnataka: A Comprehensive Socio-Demographic Analysis.” Indian Journal of Tuberculosis 72 (2): 162–8, https://doi.org/10.1016/j.ijtb.2023.12.008.Search in Google Scholar
Schurer, S., M. Alspach, J. MacRae, and G. Martin. 2016. “The Medical Care Costs of Mood Disorders: A Coarsened Exact Matching Approach.” The Economic Record 92 (296): 81–93. https://doi.org/10.1111/1475-4932.12218.Search in Google Scholar
Sengupta, R., and D. Rooj. 2019. “The Effect of Health Insurance on Hospitalization: Identification of Adverse Selection, Moral Hazard and the Vulnerable Population in the Indian Healthcare Market.” World Development 122: 110–29. https://doi.org/10.1016/j.worlddev.2019.05.012.Search in Google Scholar
Shrisharath, K., S. Hiremat, S. N. Kumar, P. Rai, S. Erappa, and A. Holla. 2022. “A Study on the Utilisation of Ayushman Bharat Arogya Karnataka (ABArK) Among COVID Patients Admitted in a Tertiary Care Hospital.” Clinical Epidemiology and Global Health 15: 101015. https://doi.org/10.1016/j.cegh.2022.101015.Search in Google Scholar
Srivastava, S., M. P. Bertone, D. Parmar, C. Walsh, and M. De Allegri. 2023. “The Genesis of the PM-JAY Health Insurance Scheme in India: Technical and Political Elements Influencing a National Reform towards Universal Health Coverage.” Health Policy and Planning 38 (7): 862–75. https://doi.org/10.1093/heapol/czad045.Search in Google Scholar
Stevens, G. A., G. King, and K. Shibuya. 2010. “Deaths from Heart Failure: Using Coarsened Exact Matching to Correct Cause-Of Death Statistics.” Population Health Metrics 8 (1): 1–9. https://doi.org/10.1186/1478-7954-8-6.Search in Google Scholar
Tangcharoensathien, V., S. Pitayarangsarit, W. Patcharanarumol, P. Prakongsai, H. Sumalee, J. Tosanguan, et al.. 2013. “Promoting Universal Financial Protection: How the Thai Universal Coverage Scheme Was Designed to Ensure Equity.” Health Research Policy and Systems 11: 1–9. https://doi.org/10.1186/1478-4505-11-25.Search in Google Scholar
Thomas, T. K. 2016. “Role of Health Insurance in Enabling Universal Health Coverage in India: A Critical Review.” Health Services Management Research 29 (4): 99–106. https://doi.org/10.1177/0951484816670191.Search in Google Scholar
Thuong, N. T. T., T. Q. Huy, D. A. Tai, and T. N. Kien. 2020. “Impact of Health Insurance on Health Care Utilisation and Out‐of‐pocket Health Expenditure in Vietnam.” BioMed Research International 2020 (1): 9065287. https://doi.org/10.1155/2020/9065287.Search in Google Scholar
United Nations. 2015. Global Sustainable Development Report 2015: Advance Unedited Version. https://sustainabledevelopment.un.org/content/documents/1758GSDR%202015%20Advance%20Unedited%20Version.pdf.Search in Google Scholar
Verma, M. 2019. “Scope of Management of Noncommunicable Diseases in India through Ayushman Bharat.” Journal of Social Health and Diabetes 7 (2): 58–60. https://doi.org/10.1055/s-0039-3401982.Search in Google Scholar
van de Ven, W. P., and F. T. Schut. 2008. “Universal Mandatory Health Insurance in the Netherlands: A Model for the United States?” Health Affairs 27 (3): 771–81. https://doi.org/10.1377/hlthaff.27.3.771.Search in Google Scholar
Vitsupakorn, S., I. Bharali, P. Kumar, G. Yamey, and W. Mao. 2021. “Early Experiences of Pradhan Mantri Jan Arogya Yojana (PM-JAY) in India: A Narrative Review. The Center for Policy Impact in Global Health.” Duke Global Working Paper Series: Number 30, February 2021.10.2139/ssrn.3797792Search in Google Scholar
Wagstaff, A. 2010. “Social Health Insurance Reexamined.” Health Economics 19 (5): 503–17. https://doi.org/10.1002/hec.1492.Search in Google Scholar
Wagstaff, A., M. Lindelow, G. Jun, X. Ling, and Q. Juncheng. 2009. “Extending Health Insurance to the Rural Population: An Impact Evaluation of China’s New Cooperative Medical Scheme.” Journal of Health Economics 28 (1): 1–19. https://doi.org/10.1016/j.jhealeco.2008.10.007.Search in Google Scholar
World Health Organization. 2023. World Health Statistics 2023: Monitoring Health for the SDGs, Sustainable Development Goals, 59. World Health Organization.Search in Google Scholar
Wyss, R., A. R. Ellis, M. A. Brookhart, C. J. Girman, M. J. Funk, R. LoCasale, et al.. 2014. “The Role of Prediction Modeling in Propensity Score Estimation: An Evaluation of Logistic Regression, bCART, and the Covariate Balancing Propensity Score.” American Journal of Epidemiology 180 (6): 645–55. https://doi.org/10.1093/aje/kwu181.Search in Google Scholar
Zhao, Q., and D. Percival. 2017. “Entropy Balancing Is Doubly Robust.” Journal of Causal Inference 5 (1): 20160010. https://doi.org/10.1515/jci-2016-0010.Search in Google Scholar
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