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Public health insurance coverage in India before and after PM-JAY: repeated cross-sectional analysis of nationally representative survey data

INTRODUCTION: The provision of non-contributory public health insurance (NPHI) to marginalised populations is a critical step along the path to universal health coverage. We aimed to assess the extent to which Ayushman Bharat-Pradhan Mantri Jan Arogya Yojana (PM-JAY)—potentially, the world’s largest...

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Autores principales: Mohanty, Sanjay K, Upadhyay, Ashish Kumar, Maiti, Suraj, Mishra, Radhe Shyam, Kämpfen, Fabrice, Maurer, Jürgen, O'Donnell, Owen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10462969/
https://www.ncbi.nlm.nih.gov/pubmed/37640493
http://dx.doi.org/10.1136/bmjgh-2023-012725
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author Mohanty, Sanjay K
Upadhyay, Ashish Kumar
Maiti, Suraj
Mishra, Radhe Shyam
Kämpfen, Fabrice
Maurer, Jürgen
O'Donnell, Owen
author_facet Mohanty, Sanjay K
Upadhyay, Ashish Kumar
Maiti, Suraj
Mishra, Radhe Shyam
Kämpfen, Fabrice
Maurer, Jürgen
O'Donnell, Owen
author_sort Mohanty, Sanjay K
collection PubMed
description INTRODUCTION: The provision of non-contributory public health insurance (NPHI) to marginalised populations is a critical step along the path to universal health coverage. We aimed to assess the extent to which Ayushman Bharat-Pradhan Mantri Jan Arogya Yojana (PM-JAY)—potentially, the world’s largest NPHI programme—has succeeded in raising health insurance coverage of the poorest two-fifths of the population of India. METHODS: We used nationally representative data from the National Family Health Survey on 633 699 and 601 509 households in 2015–2016 (pre-PM-JAY) and 2019–2021 (mostly, post PM-JAY), respectively. We stratified by urban/rural and estimated NPHI coverage nationally, and by state, district and socioeconomic categories. We decomposed coverage variance between states, districts, and households and measured socioeconomic inequality in coverage. For Uttar Pradesh, we tested whether coverage increased most in districts where PM-JAY had been implemented before the second survey and whether coverage increased most for targeted poorer households in these districts. RESULTS: We estimated that NPHI coverage increased by 11.7 percentage points (pp) (95% CI 11.0% to 12.4%) and 8.0 pp (95% CI 7.3% to 8.7%) in rural and urban India, respectively. In rural areas, coverage increased most for targeted households and pro-rich inequality decreased. Geographical inequalities in coverage narrowed. Coverage did not increase more in states that implemented PM-JAY. In Uttar Pradesh, the coverage increase was larger by 3.4 pp (95% CI 0.9% to 6.0%) and 4.2 pp (95% CI 1.2% to 7.1%) in rural and urban areas, respectively, in districts exposed to PM-JAY and the increase was 3.5 pp (95% CI 0.9% to 6.1%) larger for targeted households in these districts. CONCLUSION: The introduction of PM-JAY coincided with increased public health insurance coverage and decreased inequality in coverage. But the gains cannot all be plausibly attributed to PM-JAY, and they are insufficient to reach the goal of universal coverage of the poor.
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spelling pubmed-104629692023-08-30 Public health insurance coverage in India before and after PM-JAY: repeated cross-sectional analysis of nationally representative survey data Mohanty, Sanjay K Upadhyay, Ashish Kumar Maiti, Suraj Mishra, Radhe Shyam Kämpfen, Fabrice Maurer, Jürgen O'Donnell, Owen BMJ Glob Health Original Research INTRODUCTION: The provision of non-contributory public health insurance (NPHI) to marginalised populations is a critical step along the path to universal health coverage. We aimed to assess the extent to which Ayushman Bharat-Pradhan Mantri Jan Arogya Yojana (PM-JAY)—potentially, the world’s largest NPHI programme—has succeeded in raising health insurance coverage of the poorest two-fifths of the population of India. METHODS: We used nationally representative data from the National Family Health Survey on 633 699 and 601 509 households in 2015–2016 (pre-PM-JAY) and 2019–2021 (mostly, post PM-JAY), respectively. We stratified by urban/rural and estimated NPHI coverage nationally, and by state, district and socioeconomic categories. We decomposed coverage variance between states, districts, and households and measured socioeconomic inequality in coverage. For Uttar Pradesh, we tested whether coverage increased most in districts where PM-JAY had been implemented before the second survey and whether coverage increased most for targeted poorer households in these districts. RESULTS: We estimated that NPHI coverage increased by 11.7 percentage points (pp) (95% CI 11.0% to 12.4%) and 8.0 pp (95% CI 7.3% to 8.7%) in rural and urban India, respectively. In rural areas, coverage increased most for targeted households and pro-rich inequality decreased. Geographical inequalities in coverage narrowed. Coverage did not increase more in states that implemented PM-JAY. In Uttar Pradesh, the coverage increase was larger by 3.4 pp (95% CI 0.9% to 6.0%) and 4.2 pp (95% CI 1.2% to 7.1%) in rural and urban areas, respectively, in districts exposed to PM-JAY and the increase was 3.5 pp (95% CI 0.9% to 6.1%) larger for targeted households in these districts. CONCLUSION: The introduction of PM-JAY coincided with increased public health insurance coverage and decreased inequality in coverage. But the gains cannot all be plausibly attributed to PM-JAY, and they are insufficient to reach the goal of universal coverage of the poor. BMJ Publishing Group 2023-08-28 /pmc/articles/PMC10462969/ /pubmed/37640493 http://dx.doi.org/10.1136/bmjgh-2023-012725 Text en © Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Original Research
Mohanty, Sanjay K
Upadhyay, Ashish Kumar
Maiti, Suraj
Mishra, Radhe Shyam
Kämpfen, Fabrice
Maurer, Jürgen
O'Donnell, Owen
Public health insurance coverage in India before and after PM-JAY: repeated cross-sectional analysis of nationally representative survey data
title Public health insurance coverage in India before and after PM-JAY: repeated cross-sectional analysis of nationally representative survey data
title_full Public health insurance coverage in India before and after PM-JAY: repeated cross-sectional analysis of nationally representative survey data
title_fullStr Public health insurance coverage in India before and after PM-JAY: repeated cross-sectional analysis of nationally representative survey data
title_full_unstemmed Public health insurance coverage in India before and after PM-JAY: repeated cross-sectional analysis of nationally representative survey data
title_short Public health insurance coverage in India before and after PM-JAY: repeated cross-sectional analysis of nationally representative survey data
title_sort public health insurance coverage in india before and after pm-jay: repeated cross-sectional analysis of nationally representative survey data
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10462969/
https://www.ncbi.nlm.nih.gov/pubmed/37640493
http://dx.doi.org/10.1136/bmjgh-2023-012725
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