Evidence map›Paper›PMID 35982425›Full record

ArticleBMC health services research2022

The trust and insurance models of healthcare purchasing in the Ayushman Bharat Pradhan Mantri Jan Arogya Yojana in India: early findings from case studies of two states.

Kheya Melo Furtado, Arif Raza, Devasheesh Mathur, Nafisa Vaz, Ruchira Agrawal, Zubin Cyrus Shroff

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Article in BMC health services research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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5citing papers in PubMed
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3 · Its place in the literature

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5 citing papers in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Kheya Melo FurtadoGoa Institute of Management, Poriem, Sattari, Goa, India, 403505. kheya.furtado@gim.ac.in.
Arif RazaGoa Institute of Management, Poriem, Sattari, Goa, India, 403505.
Devasheesh MathurGoa Institute of Management, Poriem, Sattari, Goa, India, 403505.
Nafisa VazGoa Institute of Management, Poriem, Sattari, Goa, India, 403505.
Ruchira AgrawalNational Health Authority, Ministry of Health and Family Welfare, Government of India, New Delhi, India.
Zubin Cyrus ShroffAlliance for Health Policy and Systems Research, World Health Organization, Geneva, Switzerland.

Funding

World Health Organization 001
6 · The paper itself

Abstract

backgroundThe Pradhan Mantri Jan Arogya Yojana (PMJAY), a publicly funded health insurance scheme for the poor in India, was launched in 2018. Early experiences of states with various purchasing arrangements can provide valuable insights for its future performance. We sought to understand the institutional agencies and performance of the trust and insurance models of purchasing with respect to; a) Provider contracting b) Claim management c) Implementation costs.

methodsA mixed methods case study design was adopted. Two states, Uttar Pradesh (representing a trust model) and Jharkhand (representing the insurance model) were purposively selected. Data sources included document reviews, key informant interviews, quantitative scheme data from the provider empanelment and claims database, and primary data on costs. Descriptive statistics were reported for quantitative data, content analysis was used for thematic reporting of qualitative data.

resultsIn both models, the state was the final authority on empanelment decisions, with no significant influence of the insurance company. Private hospitals constituted the majority of empanelled providers, with wide variations in district-wise distribution of bed capacities in both states. The urgency of completing empanelment in the early days of the scheme created the need for both states to re-review hospitals and de-empanel those not meeting requirements. Very few quality- accredited private hospitals were empaneled. The trust displayed more oversight of support agencies for claim management, longer processing times, a higher claim rejection rate and numbers of queries raised, as compared to the insurance model. Support agencies in both states faced challenges in assessing the clinical decisions of hospitals. Cost-effectiveness showed mixed results; the trust cost less than the insurance model per beneficiary enrolled, but more per claim generated.

conclusionsEfforts are required to enable a better distribution and ensure quality of care in empanelled hospitals. The adoption of standard treatment guidelines is needed to support hospitals and implementing agencies in better claim management. The oversight of agencies through enforcement of contracts remains vital in both models. Assessing the comparative performance of trusts and insurance companies in more states at later stages of scheme implementation, would be further useful to determine their cost-effectiveness as purchasers.

Indexed as

Delivery of Health CareInsurance, HealthHospitals, PrivateHumansIndiaClaim managementHealth financingHealth insuranceIndiaPMJAYProvider contractingPurchasing modelStrategic purchasingUniversal health coverage

Identifiers

PMID35982425
PMCPMC9389741

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.