Impact of health benefit package policy interventions on service utilisation under government-funded health insurance in Punjab, India: analysis of Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (PM-JAY)

Shankar Prinja; Jyoti Dixit; Ruby Nimesh; Basant Garg; Rupinder Khurana; Amit Paliwal; Arun Kumar Aggarwal

doi:10.1016/j.lansea.2024.100462

Impact of health benefit package policy interventions on service utilisation under government-funded health insurance in Punjab, India: analysis of Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (PM-JAY)

Lancet Reg Health Southeast Asia. 2024 Aug 19:28:100462. doi: 10.1016/j.lansea.2024.100462. eCollection 2024 Sep.

Authors

Shankar Prinja¹, Jyoti Dixit¹, Ruby Nimesh¹, Basant Garg², Rupinder Khurana¹, Amit Paliwal³, Arun Kumar Aggarwal¹

Affiliations

¹ Department of Community Medicine and School of Public Health, Post Graduate Institute of Medical Education and Research (PGIMER), Chandigarh, India.
² National Health Authority, Ministry of Health and Family Welfare, Government of India, India.
³ Indo German Programme on Universal Health Coverage (IGUHC), Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ), India.

Abstract

Background: The design of health benefits package (HBP), and its associated payment and pricing system, is central to the performance of government-funded health insurance programmes. We evaluated the impact of revision in HBP within India's Pradhan Mantri Jan Arogya Yojana (PM-JAY) on provider behaviour, manifesting in terms of utilisation of services.

Methods: We analysed the data on 1.35 million hospitalisation claims submitted by all the 886 (222 government and 664 private) empanelled hospitals in state of Punjab, from August 2019 to December 2022, to assess the change in utilisation from HBP 1.0 to HBP 2.0. The packages were stratified based on the nature of revision introduced in HBP 2.0, i.e., change in nomenclature, construct, price, or a combination of these. Data from National Health System Cost Database on cost of each of the packages was used to determine the cost-price differential for each package during HBP 1.0 and 2.0 respectively. A dose-response relationship was also evaluated, based on the multiplicity of revision type undertaken, or based on extent of price correction done. Change in the number of monthly claims, and the number of monthly claims per package was computed for each package category using an appropriate seasonal autoregressive integrated moving average (SARIMA) time series model.

Findings: Overall, we found that the HBP revision led to a positive impact on utilisation of services. While changes in HBP nomenclature and construct had a positive effect, incorporating price corrections further accentuated the impact. The pricing reforms highly impacted those packages which were originally significantly under-priced. However, we did not find statistically significant dose-response relationship based on extent of price correction. Thirdly, the overall impact of HBP revision was similar in public and private hospitals.

Interpretation: Our paper demonstrates the significant positive impact of PM-JAY HBP revisions on utilisation. HBP revisions need to be undertaken with the anticipation of its long-term intended effects.

Funding: Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ).

Keywords: Behavioural economics; Health benefit packages; Health insurance; Reimbursement rates; Supplier-induced demand; Universal health coverage.