Shankar Prinja1, Maninder Pal Singh2, Kavitha Rajsekar3, Oshima Sachin3, Praveen Gedam4, Anu Nagar3, Balram Bhargava3,5. 1. Department of Community Medicine and School of Public Health, Postgraduate Institute of Medical Education and Research, Sector-12, Chandigarh, 160012, India. shankarprinja@gmail.com. 2. Department of Community Medicine and School of Public Health, Postgraduate Institute of Medical Education and Research, Sector-12, Chandigarh, 160012, India. 3. Department of Health Research, Ministry of Health and Family Welfare, Government of India, New Delhi, India. 4. National Health Authority, Ministry of Health and Family Welfare, Government of India, New Delhi, India. 5. Indian Council of Medical Research, Ministry of Health and Family Welfare, Government of India, New Delhi, India.
Abstract
BACKGROUND: In 2018, the Government of India launched Ayushman Bharat Pradhan Mantri-Jan Aarogya Yojana (AB PM-JAY), a large tax-funded health insurance scheme. In this paper, we present findings of the Costing of Health Services in India (CHSI) study, describe the process of use of cost evidence for price-setting under AB PM-JAY, and estimate its fiscal impact. METHODS: Reference costs were generated from the first phase of CHSI study, which sampled 11 tertiary public hospitals from 11 Indian states. Cost for Health Benefit Packages (HBPs) was estimated using mixed (top-down and bottom-up) micro-costing methods. The process adopted for price-setting under AB PM-JAY was observed. The cost of each HBP was compared with AB PM-JAY prices before and after the revision, and the budgetary impact of this revision in prices was estimated. FINDINGS: Following the CHSI study evidence and price consultations, 61% of AB PM-JAY HBP prices were increased while 18% saw a decline in the prices. In absolute terms, the mean increase in HBP price was ₹14,000 (₹450-₹1,65,000) and a mean decline of ₹6,356 (₹200-₹74,500) was observed. Nearly 42% of the total HBPs, in 2018, had a price that was less than 50% of the true cost, which declined to 20% in 2019. The evidence-informed revision of HBP prices is estimated to have a minimal fiscal impact (0.7%) on the AB PM-JAY claims pay-out. INTERPRETATION: Evidence-informed price-setting helped to reduce wide disparities in cost and price, as well as aligning incentives towards broader health system goals. Such strategic purchasing and price-setting requires the creation of systems of generating evidence on the cost of health services. Further research is recommended to develop a cost-function to study changes in cost with variations in time, region, prices, skill-mix and other factors.
BACKGROUND: In 2018, the Government of India launched Ayushman Bharat Pradhan Mantri-Jan Aarogya Yojana (AB PM-JAY), a large tax-funded health insurance scheme. In this paper, we present findings of the Costing of Health Services in India (CHSI) study, describe the process of use of cost evidence for price-setting under AB PM-JAY, and estimate its fiscal impact. METHODS: Reference costs were generated from the first phase of CHSI study, which sampled 11 tertiary public hospitals from 11 Indian states. Cost for Health Benefit Packages (HBPs) was estimated using mixed (top-down and bottom-up) micro-costing methods. The process adopted for price-setting under AB PM-JAY was observed. The cost of each HBP was compared with AB PM-JAY prices before and after the revision, and the budgetary impact of this revision in prices was estimated. FINDINGS: Following the CHSI study evidence and price consultations, 61% of AB PM-JAY HBP prices were increased while 18% saw a decline in the prices. In absolute terms, the mean increase in HBP price was ₹14,000 (₹450-₹1,65,000) and a mean decline of ₹6,356 (₹200-₹74,500) was observed. Nearly 42% of the total HBPs, in 2018, had a price that was less than 50% of the true cost, which declined to 20% in 2019. The evidence-informed revision of HBP prices is estimated to have a minimal fiscal impact (0.7%) on the AB PM-JAY claims pay-out. INTERPRETATION: Evidence-informed price-setting helped to reduce wide disparities in cost and price, as well as aligning incentives towards broader health system goals. Such strategic purchasing and price-setting requires the creation of systems of generating evidence on the cost of health services. Further research is recommended to develop a cost-function to study changes in cost with variations in time, region, prices, skill-mix and other factors.