Estimating the Unit Costs of Healthcare Service Delivery in India: Addressing Information Gaps for Price Setting and Health Technology Assessment
Open Access
- 14 March 2020
- journal article
- research article
- Published by Springer Science and Business Media LLC in Applied Health Economics and Health Policy
- Vol. 18 (5), 699-711
- https://doi.org/10.1007/s40258-020-00566-9
Abstract
Background India’s flagship National Health insurance programme (AB-PMJAY) requires accurate cost information for evidence-based decision-making, strategic purchasing of health services and setting reimbursement rates. To address the challenge of limited health service cost data, this study used econometric methods to identify determinants of cost and estimate unit costs for each Indian state. Methods Using data from 81 facilities in six states, models were developed for inpatient and outpatient services at primary and secondary level public health facilities. A best-fit unit cost function was identified using guided stepwise regression and combined with data on health service infrastructure and utilisation to predict state-level unit costs. Results Health service utilisation had the greatest influence on unit cost, while number of beds, facility level and the state were also good predictors. For district hospitals, predicted cost per inpatient admission ranged from 1028 (313–3429) Indian Rupees (INR) to 4499 (1451–14,159) INR and cost per outpatient visit ranged from 91 (44–196) INR to 657 (339–1337) INR, across the states. For community healthcare centres and primary healthcare centres, cost per admission ranged from 412 (148–1151) INR to 3677 (1359–10,055) INR and cost per outpatient visit ranged from 96 (50–187) INR to 429 (217–844) INR. Conclusion This is the first time cost estimates for inpatient admissions and outpatient visits for all states have been estimated using standardised data. The model demonstrates the usefulness of such an approach in the Indian context to help inform health technology assessment, budgeting and forecasting, as well as differential pricing, and could be applied to similar country contexts where cost data are limited.Funding Information
- Bill and Melinda Gates Foundation (OPP1134345)
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