Estimating the Unit Costs of Healthcare Service Delivery in India: Addressing Information Gaps for Price Setting and Health Technology Assessment

Applied Health Economics and Health Policy https://doi.org/10.1007/s40258-020-00566-9 ORIGINAL RESEARCH ARTICLE Estimating the Unit Costs of Healthcare Service Delivery in India: Addressing Information Gaps for Price Setting and Health Technology Assessment Pankaj Bahuguna1 Shankar Prinja1 · Lorna Guinness2 · Sameer Sharma1 · Akashdeep Singh Chauhan1 · Laura Downey2,3 · © The Author(s) 2020 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. Key Points for Decision Makers Electronic supplementary material The online version of this article (https://doi.org/10.1007/s40258-020-00566-9) contains supplementary material, which is available to authorized users. * Lorna Guinness * Shankar Prinja 1 Department of Community Medicine and School of Public Health, Post Graduate Institute of Medical Education and Research, Chandigarh 160012, India 2 International Decision Support Initiative, London, UK 3 School of Public Health, Imperial College London, London W2 1NY, UK There is an urgent need for healthcare cost data in India to inform priority setting, insurance reimbursement rates and budgeting. A statistical cost function is used to estimate costs for settings where there currently are no data and provides a set of state-level unit costs. The analysis shows the variability in healthcare costs across different settings and demonstrates the usefulness of such an approach in the absence of national cost datasets. Vol.:(0123456789) P. Bahuguna et al. 1 Background The costs of healthcare service delivery underpin many important policy decisions—from questions of affordability, to making choices between different technologies and innovations, to setting prices of health services. Many countries, and in particular, low- and middle-income countries, suffer from a lack of information in this area, creating an information vacuum that leads to opaque policy decisions and cost escalation in health services [1, 2]. As the modus operandi of public health systems involves the purchasing of services by the state using public money, and as international pressure to move towards systems of Universal Health Care (UHC) coverage grows, governments without cost information are increasingly vulnerable in their ability to engage in strategic purchasing of health services. Cost information allows governments to be better-equipped as price setters and allows for informed decisions around the allocation of resources between different healthcare services and technologies to ensure value for money. The challenges arising from limited healthcare cost information are magnified in the highly complex and fragmented Indian health system, where public services are purchased and delivered by a mix of both private and state providers. India operates under a model of fiscal federalism, where health is primarily the responsibility of state governments. There are a multitude of state insurance schemes in operation across the country that have been introduced to tackle the inequitable access to healthcare [3]. At the central level, the first national government taxfunded scheme for the poor and vulnerable was initiated in 2008. In 2018, the national government then launched the Ayushman Bharat-Prime Minister’s Jan Arogya Yojana (AB-PMJAY), a tax-funded national insurance programme that aims to subsume earlier national and state schemes and to provide healthcare cover of 500,000 Indian Rupees (INR) for over 500 million poor beneficiaries [4]. Despite these different schemes, to date, state governments have not used systematic, evidence-based approaches to setting prices [5]. Until recently, the process of setting prices under AB-PMJAY and other insurance schemes has been somewhat haphazard, relying on surveys of insurance claims data and interviews with experts. The government explained the severity of the problem in 2018: “we don’t have costing studies in India” [6]. While the latter statement exaggerates the issue, there are limited studies, the majority of which focussed on a single disease, technology or site. Data on private expenditures are regularly collected by the National Sample Survey Office, but this is limited to patient expenditures on healthcare and cannot be broken down fully by disease or condition [7, 8]. Insurance claims data from 22 different government-funded schemes have also been collated into a single database; however, these estimates reflect prices agreed by tender and do not represent the cost of production [7, 9]. More recently, the availability of production cost data for the public sector has begun to grow with individual costing studies that have been carried out to explore the cost-effectiveness of different technologies as well as a series of primary costing studies [10–19]. However, the paucity of cost information remains a significant fact within the Indian health system [7, 20]. Compounding the general lack of cost information, a further challenge in the practical application of cost data for price setting and health technology assessment in India is the vast heterogeneity in costs of service delivery across different types of providers, levels of the system, states and geographical settings. Previously published cost studies have highlighted the varia (...truncated)