Establishing national hospital costing systems: insights from the qualitative assessment of cost surveillance pilot in Indian hospitals

Abstract

ObjectiveThe Indian Government launched Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (PM-JAY), the world’s largest health insurance scheme, in 2018. To reform pricing and gather evidence on healthcare costs, a hospital cost-surveillance pilot was initiated among PM-JAY empanelled hospitals. We analysed the process and challenges from both healthcare providers and payer agency’s perspectives and offer recommendations for implementing similar systems in lower- and middle-income countries.DesignWe employed an open-ended, descriptive and qualitative study design using in-depth interviews (IDI) as the data collection strategy.SettingsThe interviews were conducted in both virtual and face-to-face modes depending on the convenience of the participants. The IDIs for the National Health Authority (NHA) officials and all providers in Kerala were conducted virtually, while face-to-face interviews were conducted and in Haryana and Chhattisgarh.ParticipantsStaff from 21 hospitals in three states (Haryana, Chhattisgarh and Kerala), including officials from State Health Agency (n=5) and NHA (n=3) were interviewed.ResultsThe findings highlight significant challenges in reporting cost data at the hospital level. These include a shortage of trained staff, leading to difficulties in collecting comprehensive and high-quality data. Additionally, the data collection process is resource-intensive and time-consuming, putting strain on limited capacity. Operational issues with transaction management system, such as speed, user-friendliness and frequent page expirations, also pose obstacles. Finally, current patient records data has gaps, in terms of quantity and quality, to be directly put to use for pricing.ConclusionAccurate cost data is vital for health policy decisions. Capacity building across healthcare levels is needed for precise cost collection. Integration into digital infrastructure is key to avoid burdening providers and ensure quality data capture.