Understanding barriers to electronic health record digitalization in India: a complexity theory approach
Shreya Mukherjee et al.
What the paper says
Purpose This study aims to investigate why Indian citizens resist the digitalization of their health records through a government-launched application designed to create a centralized health information system. Despite its potential to enhance health-care access, adoption remains limited, necessitating an exploration of barriers from the citizens’ perspective. Design/methodology/approach A mixed-methods approach was used. In the first phase, qualitative interviews with nonadopters identified key resistance drivers, including computer anxiety, privacy concerns, government surveillance fears, security risks and negative electronic word-of-mouth. In the second phase, data from a survey of 211 participants was analyzed using fuzzy-set Qualitative Comparative Analysis (fsQCA) to uncover configurations of these factors sufficient for resistance. Findings Findings indicate that resistance is shaped not by individual factors but by specific combinations of barriers. The intermediate fsQCA solution showed that the joint presence of all five conditions – computer anxiety, privacy concern, surveillance concern, security risk and negative eWOM – was sufficient to explain resistance. In addition, privacy concerns, security risks and government surveillance fears emerged as necessary conditions. Originality/value To the best of the authors’ knowledge, this study is among the first to examine resistance to a government-led health digitization initiative in a developing country using a configurational perspective. It applies complexity theory to uncover asymmetric pathways to resistance and extends the literature on digital health record adoption. The findings offer practical insights for policymakers to develop comprehensive strategies that address psychological, social and institutional concerns simultaneously.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.