Transforming Urban Primary Health Care Through Digitalization: The Sanjeevani Clinic Experience in Madhya Pradesh

ProblemRapid and unplanned urbanization in LMICs exacerbates health inequities, particularly among the urban poor living in slums. In Madhya Pradesh (MP), India, the state government introduced Sanjeevani clinics to provide free, quality healthcare to these populations. This study highlights lessons from digitizing these clinics and making them AI-ready with an open-source AI framework. ApproachA multisectoral collaboration between the state government, implementation, and academic partners led to their successful digitization and AI-readiness of Sanjeevani clinics. An innovative, three-tablet task-shifting model and Smart Clinic Application reduced the data entry burden. ChikitsaChakra, an open-source, probabilistic decision support framework with a voice interface was developed to glean insights from data. Local settingMadhya Pradesh has a population of over 84 million, with approximately 24 million (29%) living in urban settings. Of these, 6.7 million (28%) resided in urban weak economic clusters. Prior to the introduction of Sanjeevani clinics, the population was heavily reliant on private healthcare, incurring significant out-of-pocket expenditures (OOPE). Relevant changesDigitization created an evidence base for over 2.6 million primary care consultations, saving over $33 million in cumulative OOPE while also revealing patterns in antibiotic prescribing. Lessons learnedThe Sanjeevani clinics" success hinged on multisectoral collaboration among government bodies, nonprofits, academia, and private partners, crucial for digitalization and AI-readiness. The innovative three-tablet model and application improved data quality, reducing healthcare workers" burdens and enhancing monitoring and evaluation. ChikitsaChakra provided essential insights.