Diagnosing the Health of Digital Health: Development and Validation of a Fast and Frugal Tree (FFT) Decision Tool for Public Health Supervisors in Low-Resource Settings

Background/Objectives: Achieving Universal Health Coverage (UHC) and Sustainable Development Goal 3 in low-resource settings relies on integrating digital health systems. In India, digital health tools have expanded rapidly, yet block-level supervisors and community health workers (CHWs) continue to face “last-mile” implementation barriers. This study aimed to develop, and expert validate a user-centric Fast and Frugal Tree (FFT) decision-support tool enabling block-level public health supervisors to identify and resolve operational bottlenecks in digital health delivery. Methods: A mixed-methods study in an aspirational district with a low Human Development Index) Muzaffarpur, Bihar, included a baseline survey (n = 95 CHWs), 32 in-depth interviews, and six focus group discussions. Thematic analysis identified key operational and behavioral challenges. A 10-step FFT tool was designed and validated through a two-round modified Delphi process with 14 experts. Results: Fieldwork revealed critical deficits in device functionality, connectivity, digital literacy, and grievance redressal systems. The FFT tool maps these bottlenecks to clear, actionable steps. The Delphi consensus exceeded 90% for clarity, relevance, and completeness. The final tool achieved an overall mean Content Validity Index (CVI) of 0.90, with item-level CVI (I-CVI) scores ranging from 0.79 to 1.00 across domains such as clarity, relevance, completeness, practicality, and scalability, indicating strong and consistent expert agreement. Iterative refinement ensured contextual adaptability and field readiness. Conclusions: The validated FFT tool bridges research and practice by offering a scalable, pragmatic protocol for digital health supervision. Its adoption could improve troubleshooting, data quality, and health system performance in similar low-resource settings.