A Community-Level Digital Health Readiness Index for the US

Importance: Digital health services are expanding, yet community readiness for digital care varies widely. Without a validated, granular measure of readiness, health systems and policymakers cannot reliably enable targeted support or monitor equitable deployment. Objective: To develop and validate a reproducible census tract-level index of community digital health readiness integrating socioeconomic conditions, access to care, and digital connectivity. Design, Setting, and Participants: This cross-sectional index development and validation study analyzed public data from 2018 to 2022. The Digital Health Index (DHI) was constructed from 21 indicators with equal weighting representing 3 domains: socioeconomic, health access, and connectivity. Content validity was assessed using a 2-round Delphi panel including 37 experts. Structural validity was assessed with exploratory and confirmatory factor analyses. Convergent validity was assessed against the Social Vulnerability Index (SVI), Area Deprivation Index (ADI), and Digital Divide Index (DDI). External validity was assessed using health care spending. Robustness was assessed using leave-one-out, weight-perturbation, and group-based cross-validation analysis. Data were analyzed between June 2023 and April 2026. Main Outcomes and Measures: Primary outcomes were validation metrics, including factor structure fit indices, correlations with established indices, association with health care spending per capita, and Delphi consensus rates for each indicator. Robustness outcomes included stability of tract rankings under indicator removal or weight changes. Results: The DHI was computed for 85 396 US census tracts across all 50 states. DHI scores correlated with SVI, ADI, and DDI scores (Spearman ρ = 0.61-0.84) but prioritized different low-readiness communities, with only 33% to 44% overlap between tracts in the highest DHI decile and those in the highest SVI, ADI, or DDI deciles. Health care spending showed similar inverse associations across indices. DHI rankings remained stable in sensitivity analyses. All 21 indicators met Delphi consensus criteria after 1 or 2 rounds. Conclusions and Relevance: In this cross-sectional index development and validation study, a reproducible measure of community digital health readiness was constructed at the census tract level, integrating socioeconomic, access, and connectivity factors. The DHI may help health systems, public agencies, and researchers identify communities requiring support and track readiness over time as digital health and artificial intelligence initiatives expand.