ArticleJAMA network open2026
A Community-Level Digital Health Readiness Index for the US.
Article in JAMA network open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Digital Health Readiness and Medicare Primary Care Spending: Nationwide County-Level Observational Analysis.Journal of medical Internet research · 2026Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
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.
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Registered trials
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