Adaptation and Psychometric Validation of a Facility-Level Tool to Assess Telemedicine Readiness in Primary Care
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Background
Telehealth has expanded rapidly, yet its sustained use beyond emergency responses remains uneven. Facility and organizational conditions are modifiable determinants of healthcare intervention implementation, and readiness assessments are key steps in the early adoption and further uptake process. However, many telemedicine readiness assessment instruments lack psychometric evidence, limiting their value for benchmarking, prioritizing investments, and monitoring progress at scale.
Objective
To adapt and psychometrically validate the Telemedicine Readiness Inventory at the Facility Level (TRI-F).
Methods
We conducted a cross-sectional analysis using data from an online assessment of a large sample of primary care facilities (PCFs) in Peru, held between December 2023 and March 2024. The analytic sample included 774 PCFs, with one designated respondent per facility completing the survey. Internal structure was evaluated using exploratory factor analysis and confirmatory factor analysis. Internal consistency was estimated using Cronbach’s alpha and McDonald’s omega. Measurement invariance was evaluated across the facility complexity and the respondant’ time working at the PCF. Criterion validity was examined using Spearman correlations between the five domain scores (Organizational readiness, Processes, Digital environment, Human resources, and Regulatory issues) and proportion of telemedicine modality among overall outpatient encounters.
Results
Confirmatory factor models showed adequate fit across domains, with CFI values ranging from 0.959 to 0.999, TLI from 0.952 to 0.997, RMSEA from 0.028 to 0.065, and SRMR from 0.016 to 0.057, for the five domains assessed. Internal consistency was acceptable to high across all domains (α = 0.75-0.87; ω = 0.76-0.88). Measurement invariance was supported across the facility category and time working at the PCF, with ΔCFI values below 0.010. Criterion validity analyses showed positive but small correlations between all five domains and proportional telemedicine use (r s = 0.15–0.23; p < 0.001).
Conclusions
The adapted tool showed satisfactory structural validity, internal consistency, and measurement invariance for assessing telemedicine readiness in PCFs. The availability of percentile-based norms supports interpretation and benchmarking. The instrument can support implementation planning, monitoring, and prioritization of technical assistance in primary care settings.
