Development and Internal Evaluation of a Preliminary Technology Engagement Score in a Cardiovascular Digital-care Cohort: A Retrospective Observational Study

Abstract

Background: Digital cardiovascular-care programmes involve interactions with multiple care-team roles, but scheduled call completion may not adequately reflect clinical benefit. Aims: To characterise quality-of-life outcomes across cardiovascular disease/comorbidity cohorts enrolled in a digital cardiovascular care programme, evaluate associations between care-team engagement and outcomes, and assess a novel Technology Engagement Score (TES-v1). Study Design: Retrospective observational cohort study. Place and Duration of Study: Data were obtained from patients enrolled in the Lyfe digital cardiovascular care platform (Lupin Digital Health Pvt. Ltd., India) between January 2025 and June 2026. Methodology: A patient-level dataset was compiled from 12 predefined cardiovascular disease/comorbidity cohorts. Of the 481 participants enrolled, 298 with complete Cardio Therapist (CT), Lyfe Care Manager (LCM), and Health Coach (HC) engagement data were included. TES-v1 was developed using care-team call completion rates, baseline and follow-up SF-36 scores, and corresponding clinical outcomes. Associations between engagement metrics and outcomes were assessed, with false discovery rate (FDR) adjustment for multiple comparisons. Results: Among 481 participants, 298 (62.0%) had complete engagement data and were analysed. Statistically significant improvements in SF-36 scores were observed in 8 of 12 cohorts after FDR adjustment. Three engagement-outcome associations achieved nominal statistical significance prior to multiplicity correction. TES-v1 showed little association with SF-36 change (rho = 0.029; P = 0.613) and limited apparent discrimination for the exploratory responder outcome (AUC = 0.481). Conclusion: Digital cardiovascular care programs may improve patient-reported quality of life. As a proof-of-concept measure, TES-v1 offers a preliminary framework for quantifying multidimensional technology engagement beyond simple contact completion metrics. Prospective studies are needed to validate its predictive performance and clinical utility.