BACKGROUND: Cardiac rehabilitation (CR) improves outcomes in heart disease yet remains vastly underutilized. Remote CR enhanced with a digital health intervention (DHI) may offer higher access and improved patient-centered outcomes over non-technology approaches. We sought to pragmatically determine whether offering a DHI improves CR access, cardiac risk profile, and patient-reported outcome measures. METHODS: Adults referred to CR at a tertiary VA medical center between October 2017 and December 2021 were offered enrollment into a DHI alongside other CR modalities using shared decision-making. The DHI consisted of remote CR with a structured, 3-month home exercise program enhanced with multi-component coaching, a commercial smartphone app, and wearable activity tracker. We measured completion rates among DHI participants and evaluated changes in 6-min walk distance, cardiovascular risk factors, and patient-reported outcomes from pre- to post-intervention. RESULTS: Among 1,643 patients referred to CR, 258 (16%) consented to the DHI where the mean age was 60 ± 9 years, 93% were male, and 48% were black. A majority (90%) of the DHI group completed the program. Over 3-months, significant improvements were seen in 6MWT (mean difference [MD] -29 m; 95% CI, 10 to 49; P < 0.01) and low-density lipoprotein cholesterol (MD -11 mg/dL; 95% CI, -17 to -5; P < 0.01), and the absolute proportion of patients who reported smoking decreased (10% vs 15%; MD, -5%; 95% CI, -8% to -2%; P < 0.01) among DHI participants with available data. No adverse events were reported. CONCLUSIONS: The addition of a DHI-enhanced remote CR program was delivered in 16% of referred veterans and associated with improved CR access, markers of cardiovascular risk, and healthy behaviors in this real-world study. These findings support the continued implementation of DHIs for remote CR in real-world clinical settings. TRIAL REGISTRATION: This trial was registered on ClinicalTrials.gov: NCT02791685 (07/06/2016).

Our study examined the heterogeneity of phenotype algorithms (PA) in literature on Alzheimers disease (AD), major depressive disorder (MDD), and pulmonary arterial hypertension (PAI), focusing on the impact of PA differences on patient overlap and incidence rate variability across conditions in six observational databases. We reviewed 49 replicated PAs (13 for AD, 23 for MDD, and 13 for PAI) and found significant heterogeneity. These varied PAs identified distinct patient cohorts, resulting in significant incidence rate heterogeneity. Despite some papers reporting primary condition codes and inclusion. comprehensive documentation ensuring reproducibility was often lacking, underscoring the need for more transparent and robust research practices.