BACKGROUND Patient engagement attrition in mobile health (mHealth) remote patient monitoring programs (RPM) erodes program benefits. Systemic disparities lead to inequities in RPM adoption and usage. There is an urgent need to understand the RPM patient experience in real-world studies, especially for patients who have dropped-off in engagement, as addressing issues faced by these patients may increase the value of mHealth for patients and subsequently decrease attrition. OBJECTIVE This study sought to understand patient engagement and experiences in a lung transplant RPM mHealth intervention. METHODS Lung transplant patients (N=601) were analyzed from an mHealth intervention for complication detection from 5/4/2020 to 11/1/2022. Predictors of patient engagement were evaluated using multivariable logistic and linear regression. Semi-structured interviews were conducted with participants who had dropped-off. Themes were identified until saturation. RESULTS Patients with a transplant date one year or more before enrollment had 84% lower odds of engaging (OR 0.16, 95% CI 0.07-0.35, p<0.01), 82% lower odds of submitting pulmonary function measurements (OR 0.18, 95% CI 0.09-0.33, p<0.01), and 78% lower odds of completing symptom checklists (OR 0.22, 95% CI 0.10-0.43, p<0.01). Patients with a non-English primary language had 78% lower odds of engaging compared to English speakers (OR 0.22, 95% CI 0.07-0.67; p<0.01). Interviews revealed eight themes: Challenges with devices; Communication break-downs; Desire for “real” interactions; Better feedback around data reporting; Knowing that their data is being monitored; Understanding purpose of the chat; Understanding how their data is used; Recommendation for newer patients. CONCLUSIONS Care delivery and patient experiences with RPM in lung transplant mHealth can be improved and made more equitable by tailoring outreach and enhancements towards patients with longer time between transplant and enrollment and non-English primary languages. Attention to designing programs to provide personalization, education, and information transparency may decrease attrition rates.

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