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Background   Mobile health applications are increasingly used to support the delivery of health care services to a variety of patients. Based on data obtained from a pragmatic trial of the electronic Patient Reported Outcome (ePRO) app designed to support goal-oriented care primary care, this study aims to (1) examine how patient-reported usability changed over the one-year intervention period, and (2) explore participant attrition rate of the electronic Patient Reported Outcome app over one year study period.Methods   We performed a secondary analysis of 44 older adults with complex chronic needs enrolled in the electronic Patient Reported Outcome-digital health intervention. App usage and attrition were measured using device-generated usage logs; usability was measured using the patient-reported post-study system usability questionnaire collected at 3, 6, 9, and 12 months. Research memos were used to interpret potential contextual contributing factors to patients’ overall usage and usability score pattern. A data triangulation method of both quantitative and qualitative data was used to analyze and interpret study findings.Results   While there was gradual attrition in the use of the ePRO app, patients’ usability scores remained consistent throughout the study period. Qualitative memos suggested patients’ encounters with technical difficulties and relationship dynamics with primary providers influenced patients’ adherence to the ePRO app.Conclusion   This study highlights that the patient–provider relationship is a key determining factor that influences complex patients’ continued engagement with a Mobile health app. The finding calls attention to the measurement of usability of a Mobile health app, its impact on attrition, and contributing factors that influence patients’ attrition. Trial registration: Clinicaltrials.gov Identified NCT02917954.

digital health

Exploring the relationship between the usability of a goal-oriented mobile health application and non-usage attrition in patients with multimorbidity: A blended data analysis approach