We developed an automated, chat-based, digital health intervention using Bluetooth-enabled home spirometers to monitor for complications of lung transplantation in a real-world application. A chat-based application prompted patients to perform home spirometry, enter their forced expiratory volume in 1 second (FEV1), answer symptom queries, and provided patient education. The program alerted patients and providers to substantial FEV1 decreases and concerning symptoms. Data was integrated into the electronic health record (EHR) system and dashboards were developed for program monitoring.
Between May 2020 and December 2021, 544 patients were invited to enroll, of whom 427 were invited remotely and 117 were enrolled in-person. 371 (68%) participated by submitting ≥1 FEV1 values. Overall engagement was high, with an average of 197 unique patients submitting FEV1 data per month. In-person enrollees submitted an average of 4.6 FEV1 values per month and responded to 55% of scheduled chats. Home and laboratory FEV1 values correlated closely (rho = 0.93). There was an average of 133±59 FEV1 decline alerts and 59±23 symptom alerts per month. 72% of patients accessed education modules, and the program had a high net promoter score (53) amongst users.
We demonstrate that a novel, automated, chat-based, and EHR-integrated home spirometry intervention is well accepted, generates reliable assessments of graft function, and can deliver automated feedback and education resulting in moderately-high adherence rates. We found that in-person onboarding yields better engagement and adherence. Future work will aim to demonstrate the impact of remote care monitoring on early detection of lung transplant complications.
Abbreviations:CLAD (Chronic lung allograft dysfunction), FEV1 (Forced expiratory volume in the first second), EHR (Electronic health record), UCSF (University of California San Francisco), NPS (net promotor score)
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