Text messaging-based collection of patient data to inform prescription opioid management: Development and feasibility testing (Preprint)

Abstract

BACKGROUND Collecting patient-reported data needed by clinicians to adhere to opioid prescribing guidelines represents a significant time burden. OBJECTIVE We developed and tested an opioid management app (OM-App) to collect these data directly from patients. METHODS OM-App used a pre-existing digital health platform to deliver daily questions to patients via text-message and organize responses into a dashboard. We pilot tested OM-App over 9 months in 40 diverse participants with HIV who were prescribed opioids for chronic pain. Feasibility outcomes included: ability to export/integrate OM-App data with other research data; patient-reported barriers and adherence to OM-App use; capture of opioid-related harms, risk behaviors and pain intensity/interference; comparison of OM-App data to urine drug testing, prescription drug monitoring program data, and validated questionnaires. RESULTS OM-App data was exported/integrated into the research database after minor modifications. Thirty-nine of 40 participants were able to use OM-App, and over the study duration 70% of all OM-App questions were answered. Although the cross-sectional prevalence of opioid-related harms and risk behaviors reported via OM-App was low, some of these were not obtained via the other measures, and over the study duration all queried harms/risks were reported at least once via OM-App. Clinically meaningful changes in pain intensity/interference were captured. CONCLUSIONS OM-App was used by our diverse patient population to produce clinically relevant opioid- and pain-related data, which was successfully exported and integrated into a research database. These findings suggest that OM-App may be a useful tool for remote monitoring of patients prescribed opioids for chronic pain. CLINICALTRIAL NCT03669939 INTERNATIONAL REGISTERED REPORT RR2-doi:10.1016/j.conctc.2019.100468