Testing SAM mobile application for medication adherence

Official title: Smart About Meds (SAM) RCT

Evaluating the Effectiveness of the Smart About Meds (SAM) Medication Management Mobile Application: A Randomized Controlled Trial

About This Trial

Introduction: Almost half of patients discharged from hospital are re-admitted or return to the emergency department (ED) within 90 days. Patient nonadherence to medication changes during hospitalization and the use of potentially inappropriate medications (PIMs) both contribute to the risk of adverse events post-discharge. Smart About Meds (SAM) is a patient-centered mobile application designed to target medication nonadherence and PIMs use. This protocol describes a randomized controlled trial (RCT) to evaluate the effectiveness of SAM. Methods \& Analysis: A pragmatic, stratified RCT will be conducted among 3,250 patients discharged from internal medicine, cardiac care, cardiac surgery, vascular surgery, and respiratory units of the Royal Victoria Hospital and the Montreal General Hospital. At discharge, patients will be randomized 1:1 to usual care or the SAM intervention. SAM integrates novel user-centered features (e.g. continuously updated medication list with pill images, side-effect checker, interaction checker) with pharmacist monitoring to tackle post-discharge nonadherence to new medication regimens. SAM also notifies patients of PIMS in their regimen, with advice to discuss with their physician. Following discharge, patients will be followed for 90 days, during which the occurrence of the composite outcome of ED visits, hospital readmissions, or death will be measured. Secondary outcomes will include the individual components of the composite outcome, nonadherence to medication changes, defined as failure to fill a new prescription, filling a modified prescription at the incorrect dose, or filling discontinued medications, secondary medication adherence, patient empowerment, and health-related quality of life. An intention-to-treat analysis will evaluate the effectiveness of SAM. Multivariable logistic regression will estimate differences between treatment groups in the proportion of patients nonadherent to at least one medication change. With a sample size of 3,250, there will be 80% power to detect a 5% absolute reduction in this outcome. Two-way interaction terms will test hypothesized modifiers of SAM's effectiveness, including hospital, unit, age, sex, gender and comorbidity burden. Binary and continuous secondary outcomes will be assessed using multivariable logistic and linear regression, respectively.