Utilisation of ambulatory ECG monitoring for prediction of heart failure and stroke events and healthcare expenditure in treated and untreated patients: a retrospective cohort study.

objectiveWe evaluated the performance of risk models that incorporate ambulatory ECG data and clinical information for prediction of healthcare expenditures related to heart failure (HF) and stroke events in treated and untreated patients. DESIGN AND

settingA retrospective cohort study of Medicare patients who underwent Zio XT ambulatory monitoring in the USA was conducted between 2014 and 2020. PARTICIPANTS AND OUTCOMES: 14-day ambulatory ECG data and claims data were evaluated in the study sample which included 89 923 patients in the HF hospitalisation group, 75 870 in the new-onset HF group and 90 159 in the stroke hospitalisation group. Predictive models for new-onset HF, HF hospitalisation and stroke hospitalisation were generated using LASSO Cox regression with ambulatory ECG variables and components of the CHA

resultsThe following hazard ratios per one SD increase in the new risk score were observed for the model that included all CHA

conclusionsIntegrating arrhythmia data from ambulatory ECG monitoring into clinical risk models allows for better prediction of healthcare utilisation and cost in both treated and untreated patients at high risk for HF and stroke events.