Key result
Personalized interventions using the Well-Beat system significantly increased patient adherence to a cardiac rehabilitation program at 3 months, with 76% of patients remaining active compared to 24% in a historical control group.
Why the study?
Despite the documented benefits of cardiac rehabilitation, dropout rates remain high at 12-56%, motivating the evaluation of personalized interventions to increase patient adherence.
Does a personalized AI-based intervention system improve patient adherence to cardiac rehabilitation programs in post-cardiovascular event patients?
Cohort (n=595)
Open-label
No
Does a personalized AI-based intervention system improve patient adherence to cardiac rehabilitation programs in post-cardiovascular event patients?
The use of an AI-based personalized intervention system providing tailored HCP dialogue and automated text messages significantly increased 3-month patient adherence to cardiac rehabilitation compared to historical controls.
May support adherence interventions in cardiac rehab; hypothesis-generating pending randomized outcome trials.
OBJECTIVES: Despite documented benefits and physicians' recommendations to participate in cardiac rehabilitation (CR) programs, the average dropout rate remains between 12-56%. This study's goal was to demonstrate that using personalized interventions can significantly increase patient adherence. METHOD: Ninety-five patients (ages 18-90) eligible for the CR program were randomly recruited and received personalized interventions using the Well-Beat system. Adherence levels were compared to those of a historical control group. The Well-Beat system provided Sheba CR Health Care Provider (HCP) guidelines for personalized patient-therapist dialogue. The system also generated ongoing personalized text messages for each patient sent twice a week and related each patient's dynamic profile to their daily behavior, creating continuity, and reinforcing the desired behavior. RESULTS: A significant increase in patient adherence to the CR program: Three months after initiation, 76% remained active compared to the historical average of 24% in the matched control group (log-rank p-value = 0.001). CONCLUSIONS: Using an Artificial Intelligence (AI)-based engine that generated recommendations and messages made it possible to improve patient adherence without increasing HCP load, benefiting all. Presenting customized patient insights to the HCP and generating personalized communications along with action motivating text messages can also be useful for remote care.
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Aharon et al. (2022) conducted a cohort in Cardiovascular disease requiring cardiac rehabilitation (n=595). Well-Beat personalized interventions vs. Historical control group was evaluated on Patient adherence to the cardiac rehabilitation program at 3 months (p=<0.001). Personalized interventions using the Well-Beat system significantly increased patient adherence to a cardiac rehabilitation program at 3 months, with 76% of patients remaining active compared to 24% in a historical control group.
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