Abstract 4366999: Optimizing Representation and Retention in Hybrid Cardiac Rehabilitation: Lessons Learned from the mTECH-Rehab Randomized Controlled Trial
Abstract
Background: Cardiac rehab (CR) is a critical but underused secondary prevention program. Hybrid CR programs have the potential to improve patient access by enabling home CR sessions alongside traditional in-center sessions. However, representation and retention of patients who enroll in hybrid CR remain a knowledge gap. Methods: The mTECH-Rehab trial evaluated a 12-week hybrid CR program (center and home-based), recruiting from four inpatient sites, with outpatient delivery at affiliated and unaffiliated centers based on patient preference. We integrated strategies informed by early pilot data to facilitate representative enrollment and retention. These included remote recruitment with electronic consent, a pre-randomization run-in period, and human-centered design paired with digital engagement workflows. Participants in the intervention arm received necessary devices (smartphones, smartwatches, blood pressure monitors) to mitigate digital access barriers. Trained tech coaches ran personalized onboarding guided by a structured protocol, with on-demand participant support throughout the trial. A 4-week run-in period ensured continued interest and digital readiness. Weekly metrics included screening, enrollment, dropout, and randomization to inform adaptive outreach (Fig. 1 ). Results: Of 6,170 patients screened, 1,252 (19%) met eligibility criteria; 969 (77%) were contacted, and 259 (27%) enrolled (mean [SD] age 65 [11.7] years). Among those enrolled, 202 (78%) were randomized, and 167 (83%) of these were retained and completed follow-up. Representation by age, sex, and race remained stable across all phases (mean [SD] age = 64 [12] years enrolled and retained; 32% women enrolled, 31% retained; 9% African Americans enrolled, 10% retained), suggesting that access-related barriers did not lead to attrition ( Fig 2) . Reasons for dropout included unavailability for clinical visits (25%), insurance or logistical issues (22%), loss of contact (19%), unreliable follow-up (19%), withdrawal of consent (9%), and health issues (7%). Conclusion: In our trial, despite low enrollment of racial and ethnic groups, demographic retention and representation in hybrid CR by age, sex, and race were stable. This is an encouraging result achieved through a multifaceted strategy that included a run-in phase, digital device provision, supportive onboarding, and on-demand technology support. Whether such stability can be achieved in a real-world implementation requires further investigation.
Article Details
Authors (34)
Zaib Hussain
Johns Hopkins University, Baltimore, Maryland, United States
Asma Rayani
Johns Hopkins University, Baltimore, Maryland, United States
Nino Isakadze
Johns Hopkins School of Medicine, Baltimore, Maryland, United States
Chang Kim
Johns Hopkins University, Baltimore, Maryland, United States
Mansi Nimbalkar
Johns Hopkins University, Arlington, Virginia, United States
Jie Ding
Max Planck Institute of Microstructure Physics
Ali Asghar Kassamali
Johns Hopkins University, Baltimore, Maryland, United States
Xinyi Zhang
Robert Weinstein
Johns Hopkins School of Medicine, Baltimore, Maryland, United States
Henry Zhao
Johns Hopkins University, Glenwood, Maryland, United States
Zane MacFarlane
University of Pennsylvania, Philadelphia, Pennsylvania, United States
Yumin Gao
Johns Hopkins BSPH, Baltimore, Maryland, United States
Qicong Sheng
University of California, Los Angeles, Los Angeles, California, United States
Ashley Broderick
Johns Hopkins University, Baltimore, Maryland, United States
Alexandra Bush
Johns Hopkins Bayview MedicalCenter, Baltimore, Maryland, United States
Meghan Harp
Johns Hopkins University, Baltimore, Maryland, United States
Preeti Benjamin
Johns Hopkins University, Baltimore, Maryland, United States
Brittany Neigh
Johns Hopkins University, Baltimore, Maryland, United States
Jackie Lobien
Johns Hopkins University, Baltimore, Maryland, United States
Tara Reddy
Johns Hopkins University, Baltimore, Maryland, United States
Tanya Burley
Johns Hopkins University, Baltimore, Maryland, United States
Keith Jackson
Johns Hopkins University, Baltimore, Maryland, United States
Matthias Lee
Johns Hopkins University, Baltimore, Maryland, United States
Jeffrey Sham
Johns Hopkins University, Baltimore, Maryland, United States
Nancy Molello
Johns Hopkins University, Baltimore , Maryland, United States
Yvonne Commodore-Mensah
Kerry Stewart
Johns Hopkins University, Owings Mills, Maryland, United States
Erin Spaulding
Johns Hopkins School of Nursing, Baltimore, Maryland, United States
Daniel Hanley
Nichol McBee
Johns Hopkins University, Baltimore, Maryland, United States
Erin Michos
Johns Hopkins Medicine, Clarksville, Maryland, United States
Francoise Marvel
Johns Hopkins Hospital, Baltimore, Maryland, United States
Lena Mathews
Johns Hopkins, Baltimore, Maryland, United States
Seth Martin
Johns Hopkins School of Medicine, Baltimore, Maryland, United States