ABSTRACT
BACKGROUND: Patients admitted with decompensated heart failure (HF) are at risk for hospital readmission and poor quality of life during the discharge period. Lifestyle behavior modifications that promote the self-management of chronic cardiac diseases have been associated with an improved quality of life. However, whether a mobile health (mHealth) program can assist patients in the self-management of HF during the acute posthospital discharge period is unknown. OBJECTIVE: We aimed to develop an mHealth program designed to enhance patients' self-management of HF by increasing knowledge, self-efficacy, and symptom detection. We hypothesized that patients hospitalized with HF would be willing to use a feasibly deployed mHealth program after their hospital discharge. METHODS: We employed a patient-centered outcomes research methodology to design a stakeholder-informed mHealth program. Adult patients with HF admitted to a large academic hospital were enrolled and randomized to receive the mHealth intervention versus usual care. Our feasibility outcomes included ease of program deployment, use of the clinical escalation process, duration of participant recruitment, and participant attrition. Surveys assessing the demographics and clinical characteristics of HF were measured at baseline and at 30 and 90 days after discharge. RESULTS: The study period was between July 1, 2019, and April 7, 2020. The mean cohort (N=31) age was 60.4 (range 22-85) years. Over half of the participants were men (n=18, 58%) and 77% (n=24) were White. There were no significant differences in baseline measures. We determined that an educational mHealth program tailored for patients with HF is feasibly deployed and acceptable by patients. Though not significant, we found notable trends including a higher mean quality of life at 30 days posthospitalization among program users and a longer duration before rehospitalization, which are suggestive of better HF prognosis. CONCLUSIONS: Our mHealth tool should be further assessed in a larger comparative effectiveness trial. Our pilot intervention offers promise as an innovative means to help HF patients lead healthy, independent lives. These preliminary data suggest that patient-centered mHealth tools can enable high-risk patients to play a role in the management of their HF after discharge. TRIAL REGISTRATION: ClinicalTrials.gov NCT03982017; https://clinicaltrials.gov/ct2/show/NCT03982017.
ABSTRACT
Study objective: Remote monitoring (RM) can help patients with heart failure (HF) remain free of hospitalization. Our objective was to implement a patient-centered RM program that ensured timely clinical response, which would be associated with reduced mortality. Design: This was a retrospective, observational, propensity-matched study. Setting: A large regional health system between 9/1/2016-1/31/2018. Participants: Patients admitted with acute HF exacerbation were matched on key variables. Up to two comparison patients were selected for each RM user. Interventions: We used an algorithmic approach to assess daily physiologic data, assess symptoms, provide patient education, encourage patient self-management, and triage medical problems. Main outcome measures: We assessed all-cause mortality using Kaplan-Meier and log rank analysis. We used Cox proportional hazards to compare risk of death. Results: Our cohort of 680 RM users and 1198 comparisons were similar across baseline characteristics except age (74.7 years versus 76.6 years, p < 0.001, respectively). Having one or more admissions in the preceding 120 days was more prevalent in the RM group (35.9% versus 29.8%, p = 0.013). The 30- and 90-day all-cause readmission rates were each higher among the RM users compared with the comparison patients (p = 0.013 and p < 0.001 for 30 and 90 days, respectively). Mortality was lower in the RM group at 30 and 90 days post-discharge (p < 0.001). Conclusions: RM that responds to biometric data and encourages patient self-management can be used in a large hospital system and is associated with decreased all-cause mortality. Our findings underscore RM technology as a method to improve HF care.
