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Effectiveness of Nurse-Coordinated, Digital-Supported Collaborative Care Model in Reducing Hospital Stay and Mortality Among Patients With Heart Failure: TIME-HF Cluster RCT India

In brief

Nurse-led digital care cuts heart-failure death risk by 22% in India

In a cluster-randomized trial of 1,507 patients with reduced-ejection-fraction heart failure, a nurse-coordinated, mobile-health program increased the chance of staying out of the hospital for two years by about 4.5 percentage points and lowered all-cause mortality by roughly one-fifth. The model combined risk stratification, medication optimization and daily self-care support, suggesting a scalable approach for resource-limited settings, though longer-term outcomes remain to be studied.

Journal
Circulation (Q1)
Published
30 August 2026
Study design
Randomized controlled trial
Evidence level
Level 1, High (CEBM 1b)
Authors
Panniyammakal Jeemon, Sanjay Ganapathi, Navya Anikkady, Sunaib Ismail, Govindan Unni, Charantharayil Gopalan Bahuleyan, et al.
PMID
42668439
DOI
10.1161/CIRCULATIONAHA.126.082490

Why clinicians should know about it

  • Picked for Family Practice (top studies of the week, 6 September 2026): Cluster RCT, practice‑changing for heart failure care
  • Picked for Cardiology and Cardiovascular Medicine (top studies of the week, 6 September 2026): Cluster RCT of digital nurse‑coordinated HF care

Abstract

BACKGROUND: Heart failure with reduced ejection fraction causes high mortality and recurrent hospitalizations in India. We evaluated the effectiveness of the collaborative care model in improving days alive and out of the hospital and overall survival. METHODS: We conducted a parallel-group, cluster-randomized controlled trial involving 1507 adults with heart failure with reduced ejection fraction across 22 centers in India (CTRI/2021/11/037797). Centers were randomized 1:1 to the intervention or usual care. Participants were followed up for 2 years. The intervention included risk stratification, lifestyle and pharmacological optimization, and a nurse-coordinated, mobile health-supported disease management program with self-care education, active follow-up, and continuous outpatient monitoring throughout the study period. The primary outcome was days alive and out of the hospital, and all-cause mortality was assessed as a secondary outcome. Days alive and out of the hospital was analyzed with a one-inflated β model. All-cause mortality was analyzed with Cox proportional hazards models adjusted for the clustered study design. RESULTS: Among 1507 participants (752 usual care; 755 intervention), the mean age was 61.9 years, and 77.6% were men. All participants except one completed 24 months of follow-up. Most participants (70%) had low educational attainment; 57.3% lived in rural areas; and ischemic heart disease was the predominant cause (77.4%). Baseline characteristics were comparable between the intervention and usual care groups. In the one-inflated β model, the probability of surviving up to 730 days without hospitalization was 79.4% (95% CI, 77.7%-81.2%) in the usual care group and 84.0% (95% CI, 82.2%-85.8%) in the intervention group. Participants in the intervention group had 78% higher odds of achieving a percent days alive and out of the hospital of exactly 1 (730/730 days) compared with those in the usual care group (odds ratio, 1.78 [95% CI, 1.42-2.23]). There were 201 deaths (26.73%) in the usual care group compared with 163 deaths (21.59%) in the intervention group (risk ratio, 0.80 [95% CI, 0.67-0.97]). In the multivariable Cox proportional hazards model, the intervention group had a 22% lower mortality risk than the usual care group (hazard ratio, 0.78 [95% CI, 0.63-0.95]; P=0.028). CONCLUSIONS: A nurse-coordinated, mobile health-supported collaborative care model for heart failure with reduced ejection fraction in India increased the number of days alive and out of hospital, raised the absolute probability of remaining out of hospital by 4.5 percentage points, and reduced all-cause mortality by 22%. REGISTRATION: URL: www.ctri.nic.in; Unique identifier: CTRI/2021/11/037797.

Abstract as published, via PubMed.

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For healthcare professionals. The summary is generated by AI from the published abstract, and the evidence level is assigned automatically from the study design on the Oxford CEBM hierarchy. Neither is medical advice. Read the full paper before changing practice.