A meta-analysis of remote patient monitoring for chronic heart failure patients

J Telemed Telecare. 2014 Jan;20(1):11-7. doi: 10.1177/1357633X13517352. Epub 2013 Dec 18.

Abstract

We carried out a meta analysis of remote patient monitoring (RPM) for chronic heart failure (CHF) patients. A literature search was used to identify randomised controlled trials with more than 40 patients, published between February 2003 and February 2013. The primary outcome (mortality) was analysed using a random effect model. Thirteen studies were included (3337 patients). RPM resulted in a significantly lower mortality (risk ratio 0.76; 95% confidence interval 0.62 to 0.93) compared to usual care. The test for heterogeneity showed that articles had been extracted homogeneously (I(2)=0%, P=0.67). In order to determine which RPM model was most effective, subgroup analyses were conducted by age, severity of illness, measurement frequency, medication management and speed of intervention. The group with rapid intervention had the lowest mortality (rapid group risk ratio=0.59, non-rapid group risk ratio=0.88, P=0.05). The group with high measurement frequency had lower mortality (high frequency group risk ratio=0.62, low frequency group risk ratio=0.89, P=0.07). The group with medication management had lower mortality (medication group risk ratio=0.65, non medication group risk ratio=0.85, P=0.19). RPM is effective in chronic heart failure and rapid intervention was the most important factor in the RPM model.

Publication types

  • Meta-Analysis
  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Aged
  • Chronic Disease
  • Disease Progression
  • Heart Failure / drug therapy
  • Heart Failure / mortality
  • Heart Failure / physiopathology*
  • Humans
  • Medication Therapy Management / statistics & numerical data*
  • Middle Aged
  • Monitoring, Physiologic / methods*
  • Mortality / trends
  • Outcome and Process Assessment, Health Care / statistics & numerical data*
  • Randomized Controlled Trials as Topic
  • Severity of Illness Index
  • Telemedicine / methods*
  • Telemedicine / statistics & numerical data