| Literature DB >> 19831704 |
Stuti Dang1, Susan Dimmick, Geetanjali Kelkar.
Abstract
Information and communication technology offers promise for better coordination of care for patients with congestive heart failure (CHF). MEDLINE, EMBASE, and CINHAL databases were searched for evidence on remote monitoring of patients with heart failure (HF). The search was restricted to randomized controlled trials using either automated monitoring of signs and symptoms or automated physiologic monitoring. For this review, telephone-based monitoring of signs and symptoms was not considered remote monitoring. Studies were also excluded if they did not present outcomes related to healthcare utilization. Nine studies met selection criteria, with interventions that varied greatly. Four three-arm studies directly compared the effectiveness of two different interventions to usual care. Six of the nine studies suggested a 27%-40% reduction in overall admissions. Two two-arm studies demonstrated a 40%-46% reduction in HF-related admissions while two other three-arm studies showed similar trends; however, this was not statistically significant. Three of nine studies suggested a significant reduction in mortality (30%-67%) and three studies showed significant reduction in healthcare utilization costs. Two studies suggested a 53%-62% reduction in bed days of care. Two studies showed significant reduction in the number of Emergency Department visits. Three two-arm studies and one three-arm study demonstrated significant overall improvement in outcomes with use of telemonitoring. Available data suggest that telemonitoring is a promising strategy. More data are needed to determine the ideal patient population, technology, and parameters, frequency and duration of telemonitoring, and the exact combination of case management and close monitoring that would assure consistent and improved outcomes with cost reductions in HF.Entities:
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Year: 2009 PMID: 19831704 DOI: 10.1089/tmj.2009.0028
Source DB: PubMed Journal: Telemed J E Health ISSN: 1530-5627 Impact factor: 3.536