
pmid: 24565255
The objective of this review is to propose a conceptual model for heart failure (HF) disease management (HFDM) and to define the components of an efficient HFDM plan in reference to this model. Articles that evaluated 1 or more of the following aspects of HFDM were reviewed: (1) outpatient clinic follow-up; (2) self-care interventions to enhance patient skills; and (3) remote evaluation of worsening HF either using structured telephone support (STS) or by monitoring device data (telemonitoring). The success of programs in reducing readmissions and mortality were mixed. Outpatient follow-up programs generally resulted in improved outcomes, including decreased readmissions. Based on 1 meta-analysis, specialty clinics improved outcomes and nonspecialty clinics did not. Results from self-care programs were inconsistent and might have been affected by patient cognitive status and educational level, and intervention intensity. Telemonitoring, despite initially promising meta-analyses demonstrating a decrease in the number and duration of HF-related readmissions and all-cause mortality rates at follow-up, has not been shown in randomized trials to consistently reduce readmissions or mortality. However, evidence from device monitoring trials in particular might have been influenced by technology and design issues that might be rectified in future trials. Results from the literature suggest that the ideal HFDM plan would include outpatient follow-up at an HF specialty clinic and continuous education to improve patient self-care. The end result of this plan would lead to better understanding on the part of the patient and improved patient ability to recognize and respond to signs of decompensation.
Heart Failure, Self Care, Disease Management, Humans, Models, Theoretical, Telemedicine
Heart Failure, Self Care, Disease Management, Humans, Models, Theoretical, Telemedicine
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 20 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
