Deconstructing Heart Failure Disease Management

  1. Edward H. Wagner, MD, MPH
  1. From MacColl Institute for Healthcare Innovation, Group Health Cooperative; Seattle, WA 98101-1448.

    Frustrated by the challenges of containing costs and improving quality, many medical administrators and policymakers are turning to organized programs for patients with major chronic illnesses. These programs, generally labeled disease management, seek to provide more intensive education, monitoring, and support than may be possible in typical medical practice. Disease management nowadays is most often considered to consist of interventions delivered by a commercial entity distinct from the patient's usual source of medical care (1). Often, the programs rely on telephone contact between a distant nurse care manager and patient. Many people think of congestive heart failure (CHF), with its high rates of hospitalization and rehospitalization and increasingly effective clinical management (2), as the low-hanging fruit of disease management—a prime opportunity for early cost savings. As a result, disease management programs for CHF are proliferating. It's time to ask whether the enthusiasm is warranted.

    An important new trial in this issue by DeBusk and colleagues (3) should give pause. DeBusk and colleagues studied a telephonic CHF nurse-directed care management program in the Kaiser Permanente system. The intervention included intensive self-management counseling, pharmacologic management by protocol, and communication with the patients' physicians. The behavioral interventions were, if anything, more sophisticated and better grounded in evidence than many of those evaluated in other studies. The authors carefully executed the randomized design and study measurements, and the sample size was generous. Despite the elegance of the intervention and evaluation, they found no measurable benefit of disease management over usual care. Given the growing interest in disease management, we need to look closely at this and related trials to identify features that predict success …

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