Abstract
BackgroundIdentifying heart failure patients most likely to suffer poor outcomes is an essential part of delivering interventions to those most likely to benefit. We sought a comprehensive account of heart failure events and their cumulative economic burden by examining patient characteristics that predict increased cost or poor outcomes.MethodsWe collected electronic medical data from members of a large HMO who had a heart failure diagnosis and an echocardiogram from 1999–2004, and followed them for one year. We examined the role of demographics, clinical and laboratory findings, comorbid disease and whether the heart failure was incident, as well as mortality. We used regression methods appropriate for censored cost data.ResultsOf the 4,696 patients, 8% were incident. Several diseases were associated with significantly higher and economically relevant cost changes, including atrial fibrillation (15% higher), coronary artery disease (14% higher), chronic lung disease (29% higher), depression (36% higher), diabetes (38% higher) and hyperlipidemia (21% higher). Some factors were associated with costs in a counterintuitive fashion (i.e. lower costs in the presence of the factor) including age, ejection fraction and anemia. But anemia and ejection fraction were also associated with a higher death rate.ConclusionsClose control of factors that are independently associated with higher cost or poor outcomes may be important for disease management. Analysis of costs in a disease like heart failure that has a high death rate underscores the need for economic methods to consider how mortality should best be considered in costing studies.
Highlights
Identifying heart failure patients who are most likely to suffer poor outcomes is an essential part of delivering interventions to those most likely
Since we focus on patients in the community setting our study is relevant to the larger set of heart failure patients
When we restricted our cost analysis to those patients who survived the entire 12 month period we found cost changes in the expected direction for patients with anemia (33.27% higher, 95% CI 14.18% to 52.37%) and ejection fraction (for example, patients with normal ejection fraction had costs 15% lower compared with those who had the lowest level of ejection fraction)
Summary
Identifying heart failure patients most likely to suffer poor outcomes is an essential part of delivering interventions to those most likely to benefit. Heart failure prevalence is estimated at 1% to 2% in the US, with an annual cost (direct and indirect) of over $33 billion [1]. Identifying heart failure patients who are most likely to suffer poor outcomes is an essential part of delivering interventions to those most likely endpoints; a comprehensive understanding is dependent on capturing all of the ways that outcomes appear. These estimates may be useful for modeling the cost-effectiveness of heart failure interventions
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