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Open Access Research article

Predicting costs of care in heart failure patients

David H Smith1*, Eric S Johnson1, David K Blough3, Micah L Thorp12, Xiuhai Yang1, Amanda F Petrik1 and Kathy A Crispell4

Author affiliations

1 The Center for Health Research, Kaiser Permanente Northwest, 3800 N. Interstate Avenue, Portland, OR, 97227, USA

2 Department of Nephrology, Kaiser Permanente Northwest, 6902 SE Lake Rd Ste 100, Portland, OR, 97267, USA

3 Department of Pharmacy, University of Washington, Magnuson Health Sciences Building, H Wing, Dean's Office, H-364, Box 357631, Seattle, WA, 98195, USA

4 Department of Cardiology, Kaiser Permanente Northwest, 10100 South East Sunnyside Road, Clackamas, OR, 97015, USA

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Citation and License

BMC Health Services Research 2012, 12:434  doi:10.1186/1472-6963-12-434

Published: 30 November 2012

Abstract

Background

Identifying 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.

Methods

We 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.

Results

Of 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.

Conclusions

Close 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.