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Published on: June 10, 2025
Predicting costs of care in heart failure patients
David H Smith1, Eric S Johnson, David K Blough
1The Center for Health Research, Kaiser Permanente Northwest, 3800 N, Interstate Avenue, Portland, OR 97227, USA. David.h.smith@kpchr.org
Insights
Identifying heart failure patients with higher costs or poor outcomes is key. Comorbidities like diabetes and depression significantly increase costs, while anemia and low ejection fraction predict higher mortality.
Area of Science:
- Cardiology
- Health Economics
- Clinical Research
Background:
- Identifying patients with heart failure at high risk for adverse outcomes is crucial for targeted interventions.
- Understanding the economic burden associated with heart failure events is essential for resource allocation.
Purpose of the Study:
- To comprehensively analyze heart failure events and their economic impact.
- To identify patient characteristics predicting increased healthcare costs or poor outcomes in heart failure patients.
Main Methods:
- Electronic medical data from 4,696 heart failure patients within a large HMO (1999-2004) were analyzed.
- Patient data included demographics, clinical findings, laboratory results, comorbidities, and incident heart failure status.
- One-year follow-up data were used, employing regression methods suitable for censored cost data and mortality analysis.
Main Results:
- Several comorbidities significantly increased costs: chronic lung disease (29%), diabetes (38%), depression (36%), atrial fibrillation (15%), coronary artery disease (14%), and hyperlipidemia (21%).
- Anemia and lower ejection fraction were paradoxically associated with lower costs but higher mortality rates.
- Incident heart failure occurred in 8% of the patient cohort.
Conclusions:
- Management of heart failure should focus on controlling factors independently linked to increased costs and adverse outcomes.
- Economic analyses in high-mortality diseases like heart failure necessitate careful consideration of mortality's impact on overall cost assessment.
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.
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