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Preferences for Monitoring Comprehensive Heart Failure Care: A Latent Class Analysis
Axel C Mühlbacher1,2,3, Andrew Sadler4, Christin Juhnke4
1Health Economics and Health Care Management, Hochschule Neubrandenburg, Neubrandenburg, Germany. igm@hs-nb.de.
Patient preferences for chronic heart failure monitoring vary significantly. Understanding these diverse needs, particularly regarding mobility and risk reduction, is key to tailoring effective treatment strategies for better patient outcomes.
Area of Science:
- Cardiology and Health Services Research
- Patient-Reported Outcomes
Background:
- Chronic heart failure (CHF) management requires effective patient monitoring systems.
- Heterogeneity in patient preferences for monitoring attributes is not well understood.
Purpose of the Study:
- To measure preference heterogeneity for monitoring systems among patients with chronic heart failure.
- To identify distinct patient groups based on their preferences for monitoring care scenarios.
Main Methods:
- A best-worst scaling experiment (BWS) was conducted with 278 CHF patients.
- Latent class analysis (LCA) identified patient preference classes.
- A market simulator evaluated preferred treatment configurations within identified classes.
Main Results:
- Four distinct patient preference classes were identified using LCA.
- Key preference drivers included mobility, monitoring frequency, risk of hospitalization, and risk of death.
- Most classes prioritized improvements in mobility, mortality, and hospitalization rates, even with frequent monitoring.
Conclusions:
- Latent class analysis revealed significant preference variations among CHF patients.
- Tailoring treatment alternatives to individual patient groups can enhance care.
- Findings support improved clinical and allocative decision-making in CHF management.
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