Health Economics and Health Care Management, Hochschule Neubrandenburg, Neubrandenburg, Germany.
Gesellschaft für empirische Beratung GmbH (GEB), Freiburg, Germany.
Patient. 2024 Jan;17(1):83-95. doi: 10.1007/s40271-023-00656-5. Epub 2023 Nov 29.
To measure preference heterogeneity for monitoring systems among patients with a chronic heart failure.
A best-worst scaling experiment (BWS case 3) was conducted among patients with chronic heart failure to assess preferences for hypothetical monitoring care scenarios. These were characterized by the attributes mobility, risk of death, risk of hospitalization, type and frequency of monitoring, risk of medical device, and system-relevant complications. A latent class analysis (LCA) was used to analyze and interpret the data. In addition, a market simulator was used to examine which treatment configurations participants in the latent classes preferred.
Data from 278 respondents were analyzed. The LCA identified four heterogeneous classes. For class 1, the most decisive factor was mobility with a longer distance covered being most important. Class 2 respondents directed their attention toward attribute "monitoring," with a preferred monitoring frequency of nine times per year. The attribute risk of hospitalization was most important for respondents of class 3, closely followed by risk of death. For class 4, however, risk of death was most important. A market simulation showed that, even with high frequency of monitoring, most classes preferred therapy with high improvement in mobility, mortality, and hospitalization.
Using LCA, variations in preferences among different groups of patients with chronic heart failure were examined. This allows treatment alternatives to be adapted to individual needs of patients and patient groups. The findings of the study enhance clinical and allocative decision-making while elevating the quality of clinical data interpretation.
测量慢性心力衰竭患者对监测系统的偏好异质性。
对慢性心力衰竭患者进行最佳最差标度实验（BWS 案例 3），以评估对假设监测护理方案的偏好。这些方案的特征是属性包括活动能力、死亡风险、住院风险、监测类型和频率、医疗器械风险以及系统相关并发症。使用潜在类别分析（LCA）对数据进行分析和解释。此外，使用市场模拟器来检查潜在类别中的参与者更喜欢哪种治疗配置。
对 278 名受访者的数据进行了分析。LCA 确定了四个具有异质性的类别。对于类别 1，最关键的因素是活动能力，覆盖的距离越长越重要。类别 2 的受访者将注意力集中在“监测”属性上，首选的监测频率为每年九次。对于类别 3 的受访者，住院风险是最重要的属性，其次是死亡风险。然而，对于类别 4，死亡风险是最重要的。市场模拟表明，即使监测频率较高，大多数类别也更倾向于改善活动能力、死亡率和住院率的治疗方案。
使用 LCA 检查了慢性心力衰竭不同患者群体之间的偏好差异。这允许根据患者和患者群体的个体需求调整治疗方案。该研究的发现增强了临床和分配决策，并提高了临床数据解释的质量。
