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基于EQ-5D的病例 vignettes,从被保险人的角度引出对医疗服务利用的明确偏好。 (注:这里“vignettes”可结合具体语境灵活处理,比如“案例描述”等,因为没有更多背景很难精准翻译,这里保留原文形式供参考。)

Case vignettes based on EQ-5D to elicit stated preferences for health services utilization from the insurees' perspective.

作者信息

Eckert Julia, Lichters Marcel, Piedmont Silke, Vogt Bodo, Robra Bernt-Peter

机构信息

Institute of Social Medicine and Health Economics, University of Magdeburg, Magdeburg, Germany.

Department of Business Studies, Harz University of Applied Sciences, Wernigerode, Germany.

出版信息

BMC Health Serv Res. 2015 Oct 24;15:481. doi: 10.1186/s12913-015-1143-2.

DOI:10.1186/s12913-015-1143-2
PMID:26499771
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4619295/
Abstract

BACKGROUND

There is little evidence as to why or why not insurees decide to seek medical services. Steps prior to the entry of the insuree into the professional health care system have not been sufficiently examined and can only be partially described by secondary data of the statutory health insurance (SHI). We report the first investigation using case vignettes based on the generic health-related quality of life questionnaire EQ-5D as part of a choice study to assess insurees' stated preferences in health services utilization.

METHODS

We invited 1500 randomly selected citizens (age 30 to 70 years) from the East German state of Saxony-Anhalt by postal mail to participate in the choice study. Attributes of the case vignettes involved in choice tasks were the five dimensions of the EQ-5D. We used multilevel mixed effects logit regression analysis with the dependent variables: preference to seek medical services (model 1) and preferred time until consultation (model 2) for the assessed case vignette. The EQ-5D attributes of the case vignettes and participant characteristics served as the independent variables. We also included the respondent's certainty of choosing from the choice set, and the order of questions of the questionnaire as control variables.

RESULTS

Of the 1500 questionnaires 683 were evaluable (net response rate 48.0%). On the level of the case vignettes, problems in all five dimensions of the EQ-5D were statistically significant factors of the estimated likelihood to seek medical services (model 1). On the respondent level, there was a significant relationship between the preference for medical consultation for the assessed case vignette and the respondent's gender, age, educational level, the existence of a regular doctor, and the certainty of choosing from the choice set. Problems in four of the five dimensions of the EQ-5D (except anxiety/depression) of the case vignettes were significantly associated with the preferred time until consultation (model 2). On the respondent level, gender, educational level, the certainty of choosing from the choice set, and the order of questions of the questionnaire were significant determinants of the time until consultation.

CONCLUSIONS

Our study offers a promising new approach for the national and cross-national study of preferences in health services utilization from the insurees' perspective.

摘要

背景

关于被保险人决定寻求医疗服务的原因,几乎没有证据。在被保险人进入专业医疗保健系统之前的步骤尚未得到充分研究,并且只能通过法定健康保险(SHI)的二手数据进行部分描述。作为一项选择研究的一部分,我们报告了首次使用基于通用健康相关生活质量问卷EQ-5D的病例 vignettes 进行的调查,以评估被保险人在医疗服务利用方面的既定偏好。

方法

我们通过邮政邮件邀请了来自东德萨克森 - 安哈尔特州的1500名随机选择的公民(年龄在30至70岁之间)参与选择研究。选择任务中涉及的病例 vignettes 的属性是EQ-5D的五个维度。我们使用多级混合效应逻辑回归分析,因变量为:对评估病例 vignette 寻求医疗服务的偏好(模型1)和首选咨询时间(模型2)。病例 vignettes 的EQ-5D属性和参与者特征作为自变量。我们还将受访者从选择集中选择的确定性以及问卷问题的顺序作为控制变量。

结果

在1500份问卷中,683份可评估(净回复率48.0%)。在病例 vignettes 层面,EQ-5D所有五个维度的问题都是估计寻求医疗服务可能性的统计学显著因素(模型1)。在受访者层面,对评估病例 vignette 的医疗咨询偏好与受访者的性别、年龄、教育水平、是否有固定医生以及从选择集中选择的确定性之间存在显著关系。病例 vignettes 的EQ-5D五个维度中的四个维度(焦虑/抑郁除外)的问题与首选咨询时间显著相关(模型2)。在受访者层面,性别、教育水平、从选择集中选择的确定性以及问卷问题的顺序是咨询时间的显著决定因素。

结论

我们的研究为从被保险人角度对医疗服务利用偏好进行国内和跨国研究提供了一种有前景的新方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4aa/4619295/21046e46793a/12913_2015_1143_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4aa/4619295/21046e46793a/12913_2015_1143_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4aa/4619295/21046e46793a/12913_2015_1143_Fig1_HTML.jpg

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