基于体检大数据的生活方式条目评分系统的构建

关注Wind基金数据库的评级体系，了解基金业绩排名 #生活技巧# #理财投资建议# #基金评级#

摘要： 背景 健康体检领域的大数据应用能够确定人群的健康状况、提早发现健康隐患，对体检大数据中的生活方式信息的有效数据挖掘是早期发现慢性病风险人群、开展检后健康评估和提供个性化健康管理服务的有效手段。目前《健康体检自测问卷》虽已在国内多家体检机构用以收集体检人群的生活方式信息，但其中的生活方式条目难以采用常规的赋值方式实现对问卷所收集的健康信息进行科学的量化分析，阻碍了对人群生活方式信息的有效利用。目的 构建基于体检大数据的《健康体检自测问卷》中生活方式条目的评分系统。方法 基于多元方差分析结果确定赋值切点，再参照生活方式相关指南进行初步赋值，最后通过焦点小组会议和两轮德尔菲专家函询法，形成最终的生活方式条目评分系统。结果 以多元方差分析结果中F值排名前三的赋值切点、临床指南建议和焦点小组会议讨论实现对生活方式条目评分系统的初步构建。在两轮德尔菲专家函询中，专家积极系数均为100%，专家的判断系数为0.87，熟悉程度为0.91，权威系数为0.89。最终形成的基于体检大数据的生活方式条目评分系统包含对34个条目和13个子条目选项的赋值结果。结论 构建的生活方式条目评分系统具有较好的科学性和可信度，可为人群的生活方式信息的有效利用和数据挖掘提供理论参考。

关键词: 体检大数据, 德尔菲法, 健康体检自测问卷, 生活方式, 评分系统构建

Abstract: Background The application of big data in the field of health examination can determine the health status of the population and discover health risks in advance. Effective data mining of lifestyle information in the big data of physical examination is an effective means to early find the population at risk of chronic diseases, carry out post-examination health assessment and provide personalized health management services. At present, although the Self-Test Questionnaire for Physical examination has been used in many domestic physical examination institutions to collect the lifestyle information of the physical examination population, the lifestyle items in the questionnaire are difficult to realize the scientific quantitative analysis of the health information collected by the questionnaire with the conventional assignment method, which hinders the effective use of the lifestyle information of the population. Objective To construct a scoring system for the lifestyle items in the Physical Examination Self-test Questionnaire based on big data of physical examination. Methods Based on the results of multivariate analysis of variance, the assignment tangent points were determined, and then the preliminary assignment was conducted according to the lifestyle-related guidelines. Finally, the final lifestyle item scoring system was formed through focus group meetings and two rounds of Delphi expert letter consultation. Results Preliminary construction of a lifestyle item scoring system was achieved by using the top three F-value assignment pointcuts in multivariate analysis of variance, clinical guideline recommendations and focus group discussions. In the two rounds of Delphi expert letter consultation, the positive coefficient of experts was 100%, the coefficient of expert judgment was 0.87, the degree of familiarity was 0.91, and the coefficient of authority was 0.89. The final lifestyle item scoring system based on the big data of physical examination includes the assignment results of 34 items and 13 sub-items. Conclusions The constructed scoring system of lifestyle items is scientific and reliable, and can provide theoretical reference for effective use of people's lifestyle information and data mining.

Key words: Physical examination big data, Delphi method, Self-test questionnaire for physical examination, Life style, Scoring system construction

网址：基于体检大数据的生活方式条目评分系统的构建 https://www.yuejiaxmz.com/news/view/714870

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