Construction of evaluation indicator system for health management effects in high-risk stroke population
10.3760/cma.j.cn115624-20230313-00159
- VernacularTitle:卒中高危人群健康管理效果评价指标体系的构建
- Author:
Miao WEI
1
;
Lina GUO
;
Yuanli GUO
;
Lü PEIHUA
;
Yuru LUO
;
Yanjin LIU
Author Information
1. 郑州大学第一附属医院神经内科，郑州 450052
- Keywords:
Stroke;
High-risk population;
Health management;
Delphi technique;
Nursing administration research
- From:
Chinese Journal of Health Management
2023;17(10):721-726
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To construct an evaluation indicator system for the health management effects in high-risk stroke population.Methods:From March to May 2020, based on health ecology theory, social cognitive theory and knowledge, attitude/belief, practice theory, the first draft of the evaluation index system for health management effects of high-risk stroke groups was drawn up by literature review and group discussion. Through two rounds of Delphi expert consultation, the evaluation index system of health management effects of high-risk stroke groups was established, and the weight of each index was determined by analytic hierarchy process (AHP). A total of 22 experts were invited to participate in expert consultation. Twenty-two questionnaires were sent out in the first round, and 20 questionnaires were recovered, of which 20 were valid (90.9%). In the second round of correspondence, 20 questionnaires were sent out and 19 questionnaires were recovered, of which 19 were valid (95.0%).Results:The authority coefficients of the two rounds of expert consultation (Cr) was 0.933 and 0.937, respectively. The Kendall coordination coefficients W of importance in the second round was significantly higher than that in the first round (0.299 vs 0.172) ( P<0.001). The mean of importance score (Mj) of each index was 4.10-5.00, coefficient of variation (CV) was 0-0.235, and full mark ratio (Kj) was 0.26-1.00. Finally, an evaluation index system of the health management effects for high-risk stroke population was constructed, which included 3 first-level indicators (individual characteristics, behavior style, environmental support), 12 second-level indicators and 58 third-level indicators. Conclusions:The evaluation index system of the health management effects for high-risk stroke population is established in this study, which provides scientific quantitative indicators and evaluation tools. The enthusiasm, authority and coordination of consultation experts are strong, which indicates that the indicator system is feasible.
