社区居家养老护理问题标准化语言体系的构建

Standardized Nursing Language System Development for Community Home-based Elderly Care

目的构建社区居家养老护理问题标准化语言体系,为社区居家养老护理服务标准化和数据库的建立提供依据。方法 2017年5—8月,采用便利抽样法选取北京市4所社区卫生服务站、4所医院和2所高校的专家45名,采用德尔菲法,通过两轮专家咨询,最终确定社区居家养老护理问题标准化语言体系。结果第1轮专家咨询发放问卷45份,回收有效问卷39份,有效回收率为86.7%;第2轮专家咨询发放问卷39份,回收有效问卷32份,有效回收率为82.0%。第1轮专家咨询权威系数、判断系数、熟悉程度系数分别为0.879、0.913和0.846;第2轮专家咨询权威系数、判断系数、熟悉程度系数分别为0.880、0.892和0.869。两轮专家咨询的协调系数均具有统计学意义(P<0.05)。经专家咨询,最终确定一级指标4个,二级指标16个,三级指标73个,补充条目4个。结论社区居家养老护理问题标准化语言体系涵盖了老年人在社区居家养老中面临的常见、重要的护理问题,结果科学可靠,可作为社区居家养老老年人评估内容的指引,也为社区居家养老护理服务的标准化和养老服务大数据开发奠定基础。

Objective To develop a standardized nursing language system for community home-based elderly care（SNLSCHEC）,offering a basis for the standardization and data database construction of community home-based elderly care.Methods From May to August 2017,using convenience sampling,we formulated the final SNLSCHEC through a two-round Delphi consultation among 45 experts from 4 community health stations,4 hospitals and 2 universities in Beijing.Results 45 questionnaires were sent out and 39 were recovered in the first-round expert consultation,the valid response rate was 86.7%;39 questionnaires were sent out and 32 were recovered in the second-round expert consultation,the valid response rate was 82.0%.The authority coefficient,determination coefficient and familiar coefficient for the first round of expert consultation was 0.879,0.913 and 0.846,respectively,and 0.880,0.892 and 0.869 respectively,for the second round of expert consultation.The Kendall＇s W for both the first and second round of consultation demonstrated statistical significance（P〈0.05）.After the modification based on the consensus of the expert panel,the final SNLSCHEC includes 4 first-level indicators,16 second-level indicators and 73 third-level indicators and 4 supplemental indicators.Conclusion The SNLSCHEC covers the terminologies used in common and important elderly care in community home-based settings.Moreover,it is scientific and reliable.Therefore,it can be used as a reference for the assessment of community home-based elderly care,and as a basis for its standardization and big data development.