护理研究Issue(3)：280-282,283,4.DOI:10.3969/j.issn.10096493.2015.03.008
病人分类系统在优质护理服务病区护理人力资源配置中的应用
Application of patient classification system in nursing human resources allocation in high quality nursing service ward
摘要
Abstract
Objective:To apply patient classification system to explore nursing human resources allocation in high quality nursing service ward in specialized hospital,so as to provide scientific basis for nursing human resource allocation in high quality nursing service ward in specialized hospital.Methods:The amount of patients’care needs and the daily nursing hours of nursing personnel were selected as the research obj ects in 5 wards including department of liver disease internal medicine,department of hepatobiliary surgery,department of obstetrics liver diseases,department of infection diseases,department of oncology in September of 2013 year.The improved Ross Maddie Marcus scale(RMT PCS)survey was used,supplemented by the work involved method,to calcu-late 24 h average workload index and average disease severity of patients in each ward,according to the nursing manpower allocation ratio in modified RMT PCS scale to calculate the required number of nursing personnel in each ward.Results:Because of different diseases in each ward,patients’category accounted for the different pro-portion.The patients’severity,the average daily workload index and required nursing time per day were differ-ent.Conclusion:Using modified RMT PCS scale to classify patients and to establish a patient classification sys-tem of specialized hospital,which can provide scientific basis for nursing personnel allocation in high quality care ward.It is more conductive to the nursing management,are conductive to provide high quality of nursing service for patients.关键词
优质护理服务/改良 RMT PCS量表/病人分类/人力资源/合理配置Key words
high quality nursing service/modified RMT PCS scale/patient classification/human resources/ra-tional allocation分类
医药卫生引用本文复制引用
鲁桂兰,夏春香,沙莉,徐艳,王慧群,张立,俞曦,曹慧,陈艳..病人分类系统在优质护理服务病区护理人力资源配置中的应用[J].护理研究,2015,(3):280-282,283,4.基金项目
南京市医学科技发展项目,编号:YKK11080。 （）
