{"title":"使用模糊逻辑评估医疗保健绩效","authors":"M. S. Khan, M. A. Mansour, S. Khadar, Z. Mallick","doi":"10.7166/31-1-2150","DOIUrl":null,"url":null,"abstract":"The basic determining elements of healthcare services are the patient’s satisfaction with the service provided by hospitals, which includes behavioural and sentimental aspects and the quality and efficiency of the hospitals themselves. Patients are sometimes very confused, and so express their views very vaguely. These imprecise responses of patients add to the complexity of evaluating quality. The involvement of multiple criteria, uncertainty, and qualitative factors significantly complicates the evaluation of the quality of a healthcare service. Fuzzy logic is a method by which indistinct or hazy responses can be taken up for quality analysis, such as the prioritisation of hospitals, departments, dimensions, etc. A pilot study was carried out in this study comprising 18 private hospitals with more than 100 beds that were selected in the twin city of Bhubaneswar and Cuttack in the state of Odisha, India. Nine quality dimensions were also selected from those used in the literature. A questionnaire survey was conducted in different departments of the hospitals using the nine dimensions. Patients’ responses on a five-point Likert scale were first analysed statistically. Then ranking the dimensions and the hospitals was carried out using fuzzy analysis. The results could be used by healthcare service providers continually to improve their organisation.","PeriodicalId":49493,"journal":{"name":"South African Journal of Industrial Engineering","volume":"31 1","pages":"133-143"},"PeriodicalIF":0.5000,"publicationDate":"2020-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"EVALUATING HEALTHCARE PERFORMANCE USING FUZZY LOGIC\",\"authors\":\"M. S. Khan, M. A. Mansour, S. Khadar, Z. Mallick\",\"doi\":\"10.7166/31-1-2150\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The basic determining elements of healthcare services are the patient’s satisfaction with the service provided by hospitals, which includes behavioural and sentimental aspects and the quality and efficiency of the hospitals themselves. Patients are sometimes very confused, and so express their views very vaguely. These imprecise responses of patients add to the complexity of evaluating quality. The involvement of multiple criteria, uncertainty, and qualitative factors significantly complicates the evaluation of the quality of a healthcare service. Fuzzy logic is a method by which indistinct or hazy responses can be taken up for quality analysis, such as the prioritisation of hospitals, departments, dimensions, etc. A pilot study was carried out in this study comprising 18 private hospitals with more than 100 beds that were selected in the twin city of Bhubaneswar and Cuttack in the state of Odisha, India. Nine quality dimensions were also selected from those used in the literature. A questionnaire survey was conducted in different departments of the hospitals using the nine dimensions. Patients’ responses on a five-point Likert scale were first analysed statistically. Then ranking the dimensions and the hospitals was carried out using fuzzy analysis. The results could be used by healthcare service providers continually to improve their organisation.\",\"PeriodicalId\":49493,\"journal\":{\"name\":\"South African Journal of Industrial Engineering\",\"volume\":\"31 1\",\"pages\":\"133-143\"},\"PeriodicalIF\":0.5000,\"publicationDate\":\"2020-05-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"South African Journal of Industrial Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.7166/31-1-2150\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, INDUSTRIAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"South African Journal of Industrial Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.7166/31-1-2150","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
EVALUATING HEALTHCARE PERFORMANCE USING FUZZY LOGIC
The basic determining elements of healthcare services are the patient’s satisfaction with the service provided by hospitals, which includes behavioural and sentimental aspects and the quality and efficiency of the hospitals themselves. Patients are sometimes very confused, and so express their views very vaguely. These imprecise responses of patients add to the complexity of evaluating quality. The involvement of multiple criteria, uncertainty, and qualitative factors significantly complicates the evaluation of the quality of a healthcare service. Fuzzy logic is a method by which indistinct or hazy responses can be taken up for quality analysis, such as the prioritisation of hospitals, departments, dimensions, etc. A pilot study was carried out in this study comprising 18 private hospitals with more than 100 beds that were selected in the twin city of Bhubaneswar and Cuttack in the state of Odisha, India. Nine quality dimensions were also selected from those used in the literature. A questionnaire survey was conducted in different departments of the hospitals using the nine dimensions. Patients’ responses on a five-point Likert scale were first analysed statistically. Then ranking the dimensions and the hospitals was carried out using fuzzy analysis. The results could be used by healthcare service providers continually to improve their organisation.
期刊介绍:
The South African Journal of Industrial Engineering (SAJIE) publishes articles with the emphasis on research, development and application within the fields of Industrial Engineering and Engineering and Technology Management. In this way, it aims to contribute to the further development of these fields of study and to serve as a vehicle for the effective interchange of knowledge, ideas and experience between the research and training oriented institutions and the application oriented industry. Articles on practical applications, original research and meaningful new developments as well as state of the art surveys are encouraged.