{"title":"Statistical approaches to outcomes assessment.","authors":"R L Coleman","doi":"","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Statistical methods and software can be useful for evaluating clinical outcomes data.</p><p><strong>Method: </strong>The use of control charts and regression analysis can be particularly helpful in outcomes assessment. Control charts can reveal outlier events and patterns that require additional review leading to changes that improve outcomes. Regression analysis can show factors that affect process characteristics. This article uses examples derived from hospital outcomes assessment activities relating to length of stay, treatment planning, insurance coverage, patient characteristics, and clinical decision making.</p><p><strong>Results: </strong>Minitab statistical software is used to create control charts and perform regression analysis, and essential Minitab commands are explained.</p><p><strong>Conclusion: </strong>Through the use of the techniques described the clinical and manager can more effectively evaluate clinical outcomes data to improve healthcare quality.</p>","PeriodicalId":79476,"journal":{"name":"Best practices and benchmarking in healthcare : a practical journal for clinical and management application","volume":"1 5","pages":"242-9"},"PeriodicalIF":0.0000,"publicationDate":"1996-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Best practices and benchmarking in healthcare : a practical journal for clinical and management application","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Statistical methods and software can be useful for evaluating clinical outcomes data.
Method: The use of control charts and regression analysis can be particularly helpful in outcomes assessment. Control charts can reveal outlier events and patterns that require additional review leading to changes that improve outcomes. Regression analysis can show factors that affect process characteristics. This article uses examples derived from hospital outcomes assessment activities relating to length of stay, treatment planning, insurance coverage, patient characteristics, and clinical decision making.
Results: Minitab statistical software is used to create control charts and perform regression analysis, and essential Minitab commands are explained.
Conclusion: Through the use of the techniques described the clinical and manager can more effectively evaluate clinical outcomes data to improve healthcare quality.