A M Grant, Y Richard, E Deland, N Després, F de Lorenzi, A Dagenais, M Buteau
{"title":"Data collection and information presentation for optimal decision making by clinical managers--the Autocontrol Project.","authors":"A M Grant, Y Richard, E Deland, N Després, F de Lorenzi, A Dagenais, M Buteau","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>The Autocontrol methodology has been developed in order to support the optimisation of decision-making and the use of resources in the context of a clinical unit. The theoretical basis relates to quality assurance and information systems and is influenced by management and cognitive research in the health domain. The methodology uses population rather than individual decision making and because of its dynamic feedback design promises to have rapid and profound effect on practice. Most importantly the health care professional is the principle user of the Autocontrol system. In this methodology we distinguish three types of evidence necessary for practice change: practice based or internal evidence, best evidence derived from the literature or external evidence concerning the practice in question, and process based evidence on how to optimise the process of practice change. The software used by the system is of the executive decision support type which facilitates interrogation of large databases. The Autocontrol system is designed to interrogate the data of the patient medical record however the latter often lacks data on concomitant resource use and this must be supplemented. This paper reviews the Autocontrol methodology and gives examples from current studies.</p>","PeriodicalId":79455,"journal":{"name":"Proceedings : a conference of the American Medical Informatics Association. AMIA Fall Symposium","volume":" ","pages":"789-93"},"PeriodicalIF":0.0000,"publicationDate":"1997-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2233326/pdf/procamiaafs00001-0823.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings : a conference of the American Medical Informatics Association. AMIA Fall Symposium","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
The Autocontrol methodology has been developed in order to support the optimisation of decision-making and the use of resources in the context of a clinical unit. The theoretical basis relates to quality assurance and information systems and is influenced by management and cognitive research in the health domain. The methodology uses population rather than individual decision making and because of its dynamic feedback design promises to have rapid and profound effect on practice. Most importantly the health care professional is the principle user of the Autocontrol system. In this methodology we distinguish three types of evidence necessary for practice change: practice based or internal evidence, best evidence derived from the literature or external evidence concerning the practice in question, and process based evidence on how to optimise the process of practice change. The software used by the system is of the executive decision support type which facilitates interrogation of large databases. The Autocontrol system is designed to interrogate the data of the patient medical record however the latter often lacks data on concomitant resource use and this must be supplemented. This paper reviews the Autocontrol methodology and gives examples from current studies.