Healthcare is important to everyone, yet large variations in its quality have been well documented both between and within many countries. With demand and expenditure rising, it’s more crucial than ever to know how well the healthcare system and all its components – from staff member to regional network – are performing. This requires data, which inevitably differ in form and quality. It also requires statistical methods, the output of which needs to be presented so that it can be understood by whoever needs it to make decisions.
Statistical Methods for Healthcare Performance Monitoring
covers measuring quality, types of data, risk adjustment, defining good and bad performance, statistical monitoring, presenting the results to different audiences and evaluating the monitoring system itself. Using examples from around the world, it brings all the issues and perspectives together in a largely non-technical way for clinicians, managers and methodologists.
Statistical Methods for Healthcare Performance Monitoring is aimed at statisticians and researchers who need to know how to measure and compare performance, health service regulators, health service managers with responsibilities for monitoring performance, and quality improvement scientists, including those involved in clinical audits.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Dr. Alex Bottle is a Senior Lecturer at Imperial College London, UK
Dr. Paul Aylin is a Professor at Imperial College London, UK
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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