Objectives: The relationship between patient feedback in the General Practice Patient Survey (GPPS) and Care Quality Commission (CQC) inspections of practices was investigated to understand whether there is an association between patient views and regulator ratings of quality. The specific aims were to understand whether patients' self-reported experiences of primary care can predict CQC inspection ratings of GP practices by: (i) Measuring the association between GPPS results and CQC inspection ratings of GP practices; (ii) Building a predictive model of GP practice quality ratings that use GPPS results; and (iii) Evaluating the predictive model for risk stratification.
Design: Retrospective analysis of routinely collected data using decision tree modelling.
Setting: Primary care: GP practices in England.
Primary And Secondary Outcome Measures: GPPS scores and GP practice CQC inspection ratings during 2018.
Results: Most GP practices (72%, 974/1350) were rated as 'Good' overall by CQC. Simply assuming that all practices will be rated as 'Good' results in a correct prediction 72% of the time, and it was not possible to improve on this overall level of predictive accuracy using decision tree modelling (correct in 73% of cases). However, a set of GPPS questions were found to have value in identifying practices at elevated risk of a poor inspection rating.
Conclusions: Although there were some associations between GPPS data and CQC inspection ratings, there were limitations to the use of GPPS data for predictive analysis. This is a likely result of the majority of CQC inspections of GPs resulting in a 'Good' or 'Outstanding' rating. However, some GPPS questions were found to have value in identifying practices at higher risk of an 'Inadequate' or 'Requires Improvement' rating, and this may be valuable for surveillance purposes. For example, the CQC could use key questions from the survey to target inspection planning.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7692819 | PMC |
http://dx.doi.org/10.1136/bmjopen-2020-041709 | DOI Listing |
Br Dent J
October 2021
Primary Medical Services and Integrated Care Directorate, London, SW1W 9SZ, UK.
Introduction All dental practices in England must be registered with the Care Quality Commission (CQC). The CQC inspects approximately 10% of practices each year to ensure premises are safe. Compliance with infection prevention and control is assessed during inspections.
View Article and Find Full Text PDFEmeritus Professor , from the University of Southampton, discusses recent changes to the way in which the Care Quality Commission (CQC) conducts its health and social care inspections.
View Article and Find Full Text PDFLeadersh Health Serv (Bradf Engl)
May 2021
Suffolk Business School, University of Suffolk, Ipswich, UK.
Purpose: As part of their inspection of care homes in England, the statutory inspector (the Care Quality Commission [CQC]) makes a judgement on the quality of the home's leadership. Their view is critical as it is intended to inform consumer choice and because the statutory nature of inspection means these views hold considerable authority. The purpose of this paper is to look at the content of a selection of reports and seek to determine what the CQC understands by the concept of "good leadership".
View Article and Find Full Text PDFObjectives: The relationship between patient feedback in the General Practice Patient Survey (GPPS) and Care Quality Commission (CQC) inspections of practices was investigated to understand whether there is an association between patient views and regulator ratings of quality. The specific aims were to understand whether patients' self-reported experiences of primary care can predict CQC inspection ratings of GP practices by: (i) Measuring the association between GPPS results and CQC inspection ratings of GP practices; (ii) Building a predictive model of GP practice quality ratings that use GPPS results; and (iii) Evaluating the predictive model for risk stratification.
Design: Retrospective analysis of routinely collected data using decision tree modelling.
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