BackgroundUK general practice faces a workforce crisis, with general practitioner (GP) shortages, organisational change, substantial pressures across the whole health-care system and an ageing population with increasingly complex health needs. GPs require lengthy training, so retaining the existing workforce is urgent and important.Objectives(1) To identify the key policies and strategies that might (i) facilitate the retention of experienced GPs in direct patient care or (ii) support the return of GPs following a career break. (2) To consider the feasibility of potentially implementing those policies and strategies.DesignThis was a comprehensive, mixed-methods study.SettingThis study took place in primary care in England.ParticipantsGeneral practitioners registered in south-west England were surveyed. Interviews were with purposively selected GPs and primary care stakeholders. A RAND/UCLA Appropriateness Method (RAM) panel comprised GP partners and GPs working in national stakeholder organisations. Stakeholder consultations included representatives from regional and national groups.Main outcome measuresSystematic review – factors affecting GPs’ decisions to quit and to take career breaks. Survey – proportion of GPs likely to quit, to take career breaks or to reduce hours spent in patient care within 5 years of being surveyed. Interviews – themes relating to GPs’ decision-making. RAM – a set of policies and strategies to support retention, assessed as ‘appropriate’ and ‘feasible’. Predictive risk modelling – predictive model to identify practices in south-west England at risk of workforce undersupply within 5 years. Stakeholder consultation – comments and key actions regarding implementing emergent policies and strategies from the research.ResultsPast research identified four job-related ‘push’ factors associated with leaving general practice: (1) workload, (2) job dissatisfaction, (3) work-related stress and (4) work–life balance. The survey, returned by 2248 out of 3370 GPs (67%) in the south-west of England, identified a high likelihood of quitting (37%), taking a career break (36%) or reducing hours (57%) within 5 years. Interviews highlighted three drivers of leaving general practice: (1) professional identity and value of the GP role, (2) fear and risk associated with service delivery and (3) career choices. The RAM panel deemed 24 out of 54 retention policies and strategies to be ‘appropriate’, with most also considered ‘feasible’, including identification of and targeted support for practices ‘at risk’ of workforce undersupply and the provision of formal career options for GPs wishing to undertake portfolio roles. Practices at highest risk of workforce undersupply within 5 years are those that have larger patient list sizes, employ more nurses, serve more deprived and younger populations, or have poor patient experience ratings. Actions for national organisations with an interest in workforce planning were identified. These included collection of data on the current scope of GPs’ portfolio roles, and the need for formal career pathways for key primary care professionals, such as practice managers.LimitationsThe survey, qualitative research and modelling were conducted in one UK region. The research took place within a rapidly changing policy environment, providing a challenge in informing emergent policy and practice.ConclusionsThis research identifies the basis for current concerns regarding UK GP workforce capacity, drawing on experiences in south-west England. Policies and strategies identified by expert stakeholders after considering these findings are likely to be of relevance in addressing GP retention in the UK. Collaborative, multidisciplinary research partnerships should investigate the effects of rolling out some of the policies and strategies described in this report.Study registrationThis study is registered as PROSPERO CRD42016033876 and UKCRN ID number 20700.FundingThe National Institute for Health Research Health Services and Delivery Research programme.
Background: Surveys collecting patient experience data often contain a large number of items covering a wide range of experiences. Knowing which areas to prioritize for improvements efforts can be difficult. Objective: To examine which aspects of care experience are the key drivers of overall satisfaction with cancer care. Methods: Secondary analysis of the National Cancer Patient Experience Survey. Logistic regression was used to examine the relationship between overall satisfaction and 10 core questions covering aspects of experience applicable to all patients. Supplementary analyses examined a further 16 questions applying only to patients in certain groups or on specific treatment pathways. Results: Of 68 340 included patients, 58 697 (86%) rated overall satisfaction highly (8 or more out of 10). The strongest predictors of overall satisfaction across all models were responses to 2 questions on experience of care administration and care coordination (odds ratio [OR] = 2.11, 95% confidence interval [95% CI = 2.05-2.17, P < .0001; OR = 2.03, 95% CI = 1.97-2.09, P < .0001, respectively, per 1 standard deviation change). Conclusion: Focusing improvement efforts on care administration and coordination has potential to improve overall satisfaction with oncological care across diverse patient groups/care pathways.
Despite aiming for the same target pump flow, periodic limitations of venous return to the pump resulted in a significant reduction in average flow delivered to the patient by Mini-CPB. Less haemodilution compensated for this reduction, so that the average oxygen delivery was the same. The association between oxygen delivery and postoperative change in plasma creatinine was evident in both groups. Further work to understand whether there is a particular cohort of patients who benefit (or are put at risk) by one method of CPB vs the other is warranted.
ObjectiveThis study aimed to develop a risk prediction model identifying general practices at risk of workforce supply–demand imbalance.DesignThis is a secondary analysis of routine data on general practice workforce, patient experience and registered populations (2012 to 2016), combined with a census of general practitioners’ (GPs’) career intentions (2016).Setting/ParticipantsA hybrid approach was used to develop a model to predict workforce supply–demand imbalance based on practice factors using historical data (2012–2016) on all general practices in England (with over 1000 registered patients n=6398). The model was applied to current data (2016) to explore future risk for practices in South West England (n=368).Primary outcome measureThe primary outcome was a practice being in a state of workforce supply–demand imbalance operationally defined as being in the lowest third nationally of access scores according to the General Practice Patient Survey and the highest third nationally according to list size per full-time equivalent GP (weighted to the demographic distribution of registered patients and adjusted for deprivation).ResultsBased on historical data, the predictive model had fair to good discriminatory ability to predict which practices faced supply–demand imbalance (area under receiver operating characteristic curve=0.755). Predictions using current data suggested that, on average, practices at highest risk of future supply–demand imbalance are currently characterised by having larger patient lists, employing more nurses, serving more deprived and younger populations, and having considerably worse patient experience ratings when compared with other practices. Incorporating findings from a survey of GP’s career intentions made little difference to predictions of future supply–demand risk status when compared with expected future workforce projections based only on routinely available data on GPs’ gender and age.ConclusionsIt is possible to make reasonable predictions of an individual general practice’s future risk of undersupply of GP workforce with respect to its patient population. However, the predictions are inherently limited by the data available.
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