A hole in the bucket? Exploring England’s retention rates of recently qualified GPs

A hole in the bucket? 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Exploring England’s retention rates of recently qualified GPs William L Palmer, Lucina Rolewicz, Victoria Tzortziou-Brown, Giuliano Russo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4565547/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Mar, 2025 Read the published version in Human Resources for Health → Version 1 posted 10 You are reading this latest preprint version Abstract Background As the senior medics within primary care services, general practitioners (GPs) have a pivotal role within the National Health Service (NHS). Despite several commitments made by government to increase the number of GPs in England, the level has consistently fallen. Much attention has been paid to recruitment of trainee GPs and overall retention, whereas this study sought to examine the specific transition from ending training to joining the NHS. Methods The study used aggregated, published administrative data to examine rates at which 14,302 doctors leaving their third year of specialty training (GP ST3s) became fully qualified NHS GPs between 2018 and 2023. We separately analysed average levels of part-time working of those joining the NHS from 21,293 fully qualified joiners in England between 2017 and 2023. We calculated joiner and participation rates and used generalised linear mixed-effects models to explore possible demographic, period and cohort effects. Results Of those doctors leaving their third year of training since 2018, around a third (34.3%) had taken up a fully qualified GP role in NHS general practice six months after finishing training, rising to 47.5% within one year, and 62.2% within two years. Average estimated participation rates of joiners seemed to remain consistent at about 65-69% of a full-time contract between 2017 and 2023. Joiner rates were lower for doctors with a primary medical qualification from outside the UK and, over a two-year timeframe, both UK and non-UK trained male GP ST3s. Our statistical modelling suggests that there is a significant ‘period effect’ in connection to the recent Covid-19 pandemic, with apparent differences in the likelihood of GP ST3s joining the NHS in a fully-qualified role at certain points in time, and an effect among some cohorts, with doctors who left specialty training in specific periods having significantly different joiner rates. Conclusion The GP pipeline is expanding, but we find no evidence that retention of newly trained GPs is improving. We discuss possible factors for such attrition, from barriers to hiring new doctors, to their diminishing interest in joining the NHS. More work is needed to further explore the changing career behaviours of subsequent cohorts and demographics of doctors completing GP training. Physicians general practitioners family doctors registrars specialty training medical students recruitment NHS trainees workforce retention Figures Figure 1 Figure 2 INTRODUCTION AND BACKGROUND General practice is essential for population health, the efficiency of health systems, and ultimately the attainment of universal health coverage worldwide [1]. And as the senior medics within these services, general practitioners (known as family physicians in some countries) have a pivotal role, with responsibility for providing continuous whole person medical care, and managing risk, uncertainty and medical complexity [2,3]. However, recruiting and retaining general practitioners (GPs) has historically been difficult[4]. The international literature suggests that worse pay, lower prestige, compulsory rural placements, elevated risk of burn-out, and a deteriorating working environment, might all be factors[5,6]. Recent policies have mainly focused on increasing training numbers despite the recognition that workforce retention needs to be prioritised too [7]. Across the United Kingdom’s publicly funded National Health Service (NHS), the GP workforce appears to have been particularly affected by underinvestment in some areas, the Covid-19 pandemic, and the country’s aging population and shifting epidemiological profile[8]. The present paper is part of a special collection on the crisis of the medical workforce in Europe and offers a contribution to the exploration of aspects of the complex crisis of the GP workforce in the UK [9]. “General practitioner” is a protected title requiring specific professional registration to use. Becoming a GP in the UK typically takes a minimum of ten years of medical training. Five of these years are usually in undergraduate medical education, two years are spent in the postgraduate UK Foundation Training programme and a minimum of an additional 3 years in GP specialty training [10]. GP training is open to UK medical graduates who have completed the foundation training; however, an increasing proportion of training places are also open to candidates from overseas. Indeed, the proportion of international medical graduates (IMGs) filling GP training roles is on the rise, from just under one-fifth (19%) in 2017 to 46% in 2023 [11,12]. As of December 2023, there were around 6,300 general practices across England – independent contractors, commissioned by the NHS – engaging approximately 27,000 fully-qualified, full-time equivalent (FTE) GPs. Following their qualification, those GPs remaining in the NHS will usually practise either as independent contractors (or partners) running a practice, or as salaried GPs employed by a GP practice and/or as a locum GP filling in rota gaps (see Table 1 in the Methods). The general practice model in England requires sufficient GPs to act as partners, providing much of the organisational development capacity to meet the changing contractual, regulatory, and training requirements. It also requires enough GPs in general who can respond to the increasing demands of medical complexity in the community and can provide continuity of care [13]. If there are not enough GPs to provide and manage care, this is felt by patients struggling to book timely appointments, being unable to see their usual GP, and having a less positive experience of care overall. GPs are also required to supervise the wider clinical team. There is a vast gap between ambition and reality in terms of numbers of GPs in England. This is despite several commitments made to increase the number of GPs in the last decade, including a pledge of 6,000 more GPs by 2024 as part of the UK government’s 2019 election manifesto [14]. However, the number of fully qualified FTE GPs in England has been consistently falling, with a decrease of 1,833 in the seven years to December 2023 against the backdrop of a growing and aging population [15]. The government has set out ambitious plans to increase the number of GPs in England. The NHS Long Term Workforce Plan suggests that the number of GPs needs to increase by 39-47% (14-17,000) by 2036/37 in order to meet demand and pledges to increase the number of GP training places by 50% by 2031/32 [16]. The competition for GP training places has been increasing in recent years and there is an almost 100% fill rate of such places [17]. However, the efficiency of this training pipeline has been brought into question; previous work has suggested that on average, an estimated two training posts are required in England to get one fully qualified, FTE GP joining the NHS medical workforce (GP joiner) [18]. Such conversion rates of GP specialty trainees (GP registrars) into GP joiners are an important indicator of the efficiency of medical training. Previously surveys have found that 13% of GP registrars say they don’t expect to work as GPs in the future and 60% do not report positive feelings about their future career prospects as a GP in the UK, [19] [20] with career intentions adversely influenced by, for example, perceptions of workload pressure, low morale and poor work-life balance, as well as negative portrayals of general practice by politicians and the media [21]. METHODS The aim of this paper is to describe the rate of GP registrars in their third year of training (GP ST3s) subsequently joining NHS general practice as fully qualified practitioners (GP joiners) in England, within the context of other physician roles in the NHS (see Table 1). Table 1: Overview of key medical roles in general practice considered in our analysis Role Role description GP partner Self-employed practitioner that owns part of the practice and is subcontracted to provide services for the NHS. Provides both clinical sessions and business management. GP registrar Doctors training to become general practitioners. GP regular locum A practitioner that provides temporary cover in the absence of regular practitioners on a fairly predictable or consistent basis. Those working on less predictable patterns are referred to as ‘ad hoc locums’ GP retainer Practitioners considering leaving the profession that are supported by financial and educational resources to remain in clinical practice. Salaried GP A contracted practitioner employed by a practice that receives a set salary. GP ST3 Doctors in their third year of specialty GP training. GP joiner New doctors joining practices providing NHS services as fully qualified GPs after completing specialty training – this includes partners, salaried GPs and regular locums. Source: Authors. Drawing from the existing literature on GP registrars in the UK [19,20], our starting hypothesis was that there is a substantial loss in workforce capacity caused by many doctors reaching the end of their training and then either not participating in NHS work, or, if joining the NHS workforce, not working full-time. We therefore set out to analyse the changing transition rates, from the third year of GP training to joining the fully qualified GP workforce, across the five years to 2023. The study covers two aspects of the transition of GP ST3s in NHS GP services: the proportion of GP ST3s appearing in the NHS GP workforce dataset as fully qualified GPs working in partner, salaried or regular locum[1] roles (joiner rates) ; and the average contracted hours of joiners, as a proportion of a typical full-time contract (participation rates) . We first explored descriptively the available quantitative data; we then complemented descriptive statistics with statistical modelling to provide evidence of association between the components for any trends. We sought to explore the effects of different behaviours of new cohorts completing training (so called cohort effect ) and the underlying change in landscape which might affect joiner and participation rates, including during the Covid-19 pandemic ( period effect ). Data sources The data on joiner rates – used in the descriptive analysis and statistical modelling – were extracted from publicly available datasets published by NHS Digital, now part of NHS England, and were reported quarterly from September 2018 to December 2023. A dataset tracking 14,325 GP ST3s in England into fully qualified GP roles was used, with breakdowns by gender and country of qualification [22]. For participation rates, data on 21,293 fully qualified GP joiners in England was analysed, using the age and gender breakdowns of the GP ST3 practice-level data [23]. Data on participation rates were taken annually from September 2017 to December 2023 [23]. Data analysis For the descriptive analysis (reported in Table 2), joiner rates – and relative risks – were calculated, disaggregated by cohort, gender and country of primary medical qualification. Participation rates among fully qualified practitioners joining the workforce (reported in Table 3) were calculated by dividing full-time equivalent by headcount number. These participation rates were adjusted (to reduce the influence of participation rates of those re-joiners rather than those directly from the domestic training pipeline) using GP ST3 age and gender breakdowns of those in their last year in a GP training post to estimate the average level of participation for each cohort joining the GP workforce from a third year training post. For the statistical modelling, we used generalised linear mixed-effects models to make statistical inferences about how our model predictors influenced the number of joiners in a given period. Our modelling framework is also known as a Hierarchical Age-Period-Cohort-Cross-Classified Random Effects Model, which can be used for data that is classified by age or time across multiple time periods and cohorts [24]. We included fixed effects for the time in months between GP ST3s last seen in specialty training and taking up a fully qualified GP role (referred to as ‘duration’), month of the year last seen in specialty training (to account for seasonality around reasons for leaving), and included random effects for cohort (the quarter and year in which doctors were last seen in specialty training) and period (the quarter and year at which doctors returned as a fully qualified GP) (Appendix 2, Equation i). In some versions of the model (as flagged in the results) we also included fixed effects to capture demographic details around gender and country of qualification (UK and non-UK) (Appendix 2, Equation ii). Analysis was conducted in RStudio 4.3.2 and Microsoft Excel. To quantify the relationship between the fixed effects and the likelihood of joining the fully qualified GP workforce, we presented odds ratios with 95% confidence intervals at the 5% significance level. We extracted the random effect components of our models, which were presented as conditional log odds with 95% confidence intervals for both the cohort and period effects (see Appendix 2 for further details on statistical modelling). RESULTS The results section starts with a description of the doctor population covered by the data, before giving a descriptive summary of variation and trends in joiner rates and then participation rates. We then cover the findings from the exploratory statistical modelling. Across the 21 cohorts, between September 2018 and September 2023, 14,325 doctors left their final year of GP training (GP ST3s). Our findings show that the GP training pipeline is expanding; the number at the end of training increased over time with 2,363 doctors leaving their final year of training in the year to June 2019 compared to 3,358 in the corresponding period four years later. Around three-fifths (61.4%) of GP ST3s were female, and two-thirds (67.1%) gained their primary medical qualification in the UK with the remainder from EEA (4.4%) and elsewhere (28.5%). Fewer than three-in-five (57.5%; 8,237) of these doctors were identified in the NHS GP workforce subsequent to finishing training as a fully-qualified GP by December 2023 while the remaining 6,088 have yet to be identified in the data. By displaying the proportion who have joined the NHS in relation to months elapsed since that cohort left their ST3 year, we can visualise the variation in the likelihood of different GP ST3 cohorts joining at various times after leaving training (Figure 1). Figure 1: Progression rates of GPST3s joining the NHS GP workforce Source: NHS England – Tracking GPs in training into fully-qualified general practice roles (2024). Excluding those recent cohorts for which insufficient time has elapsed for them to be captured within the timeframes, of those doctors in their third year of training since 2018, around a third (34.3%) had taken up a fully qualified GP role in NHS general practice six months after finishing training rising to 47.5% within one year, 62.2% within two years, and 70.8% within three years. These joiner rates were not consistent across cohorts or characteristics (Table 2). For example, overall doctors with a primary medical qualification from outside the UK were less likely to transition to fully-qualified NHS GP roles within 6 months (-3.4 percentage points; unadjusted relative risk (RR) 0.91, 95% CI (confidence interval) 0.86 – 0.95) with the disparity increasing over a two-year period (-11.7 percentage points; RR 0.82, CI 0.79 – 0.86). Both UK and non-UK trained male GP ST3s were less likely to join within a two-year timeframe compared to female GP ST3s (-4.9 percentage points; RR 0.92, CI 0.89 – 0.96). Male non-UK trained GP ST3s seem to have the lowest overall joining rates at two years (RR 0.89, CI 0.69 – 0.87). Since around 2021, there appears to have been a decline in the proportion of GP ST3s taking up fully-qualified GP roles in NHS general practice services. We found 34.1% of GP ST3s in the year to June 2019 took up a fully-qualified role within 6 months, with this proportion increasing for the cohort who left training the following year (39.4%, RR 1.15, CI 1.07-1.24) before declining. The recent two annual cohorts (those leaving in the year to June 2022 and to June 2023) appear to have generally lower joiner rates although these results were not always statistically significantly different to the baseline (year to June 2019). We present a visualisation of joiner rates disaggregated by region of qualification and gender in Figure 3 in Appendix 1. Results from generalised linear mixed-effects models The findings from the statistical modelling support the previously described findings around associations between joiner rates and demographics. Nearly all of the fixed effects were significant predictors in how likely GP ST3s were to join the fully qualified NHS GP workforce. Male GP ST3s were less likely to join than female GP ST3s (Odds ratio, OR 0.94, CI 0.89 – 0.98), while those who studied medicine in the UK were more likely to join than those who trained outside of the UK but took up a specialty training post in England (OR 1.20, CI 1.14 – 1.27) (Figure 4, Appendix 2). We also found an association between when in the year GP ST3s left their training and their likelihood of joining the NHS. Relative to those last seen in their third year of specialty training in the three months to December, those last seen in three months to June were more likely to join as a fully qualified GP (OR 1.19, CI 1.04 – 1.37), but there was no significant difference in the likelihood of GP ST3s joining among those last seen in the three months to March (OR 0.91, CI 0.78 – 1.06) or September (OR 0.90, CI 0.78 – 1.04). As expected, our analysis also showed that the odds of joining increased at a decreasing rate as the length of time between training and acquiring a fully qualified role increased (OR 1.09, CI 1.07 – 1.10). We identified a significant effect among some cohorts. After adjusting for duration and seasonality, GP ST3s who left specialty training in the three months to March 2020 were most likely to join the fully qualified workforce, while those who left specialty training in the three months to September 2023 were least likely to join (Figure 5, Appendix 2). After adjusting for gender and country of qualification, some differences persisted including significantly lower joiner rates for the cohort leaving in the three months to June 2021 and higher rates among those last seen in specialty training in three months to March 2020 and to September 2020 (Figure 2). We also identified a significant ‘period effect’ with apparent differences in the likelihood of GP ST3s joining the NHS in a fully qualified role at a particular point in time. Specifically, after adjustments for duration and seasonality effects, doctors were least likely to join in the three months to March 2020 and most likely to join in the subsequent three months (to June 2020) (Figure 6, Appendix 2). The differences persisted even after adjusting for demographic factors for gender and country of qualification (Figure 2). Table 2: Joiner rates at 6 and 24 months after leaving training (unadjusted) Joined within 6 months Joined within 24 months Number leaving ≥ 6 months ago (%) % identified in fully-qualified NHS role Relative risk (95% CI) Number leaving ≥ 24 months ago (%) % identified in fully-qualified NHS role Relative risk (95% CI) All 13,601 34.3% 8,463 62.2% Demographics UK trained All 9,220 (67.8%) 35.4% (ref) 6,106 (72.1%) 65.4% (ref) Non-UK trained All 4,381 (32.2%) 32.0% 0.91 (0.86– 0.95) 2,357 (27.9%) 53.7% 0.82 (0.79 – 0.86) All Female 8,288 (60.9%) 33.7% (ref) 5,289 (62.5%) 64.0% (ref) All Male 5,313 (39.1%) 35.3% 1.05 (1.00 – 1.10) 3,174 (37.5%) 59.1% 0.92 (0.89 – 0.96) UK trained Female 6,018 (44.2%) 35.2% (ref) 4,043 (47.8%) 66.6% (ref) Male 3,202 (23.5%) 35.7% 1.02 (0.93 – 1.10) 2,063 (24.4%) 63.1% 0.95 (0.87 – 1.03) Non-UK trained Female 2,270 (16.7%) 29.7% 0.84 (0.76 – 0.93) 1,246 (14.7%) 55.6% 0.83 (0.75 – 0.93) Male 2,111 (15.5%) 34.5% 0.98 (0.89 – 1.08) 1,111 (13.1%) 51.6% 0.89 (0.69 – 0.87) Year cohort left training Year to June 2019 2,355 (17.3%) 34.1% (ref) 2,355 (27.8%) 62.2% (ref) Year to June 2020 2,375 (17.5%) 39.4% 1.15 (1.07-1.24) 2,375 (28.1%) 66.9% 1.08 (1.03 – 1.12) Year to June 2021 2,762 (20.3%) 35.7% 1.04 (0.97 – 1.13) 2,762 (32.6%) 60.5% 0.97 (0.93 – 1.02) Year to June 2022 2,751 (20.2%) 31.7% 0.93 (0.86 – 1.00) 971 (11.5%) 55.4% a 0.89 (0.84 – 0.95) Year to June 2023 3,358 (24.7%) 31.8% 0.93 (0.86 – 1.00) n/a n/a n/a Notes: a Data cover cohort leaving ST3 in 6-months to December 2021. Figure 2: Likelihood (log odds) of GP ST3s joining the NHS fully qualified GP workforce by year of GP ST3 training, by month and year of leaving GP ST3 training (cohort effect) and by date of joining the NHS workforce (period effect) , adjusting for duration, gender, country of qualification and seasonality Source: NHS England – Tracking GPs in training into fully-qualified general practice roles (2024). Participation rates As well as joiner rates, we also explored differences in ‘participation rate’ which relates to the contracted hours of joiners. In the year to December 2023, the average participation – the extent to which staff are employed on a full-time contract – of fully qualified GP joiners was 64%. When breaking participation down by five-year age category among those who joined between 2017-18 and 2022-23, participation varied from 47% among GPs aged 65 and over to 73% among those under 30. Average participation rates are lower for female GPs (60.9%). If it is assumed that new GP joiners follow the age and gender distribution of those in their third year of GP training, then the participation rate would be in the region of 66% in 2022-23. These levels do vary to a degree from year-to-year but were similar to those seen in the baseline year, five years’ prior (67%) (Table 3). Table 3: Frequency and participation rate of new fully qualified GPs joining the workforce by age, gender and year of joining, 2017-18 to 2022-23 Numbers joining (headcount) Average participation, % full-time contract All 21,293 64.1% (66.6%) Gender Female 13,258 60.9% Male 8,035 69.3% Age Under 30 1,124 72.6% 30-34 6,993 66.4% 35-39 5,032 62.1% 40-44 3,170 61.8% 45-49 2,085 63.5% 50-54 1,320 64.8% 55-59 880 62.9% 60-64 428 54.2% 65 and over 273 47.3% Year joined Age-gender adjusted 2017-18 3,291 64.8% 67.0% 2018-19 4,022 63.3% 66.1% 2019-20 3,787 62.3% 64.9% 2020-21 3,425 64.6% 67.7% 2021-22 3,075 66.8% 69.0% 2022-23 3,693 63.2% 65.8% Source: NHS England – General Practice Workforce (2024). [23] Note: Due to missing data values, some demographic breakdowns may not sum the total number of joiners. Age-gender adjustments to participation rates were based on the composition of ST3 GPs in the same year that the fully qualified GP joiner data relate to. Since most GPs will not take up a fully qualified role within a year of completing training, these rates should be interpreted with caution. DISCUSSION While the GP workforce equation has often been characterised in the literature as a ‘recruitment or retention crisis’ [16,25,26], our paper focuses on the critical issue of conversion of GP training numbers to NHS GP joiners in England. The leak in the pipeline from training through to participation in the NHS workforce as fully-qualified GPs has been highlighted previously [18]; exploiting newly published data, we explored the nature of the challenge in greater depth. Our analysis of GP ST3s’ NHS career progression highlights a substantial attrition rate in the GP workforce model; of those doctors in their final stage of training since 2018, fewer than two-thirds (62.2%) had taken up a fully qualified GP role in NHS general practice within two years. This trend in recent years appears to have worsened, as little more than half (55.4%) of those that left their third year of training between June and December 2021 had taken up fully-qualified NHS GP roles within two years and by December 2023. Some demographics display especially low joiner rates, particularly males with a primary medical qualification from outside the UK, of which only 51.6% leaving their third year of training appear to take up fully qualified roles in NHS general practice within 2 years. Our exploratory statistical analysis also provides some evidence that certain cohorts of GP ST3s were more likely to join as fully-qualified GPs (such as those that left in 2020) and at certain periods of time newly qualified doctors were more likely to be recruited. For example, the three months to June 2020 saw significantly higher joiner rates relative to average, though this may be an artifact of Covid-19 with a catch-up in recruitment after lower rates in the previous 3 months as the pandemic first hit. The impact of these low joiner rates on overall NHS capacity are compounded by relatively high but fairly stable levels of less than full time working. The average contracted hours of GPs joining the workforce are around two-thirds of a full-time contract. Rates are lower for female GPs (60.9%), and broadly decline by age. Taking the joiner rates and participation rates together, it means that, for every 10 doctors leaving the third year of GP training, the NHS will secure around 4 full-time equivalent fully qualified GPs within 2 years, excluding those that might be working as ad-hoc locums. Our findings need to be interpreted with a degree of caution, as we acknowledge data limitations, and our results will need to be triangulated with other workforce data sources. For example, our analysis did not include ad-hoc GP locums within the NHS because this group were not captured within the data; however, separate analyses suggest that around a third of GP ST3 leavers not taking up substantive NHS GP roles may have worked as an ad-hoc locum. The data do also not pick up, for instance, GPs working exclusively in certain settings such as out of hours services, or A&E streaming [22]. This may have underestimated conversion rates to GP roles but given the importance of – and current challenges around – a sustainable supply of substantive GP roles in NHS general practices, the rates we present remain of significant policy importance. Our reported participation rates may also be affected by this lack of information on, for example, ad-hoc locum sessions. We consider that several supply as well as demand-side factors might be responsible for such delays in joining the primary care medical workforce. On the one hand, it is fairly established that GP jobs have become increasingly complex and demanding, particularly after the recent pandemic [27]. A questionnaire of 25 European countries in 2015 showed that nations where GPs undertook more than 25 direct patient consultations per day experienced more problems in GP retention and recruitment [28]. The definition of clinical sessions in existing NHS GP contracts and the implementation of such contracts often underestimate the actual GP workload [27]. By experiencing their tutors’ workload, it does not seem unreasonable that trainees may be put off from pursuing a full-time career in general practice[19]. Similarly, doctors might delay committing to a substantive GP role where contracts do not sufficiently capture additional, non-clinical activities such as education, management and research which may be better captured within secondary care specialist consultant contracts. At the same time, there are reports it might have become increasingly difficult for GP practices to contract newly-trained GPs because of funding shortfalls at different levels [29]. The introduction of the Additional Roles Reimbursement Scheme (ARRS) in 2019 meant that practices could benefit from additional staff at no direct cost to their practice and resulted in an additional 22,000 staff being recruited. The ARRS scheme however does not include salaried GPs. Therefore, the relative costs to practices of employing GPs combined with wider financial pressures within general practice may have resulted in fewer GP job opportunities [30]. Our work carries important policy implications for governments in the UK as well as in other European countries. First of all, if one-third of recently trained specialists these days fail to join the primary care workforce, this means that more GPs need to be trained or retained to meet the increasing health needs and demand for healthcare services from an aging population, exacerbating an already complex planning exercise [31]. Secondly, the root causes for the identified leak need to be fully understood and tackled, with a view to adequately staffing primary care services. We identified a need for additional information on variety and intensity of roles that GPs undertake within the NHS, as well on vacancies (both filled and unfilled) which is particularly problematic in light of recent reports of GPs being made redundant or unable to find work [16,32]. Such data would allow the necessary analyses to gain a greater understanding of the nature and reasons for joiner and participation rates. Government has sought to attract GPs into the NHS through a range of schemes including GP International Induction Programme, improved visa sponsorship arrangements, GP Fellowship Programme, the Supporting Mentors Scheme and the New to Partnership Payment [18]. However, the continuation of funding for several of these initiatives is uncertain. Some areas find it more challenging to attract GPs. These are typically more deprived and remote locations that are not regularly used for medical school placements and are therefore less familiar to newer doctors [33]. The findings of particularly low levels of overseas doctors completing GP training going on to take up fully qualified GP roles is particularly important in view of the increasing proportion of IMG trainees. Induction and training support schemes are attempting to address the differential exam attainment of IMGs in the GP licensing exams [34], and policies have been introduced to remove potential barriers to IMG GP trainees joining the NHS workforce once they have completed their training. The effectiveness of such initiatives needs ongoing monitoring. CONCLUSION As the senior medics within their services, GPs have a pivotal role for the sustainability of the primary care system. However, in England there have been repeated failures to meet the ambitions to increase the number of fully-qualified GPs and, instead, numbers have fallen worryingly. Much attention has been paid to the recruitment of trainee GPs; however, our analysis shines a light on a critical part of the workforce model namely the domestic training pipeline and, specifically, the transition from ending training to joining the NHS. Using published data, we estimated that for every 10 doctors leaving training around 4 fully-qualified full-time equivalent GPs join NHS services within two years – and we provide evidence of differences between demographics (particularly lower joiner rates for overseas trained medics), differences in behaviours of doctors leaving over time (cohort effect), and different labour market conditions over time (period effect). Further work is also suggested. The differences in career behaviours between demographics appear to be changing over time and this should be studied further. Conversion rates for GPs should be compared to rates for other specialties, to identify whether this issue is unique to general practice or is more common across other areas of medicine. Given the importance of GP retention to the sustainability of GP services, national and regional bodies must act fast to better understand the factors influencing this apparent suboptimal transition from training to joining the NHS workforce and identify and implement urgent solutions. Abbreviations FTE full-time equivalent GP ST3 doctor in third year of GP specialty training GP general practitioner NHS National Health Service in England Declarations Availability of data and materials This study explored publicly available data. Additional results from our analysis can be made available for reasonable requests. Acknowledgements We would like to thank Cono Ariti for his statistical advice on this study. Funding This study received the financial support of the UK Medical Research Council and Newton Fund [grant number MRC/R022747/1]. Ethics declaration None References Hanson K, Brikci N, Erlangga D, Alebachew A, Allegri MD, Balabanova D, et al. 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The state of medical education and practice in the UK: The workforce report 2022 [Internet]. Regent’s Place 350 Euston Road, London: General Medical Council; 2022. Available from: https://www.gmc-uk.org/-/media/documents/workforce-report-2022---full-report_pdf-94540077.pdf RCGP. RCGP General Election Manifesto [Internet]. 2024 [cited 2024 May 2]. Available from: https://www.rcgp.org.uk/representing-you/manifesto Forbes LJ, Forbes H, Sutton M, Checkland K, Peckham S. Changes in patient experience associated with growth and collaboration in general practice: observational study using data from the UK GP Patient Survey. Br J Gen Pract. 2020;70:e906–15. Iacobucci G. Tories promise 6000 extra GPs by 2024. BMJ. 2019;367:l6463. Nuffield Trust. General practice [Internet]. Nuffield Trust. 2024 [cited 2024 May 2]. Available from: https://www.nuffieldtrust.org.uk/nhs-staffing-tracker/general-practice NH England. NHS Long Term Workforce Plan [Internet]. London, UK: National Healthcare System; 2024. Available from: https://www.england.nhs.uk/publication/nhs-long-term-workforce-plan/ NHS England. 2023 Competition ratios [Internet]. NHS England | Workforce, training and education | Medical Hub. 2024 [cited 2024 May 2]. Available from: https://medical.hee.nhs.uk/medical-training-recruitment/medical-specialty-training/competition-ratios/2023-competition-ratios Palmer B, Rolewicz L, Dodsworth E. Waste not, want not: Strategies to improve the supply of clinical staff to the NHS [Internet]. London, UK: Nuffield Trust; 2023. Available from: https://www.nuffieldtrust.org.uk/research/waste-not-want-not-strategies-to-improve-the-supply-of-clinical-staff-to-the-nhs Lalljee J. How do UK medical school places translate to fully trained GPs? [Internet]. Pulse Today. 2023 [cited 2024 May 2]. Available from: https://www.pulsetoday.co.uk/analysis/pulse-on-workforce/how-do-uk-medical-school-places-translate-to-fully-trained-gps/ British Medical Association. Survey reveals extent of pressures on GP registrars [Internet]. BMA News. 2023 [cited 2024 May 2]. Available from: https://www.bma.org.uk/news-and-opinion/survey-reveals-extent-of-pressures-on-gp-registrars Dale J, Russell R, Scott E, Owen K. Factors influencing career intentions on completion of general practice vocational training in England: a cross-sectional study. BMJ Open. 2017;7:e017143. NHS England. Tracking GPs in training into fully-qualified general practice roles [Internet]. NHS England Digital. 2024 [cited 2024 May 2]. Available from: https://digital.nhs.uk/supplementary-information/2024/tracking-gps-in-training-into-fully-qualified-general-practice-roles---december-2023023 NHS England. General Practice Workforce, 31 December 2023 [Internet]. NHS England Digital. 2024 [cited 2024 May 2]. Available from: https://digital.nhs.uk/data-and-information/publications/statistical/general-and-personal-medical-services/31-december-2023 [1] Y. Yang and K. C. Land, "Mixed-effects models and hierarchical APC and cross-classified random-effects models (HAPC-CCREM): Part I. Basics" in Handbook of Advanced Multilevel Analysis, J. Hox and J.K. Roberts, Eds. New York, NY: Routledge, 2010, pp. 101–142. [Online]. Available from: https://www.taylorfrancis.com/chapters/oa-mono/10.1201/b13902-7/mixed-effects-models-hierarchical-apc-cross-classified-random-effects-models-hapc-ccrem-part-basics-yang-yang-kenneth-land RCGP. Fit for the Future: Retaining the GP workforce [Internet]. London, UK: Royal College of General Practitioners; 2022. Available from: https://www.rcgp.org.uk/getmedia/155e72a9-47b9-4fdd-a322-efc7d2c1deb4/retaining-gp-workforce-report.pdf Chilvers R, Richards SH, Fletcher E, Aylward A, Dean S, Salisbury C, et al. Identifying policies and strategies for general practitioner retention in direct patient care in the United Kingdom: a RAND/UCLA appropriateness method panel study. BMC Family Practice. 2019;20:130. Barnard R, Spooner S, Hubmann M, Checkland K, Campbell J, Swinglehurst D. The hidden work of general practitioners: An ethnography. Social Science & Medicine. 2024;350:116922. McCarthy M. Sustainable general practice: looking across Europe. Br J Gen Pract. 2016;66:36–36. Ungoed-Thomas J, Tapper J. Revealed: locum GPs in England can’t find work as surgeries buckle under patient demand. The Observer [Internet]. 2024 May 12 [cited 2024 May 15]; Available from: https://www.theguardian.com/society/article/2024/may/12/england-locum-gps-doctors-work-surgeries-british-medical-association Kaffash J. Number of GP vacancies advertised almost halves in a year [Internet]. Pulse Today. 2023 [cited 2024 May 15]. Available from: https://www.pulsetoday.co.uk/news/workforce/number-of-gp-vacancies-advertised-almost-halves-in-a-year/ Waters A. No point in increasing GP recruitment without focus on retention, say leaders. BMJ. 2022;379:o2833. NHS England. GP Earnings and Expenses Estimates, 2021/22 [Internet]. NHS England Digital. 2024 [cited 2024 May 2]. Available from: https://digital.nhs.uk/data-and-information/publications/statistical/gp-earnings-and-expenses-estimates/2021-22 Armstrong MJ, Wildman JM, Sowden S. How to address the inverse care law and increase GP recruitment in areas of socioeconomic deprivation: a qualitative study of GP trainees’ views and experiences in the UK. BJGP Open [Internet]. 2024 [cited 2024 May 15]; Available from: https://bjgpopen.org/content/early/2024/04/29/BJGPO .2023.0201 Siriwardena AN, Botan V, Williams N, Emerson K, Kameen F, Pope L, et al. Performance of ethnic minority versus White doctors in the MRCGP assessment 2016–2021: a cross-sectional study. Br J Gen Pract. 2023;73:e284–93. Footnotes We did not include ‘ad-hoc’ GP locums, (locum or sessional GPs who typically work briefly at practices, such as a single one-off session, to cover for short-term or unexpected absences) because information about them is captured in a different way to the rest of the workforce. Additional Declarations Competing interest reported. WLP, LR and GR have no completing interests VTB is a GP academic, practising GP and the Royal College of General Practitioners Vice Chair. Supplementary Files Appendix12.docx Cite Share Download PDF Status: Published Journal Publication published 03 Mar, 2025 Read the published version in Human Resources for Health → Version 1 posted Editorial decision: Revision requested 15 Oct, 2024 Reviews received at journal 09 Oct, 2024 Reviewers agreed at journal 06 Oct, 2024 Reviewers agreed at journal 07 Aug, 2024 Reviews received at journal 05 Aug, 2024 Reviewers agreed at journal 29 Jul, 2024 Reviewers invited by journal 20 Jun, 2024 Editor assigned by journal 15 Jun, 2024 Submission checks completed at journal 11 Jun, 2024 First submitted to journal 11 Jun, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4565547","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":321243711,"identity":"c45a02cf-d517-4701-9ef4-f9200987961f","order_by":0,"name":"William L Palmer","email":"data:image/png;base64,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","orcid":"","institution":"Nuffield Trust","correspondingAuthor":true,"prefix":"","firstName":"William","middleName":"L","lastName":"Palmer","suffix":""},{"id":321243713,"identity":"a44d4a7a-6f91-48b3-9ba5-212945d41953","order_by":1,"name":"Lucina Rolewicz","email":"","orcid":"","institution":"Nuffield Trust","correspondingAuthor":false,"prefix":"","firstName":"Lucina","middleName":"","lastName":"Rolewicz","suffix":""},{"id":321243715,"identity":"406f48e1-064f-44f5-8a7d-31d29f5e3277","order_by":2,"name":"Victoria Tzortziou-Brown","email":"","orcid":"","institution":"Queen Mary University of London","correspondingAuthor":false,"prefix":"","firstName":"Victoria","middleName":"","lastName":"Tzortziou-Brown","suffix":""},{"id":321243717,"identity":"23d1ea98-bd00-43e1-905c-c083bc7c5015","order_by":3,"name":"Giuliano Russo","email":"","orcid":"","institution":"Queen Mary University of London","correspondingAuthor":false,"prefix":"","firstName":"Giuliano","middleName":"","lastName":"Russo","suffix":""}],"badges":[],"createdAt":"2024-06-11 16:36:04","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4565547/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4565547/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12960-025-00980-x","type":"published","date":"2025-03-03T15:56:55+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":59484594,"identity":"a08ea595-735b-497c-82dd-4c780bc6244d","added_by":"auto","created_at":"2024-07-02 10:45:20","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":35661,"visible":true,"origin":"","legend":"\u003cp\u003eProgression rates of GPST3s joining the NHS GP workforce\u003c/p\u003e\n\u003cp\u003eSource: NHS England – Tracking GPs in training into fully-qualified general practice roles (2024).\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4565547/v1/d77d7fa5d3b9d092081307be.jpg"},{"id":59484592,"identity":"6e27ee62-dda9-46bd-9c4f-9fad2d811108","added_by":"auto","created_at":"2024-07-02 10:45:20","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":51292,"visible":true,"origin":"","legend":"\u003cp\u003eLikelihood (log odds) of GP ST3s joining the NHS fully qualified GP workforce by year of GP ST3 training, by month and year of leaving GP ST3 training (cohort effect) and by date of joining the NHS workforce (period effect) , adjusting for duration, gender, country of qualification and seasonality\u003c/p\u003e\n\u003cp\u003eSource: NHS England – Tracking GPs in training into fully-qualified general practice roles (2024).\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4565547/v1/f46d024148bd6536ca09394f.jpg"},{"id":78181299,"identity":"f784ef9e-eb3e-4e92-affb-7e70e0772515","added_by":"auto","created_at":"2025-03-10 17:45:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":640865,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4565547/v1/55ed9f5c-667f-4b85-82af-28079976aa97.pdf"},{"id":59484595,"identity":"2d76099d-195f-4e8b-ae4f-3dbd85a7f35f","added_by":"auto","created_at":"2024-07-02 10:45:20","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":423573,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix12.docx","url":"https://assets-eu.researchsquare.com/files/rs-4565547/v1/c5e9cc9ce80a344fd275bda6.docx"}],"financialInterests":"Competing interest reported. WLP, LR and GR have no completing interests\nVTB is a GP academic, practising GP and the Royal College of General Practitioners Vice Chair.","formattedTitle":"A hole in the bucket? Exploring England’s retention rates of recently qualified GPs","fulltext":[{"header":"INTRODUCTION AND BACKGROUND","content":"\u003cp\u003eGeneral practice is essential for population health, the efficiency of health systems, and ultimately the attainment of universal health coverage worldwide\u0026nbsp;[1]. \u0026nbsp;And as the senior medics within these services, general practitioners (known as family physicians in some countries) have a pivotal role, with responsibility for providing continuous whole person medical care, and managing \u0026nbsp;risk, uncertainty and medical complexity\u0026nbsp;[2,3].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHowever, recruiting and retaining general practitioners (GPs) \u0026nbsp;has historically been difficult[4]. The international literature suggests that worse pay, lower prestige, compulsory rural placements, elevated risk of burn-out, and a deteriorating working environment, might all be factors[5,6]. Recent policies have mainly focused on increasing training numbers despite the recognition that workforce retention needs to be prioritised too\u0026nbsp;[7].\u003c/p\u003e\n\u003cp\u003eAcross the United Kingdom\u0026rsquo;s publicly funded National Health Service (NHS), the GP workforce appears to have been particularly affected by underinvestment in some areas, the Covid-19 pandemic, and the country\u0026rsquo;s aging population and shifting epidemiological profile[8]. The present paper is part of a special collection on the crisis of the medical workforce in Europe and offers a contribution to the exploration of aspects of the complex crisis of the GP workforce in the UK\u0026nbsp;[9].\u003c/p\u003e\n\u003cp\u003e\u0026ldquo;General practitioner\u0026rdquo; is a protected title requiring specific professional registration to use. Becoming a GP in the UK typically takes a minimum of ten years of medical training. Five of these years are usually in undergraduate medical education, two years are spent in the postgraduate UK Foundation Training programme and a minimum of an additional 3 years in GP specialty training\u0026nbsp;[10]. GP training is open to UK medical graduates who have completed the foundation training; however, an increasing proportion of training places are also open to candidates from overseas. Indeed, the proportion of international medical graduates (IMGs) filling GP training roles is on the rise, from just under one-fifth (19%) in 2017 to 46% in 2023\u0026nbsp;[11,12].\u003c/p\u003e\n\u003cp\u003eAs of December 2023, there were around 6,300 general practices across England \u0026ndash; independent contractors, commissioned by the NHS \u0026ndash; engaging approximately 27,000 fully-qualified, full-time equivalent (FTE) GPs. Following their qualification, those GPs remaining in the NHS will usually practise either as independent contractors (or partners) running a practice, or as salaried GPs employed by a GP practice and/or as a locum GP filling in rota gaps (see Table 1 in the Methods).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe general practice model in England requires sufficient GPs to act as partners, providing much of the organisational development capacity to meet the changing contractual, regulatory, and training requirements. It also requires enough GPs in general who can respond to the increasing demands of medical complexity in the community and can provide continuity of care\u0026nbsp;[13]. If there are not enough GPs to provide and manage care, this is felt by patients struggling to book timely appointments, being unable to see their usual GP, and having a less positive experience of care overall. GPs are also required to supervise the wider clinical team.\u003c/p\u003e\n\u003cp\u003eThere is a vast gap between ambition and reality in terms of numbers of GPs in England. This is despite several commitments made to increase the number of GPs in the last decade, including a pledge of 6,000 more GPs by 2024 as part of the UK government\u0026rsquo;s 2019 election manifesto\u0026nbsp;[14]. However, the number of fully qualified FTE GPs in England has been consistently falling, with a decrease of 1,833 in the seven years to December 2023 against the backdrop of a growing and aging population\u0026nbsp;[15].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe government has set out ambitious plans to increase the number of GPs in England. The NHS Long Term Workforce Plan suggests that the number of GPs needs to increase by 39-47% (14-17,000) by 2036/37 in order to meet demand and pledges to increase the number of GP training places by 50% by 2031/32\u0026nbsp;[16]. The competition for GP training places has been increasing in recent years and there is an almost 100% fill rate of such places\u0026nbsp;[17].\u003c/p\u003e\n\u003cp\u003eHowever, the efficiency of this training pipeline has been brought into question; previous work has suggested that on average, an estimated two training posts are required in England to get one fully qualified, FTE GP joining the NHS medical workforce (GP joiner) [18]. Such conversion rates of GP specialty trainees (GP registrars) into GP joiners are an important indicator of the efficiency of medical training. Previously surveys have found that 13% of GP registrars say they don\u0026rsquo;t expect to work as GPs in the future and 60% do not report positive feelings about their future career prospects as a GP in the UK, [19] [20] with career intentions adversely influenced by, for example, perceptions of workload pressure, low morale and poor work-life balance, as well as negative portrayals of general practice by politicians and the media [21].\u0026nbsp;\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eThe aim of this paper is to describe the rate of GP registrars in their third year of training (GP ST3s) subsequently joining NHS general practice as fully qualified practitioners (GP joiners) in England, within the context of other physician roles in the NHS (see Table 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;1: Overview of key medical roles in general practice considered in our analysis\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.3044925124792%\" valign=\"top\"\u003e\n \u003cp\u003eRole\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"82.6955074875208%\" valign=\"top\"\u003e\n \u003cp\u003eRole description\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.3044925124792%\" valign=\"top\"\u003e\n \u003cp\u003eGP partner\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"82.6955074875208%\" valign=\"top\"\u003e\n \u003cp\u003eSelf-employed practitioner that owns part of the practice and is subcontracted to provide services for the NHS. Provides both clinical sessions and business management.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.3044925124792%\" valign=\"top\"\u003e\n \u003cp\u003eGP registrar\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"82.6955074875208%\" valign=\"top\"\u003e\n \u003cp\u003eDoctors training to become general practitioners.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.3044925124792%\" valign=\"top\"\u003e\n \u003cp\u003eGP regular locum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"82.6955074875208%\" valign=\"top\"\u003e\n \u003cp\u003eA practitioner that provides temporary cover in the absence of regular practitioners on a fairly predictable or consistent basis. Those working on less predictable patterns are referred to as \u0026lsquo;ad hoc locums\u0026rsquo;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.3044925124792%\" valign=\"top\"\u003e\n \u003cp\u003eGP retainer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"82.6955074875208%\" valign=\"top\"\u003e\n \u003cp\u003ePractitioners considering leaving the profession that are supported by financial and educational resources to remain in clinical practice.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.3044925124792%\" valign=\"top\"\u003e\n \u003cp\u003eSalaried GP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"82.6955074875208%\" valign=\"top\"\u003e\n \u003cp\u003eA contracted practitioner employed by a practice that receives a set salary.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.3044925124792%\" valign=\"top\"\u003e\n \u003cp\u003eGP ST3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"82.6955074875208%\" valign=\"top\"\u003e\n \u003cp\u003eDoctors in their third year of specialty GP training.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.3044925124792%\" valign=\"top\"\u003e\n \u003cp\u003eGP joiner\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"82.6955074875208%\" valign=\"top\"\u003e\n \u003cp\u003eNew doctors joining practices providing NHS services as fully qualified GPs after completing specialty training \u0026ndash; this includes partners, salaried GPs and regular locums.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSource: Authors.\u003c/p\u003e\n\u003cp\u003eDrawing from the existing literature on GP registrars in the UK\u0026nbsp;[19,20], our starting hypothesis was that there is a substantial loss in workforce capacity caused by many doctors reaching the end of their training and then either not participating in NHS work, or, if joining the NHS workforce, not working full-time. We therefore set out to analyse the changing transition rates, from the third year of GP training to joining the fully qualified GP workforce, across the five years to 2023. The study covers two aspects of the transition of GP ST3s in NHS GP services:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003ethe proportion of GP ST3s appearing in the NHS GP workforce dataset as fully qualified GPs working in partner, salaried or regular locum[1] roles \u003cem\u003e(joiner rates)\u003c/em\u003e; and\u003c/li\u003e\n \u003cli\u003ethe average contracted hours of joiners, as a proportion of a typical full-time contract \u003cem\u003e(participation rates)\u003c/em\u003e.\u0026nbsp;\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eWe first explored descriptively the available quantitative data; we then complemented descriptive statistics with statistical modelling to provide evidence of association between the components for any trends. We sought to explore the effects of different behaviours of new cohorts completing training (so called \u003cem\u003ecohort effect\u003c/em\u003e) and the underlying change in landscape which might affect joiner and participation rates, including during the Covid-19 pandemic (\u003cem\u003eperiod effect\u003c/em\u003e).\u003c/p\u003e\n\u003ch2\u003eData sources\u003c/h2\u003e\n\u003cp\u003eThe data on joiner rates \u0026ndash; used in the descriptive analysis and statistical modelling \u0026ndash; were extracted from publicly available datasets published by NHS Digital, now part of NHS England, and were reported quarterly from September 2018 to December 2023. A dataset tracking 14,325 GP ST3s in England into fully qualified GP roles was used, with breakdowns by gender and country of qualification [22].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor participation rates, data on 21,293 fully qualified GP joiners in England was analysed, using the age and gender breakdowns of the GP ST3 practice-level data\u0026nbsp;[23]. Data on participation rates were taken annually from September 2017 to December 2023\u0026nbsp;[23].\u003c/p\u003e\n\u003ch2\u003eData analysis\u003c/h2\u003e\n\u003cp\u003eFor the descriptive analysis (reported in Table 2), joiner rates \u0026ndash; and relative risks \u0026ndash; were calculated, disaggregated by cohort, gender and country of primary medical qualification. Participation rates among fully qualified practitioners joining the workforce (reported in Table 3) were calculated by dividing full-time equivalent by headcount number. These participation rates were adjusted (to reduce the influence of participation rates of those re-joiners rather than those directly from the domestic training pipeline) using GP ST3 age and gender breakdowns of those in their last year in a GP training post to estimate the average level of participation for each cohort joining the GP workforce from a third year training post.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor the statistical modelling, we used generalised linear mixed-effects models to make statistical inferences about how our model predictors influenced the number of joiners in a given period. Our modelling framework is also known as a Hierarchical Age-Period-Cohort-Cross-Classified Random Effects Model, which can be used for data that is classified by age or time across multiple time periods and cohorts [24]. We included fixed effects for the time in months between GP ST3s last seen in specialty training and taking up a fully qualified GP role (referred to as \u0026lsquo;duration\u0026rsquo;), month of the year last seen in specialty training (to account for seasonality around reasons for leaving), and included random effects for cohort (the quarter and year in which doctors were last seen in specialty training) and period (the quarter and year at which doctors returned as a fully qualified GP) (Appendix 2, Equation i). In some versions of the model (as flagged in the results) we also included fixed effects to capture demographic details around gender and country of qualification (UK and non-UK) (Appendix 2, Equation ii). Analysis was conducted in RStudio 4.3.2 and Microsoft Excel.\u003c/p\u003e\n\u003cp\u003eTo quantify the relationship between the fixed effects and the likelihood of joining the fully qualified GP workforce, we presented odds ratios with 95% confidence intervals at the 5% significance level. We extracted the random effect components of our models, which were presented as conditional log odds with 95% confidence intervals for both the cohort and period effects (see Appendix 2 for further details on statistical modelling).\u003c/p\u003e\n\u003cdiv id=\"ftn1\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eThe results section starts with a description of the doctor population covered by the data, before giving a descriptive summary of variation and trends in joiner rates and then participation rates. We then cover the findings from the exploratory statistical modelling.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAcross the 21 cohorts, between September 2018 and September 2023, 14,325 doctors left their final year of GP training (GP ST3s). Our findings show that the GP training pipeline is expanding; the number at the end of training increased over time with 2,363 doctors leaving their final year of training in the year to June 2019 compared to 3,358 in the corresponding period four years later. Around three-fifths (61.4%) of GP ST3s were female, and two-thirds (67.1%) gained their primary medical qualification in the UK with the remainder from EEA (4.4%) and elsewhere (28.5%).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFewer than three-in-five (57.5%; 8,237) of these doctors were identified in the NHS GP workforce subsequent to finishing training as a fully-qualified GP by December 2023 while the remaining 6,088 have yet to be identified in the data. By displaying the proportion who have joined the NHS in relation to months elapsed since that cohort left their ST3 year, we can visualise the variation in the likelihood of different GP ST3 cohorts joining at various times after leaving training (Figure 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFigure 1: Progression rates of GPST3s joining the NHS GP workforce\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSource: NHS England \u0026ndash; Tracking GPs in training into fully-qualified general practice roles (2024).\u003c/p\u003e\n\u003cp\u003eExcluding those recent cohorts for which insufficient time has elapsed for them to be captured within the timeframes, of those doctors in their third year of training since 2018, around a third (34.3%) had taken up a fully qualified GP role in NHS general practice six months after finishing training rising to 47.5% within one year, 62.2% within two years, and 70.8% within three years.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThese joiner rates were not consistent across cohorts or characteristics (Table 2). For example, overall doctors with a primary medical qualification from outside the UK were less likely to transition to fully-qualified NHS GP roles within 6 months (-3.4 percentage points; unadjusted relative risk (RR) 0.91, 95% CI (confidence interval) 0.86 \u0026ndash; 0.95) with the disparity increasing over a two-year period (-11.7 percentage points; RR 0.82, CI 0.79 \u0026ndash; 0.86).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBoth UK and non-UK trained male GP ST3s were less likely to join within a two-year timeframe compared to female GP ST3s (-4.9 percentage points; RR 0.92, CI 0.89 \u0026ndash; 0.96). Male non-UK trained GP ST3s seem to have the lowest overall joining rates at two years (RR 0.89, CI 0.69 \u0026ndash; 0.87).\u003c/p\u003e\n\u003cp\u003eSince around 2021, there appears to have been a decline in the proportion of GP ST3s taking up fully-qualified GP roles in NHS general practice services. We found 34.1% of GP ST3s in the year to June 2019 took up a fully-qualified role within 6 months, with this proportion increasing for the cohort who left training the following year (39.4%, RR 1.15, CI 1.07-1.24) before declining. The recent two annual cohorts (those leaving in the year to June 2022 and to June 2023) appear to have generally lower joiner rates although these results were not always statistically significantly different to the baseline (year to June 2019). We present a visualisation of joiner rates disaggregated by region of qualification and gender in Figure 3 in Appendix 1. \u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eResults from generalised linear mixed-effects models\u003c/h2\u003e\n\u003cp\u003eThe findings from the statistical modelling support the previously described findings around associations between joiner rates and demographics. Nearly all of the fixed effects were significant predictors in how likely GP ST3s were to join the fully qualified NHS GP workforce. Male GP ST3s were less likely to join than female GP ST3s (Odds ratio, OR 0.94, CI 0.89 \u0026ndash; 0.98), while those who studied medicine in the UK were more likely to join than those who trained outside of the UK but took up a specialty training post in England (OR 1.20, CI 1.14 \u0026ndash; 1.27) (Figure 4, Appendix 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe also found an association between when in the year GP ST3s left their training and their likelihood of joining the NHS. Relative to those last seen in their third year of specialty training in the three months to December, those last seen in three months to June were more likely to join as a fully qualified GP (OR 1.19, CI 1.04 \u0026ndash; 1.37), but there was no significant difference in the likelihood of GP ST3s joining among those last seen in the three months to March (OR 0.91, CI 0.78 \u0026ndash; 1.06) or September (OR 0.90, CI 0.78 \u0026ndash; 1.04). As expected, our analysis also showed that the odds of joining increased at a decreasing rate as the length of time between training and acquiring a fully qualified role increased (OR 1.09, CI 1.07 \u0026ndash; 1.10).\u003c/p\u003e\n\u003cp\u003eWe identified a significant effect among some cohorts. After adjusting for duration and seasonality, GP ST3s who left specialty training in the three months to March 2020 were most likely to join the fully qualified workforce, while those who left specialty training in the three months to September 2023 were least likely to join (Figure 5, Appendix 2). After adjusting for gender and country of qualification, some differences persisted including significantly lower joiner rates for the cohort leaving in the three months to June 2021 and higher rates among those last seen in specialty training in three months to March 2020 and to September 2020 (Figure 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe also identified a significant \u0026lsquo;period effect\u0026rsquo; with apparent differences in the likelihood of GP ST3s joining the NHS in a fully qualified role at a particular point in time. Specifically, after adjustments for duration and seasonality effects, doctors were least likely to join in the three months to March 2020 and most likely to join in the subsequent three months (to June 2020) (Figure 6, Appendix 2). The differences persisted even after adjusting for demographic factors for gender and country of qualification (Figure 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;2: Joiner rates at 6 and 24 months after leaving training (unadjusted)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eJoined within 6 months\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eJoined within 24 months\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNumber leaving \u0026ge; 6 months ago (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e% identified in fully-qualified NHS role\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRelative risk (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNumber leaving \u0026ge; 24 months ago (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e% identified in fully-qualified NHS role\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRelative risk (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eAll\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13,601\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8,463\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e62.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eDemographics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUK trained\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAll\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9,220 (67.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35.4%\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e(ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6,106 (72.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e65.4%\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e(ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNon-UK trained\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAll\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4,381 (32.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e32.0%\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003cp\u003e(0.86\u0026ndash; 0.95)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2,357 (27.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e53.7%\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003cp\u003e(0.79 \u0026ndash; 0.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAll\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8,288 (60.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e33.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e(ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5,289 (62.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e64.0%\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e(ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAll\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5,313 (39.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35.3%\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.05\u003c/p\u003e\n \u003cp\u003e(1.00 \u0026ndash; 1.10)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3,174 (37.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e59.1%\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003cp\u003e(0.89 \u0026ndash; 0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eUK trained\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6,018 (44.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35.2%\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e(ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4,043 (47.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e66.6%\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e(ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3,202 (23.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35.7%\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.02\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.93 \u0026ndash; 1.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2,063 (24.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e63.1%\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.95\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.87 \u0026ndash; 1.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eNon-UK trained\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2,270 (16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29.7%\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.84\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.76 \u0026ndash; 0.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1,246 (14.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e55.6%\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.83\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.75 \u0026ndash; 0.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2,111 (15.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34.5%\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.98\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.89 \u0026ndash; 1.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1,111 (13.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e51.6%\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.89\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.69 \u0026ndash; 0.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eYear cohort left training\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eYear to June 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2,355 (17.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34.1%\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e(ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2,355 (27.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e62.2%\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e(ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eYear to June 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2,375 (17.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39.4%\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.15\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.07-1.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2,375 (28.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e66.9%\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.08\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(1.03 \u0026ndash; 1.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eYear to June 2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2,762 (20.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35.7%\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.04\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.97 \u0026ndash; 1.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2,762 (32.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e60.5%\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.97\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.93 \u0026ndash; 1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eYear to June 2022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2,751 (20.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31.7%\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.93\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.86 \u0026ndash; 1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e971 (11.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e55.4%\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.89\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.84 \u0026ndash; 0.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eYear to June 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3,358 (24.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31.8%\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.93\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(0.86 \u0026ndash; 1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003en/a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003en/a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003en/a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNotes: \u003csup\u003ea\u003c/sup\u003e Data cover cohort leaving ST3 in 6-months to December 2021.\u003c/p\u003e\n\u003cp\u003eFigure 2: Likelihood (log odds) of GP ST3s joining the NHS fully qualified GP workforce by year of GP ST3 training, by month and year of leaving GP ST3 training (cohort effect) and by date of joining the NHS workforce (period effect) , adjusting for duration, gender, country of qualification and seasonality\u003c/p\u003e\n\u003cp\u003eSource: NHS England \u0026ndash; Tracking GPs in training into fully-qualified general practice roles (2024).\u003c/p\u003e\n\u003ch2\u003eParticipation rates\u003c/h2\u003e\n\u003cp\u003eAs well as joiner rates, we also explored differences in \u0026lsquo;participation rate\u0026rsquo; which relates to the contracted hours of joiners. In the year to December 2023, the average participation \u0026ndash; the extent to which staff are employed on a full-time contract \u0026ndash; of fully qualified GP joiners was 64%. When breaking participation down by five-year age category among those who joined between 2017-18 and 2022-23, participation varied from 47% among GPs aged 65 and over to 73% among those under 30. Average participation rates are lower for female GPs (60.9%).\u003c/p\u003e\n\u003cp\u003eIf it is assumed that new GP joiners follow the age and gender distribution of those in their third year of GP training, then the participation rate would be in the region of 66% in 2022-23. These levels do vary to a degree from year-to-year but were similar to those seen in the baseline year, five years\u0026rsquo; prior (67%) (Table 3).\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;3: Frequency and participation rate of new fully qualified GPs joining the workforce by age, gender and year of joining, 2017-18 to 2022-23\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003eNumbers joining (headcount)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.816326530612244%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eAverage participation, % full-time contract\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003eAll\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e21,293\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.816326530612244%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e64.1% (66.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.816326530612244%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e13,258\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.816326530612244%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e60.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e8,035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.816326530612244%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e69.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.816326530612244%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003eUnder 30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e1,124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.816326530612244%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e72.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e30-34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e6,993\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.816326530612244%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e66.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e35-39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e5,032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.816326530612244%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e62.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e40-44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e3,170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.816326530612244%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e61.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e45-49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e2,085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.816326530612244%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e63.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e50-54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e1,320\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.816326530612244%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e64.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e55-59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e880\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.816326530612244%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e62.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e60-64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e428\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.816326530612244%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e54.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e65 and over\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.816326530612244%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e47.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003eYear joined\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" valign=\"top\"\u003e\n \u003cp\u003eAge-gender adjusted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e2017-18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e3,291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" valign=\"top\"\u003e\n \u003cp\u003e64.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" valign=\"top\"\u003e\n \u003cp\u003e67.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e2018-19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e4,022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" valign=\"top\"\u003e\n \u003cp\u003e63.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" valign=\"top\"\u003e\n \u003cp\u003e66.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e2019-20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e3,787\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" valign=\"top\"\u003e\n \u003cp\u003e62.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" valign=\"top\"\u003e\n \u003cp\u003e64.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e2020-21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e3,425\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" valign=\"top\"\u003e\n \u003cp\u003e64.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" valign=\"top\"\u003e\n \u003cp\u003e67.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e2021-22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.591836734693878%\" valign=\"top\"\u003e\n \u003cp\u003e3,075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" valign=\"top\"\u003e\n \u003cp\u003e66.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\" valign=\"top\"\u003e\n \u003cp\u003e69.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003e2022-23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.591836734693878%\"\u003e\n \u003cp\u003e3,693\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\"\u003e\n \u003cp\u003e63.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.408163265306122%\"\u003e\n \u003cp\u003e65.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSource: NHS England \u0026ndash; General Practice Workforce (2024).\u0026nbsp;[23]\u003c/p\u003e\n\u003cp\u003eNote: Due to missing data values, some demographic breakdowns may not sum the total number of joiners. Age-gender adjustments to participation rates were based on the composition of ST3 GPs in the same year that the fully qualified GP joiner data relate to. Since most GPs will not take up a fully qualified role within a year of completing training, these rates should be interpreted with caution.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eWhile the\u0026nbsp;GP workforce equation has often been characterised in the literature as a \u0026lsquo;recruitment or retention crisis\u0026rsquo;\u0026nbsp;[16,25,26], our paper focuses on the critical issue of conversion of GP training numbers to NHS GP joiners in England.\u0026nbsp;The leak in the pipeline from training through to participation in the NHS workforce as fully-qualified GPs has been highlighted previously\u0026nbsp;[18];\u0026nbsp;exploiting newly published data, we explored the nature of the challenge in greater depth.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur analysis of GP ST3s\u0026rsquo; NHS career progression highlights a substantial attrition rate in the GP workforce model; of those doctors in their final stage of training since 2018, fewer than two-thirds (62.2%) had taken up a fully qualified GP role in NHS general practice within two years. This trend in recent years appears to have worsened, as little more than half (55.4%) of those that left their third year of training between June and December 2021 had taken up fully-qualified NHS GP roles within two years and by December 2023. Some demographics display especially low joiner rates, particularly males with a primary medical qualification from outside the UK, of which only 51.6% leaving their third year of training appear to take up fully qualified roles in NHS general practice within 2 years.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur exploratory statistical analysis also provides some evidence that certain cohorts of GP ST3s were more likely to join as fully-qualified GPs (such as those that left in 2020) and at certain periods of time newly qualified doctors were more likely to be recruited. For example, the three months to June 2020 saw significantly higher joiner rates relative to average, though this may be an artifact of Covid-19 with a catch-up in recruitment after lower rates in the previous 3 months as the pandemic first hit.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe impact of these low joiner rates on overall NHS capacity are compounded by relatively high but fairly stable levels of less than full time working. The average contracted hours of GPs joining the workforce are around two-thirds of a full-time contract. Rates are lower for female GPs (60.9%), and broadly decline by age. Taking the joiner rates and participation rates together, it means that, for every 10 doctors leaving the third year of GP training, the NHS will secure around 4 full-time equivalent fully qualified GPs within 2 years, excluding those that might be working as ad-hoc locums. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur findings need to be interpreted with a degree of caution, as we acknowledge data limitations, and our results will need to be triangulated with other workforce data sources. \u0026nbsp;For example,\u0026nbsp;our analysis did not include ad-hoc GP locums within the NHS because this group were not captured within the data; however, separate analyses suggest that around a third of GP ST3 leavers not taking up substantive NHS GP roles may have worked as an ad-hoc locum. The data do also not pick up, for instance, GPs working exclusively in certain settings such as out of hours services, or A\u0026amp;E streaming\u0026nbsp;[22]. This may have underestimated conversion rates to GP roles but given the importance of \u0026ndash; and current challenges around \u0026ndash; a sustainable supply of substantive GP roles in NHS general practices, the rates we present remain of significant policy importance. Our reported participation rates may also be affected by this lack of information on, for example, ad-hoc locum sessions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe consider that several supply as well as demand-side factors might be responsible for such delays in joining the primary care medical workforce. On the one hand, it is fairly established that GP jobs have become increasingly complex and demanding, particularly after the recent pandemic\u0026nbsp;[27]. A questionnaire of 25 European countries in 2015 showed that nations where GPs undertook more than 25 direct patient consultations per day experienced more problems in GP retention and recruitment\u0026nbsp;[28]. The definition of clinical sessions in existing NHS GP contracts and the implementation of such contracts often underestimate the actual GP workload\u0026nbsp;[27]. By experiencing their tutors\u0026rsquo; workload, it does not seem unreasonable that trainees may be put off from pursuing a full-time career in general practice[19]. Similarly, doctors might delay committing to a substantive GP role where contracts do not sufficiently capture additional, non-clinical activities such as education, management and research which may be better captured within secondary care specialist consultant contracts.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAt the same time, there are reports it might have become increasingly difficult for GP practices to contract newly-trained GPs because of funding shortfalls at different levels\u0026nbsp;[29]. The introduction of the Additional Roles Reimbursement Scheme (ARRS) in 2019 meant that practices could benefit from additional staff at no direct cost to their practice and resulted in an additional 22,000 staff being recruited. The ARRS scheme however does not include salaried GPs. Therefore, the relative costs to practices of employing GPs combined with wider financial pressures within general practice may have resulted in fewer GP job opportunities\u0026nbsp;[30].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur work carries important policy implications for governments in the UK as well as in other European countries. First of all, if one-third of recently trained specialists these days fail to join the primary care workforce, this means that more GPs need to be trained or retained to meet the increasing health needs and demand for healthcare services from an aging population, exacerbating an already complex planning exercise\u0026nbsp;[31].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSecondly, the root causes for the identified leak need to be fully understood and tackled, with a view to adequately staffing primary care services. \u0026nbsp; We identified a need for additional information on variety and intensity of roles that GPs undertake within the NHS, as well on vacancies (both filled and unfilled) which is particularly problematic in light of recent reports of GPs being made redundant or unable to find work\u0026nbsp;[16,32]. Such data would allow the necessary analyses to gain a greater understanding of the nature and reasons for joiner and participation rates. Government has sought to attract GPs into the NHS through a range of schemes including GP International Induction Programme, improved visa sponsorship arrangements, GP Fellowship Programme, the Supporting Mentors Scheme and the New to Partnership Payment\u0026nbsp;[18]. However, the continuation of funding for several of these initiatives is uncertain. Some areas find it more challenging to attract GPs. These are typically more deprived and remote locations that are not regularly used for medical school placements and are therefore less familiar to newer doctors\u0026nbsp;[33].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe findings of particularly low levels of overseas doctors completing GP training going on to take up fully qualified GP roles is particularly important in view of the increasing proportion of IMG trainees. Induction and training support schemes are attempting to address the differential exam attainment of IMGs in the GP licensing exams [34], and policies have been introduced to remove potential barriers to IMG GP trainees joining the NHS workforce once they have completed their training. The effectiveness of such initiatives needs ongoing monitoring.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eAs the senior medics within their services, GPs have a pivotal role for the sustainability of the primary care system. However, in England there have been repeated failures to meet the ambitions to increase the number of fully-qualified GPs and, instead, numbers have fallen worryingly. Much attention has been paid to the recruitment of trainee GPs; however, our analysis shines a light on a critical part of the workforce model namely the domestic training pipeline and, specifically, the transition from ending training to joining the NHS.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUsing published data, we estimated that for every 10 doctors leaving training around 4 fully-qualified full-time equivalent GPs join NHS services within two years \u0026ndash; and we provide evidence of differences between demographics (particularly lower joiner rates for overseas trained medics), differences in behaviours of doctors leaving over time (cohort effect), and different labour market conditions over time (period effect).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFurther work is also suggested. The differences in career behaviours between demographics appear to be changing over time and this should be studied further. Conversion rates for GPs should be compared to rates for other specialties, to identify whether this issue is unique to general practice or is more common across other areas of medicine. Given the importance of GP retention to the sustainability of GP services, national and regional bodies must act fast to better understand the factors influencing this apparent suboptimal transition from training to joining the NHS workforce and identify and implement urgent solutions.\u0026nbsp;\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFTE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003efull-time equivalent\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGP ST3\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003edoctor in third year of GP specialty training\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003egeneral practitioner\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNHS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNational Health Service in England\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThis study explored publicly available data. Additional results from our analysis can be made available for reasonable requests.\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eWe would like to thank Cono Ariti for his statistical advice on this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis study received the financial support of the UK Medical Research Council and Newton Fund [grant number MRC/R022747/1].\u003c/p\u003e\n\u003cp\u003eEthics declaration\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHanson K, Brikci N, Erlangga D, Alebachew A, Allegri MD, Balabanova D, et al. The Lancet Global Health Commission on financing primary health care: putting people at the centre. The Lancet Global Health. 2022;10:e715\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBi Y-N, Liu Y-A. 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Br J Gen Pract. 1999;49:829\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcPake B, Scott A, Edoka I. Analyzing Markets for Health Workers: Insights from Labor and Health Economics [Internet]. The World Bank; 2014 [cited 2023 Mar 27]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://elibrary.worldbank.org/doi/abs/\u003c/span\u003e\u003cspan address=\"https://elibrary.worldbank.org/doi/abs/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1596/978-1-4648-0224-9\u003c/span\u003e\u003cspan address=\"10.1596/978-1-4648-0224-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRusso G, Cassenote AJF, Guilloux AGA, Scheffer MC. 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Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.pulsetoday.co.uk/analysis/pulse-on-workforce/how-do-uk-medical-school-places-translate-to-fully-trained-gps/\u003c/span\u003e\u003cspan address=\"https://www.pulsetoday.co.uk/analysis/pulse-on-workforce/how-do-uk-medical-school-places-translate-to-fully-trained-gps/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBritish Medical Association. Survey reveals extent of pressures on GP registrars [Internet]. BMA News. 2023 [cited 2024 May 2]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bma.org.uk/news-and-opinion/survey-reveals-extent-of-pressures-on-gp-registrars\u003c/span\u003e\u003cspan address=\"https://www.bma.org.uk/news-and-opinion/survey-reveals-extent-of-pressures-on-gp-registrars\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDale J, Russell R, Scott E, Owen K. Factors influencing career intentions on completion of general practice vocational training in England: a cross-sectional study. BMJ Open. 2017;7:e017143.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNHS England. Tracking GPs in training into fully-qualified general practice roles [Internet]. NHS England Digital. 2024 [cited 2024 May 2]. 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Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.rcgp.org.uk/getmedia/155e72a9-47b9-4fdd-a322-efc7d2c1deb4/retaining-gp-workforce-report.pdf\u003c/span\u003e\u003cspan address=\"https://www.rcgp.org.uk/getmedia/155e72a9-47b9-4fdd-a322-efc7d2c1deb4/retaining-gp-workforce-report.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChilvers R, Richards SH, Fletcher E, Aylward A, Dean S, Salisbury C, et al. Identifying policies and strategies for general practitioner retention in direct patient care in the United Kingdom: a RAND/UCLA appropriateness method panel study. BMC Family Practice. 2019;20:130.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarnard R, Spooner S, Hubmann M, Checkland K, Campbell J, Swinglehurst D. The hidden work of general practitioners: An ethnography. Social Science \u0026amp; Medicine. 2024;350:116922.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcCarthy M. Sustainable general practice: looking across Europe. Br J Gen Pract. 2016;66:36\u0026ndash;36.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUngoed-Thomas J, Tapper J. Revealed: locum GPs in England can\u0026rsquo;t find work as surgeries buckle under patient demand. The Observer [Internet]. 2024 May 12 [cited 2024 May 15]; Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.theguardian.com/society/article/2024/may/12/england-locum-gps-doctors-work-surgeries-british-medical-association\u003c/span\u003e\u003cspan address=\"https://www.theguardian.com/society/article/2024/may/12/england-locum-gps-doctors-work-surgeries-british-medical-association\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKaffash J. Number of GP vacancies advertised almost halves in a year [Internet]. Pulse Today. 2023 [cited 2024 May 15]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.pulsetoday.co.uk/news/workforce/number-of-gp-vacancies-advertised-almost-halves-in-a-year/\u003c/span\u003e\u003cspan address=\"https://www.pulsetoday.co.uk/news/workforce/number-of-gp-vacancies-advertised-almost-halves-in-a-year/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWaters A. No point in increasing GP recruitment without focus on retention, say leaders. BMJ. 2022;379:o2833.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNHS England. GP Earnings and Expenses Estimates, 2021/22 [Internet]. NHS England Digital. 2024 [cited 2024 May 2]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://digital.nhs.uk/data-and-information/publications/statistical/gp-earnings-and-expenses-estimates/2021-22\u003c/span\u003e\u003cspan address=\"https://digital.nhs.uk/data-and-information/publications/statistical/gp-earnings-and-expenses-estimates/2021-22\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArmstrong MJ, Wildman JM, Sowden S. How to address the inverse care law and increase GP recruitment in areas of socioeconomic deprivation: a qualitative study of GP trainees\u0026rsquo; views and experiences in the UK. 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Br J Gen Pract. 2023;73:e284\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Footnotes","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e We did not include \u0026lsquo;ad-hoc\u0026rsquo; GP locums, (locum or sessional GPs who typically work briefly at practices, such as a single one-off session, to cover for short-term or unexpected absences) because information about them is captured in a different way to the rest of the workforce.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"human-resources-for-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"hrhe","sideBox":"Learn more about [Human Resources for Health](http://human-resources-health.biomedcentral.com)","snPcode":"12960","submissionUrl":"https://submission.nature.com/new-submission/12960/3","title":"Human Resources for Health","twitterHandle":"@HRH_Journal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Physicians, general practitioners, family doctors, registrars, specialty training, medical students, recruitment, NHS, trainees, workforce, retention","lastPublishedDoi":"10.21203/rs.3.rs-4565547/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4565547/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground\u003c/p\u003e\n\u003cp\u003eAs the senior medics within primary care services, general practitioners (GPs) have a pivotal role within the National Health Service (NHS). Despite several commitments made by government to increase the number of GPs in England, the level has consistently fallen. Much attention has been paid to recruitment of trainee GPs and overall retention, whereas this study sought to examine the specific transition from ending training to joining the NHS.\u003c/p\u003e\n\u003cp\u003eMethods\u003c/p\u003e\n\u003cp\u003eThe study used aggregated, published administrative data to examine rates at which 14,302 doctors leaving their third year of specialty training (GP ST3s) became fully qualified NHS GPs between 2018 and 2023. We separately analysed average levels of part-time working of those joining the NHS from 21,293 fully qualified joiners in England between 2017 and 2023. We calculated joiner and participation rates and used generalised linear mixed-effects models to explore possible demographic, period and cohort effects.\u003c/p\u003e\n\u003cp\u003eResults\u003c/p\u003e\n\u003cp\u003eOf those doctors leaving their third year of training since 2018, around a third (34.3%) had taken up a fully qualified GP role in NHS general practice six months after finishing training, rising to 47.5% within one year, and 62.2% within two years. Average estimated participation rates of joiners seemed to remain consistent at about 65-69% of a full-time contract between 2017 and 2023.\u003c/p\u003e\n\u003cp\u003eJoiner rates were lower for doctors with a primary medical qualification from outside the UK and, over a two-year timeframe, both UK and non-UK trained male GP ST3s. Our statistical modelling suggests that there is a significant ‘period effect’ in connection to the recent Covid-19 pandemic, with apparent differences in the likelihood of GP ST3s joining the NHS in a fully-qualified role at certain points in time, and an effect among some cohorts, with doctors who left specialty training in specific periods having significantly different joiner rates.\u003c/p\u003e\n\u003cp\u003eConclusion\u003c/p\u003e\n\u003cp\u003eThe GP pipeline is expanding, but we find no evidence that retention of newly trained GPs is improving. We discuss possible factors for such attrition, from barriers to hiring new doctors, to their diminishing interest in joining the NHS. More work is needed to further explore the changing career behaviours of subsequent cohorts and demographics of doctors completing GP training.\u003c/p\u003e","manuscriptTitle":"A hole in the bucket? Exploring England’s retention rates of recently qualified GPs","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-02 10:45:15","doi":"10.21203/rs.3.rs-4565547/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-10-15T11:31:04+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-09T21:48:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"160083516876282955664470419193739643359","date":"2024-10-07T02:48:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"186065995081836605049254492226857233127","date":"2024-08-07T09:07:13+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-05T15:45:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"105975297445718261504424758934885445152","date":"2024-07-29T12:12:43+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-20T08:21:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-15T08:13:37+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-12T01:16:46+00:00","index":"","fulltext":""},{"type":"submitted","content":"Human Resources for Health","date":"2024-06-11T16:34:20+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"human-resources-for-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"hrhe","sideBox":"Learn more about [Human Resources for Health](http://human-resources-health.biomedcentral.com)","snPcode":"12960","submissionUrl":"https://submission.nature.com/new-submission/12960/3","title":"Human Resources for Health","twitterHandle":"@HRH_Journal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9a672ac0-a2a9-438d-90f2-36cb4638b9ce","owner":[],"postedDate":"July 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-03-10T17:09:18+00:00","versionOfRecord":{"articleIdentity":"rs-4565547","link":"https://doi.org/10.1186/s12960-025-00980-x","journal":{"identity":"human-resources-for-health","isVorOnly":false,"title":"Human Resources for Health"},"publishedOn":"2025-03-03 15:56:55","publishedOnDateReadable":"March 3rd, 2025"},"versionCreatedAt":"2024-07-02 10:45:15","video":"","vorDoi":"10.1186/s12960-025-00980-x","vorDoiUrl":"https://doi.org/10.1186/s12960-025-00980-x","workflowStages":[]},"version":"v1","identity":"rs-4565547","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4565547","identity":"rs-4565547","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}