Widening access to medicine may improve general practitioner recruitment in deprived and rural communities: survey of GP origins and current place of work

The study design was a cross-sectional survey via e-mail. NHS Scotland Information Services Division holds data on all GPs contracted to work in Scottish general practices, but only holds e-mail addresses for a proportion. An email invitation which included a web-link to an online questionnaire was sent in 2010 to the 2,050 (41.8 %) GPs in Scotland for whom email addresses were available. One reminder email was sent during the data collection period. It was not possible to directly compare responders and non-responders, but where possible responders were compared to all Scottish GPs in order to inform a judgement about representativeness. For this purpose, aggregate data on the age and sex of GPs in 2010 were obtained from publicly available sources [35]. Publicly available data on practice location were only available for March 2015 [36].

Outcomes: participants were asked to provide the identifier code for the practice in which they currently worked in order that it could be classified as being either in a socioeconomically deprived or remote setting using NHS Scotland centrally held data. Highly deprived practices were defined as those 80 (7.9 %) Scottish practices where more than 50 % of the registered patient population lived in the most deprived 15 % of Scottish postcodes (a measure used by the Scottish Government to identify and target the most deprived areas). Remote practices were defined as those 191 (18.9 %) Scottish practices where the majority of registered patients live 30 min or more drive time from an urban area of >10,000 people (part of the Scottish Executive Urban–rural Classification [SUERC], also a measure used by Scottish Government for planning purposes) [16].

Explanatory variables: socioeconomic status at the time of application to medical school was assessed using the Office for National Statistics self-coded version of the National Statistics Socio-Economic Classification (NS-SEC) as it applied to their parents or guardians. For Scottish residents, postcode at time of application to medical school was used to define SEURC category. Participants also provided data about their age, sex and year of graduation.

Analysis used PASW Statistics version 17 (IBM). Descriptive analysis used cross-tabulation to examine the distribution of GP characteristics in relation to the two outcomes (working in a remote practice; working in a deprived practice). Binary logistic regression was used to examine univariate and adjusted associations between GP characteristics and the two outcomes. Model fitting was sequential based on the most significantly associated individual variable, with model fit assessed using the Akaike Information Criteria to ensure fitting the most parsimonious model given the small number of outcomes available for evaluation.

The NHS Tayside Research Ethics Service evaluated the study and advised that it did not need full Research Ethics Committee review (reference 10/GA/064).

This study found that childhood background in terms of parental socioeconomic status and more remote residence was associated with subsequent practice in more deprived and more remote locations respectively. Both relationships appeared to have a dose–response pattern, in that the ‘more rural’ their background or ‘more deprived’ their upbringing was in terms of SES, the more likely they were to work in a setting that mirrored this. However, the only statistically significant effects were seen for the most extreme categories of rurality or SES, although the relatively small size of the study means that confidence intervals for other categories are wide and overlapping. However the proportion of respondents with parents with lower socioeconomic status was small and the majority of GPs working in the most deprived practices still had parents with professional or managerial occupations (reflecting that three-quarters of respondents had such a background). GPs from the other UK countries were also more likely to work in remote practices, possibly explained by doctors moving to Scotland in part because of a preference for rural life. GPs who did not originate from the UK were not more likely than average to work in rural areas. The findings are therefore consistent with the argument that increased contextual selection of students might improve recruitment to under-served communities.

This cross sectional study used retrospective data to estimate socio-economic class and remoteness at the time of application to medical school. It is therefore open to a number of biases, especially given the relatively low response rate and our limited ability to compare responders and non-responders (although responders were similar to all Scottish GPs with the exception of being more likely to be middle-aged, which may reflect that younger GPs are less likely to be partners and therefore less likely to have a permanent e-mail on record). It is also important to note that the area an individual lived or their SES at point of entry to medical school may differ from the experience they had while growing up. However the distribution of respondents’ socioeconomic status at the time they entered medical school is strikingly similar to that of current medical school entrants [3]. Given the limited numbers of doctors either from very deprived or remote areas or working in such areas, some analytic subgroups are small and corresponding confidence intervals wide. Thus, further evidence is clearly needed and long-term prospective studies are ideally required to investigate this more fully as many other factors, such as type of school or medical school attended may also be important, as may recall bias.

The relevant existing literature concerning widening access primarily originates from the USA, Canada and Australia and it is hard to know how transferrable the findings may be to the UK given the differences in health care systems, culture and employment patterns. Our finding that doctors from less affluent backgrounds are more likely to serve highly deprived communities is consistent with US findings [21, 25, 37], and the association between rural background and subsequent remote practice is also consistent with international evidence [23–30]. A recent National Audit Office report highlighted that in 2008, despite an increase in GP numbers of 5,700 over the preceding 10 years, 65 % of Spearhead Primary Care Trusts (areas with poor health outcomes) had fewer GPs per head of population than the national average [33]. This mismatch of need and GP supply indicates that enhancing general practice for deprived communities should clearly be a priority [38], and a key first step in that is improving GP recruitment in these areas to ensure that there are adequate numbers of GPs working in such areas. The literature concerning rural practice should be considered with caution in relation to the UK, as few areas would be considered remote by international standards and the nature of deprivation and resource allocation very localised [39]. We could not locate any relevant peer reviewed literature, suggesting this may also be an area worthy of further study. Research suggests that many GPs remain in the same geographical region as their place of training [40], so considering how training programs can champion practice in rural or deprived areas may be one approach to enhance recruitment and retention. Although our findings may have relevance to recruitment or workforce planning, it is important at an individual level not to presume thatphysicians from a low SES or rural background would wish to, or should be expected to work in a related area.

This research supports the argument that widening access to medical schools might plausibly improve GP recruitment in for under-served communities. However, if the aim is to improve recruitment of GPs to practices servicing the most deprived or most remote communities, then it is unclear whether this is best achieved by increasing recruitment of medical students from such communities, or ensuring that high-quality undergraduate and postgraduate training opportunities are available to all students and trainees in those areas. In practice, no single ‘magic bullet’ fix is likely to solve recruitment problems in the most deprived and most remote areas, and for many is less important than the promotion of social mobility and social justice. In order to understand whether widening access delivers its intended aims, longitudinal research is needed to understand how academic ability, non-academic skills, demographic and social characteristics are associated with career choice, performance and progression, and eventually quality and safety of care.