Do undergraduate general practice placements propagate the ‘inverse care law’?

ABSTRACT

Introduction

Fifty years since Dr Tudor-Hart’s publication of the ‘Inverse Care Law’, all-cause mortality rates and COVID-19 mortality rates are higher in more deprived areas. Part of the solution is to increase access and availability to healthcare in underserved and deprived areas. This paper examined how socio-economically representative the undergraduate general practice placements are in Northern Ireland (NI).

Methods

A quantitative study of general practices involved in undergraduate medical placements through Queen’s University Belfast, comparing practice lists by deprivation indices, examining both blanket deprivation and deprivation quintile trends for teaching and non-teaching practices.

Results

Deprivation data for 135 teaching practices were compared against the 323 NI practices. Teaching practices had fewer patients living in the most deprived quintiles compared with non-teaching practices. Fewer practices with blanket deprivation were involved in undergraduate medical education, 32% compared with 42% without blanket deprivation. Practices in areas of blanket deprivation were under-represented as teaching practices, 10%, compared to 14% of NI general practices that met this criterion.

Conclusion

Practices with blanket deprivation were under-represented as teaching practices. Exposure to general practice in deprived areas is an essential step to improving future workforce recruitment and ultimately to closing the health inequalities gap. Ensuring practices in high-need areas are proportionately represented in undergraduate placements is one way to direct action in addressing the ‘Inverse Care Law’. This study is limited to NI and further work is required to compare institutions across the UK and Ireland.

KEYWORDS:

• Education
• medical
• general practice
• primary care
• poverty
• health inequalities

Introduction

People living in areas of deprivation have a disproportionate burden of disease [1]; experiencing greater disease complexity, multi-morbidity and psychological problems [2]. This was further exposed during the COVID-19 pandemic with those living in the most deprived areas facing the greatest impact [3,4]. Data from the Office for National Statistics early in the pandemic [5] showed death rates from COVID-19 were twice as high in the most deprived, compared to the most affluent, deciles. Marmot and Allen [6] described the impact as ‘a clear social gradient: the more deprived the area the higher the mortality’.

Half a century ago, Tudor-Hart proposed the concept of an ‘inverse care law’; ‘The availability of good medical care tends to vary inversely with the need for it in the population served. This inverse care law operates more completely where medical care is most exposed to market forces, and less so where such exposure is reduced’ [7].

This ‘law’, whereby, those with the highest need are least likely to receive it has been the subject of much analysis over the past year [8–10]. Tudor-Hart went on to explain that medical education propagated the inverse care law, as medical students practised ‘ideal medicine under ideal conditions’ encouraging graduates to; ‘leave those who need them most and go to those who need them least’ (ibid) [7]. A similar deficit was acknowledged by the Independent Commission on the Education of Health Professionals in 2010, concluding that globally: ‘the content, organisation, and delivery of health professionals’ education have failed to serve the needs and interests of patients and populations’ [11].

Creating a proactive undergraduate medical curriculum that integrates deprivation-based practice, is crucial for the future provision of healthcare in areas of deprivation [12,13]. The General Medical Council publication Outcomes for Graduates, which sets the standards for medical curricula in the UK, requires that newly-qualified doctors should be able to recognise the effects of poverty and affluence on health, understand the impact of health inequalities, and the social determinants of health [14].

Work done by the Deep End Project in Scotland highlighted that insufficient exposure for students and trainees to medical issues in the context of areas of deprivation resulted in a lack of confidence, skills, and a reduced desire to work in such areas [15]. A systematic review on clinical placements in underserved areas showed that regardless of a medical student’s background, they were more likely to undertake a formal post in an underserved rural area following a prior student placement [16]. This extends to prospective medical students, with general practice work-experience improving prospective medical students' aspirations to pursue a career in GP [17]. Research in England showed that GP practices engaging in medical education were not necessarily representative of English general practice, being overall more rural, white and in better health [18]. A similar theme was seen in postgraduate training in Scotland, with training GP practices more likely to be in affluent areas [19]. The maxim ‘You don’t know what you don’t know’ applies: expanding students’ exposure to healthcare within areas of deprivation provides a foundational awareness in the first instance and the potential to develop an interest to work in these communities.

There are notable examples of programmes and initiatives run by individual medical schools and third-sector organisations, which aim to increase ‘exposure’ to medical care in areas of deprivation. These include the Difficult and Deprived Areas Programme (DDAP) in the North East of England [20] the work of Fairhealth in medical education [21] and the benefits in recruitment and retention through the work of the Deep End Pioneer Scheme [8]. However, there is little published information about the extent to which this is being intentionally addressed within the undergraduate curricula of UK medical schools.

In recent years, in part due to recruitment and retention issues of GPs, there has been a concerted focus on clinical experience for medical students in the context of general practice [22]. General practice in the UK and Ireland provides healthcare within bounded geographical locations to local populations often sharing a number of characteristics, among them, level of deprivation. The recently published Royal College of General Practitioners and Society for Academic Primary Care digital textbook Learning General Practice [23] provides a framework for medical students with a section dedicated to the social determinants of health. Insufficient exposure to general practice in areas of deprivation potentially sets the foundations for poor recruitment and retention of staff, further propagating the ‘inverse care law’ and worse health outcomes for those living with the highest need: the ‘inverse teaching law’.

In this work, we aimed to pose the question: ‘Do undergraduate general practice placements propagate the “inverse care law” by limiting the opportunity to experience primary healthcare in the areas of highest need, during medical school?’ and to answer the question for the Northern Ireland (NI) context.

In NI, more than 1 in 3 people (37%) live in socio-economic deprivation compared to approximately 1 in 5 in England, Scotland and Wales (18–22%) [24]. The reasons for this are complex and multifactorial, but in part due to the recent history of civil conflict and the ongoing implications for healthcare provision. The ‘Troubles’ refers to conflict spanning three decades resulting in over 3,500 deaths and 30,000 people injured [25]. This legacy is evident in the high exposure to trauma [25,26], the prevalence of ‘diseases of despair’, such as substance misuse and alcohol dependency alongside deprivation [27] and the highest suicide rate with the UK and Ireland [27].

Method

At the time of the study, Queen’s University Belfast (QUB) was the only medical school placing students in general practices, giving a unique insight across NI as a whole, through the clinical placement activity of one institution. Using the National Health Application & Infrastructure Services (NHAIS), aggregated practice-level deprivation data was collated for each GP list across NI.

The Northern Ireland Statistics and Research Agency (NISRA) Multiple Deprivation Measure 2017 was used, in which the deprivation results are published at Super Output Area (SOA) level [28,29]. There are 890 SOAs in NI. Each SOA has a population range between 1,300 and 2,800 people [30]. These are ranked 1 (most deprived) to 890 (least deprived), placing 178 SOAs in each quintile of deprivation. Individual post-codes can be translated into an SOA. The postcodes of patients registered in each practice were grouped to the quintile of deprivation as per SOA. Using these data quintiles, it was possible to derive the percentage of registered patients in each practice, living in each quintile of deprivation. This allowed for a deprivation profile of all GP practices, within Northern Ireland.

This profiling identified practices with ‘blanket deprivation’ as well as reviewing the mean percentages of patients in each quintile of deprivation. A working definition of a ‘general practice with blanket deprivation’ was chosen as a practice with more than 50% of the registered patient list living in the most deprived quintile of SOAs, as per registered patient postcodes. Using quintile of deprivation is in keeping with the NHS England and the NHS Improvement Core20PLUS5 approach of supporting health inequalities by focusing on the target population in the most deprived 20% [31]. The cut off at 50% of the patient list follows similar definition used in ‘Deep End’ work whereby the ‘Deep End’ is defined as practices with over half (50%) of the patient list in the most deprived cohort as per local indices of multiple deprivation [32]. To enhance the analysis further, the total patient means in each quintile was calculated and compared between teaching and non-teaching practices.

In March 2021, the School of Medicine at QUB had 140 practices actively engaged in hosting undergraduate medical students. These teaching practices were ranked within all 323 general practices using the NHAIS April 2020 data, providing the proportion of patients in each deprivation quintile. This permitted the identification of the number of NI GP teaching practices serving areas of ‘blanket deprivation’, as well as comparisons between percentages of patients living in each quintile of deprivation.

Results

Of the original list of 140 GP practices, 135 were matched to the NHAIS data set, three practices were duplicated on the list, and the remaining two practices did not have enough specific information to identify the exact practice, for instance, based within a health centre with multiple general practices listed at the address provided: therefore they were excluded from the research study.

Fourteen of the 135 (10.4%) general practices receiving medical students as part of their undergraduate medical educational programme were categorised as general practices with blanket deprivation. This compares to 13.6% of practices across NI that meet these criteria (Table 1).

Table 1. Breakdown of registered teaching practices by deprivation versus national average.

	QUB registered teaching practices	Northern Ireland National Comparison
More than 50% of patient list living in most deprived quintile ‘Deprived Practice’	10.4%	13.6%
Less than 50% of patient list living in most deprived quintile ‘Non-deprived Practice’	89.6%	86.4%

Dividing NI GP practices into blanket versus non-blanket deprivation, 32% of the former and 42% of the latter were involved in medical education. Analysis by patients per quintile of deprivation showed that teaching practices had, on average, fewer registered patients in the most deprived quintiles. Table 2 shows the average results. Mean average shows increased patient numbers registered to postcodes in the most affluent quintiles. Figure 1 shows the correlation, with teaching practices (TP) trending towards more patients registered in affluent postcodes and therefore least deprived quintiles 4 and 5.

Table 2. Average values for percentages of patients per deprivation quintile for teaching practices (TP) and non-teaching practices (NTP).

	Quintile 1 most deprived		Quintile 2		Quintile 3		Quintile 4		Quintile 5 least deprived
	TP	NTP	TP	NTP	TP	NTP	TP	NTP	TP	NTP
Mean	6.40%	20.60%	13.50%	21.30%	13.60%	19.70%	13.00%	20.30%	20.00%	17.90%
Mode	6.73%	4.50%	34.20%	9.00%	13.70%	12.60%	32.50%	15.80%	0.02%	0.00%
Median	9.67%	13.00%	16.70%	16.73%	14.30%	14.91%	15.70%	15.79%	12.50%	11.16%

Figure 1. The mean percentage of patients per quintile of deprivation, in teaching practices (TP) and non-teaching practices (NTP).

Discussion

We found that within Northern Ireland, the current undergraduate general practice placements allowed for some exposure to high need deprived areas, but this was not representative of general practice across Northern Ireland. Thus, it is likely propagating the ‘inverse care law’. When looking at the mean percentage of patients per deprivation quintile, non-teaching practices (NTP) corresponded more closely to the national Northern Ireland picture. This was not the case for teaching practices (TP), where patient populations had lower proportions of patients living in areas of highest deprivation (Q1–Q2). Additionally, the proportion of general practices in areas of blanket deprivation, was below that for NI as a whole, with 10% of QUB teaching practices meeting this criterion compared to the NI average of approximately 14% of practices. This is further compounded by a higher proportion of ‘non-blanket deprivation’ practices being involved in medical education (42%) compared to 32% of blanket deprivation practices.

This finding raises questions about why practices with blanket deprivation are less likely to be involved in undergraduate training. The inequity in workforce of full-time equivalent GPs in areas of deprivation, practically means there are fewer possible trainers and GP tutors [33,34]. As well as the increased work pressures and strains that working in areas of deprivation can have, GPs working in areas of deprivation have increased patient lists [34–36], increased demand for appointments [35], shorter appointments with more complexity [37] and reported higher stress among the workforce [2].

Ongoing engagement in the delivery of medical education at practice level could be an artefact of practice history with the interest, and involvement in teaching, mainly among newly-recruited GP partners. In this way, reluctance to take on teaching or a willingness to give it up due to the pressures highlighted above may mean that attrition to teaching is higher in these blanket deprivation practices.

There may also be patient factors to consider: with higher mental health co-morbidity in areas of high deprivation [35,36,38,39], it is plausible that students are less welcome in the consultations or could add to the complexity faced by the clinician. Practically, there may be factors of space availability [40], with practices in areas of blanket deprivation tending to be situated in more inner-city locations, where the premises may be smaller, with less space to host students. These factors present potential barriers in the ability of a practice in an area of blanket deprivation to host students.

We suggest possible solutions and actions to address these barriers might include (1) active recruitment of practices from areas of deprivation that have never been involved in teaching; (2) incentive schemes; (3) enabling buddying of practices to share workload. We are not aware of any such schemes. It would be incumbent on funders of clinical placements to ensure funding fairness and equity especially when comparing primary and secondary care [40], given the importance of primary care in the future of healthcare.

The next step could be to move beyond simply ensuring there is this adequate and universal coverage of general practices across the socio-economic landscape, instead exploring the extent to which the impact of deprivation is highlighted to students during their clinical placement. It would be helpful to investigate how this impacts post-graduate general practice training programmes, and whether the concept of undergraduate placements propagating the ‘inverse care law’ projects to postgraduate training.

Limitations

The study focuses on general practice placements, and the role of undergraduate primary care placements to propagate or address the ‘inverse care law’, where these high-need areas are comparatively under-doctored [34] (Table 3). It does not take into account secondary or hospital placements and how exposure to deprivation varies for undergraduates in these settings. As deprivation data in each jurisdiction is calculated differently, direct comparisons between medical schools across the UK and Ireland, should be undertaken with caution. In NI, using SOA data, deprivation data points and values are not given; therefore, this can under- or over-estimate deprivation, by way of there always being a highest and lowest decile or quintile. It is, however, broadly acknowledged that there is an increased prevalence of deprivation in NI [24], therefore likely that the involvement of practices working in areas of underserved and deprived populations is under-estimated if compared to the UK as a whole, with medical students in NI likely having a higher probability of being exposed to deprivation within the primary care setting.

Table 3. Results table data with the breakdown of each practice.

General practice	Quintile 1	Quintile 2	Quintile 3	Quintile 4	Quintile 5	>50% patients in most deprived quintile?
1	13.20%	21.76%	45.58%	11.84%	6.57%	No
2	32.62%	7.40%	22.91%	13.92%	23.12%	No
3	44.52%	15.57%	7.42%	15.84%	15.07%	No
4	0.99%	1.91%	1.87%	83.78%	11.21%	No
5	6.73%	34.16%	13.71%	32.48%	12.44%	No
6	3.40%	6.08%	1.50%	22.80%	65.87%	No
7	62.38%	8.56%	16.65%	4.00%	8.20%	Yes
8	29.56%	17.26%	3.67%	26.43%	22.73%	No
9	0.47%	45.76%	50.88%	1.36%	0.82%	No
10	26.49%	15.37%	9.72%	14.55%	33.46%	No
11	48.57%	11.85%	9.60%	10.98%	18.67%	No
12	2.97%	6.30%	26.23%	38.35%	25.48%	No
13	0.23%	1.68%	1.55%	15.72%	80.72%	No
14	3.41%	3.73%	4.72%	38.83%	48.90%	No
15	1.08%	10.52%	7.29%	17.53%	63.38%	No
16	5.24%	15.94%	14.70%	13.29%	50.52%	No
17	27.16%	20.28%	17.52%	28.51%	5.50%	No
18	48.27%	18.35%	8.78%	12.89%	9.46%	No
19	6.12%	63.09%	28.90%	1.25%	0.02%	No
20	5.05%	16.68%	20.82%	15.04%	42.24%	No
21	66.13%	4.30%	10.16%	5.88%	13.21%	Yes
22	0.36%	55.25%	35.29%	5.06%	0.11%	No
23	13.31%	13.07%	13.80%	16.66%	43.02%	No
24	9.67%	22.90%	14.65%	26.53%	26.18%	No
25	26.76%	28.76%	24.77%	19.25%	0.18%	No
26	0.50%	0.64%	0.84%	82.81%	15.04%	No
27	0.67%	37.00%	56.65%	0.62%	0.00%	No
28	32.92%	22.41%	25.11%	19.32%	0.07%	No
29	0.08%	18.85%	25.07%	55.62%	0.10%	No
30	0.03%	27.64%	14.23%	40.56%	17.33%	No
31	21.33%	23.63%	35.07%	10.46%	8.90%	No
32	5.49%	27.93%	55.34%	9.04%	0.02%	No
33	50.95%	14.77%	13.47%	7.14%	13.24%	Yes
34	4.60%	14.45%	11.45%	38.13%	31.14%	No
35	5.49%	27.93%	55.34%	9.04%	0.02%	No
36	6.73%	34.16%	13.71%	32.48%	12.44%	No
37	55.03%	16.11%	6.92%	10.34%	8.25%	Yes
38	1.33%	23.30%	2.45%	33.10%	39.75%	No
39	7.84%	19.35%	14.94%	15.70%	41.99%	No
40	4.44%	15.54%	10.98%	28.70%	40.14%	No
41	0.09%	0.24%	37.69%	15.80%	45.85%	No
42	1.48%	37.44%	30.83%	29.64%	0.06%	No
43	5.64%	19.01%	15.57%	13.26%	45.97%	No
44	5.67%	28.22%	54.73%	9.18%	0.02%	No
45	35.67%	17.35%	18.48%	9.49%	18.72%	No
46	65.99%	5.54%	7.94%	7.52%	12.22%	Yes
47	0.32%	2.82%	43.07%	4.19%	49.28%	No
48	5.99%	39.69%	40.43%	12.66%	1.03%	No
49	32.07%	7.79%	10.23%	14.56%	34.95%	No
50	47.32%	12.22%	14.04%	10.83%	15.43%	No
51	41.65%	10.98%	10.91%	14.55%	21.72%	No
52	1.09%	34.00%	30.92%	33.61%	0.10%	No
53	1.60%	45.54%	25.60%	13.10%	13.64%	No
54	0.20%	0.09%	0.68%	90.34%	8.53%	No
55	25.77%	23.39%	20.20%	25.14%	4.78%	No
56	0.22%	6.37%	64.29%	28.97%	0.14%	No
57	5.25%	9.56%	29.06%	27.97%	27.78%	No
58	15.17%	14.46%	14.40%	16.01%	39.75%	No
59	62.31%	13.44%	12.59%	4.19%	7.29%	Yes
60	34.95%	12.96%	14.89%	16.03%	21.04%	No
61	13.43%	14.33%	14.31%	15.79%	41.96%	No
62	14.66%	14.54%	14.08%	22.65%	33.53%	No
63	38.89%	9.68%	20.35%	11.16%	19.74%	No
64	0.55%	2.33%	5.43%	22.92%	68.59%	No
65	9.00%	22.85%	14.06%	26.97%	27.04%	No
66	35.43%	13.47%	48.88%	0.37%	0.01%	No
67	10.71%	8.24%	6.87%	11.03%	63.02%	No
68	5.70%	16.27%	14.23%	15.40%	48.24%	No
69	33.37%	6.08%	19.81%	36.35%	3.65%	No
70	0.30%	5.11%	8.52%	11.36%	74.66%	No
71	9.65%	20.76%	14.77%	23.60%	31.07%	No
72	25.16%	18.00%	7.18%	17.90%	31.68%	No
73	0.10%	4.09%	4.37%	47.86%	43.09%	No
74	4.50%	15.05%	11.94%	36.45%	31.60%	No
75	29.44%	7.28%	22.12%	37.18%	3.30%	No
76	35.46%	35.43%	23.49%	1.85%	0.02%	No
77	1.14%	60.03%	12.62%	23.78%	1.82%	No
78	12.29%	18.33%	25.03%	9.70%	34.44%	No
79	28.48%	35.52%	12.13%	22.66%	0.10%	No
80	1.51%	2.28%	23.74%	63.93%	8.44%	No
81	0.24%	69.03%	23.96%	5.49%	0.64%	No
82	0.13%	8.28%	64.39%	26.67%	0.05%	No
83	0.21%	21.70%	38.14%	34.18%	5.57%	No
84	1.69%	5.58%	1.18%	12.38%	78.84%	No
85	8.92%	60.98%	15.23%	14.23%	0.07%	No
86	10.23%	6.44%	3.36%	20.18%	59.51%	No
87	55.66%	17.93%	4.93%	10.97%	8.91%	Yes
88	2.15%	32.53%	53.87%	11.19%	0.05%	No
89	1.62%	63.92%	25.01%	9.14%	0.02%	No
90	3.56%	19.51%	2.30%	15.49%	58.99%	No
91	8.15%	14.45%	2.72%	21.41%	52.97%	No
92	63.22%	17.05%	4.05%	8.24%	6.38%	Yes
93	36.48%	13.67%	13.71%	15.61%	20.17%	No
94	0.21%	17.71%	36.86%	42.09%	2.62%	No
95	0.44%	2.37%	7.81%	86.90%	2.23%	No
96	92.81%	5.67%	0.14%	0.14%	0.07%	Yes
97	45.86%	48.03%	1.88%	0.08%	0.00%	No
98	25.47%	25.72%	21.55%	23.02%	3.49%	No
99	58.83%	25.92%	13.84%	0.05%	0.00%	Yes
100	18.88%	31.65%	43.79%	5.38%	0.01%	No
101	15.00%	31.00%	48.15%	5.35%	0.02%	No
102	11.27%	4.42%	28.17%	20.91%	35.03%	No
103	0.01%	2.78%	3.99%	23.17%	69.77%	No
104	18.58%	5.88%	15.55%	25.67%	34.22%	No
105	2.95%	17.11%	62.52%	6.86%	10.03%	No
106	70.12%	6.97%	10.99%	4.09%	7.79%	Yes
107	15.60%	60.24%	16.09%	7.29%	0.00%	No
108	2.49%	8.85%	8.59%	9.52%	70.51%	No
109	16.39%	20.52%	3.25%	33.11%	26.47%	No
110	4.26%	18.42%	2.46%	30.75%	43.95%	No
111	54.43%	15.78%	11.94%	6.33%	11.20%	Yes
112	45.61%	16.90%	13.88%	9.19%	14.02%	No
113	2.96%	37.27%	55.51%	3.88%	0.02%	No
114	20.51%	23.62%	35.30%	11.05%	8.90%	No
115	1.11%	5.88%	3.81%	40.73%	48.28%	No
116	9.45%	22.76%	42.96%	17.03%	7.41%	No
117	27.09%	28.47%	24.82%	19.05%	0.31%	No
118	5.77%	35.64%	14.32%	32.35%	11.59%	No
119	13.87%	24.61%	20.13%	32.47%	7.63%	No
120	1.83%	2.52%	52.81%	41.27%	0.52%	No
121	61.54%	8.48%	10.53%	8.07%	10.89%	Yes
122	0.58%	35.18%	62.19%	0.67%	0.00%	No
123	20.47%	17.63%	13.73%	16.92%	30.80%	No
124	13.39%	34.80%	45.73%	5.66%	0.00%	No
125	0.19%	1.82%	53.49%	42.79%	1.31%	No
126	6.38%	10.21%	17.19%	15.68%	50.37%	No
127	2.06%	12.80%	70.72%	11.04%	1.84%	No
128	18.11%	7.96%	11.09%	14.32%	48.25%	No
129	39.33%	7.55%	6.48%	10.69%	35.29%	No
130	45.59%	43.23%	7.56%	2.06%	0.00%	No
131	23.25%	24.41%	9.28%	29.96%	12.59%	No
132	21.23%	56.70%	10.81%	8.76%	1.42%	No
133	37.83%	9.00%	5.81%	20.49%	26.65%	No
134	57.98%	3.21%	16.82%	13.15%	8.47%	Yes
135	20.41%	31.74%	8.61%	27.09%	11.78%	No

This work focuses on blanket deprivation: it is possible that a focus on ‘pocket deprivation’ would have merit. Perhaps, a pocket deprivation approach would show that many students do get some experience to the health needs of those in deprived areas, although this would not answer the question around the intentionality of institutions in placing students in the most deprived practices. One approach might be to promote learning activities within these non-blanket deprivation practices to identify disparate health outcomes among selected high deprivation cohorts of these practices.

Conclusion

This paper posed the question: ‘Do undergraduate general practice placements propagate the “inverse care law” by limiting the opportunity to experience primary healthcare in the areas of highest need, during medical school?’ Analysing the intentionality of medical schools in ensuring the doctors of tomorrow are placed in practices reflective of general practice as a whole, is one method of answering it; it is also a method by which to direct action. This study was limited to one institution, covering the entirety of Northern Ireland. It demonstrated under-representation of general practices serving the most deprived populations being involved in undergraduate medical education. Thus, it can be argued that undergraduate placements are currently propagating the ‘inverse care law’, rather than tackling it.

The authors’ institution has launched a new undergraduate curriculum in 2020 within which, when fully implemented in the 2024–25 academic year, 25% of clinical time will be spent in general practice. The insights provided in this paper afford the opportunity to endeavour intentionally to have all students experiencing and reflecting on healthcare in areas of high deprivation, with the ultimate aim of training doctors with an interest to close the health inequalities gap. As Government looks to ‘Level Up’ society and medical schools increase general practice placements, consideration of whether the selection of teaching practices is reflective of general practice is imperative. Failure to do so, may result in more medical students pursuing a career in general practice, but not necessarily in high need, socio-economically deprived areas thus inadvertently, widening inequalities. It is important to continue looking for ways to improve, as Marmot summarised when referring to addressing health inequities and inequalities: ‘Do something, do more, do it better’ [41].

Ethical considerations

The study did not require ethical approval.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This study was undertaken as part of Daniel Butler's General Practice Academic Research Training Scheme through the Northern Ireland Medical Dental Training Agency, Queen's University Belfast and Northern Ireland Health & Social Care Research and Development Division.