Innovative, paired careers tutorials: increasing the number of medical students choosing general practice as a career

Background: With a crisis in general practice recruitment, to maintain the current workforce, the Department of Health and Social Care quote a need for 50% of our medical students to choose general practice as a career. There is much variety between medical schools and Nottingham University, alongside most others does not achieve this. Aim: To increase the number of medical students at Nottingham University who would consider a career in general practice.Design and Setting: Innovative, paired careers tutorials embedded into a new 4-week general practice attachment at Nottingham University with student evaluation.Method: 2 paired careers tutorials, giving guided careers advice to 4th year medical students, using the strapline “General Practice can be whatever you want it to be….”. The tutorials promoted portfolio GPs and enabled students to look at their current career choice and how general practice could fit into that. Paired evaluation in week 1 and 4 was completed. Students were asked open-ended questions regarding current career choices and (using a 5 point Likert scale) whether: “General practice is a possible career choice for me”. Due to the new nature of the course, the first, of four cohorts was excluded from the evaluation to ensure standardised teaching and remove potential bias. The data analysed using the Wilcoxon signed rank test.Results: We surveyed 218 students with a response rate of 218(100%). At the end of the module, in the second careers tutorial, 80(36.7%) gave a higher score suggesting they were more likely to choose general practice as a future career, 107(49.1%) had no change in score and only 31(14.2%) provided a lower score.There was a significantly higher median score at the end of the attachment the median (IQR) pre-survey score was 3 (3-4) and the median (IQR) post-survey score was 4(3-5). P

Screening for atrial fibrillation in primary care

Background Screening for atrial fibrillation (AF) has been recommended but is yet to be implemented in clinical practice. However, the most effective approaches for screening are not known and it is unclear if screening could feasibly be implemented in primary care. Aims and methods The overall aims were to determine how AF screening might feasibly and effectively be introduced into primary care in the United Kingdom (UK). Objectives were: 1) to determine the range and accuracies of methods for detecting pulse irregularities attributable to AF, 2) to determine the range and accuracies of methods for diagnosing AF using 12-lead electrocardiograms (ECGs) and 3) to investigate the feasibility and opinions of healthcare professionals (HCPs) in primary care about implementing AF screening. Three studies were undertaken: 1) a systematic review and meta-analysis of the diagnostic accuracy of methods for detecting pulse irregularities caused by AF, 2) a systematic review and meta-analysis of the diagnostic accuracy of methods for diagnosing AF using 12-lead ECG and 3) a survey of HCPs in primary care about screening implementation. Results Study 1: Blood pressure monitors (BPMs) and non-12-lead ECGs had the greatest accuracy for detecting pulse irregularities attributable to AF [BPM: sensitivity 0.98 (95% CI 0.92-1.00), specificity 0.92 (95% CI 0.88-0.95), positive likelihood ratio (PLR) 12.1 (95% C.I 8.2-17.8) and negative likelihood ratio (NLR) 0.02 (95% C.I 0.00-0.09); non-12-lead ECG: sensitivity 0.91 (95% CI 0.86-0.94), specificity 0.95 (95% CI 0.92-0.97), PLR 20.1 (95% C.I 12-33.7), NLR 0.09 (95% C.I 0.06 to 0.14); there were similar findings for smart-phone applications although these studies were small in size. The sensitivity and specificity of pulse palpation were 0.92 (95% CI 0.85-0.96) and 0.82 (95% CI 0.76-0.88), respectively (PLR 5.2 (95% C.I 3.8-7.2), NLR 0.1 (0.05-0.18)]. Study 2: The sensitivity and specificity of automated software were 0.89 (95% CI 0.82-0.93) and 0.99 (95% CI 0.99-0.99), respectively; PLR 96.6 (95% C.I 64.2-145.6); NLR 0.11 (95% C.I 0.07-0.18). ECG interpretation by any HCPs had a similar sensitivity for diagnosing AF as automated software but a lower specificity [sensitivity 0.92 (95% CI 0.81-0.97), specificity 0.93 (95% CI 0.76-0.98), PLR 13.9 (95% C.I 3.5-55.3), NLR 0.09 (95% C.I 0.03-0.22). Sub-group analyses of primary care professionals found greater specificity for General Practitioners (GPs) than nurses [GPs: sensitivity 0.91 (95% C.I 0.68-1.00); specificity 0.96 (95% C.I 0.89-1.00). Nurses: sensitivity 0.88 (95% C.I 0.63-1.00); specificity 0.85 (95% C.I 0.83-0.87)]. Study 3: 39/48 (81%) practices had an ECG machine and diagnosed AF in-house. Fewer non-GP HCPs reported having excellent knowledge about ECG interpretation, diagnosing and treating AF than GPs [Proportion (95% CI): ECG interpretation = GPs: 5.9 (2.8-12.0); healthcare assistants (HCAs): 0; nurses: 2.0 (0.3-13.9); Nurse practitioners (NPs): 11.8 (3.0-36.4). Diagnosing AF = GPs: 26.3 (17.8-37.0); HCAs: 0; nurses: 2.0 (0.3-12.9); NPs: 11.8 (2.7-38.8). Treating AF = GPs: 16.9 (9.9-27.4); HCAs: 0; nurses: 0; NPs: 5.9 (0.8-34.0)]. A greater proportion of non-GP HCPs reported they would benefit from ECG training specifically for AF diagnosis than GPs [proportion (95% CI) GPs: 11.9% (6.8-20.0); HCAs: 37.0% (21.7-55.5); nurses: 44.0% (30.0-59.0); NPs 41.2% (21.9-63.7)]. Barriers included time, workload and capacity to undertake screening activities, although training to diagnose and manage AF was a required facilitator. Conclusions BPMs and non-12-lead ECG were most accurate for detecting pulse irregularities caused by AF. Automated ECG-interpreting software most accurately excluded AF, although its ability to diagnose this was similar to all other HCP groups. Within primary care, the specificity of AF diagnosis was greater for GPs than nurses. Inner-city general practices were found to have adequate access to resources for AF screening. Non-GP HCPs would like to up-skill in the diagnosis and management of AF and they may have a role in future AF screening. However, organisational barriers, such as lack of time, staff and capacity, should be overcome for AF screening to be feasibly implemented within primary car

Screening for atrial fibrillation in primary care

Background Screening for atrial fibrillation (AF) has been recommended but is yet to be implemented in clinical practice. However, the most effective approaches for screening are not known and it is unclear if screening could feasibly be implemented in primary care. Aims and methods The overall aims were to determine how AF screening might feasibly and effectively be introduced into primary care in the United Kingdom (UK). Objectives were: 1) to determine the range and accuracies of methods for detecting pulse irregularities attributable to AF, 2) to determine the range and accuracies of methods for diagnosing AF using 12-lead electrocardiograms (ECGs) and 3) to investigate the feasibility and opinions of healthcare professionals (HCPs) in primary care about implementing AF screening. Three studies were undertaken: 1) a systematic review and meta-analysis of the diagnostic accuracy of methods for detecting pulse irregularities caused by AF, 2) a systematic review and meta-analysis of the diagnostic accuracy of methods for diagnosing AF using 12-lead ECG and 3) a survey of HCPs in primary care about screening implementation. Results Study 1: Blood pressure monitors (BPMs) and non-12-lead ECGs had the greatest accuracy for detecting pulse irregularities attributable to AF [BPM: sensitivity 0.98 (95% CI 0.92-1.00), specificity 0.92 (95% CI 0.88-0.95), positive likelihood ratio (PLR) 12.1 (95% C.I 8.2-17.8) and negative likelihood ratio (NLR) 0.02 (95% C.I 0.00-0.09); non-12-lead ECG: sensitivity 0.91 (95% CI 0.86-0.94), specificity 0.95 (95% CI 0.92-0.97), PLR 20.1 (95% C.I 12-33.7), NLR 0.09 (95% C.I 0.06 to 0.14); there were similar findings for smart-phone applications although these studies were small in size. The sensitivity and specificity of pulse palpation were 0.92 (95% CI 0.85-0.96) and 0.82 (95% CI 0.76-0.88), respectively (PLR 5.2 (95% C.I 3.8-7.2), NLR 0.1 (0.05-0.18)]. Study 2: The sensitivity and specificity of automated software were 0.89 (95% CI 0.82-0.93) and 0.99 (95% CI 0.99-0.99), respectively; PLR 96.6 (95% C.I 64.2-145.6); NLR 0.11 (95% C.I 0.07-0.18). ECG interpretation by any HCPs had a similar sensitivity for diagnosing AF as automated software but a lower specificity [sensitivity 0.92 (95% CI 0.81-0.97), specificity 0.93 (95% CI 0.76-0.98), PLR 13.9 (95% C.I 3.5-55.3), NLR 0.09 (95% C.I 0.03-0.22). Sub-group analyses of primary care professionals found greater specificity for General Practitioners (GPs) than nurses [GPs: sensitivity 0.91 (95% C.I 0.68-1.00); specificity 0.96 (95% C.I 0.89-1.00). Nurses: sensitivity 0.88 (95% C.I 0.63-1.00); specificity 0.85 (95% C.I 0.83-0.87)]. Study 3: 39/48 (81%) practices had an ECG machine and diagnosed AF in-house. Fewer non-GP HCPs reported having excellent knowledge about ECG interpretation, diagnosing and treating AF than GPs [Proportion (95% CI): ECG interpretation = GPs: 5.9 (2.8-12.0); healthcare assistants (HCAs): 0; nurses: 2.0 (0.3-13.9); Nurse practitioners (NPs): 11.8 (3.0-36.4). Diagnosing AF = GPs: 26.3 (17.8-37.0); HCAs: 0; nurses: 2.0 (0.3-12.9); NPs: 11.8 (2.7-38.8). Treating AF = GPs: 16.9 (9.9-27.4); HCAs: 0; nurses: 0; NPs: 5.9 (0.8-34.0)]. A greater proportion of non-GP HCPs reported they would benefit from ECG training specifically for AF diagnosis than GPs [proportion (95% CI) GPs: 11.9% (6.8-20.0); HCAs: 37.0% (21.7-55.5); nurses: 44.0% (30.0-59.0); NPs 41.2% (21.9-63.7)]. Barriers included time, workload and capacity to undertake screening activities, although training to diagnose and manage AF was a required facilitator. Conclusions BPMs and non-12-lead ECG were most accurate for detecting pulse irregularities caused by AF. Automated ECG-interpreting software most accurately excluded AF, although its ability to diagnose this was similar to all other HCP groups. Within primary care, the specificity of AF diagnosis was greater for GPs than nurses. Inner-city general practices were found to have adequate access to resources for AF screening. Non-GP HCPs would like to up-skill in the diagnosis and management of AF and they may have a role in future AF screening. However, organisational barriers, such as lack of time, staff and capacity, should be overcome for AF screening to be feasibly implemented within primary car

Innovative, paired careers tutorials: increasing the number of medical students choosing general practice as a career

Background: With a crisis in general practice recruitment, to maintain the current workforce, the Department of Health and Social Care quote a need for 50% of our medical students to choose general practice as a career. There is much variety between medical schools and Nottingham University, alongside most others does not achieve this. Aim: To increase the number of medical students at Nottingham University who would consider a career in general practice. Design and Setting: Innovative, paired careers tutorials embedded into a new 4-week general practice attachment at Nottingham University with student evaluation. Method: 2 paired careers tutorials, giving guided careers advice to 4th year medical students, using the strapline “General Practice can be whatever you want it to be….”. The tutorials promoted portfolio GPs and enabled students to look at their current career choice and how general practice could fit into that. Paired evaluation in week 1 and 4 was completed. Students were asked open-ended questions regarding current career choices and (using a 5 point Likert scale) whether: “General practice is a possible career choice for me”. Due to the new nature of the course, the first, of four cohorts was excluded from the evaluation to ensure standardised teaching and remove potential bias. The data analysed using the Wilcoxon signed rank test. Results: We surveyed 218 students with a response rate of 218(100%). At the end of the module, in the second careers tutorial, 80(36.7%) gave a higher score suggesting they were more likely to choose general practice as a future career, 107(49.1%) had no change in score and only 31(14.2%) provided a lower score. There was a significantly higher median score at the end of the attachment the median (IQR) pre-survey score was 3 (3-4) and the median (IQR) post-survey score was 4(3-5). P=<0.0001. Conclusion: Increasing medical student exposure to general practice with innovative, paired, careers tutorials increased the number of students who would consider a career in general practice

Screening for atrial fibrillation – a cross-sectional survey of healthcare professionals in primary care

Introduction: Screening for atrial fibrillation (AF) in primary care has been recommended; however, the views of healthcare professionals (HCPs) are not known. This study aimed to determine the opinions of HCP about the feasibility of implementing screening within a primary care setting. Methods: A cross-sectional mixed methods census survey of 418 HCPs from 59 inner-city practices (Nottingham, UK) was conducted between October-December 2014. Postal and web-surveys ascertained data on existing methods, knowledge, skills, attitudes, barriers and facilitators to AF screening using Likert scale and open-ended questions. Responses, categorized according to HCP group, were summarized using proportions, adjusting for clustering by practice, with 95% C.Is and free-text responses using thematic analysis. Results: At least one General Practitioner (GP) responded from 48 (81%) practices. There were 212/418 (51%) respondents; 118/229 GPs, 67/129 nurses [50 practice nurses; 17 Nurse Practitioners (NPs)], 27/60 healthcare assistants (HCAs). 39/48 (81%) practices had an ECG machine and diagnosed AF in-house. Non-GP HCPs reported having less knowledge about ECG interpretation, diagnosing and treating AF than GPs. A greater proportion of non-GP HCPs reported they would benefit from ECG training specifically for AF diagnosis than GPs [proportion (95% CI) GPs: 11.9% (6.8–20.0); HCAs: 37.0% (21.7–55.5); nurses: 44.0% (30.0–59.0); NPs 41.2% (21.9–63.7)]. Barriers included time, workload and capacity to undertake screening activities, although training to diagnose and manage AF was a required facilitator. Conclusion: Inner-city general practices were found to have adequate access to resources for AF screening. There is enthusiasm by non-GP HCPs to up-skill in the diagnosis and management of AF and they may have a role in future AF screening. However, organisational barriers, such as lack of time, staff and capacity, should be overcome for AF screening to be feasibly implemented within primary care

Innovative, paired careers tutorials: increasing the number of medical students choosing general practice as a career

Background: With a crisis in general practice recruitment, to maintain the current workforce, the Department of Health and Social Care quote a need for 50% of our medical students to choose general practice as a career. There is much variety between medical schools and Nottingham University, alongside most others does not achieve this. Aim: To increase the number of medical students at Nottingham University who would consider a career in general practice. Design and Setting: Innovative, paired careers tutorials embedded into a new 4-week general practice attachment at Nottingham University with student evaluation. Method: 2 paired careers tutorials, giving guided careers advice to 4th year medical students, using the strapline “General Practice can be whatever you want it to be….”. The tutorials promoted portfolio GPs and enabled students to look at their current career choice and how general practice could fit into that. Paired evaluation in week 1 and 4 was completed. Students were asked open-ended questions regarding current career choices and (using a 5 point Likert scale) whether: “General practice is a possible career choice for me”. Due to the new nature of the course, the first, of four cohorts was excluded from the evaluation to ensure standardised teaching and remove potential bias. The data analysed using the Wilcoxon signed rank test. Results: We surveyed 218 students with a response rate of 218(100%). At the end of the module, in the second careers tutorial, 80(36.7%) gave a higher score suggesting they were more likely to choose general practice as a future career, 107(49.1%) had no change in score and only 31(14.2%) provided a lower score. There was a significantly higher median score at the end of the attachment the median (IQR) pre-survey score was 3 (3-4) and the median (IQR) post-survey score was 4(3-5). P=<0.0001. Conclusion: Increasing medical student exposure to general practice with innovative, paired, careers tutorials increased the number of students who would consider a career in general practice

The association between Situational Judgement Test (SJT) scores and professionalism concerns in undergraduate medical education

Introduction: Situational judgement tests (SJTs) are widely used in selecting medical students and doctors. Emerging evidence suggests SJTs are capable of testing an individual’s ability to respond to role-relevant professionalism scenarios, however, evidence is lacking for their use in identifying students with concerning professional behaviours.This study aimed to determine the association between medical student professionalism-based SJT scores and recorded professionalism concerns during training.Methods: A cross-sectional study was conducted utilising SJT scores from second-year medical students and occurrences of student professionalism concerns. Concerns were reviewed and mapped to General Medical Council standards. Multivariate logistic regression was used to determine associations between SJT scores and professionalism concerns.Results: 247 students were included in the study. For every point increase in SJT score, students were 10% less likely to have multiple professionalism concerns [OR (95% CI) 0.90 (0.83–0.97); p = .007].Students scoring below 1 and 2 standard deviations from the mean score were 4 and 11-times more likely to have multiple concerns [OR (95% CI) 4.52 (1.12–18.25); p = .034] and [OR (95% CI) 11.45 (1.72–76.15); p = .012].Conclusion: Lower SJT scores were significantly associated with an increased risk of professionalism concerns. These findings support the potential for SJT exams to identify medical students that may require closer supervision and remediation during undergraduate education

General Practitioners’ views of blood pressure control in people with and without dementia

Introduction: Since 2012, our group has undertaken a programme of research examining the treatment of hypertension in people with dementia. Hypertension is managed by GPs, who are guided by NICE guidelines, which make no mention of different management in people with dementia. We sought to explore the views of GPs on whether they manage hypertension differently in people with dementia. Method: We chose to try using an on-online survey to seek views, with both open and closed questions. We offered vignettes describing 71 and 83 year old women without cognitive impairment or with dementia, and a free text box – comments provided in this box were analysed thematically. Results: Although 427 GPs responded to the questionnaire, this was only 7% of all GPs eligible. Responding GPs were twice as likely not to offer treatment to the patient aged 71 with dementia and a BP above 140/90 (NICE threshold) compared to one without dementia (23.9% vs 11.7%). A similar finding was found when the vignettes involving 83 year old women with and without dementia (using 160/100, the NICE threshold for this age group) where 7.3% would not offer treatment in the woman with dementia compared to 3.3% in those without dementia. The analysis of free text identified four major themes, which were labelled as ‘complex decisions, ‘blood pressure measurement‘, ‘uncertainties around treatment’ and ‘compliance with guidelines’. Discussion: The low response rate in this survey makes the findings potentially unreliable, and other methods of ascertaining GP views, intentions or practices should be considered. Despite this, the findings from this study, in particular the free text comments indicate that the management of hypertension in people with dementia, is likely to be more complex than current guidelines indicate, and we propose that further research and clarification of best practice would be helpful

Accuracy of methods for detecting an irregular pulse and suspected atrial fibrillation: a systematic review and meta-analysis

Background: Pulse palpation has been recommended as the first step of screening to detect atrial fibrillation. We aimed to determine and compare the accuracy of different methods for detecting pulse irregularities caused by atrial fibrillation. Methods: We systematically searched MEDLINE, EMBASE, CINAHL and LILACS until 16 March 2015. Two reviewers identified eligible studies, extracted data and appraised quality using the QUADAS-2 instrument. Meta-analysis, using the bivariate hierarchical random effects method, determined average operating points for sensitivities, specificities, positive and negative likelihood ratios (PLR, NLR); we constructed summary receiver operating characteristic plots. Results: Twenty-one studies investigated 39 interventions (n = 15,129 pulse assessments) for detecting atrial fibrillation. Compared to 12-lead electrocardiography (ECG) diagnosed atrial fibrillation, blood pressure monitors (BPMs; seven interventions) and non-12-lead ECGs (20 interventions) had the greatest accuracy for detecting pulse irregularities attributable to atrial fibrillation (BPM: sensitivity 0.98 (95% confidence interval (CI) 0.92–1.00), specificity 0.92 (95% CI 0.88–0.95), PLR 12.1 (95% CI 8.2–17.8) and NLR 0.02 (95% CI 0.00–0.09); non-12-lead ECG: sensitivity 0.91 (95% CI 0.86–0.94), specificity 0.95 (95% CI 0.92–0.97), PLR 20.1 (95% CI 12–33.7), NLR 0.09 (95% CI 0.06–0.14)). There were similar findings for smartphone applications (six interventions) although these studies were small in size. The sensitivity and specificity of pulse palpation (six interventions) were 0.92 (95% CI 0.85–0.96) and 0.82 (95% CI 0.76–0.88), respectively (PLR 5.2 (95% CI 3.8–7.2), NLR 0.1 (95% CI 0.05–0.18)). Conclusions: BPMs and non-12-lead ECG were most accurate for detecting pulse irregularities caused by atrial fibrillation; other technologies may therefore be pragmatic alternatives to pulse palpation for the first step of atrial fibrillation screening