GP training confusion: call for urgent talks

The AMA has voiced “grave concerns” about the Federal Government’s handling of far-reaching changes to general practitioner training under the shadow of looming doctor shortages.

AMA President Associate Professor Brian Owler has written to Health Minister Sussan Ley seeking an urgent meeting to discuss the implementation of changes to GP training announced in last year’s Budget.

A/Professor Owler warned the Minister that the medical profession was “fast losing confidence in the process, and history shows that the last time GP training was reformed by the Government it took many years to recover”.

In its 2014-15 Budget, the Federal Government abolished General Practice Education and Training (GPET) and the Prevocational General Practice Placements Program (PGPPP), axed funding to the Confederation of Postgraduate Medical Education Councils and absorbed Health Workforce Australia and GPET within the Health Department.

Under the sweeping changes, the Health Department will have responsibility for overseeing GP training.

The changes have stoked warnings that, combined with cuts to valuable programs and fears of massive hikes in student fees, they pose a serious risk to the quality and viability of general practice training, placing the profession at long-term risk.

Concerns have centred on the short time frame to implement the changes, the Department’s lack of experience in managing training programs, and the profession’s loss of supervision over training.

A/Professor Owler said expert AMA representatives who have been consulting with the Government and Health Department on the implementation of the changes have been alarmed by on-going delays and a lack of detail being provided by the Department on crucial matters such as the funding of professional oversight and governance arrangements.

“Unfortunately, we are now in a position where we simply do not know what the structure and delivery of GP training will look like beyond 2015,” the AMA President said in his letter to Ms Ley.

He said briefing papers provided by the Health Department for those attending its stakeholder meetings were “generally scant on detail and do not adequately deal with key issues, such as the future role of the GP Colleges”.

A/Professor Owler said the overwhelming view in the medical profession was that the Colleges should be given responsibility for the governance and management of GP training.

Anxiety about the changes has been heightened by predictions the nation could face a critical shortage of doctors in the next decade.

The ageing of the GP workforce and the struggle to attract students to specialise in general practice has contributed to forecasts of a shortfall of 2700 doctors by 2025 unless there is a major investment in training.

Last month Health Minister Sussan Ley re-announced the allocation of $157 million to extend the life of two medical training programs – the Specialist Training Program and the Emergency Medicine Program – through to the end of 2016.

Ms Ley said the programs were being sustained for an extra year while the Government continued to consult with the medical Colleges and other stakeholders about reforms to come into effect in 2017.

“This consultation will focus on in-depth workforce planning to better match investments in training with identified specialities of potential shortage and areas that may be over-subscribed into the future,” the Minister said. “Workforce planning is something that doctors and health professionals have been raising with me during my country-wide consultations to ensure those areas of expected shortages are addressed sooner rather than later.”

But Shadow Health Minister Catherine King condemned what she described as a “short-term fix”.

Ms King said the Government had thrown the entire field of specialist medical training into chaos by delaying confirmation of contracts just weeks before candidate interviews were due to commence.

Ms King warned that any cut to funding to specialist training would result I fewer specialists working in areas where they are needed most.

Adrian Rollins

Deaths from childhood asthma, 2004–2013: what lessons can we learn?

New South Wales data highlight areas for improvement in asthma management

The NSW Child Death Review Team annual report 2013 included an analysis of deaths from asthma during the 10-year period 2004–2013.1 A total of 20 children, aged up to 17 years, died from asthma in New South Wales. While this death rate was low, and therefore the findings need to be interpreted cautiously, lessons from the analysis can be extrapolated to help reduce morbidity and mortality associated with asthma in children. The main findings were:

deaths from asthma among children were rare, and more common in older children
there has been a recent increase in deaths, the cause of which is not clear
risk factors include low socioeconomic status, psychosocial problems, and Asian and Pacific Islander backgrounds
all the children who died had been diagnosed with asthma; most had persistent asthma and were atopic; seven had a history of food allergy (five confirmed on skin prick testing); and three had a history of anaphylaxis and had been prescribed or had used an adrenaline autoinjector
younger children were more likely to be hospitalised and less likely to die, and older children were less likely to be hospitalised and more likely to die
three-quarters of those who died had been hospitalised in the previous 5 years and 11 had been hospitalised in the year before their death, of whom eight did not receive follow-up care
all those who died had seen a general practitioner about their asthma, but regular review was uncommon (most just saw a GP when they were unwell) and only eight of those who died had seen a specialist
two-thirds of those who died had been given a written asthma action plan and about half had one developed in the year before death
written asthma action plans were on the school files of half (seven) of the children who were attending school and five of these were developed in the year before death
most of those who died had been prescribed reliever and preventer medication (19); most were using inhaled corticosteroids (ICSs) (17); and 15 of those who were using ICSs were also using a long-acting β-agonist (LABA) and/or an oral corticosteroid (13 and five, respectively)
the records of nine children who died indicated that asthma medications were not being used as recommended (intermittent preventer use in eight cases, irregular reliever use in one case)
for most of those who died (17), factors that may have increased risk of death were identified; these included: suboptimal asthma control, presentation or admission to hospital in the year before death, poor follow-up care, poor adherence to medication or written asthma action plan, lack of written asthma action plan, and exposure to tobacco smoke.

Possible adverse effects of therapy

One concerning matter that was identified was the large number of children who had been prescribed ICS–LABA combination therapy. While this may have reflected asthma severity, just under half of the children were using their preventer therapy intermittently, which is suboptimal. Concerns about inappropriate prescribing of ICS–LABA combination therapy as first-line preventer therapy (also often used intermittently) prompted the recent Pharmaceutical Benefits Advisory Committee Post-market Review of Pharmaceutical Benefits Scheme Medicines Used to Treat Asthma in Children (http://www.pbs.gov.au/info/reviews/asthma-children-reviews). This review confirmed the ongoing inappropriate use of ICS–LABA combination therapy as well as the lack of evidence of efficacy and potential adverse effects (increased exacerbation risk,2,3 loss of bronchoprotection against exercise-induced asthma and loss of efficacy of short-acting β-agonists [SABAs]4) of LABAs in children.

A recent study has also highlighted the possibility that a particular polymorphism in the β receptor gene (homozygous for arginine at codon 16) may predispose patients to these adverse effects.5 Thus, LABA use in the children who died from asthma may have, theoretically, put these children at risk of severe exacerbation and reduced the efficacy of SABAs during acute episodes of wheezing. It might, therefore, explain the increase in asthma deaths seen in recent years. It might also be responsible for increases in exacerbations and episodes of exercise-induced asthma in children who are taking LABAs, particularly those who may be genetically predisposed to adverse effects.

Recommendations

The recently revised National Asthma Council Australia Australian asthma handbook highlights the importance of a stepwise approach to asthma management in children and emphasises that ICS–LABA combination therapy should not be used as first-line preventer therapy in children. Instead, LABA add-on therapy should be reserved as one of the three possible options for step-up treatment in children with persistent asthma who continue to have poor asthma control despite low-dose ICS treatment. The other two possible options for step-up treatment are montelukast add-on therapy and increased ICS dose. Each of these step-up options may be a potential optimal approach in different patients.6

The handbook also recommends that because of lack of evidence of efficacy and safety in preschool children, LABAs should not be used in children 5 years or younger.6 This recommendation is also included in the recently revised Global Initiative for Asthma guidelines.7

Another recommendation in the Australian asthma handbook is to consider specialist review for children requiring step-up treatment, particularly those with ongoing poor asthma control.6 Although the children who died from asthma met this criterion, fewer than half had seen a specialist for review of their asthma. In addition, regular asthma reviews and follow-up care after hospital admission for asthma were uncommon. This probably reflects general non-adherence to asthma management guidelines for children, which could result in unnecessary morbidity.

It is pertinent to also highlight that the risk factors identified in the children who died from asthma (namely suboptimal asthma control, presentation or admission to hospital in the year before death, poor adherence to medication or written asthma action plan and lack of written asthma action plan) predict future asthma risk and therefore ongoing asthma morbidity. The three most common reasons for poor asthma control are misdiagnosis, poor adherence to medication and poor inhaler technique.6 While inhaler technique could not be checked in the review of asthma deaths, poor adherence to medication or written asthma action plan and lack of written asthma action plan were identified as risk factors in the children who died from asthma.

The Australian asthma handbook also recommends education about asthma medication, inhaler technique, preventing symptoms, managing acute episodes, self-monitoring and asthma control, as well as regular reviews and a written asthma action plan to help the patient and/or caregiver recognise and manage acute asthma episodes.6 There is also evidence to support the benefit of providing a written asthma action plan in paediatric emergency settings.8

Innovative strategies

Innovative educational strategies aimed at primary health care have been shown to improve asthma outcomes in children. A randomised controlled trial of the Practitioner Asthma Communication and Education (PACE) Australia program showed increased use of written asthma action plans by GPs, more appropriate evidence-based management of childhood asthma, and a higher rate of spacer prescription.9 The National Asthma Council Australia now has funding for wider dissemination of the PACE Australia program through GP networks.

Giving Asthma Support to Patients (GASP) is an online tool that was developed in New Zealand to provide asthma education at point of care and to provide primary health care professionals with the skills and knowledge they need to undertake a structured asthma assessment.10 For a retrospective cohort of patients aged 5–64 years, use of GASP resulted in decreased risk of exacerbation, hospital admission and emergency department presentation, decreased requirement for oral corticosteroids and less reliance on bronchodilators.10 Asthma Foundation NSW is in the process of producing an Australian version of GASP, consistent with Australian recommendations, which will be piloted in general practices.

Conclusion

Findings from the review of asthma deaths in NSW can help optimise management of childhood asthma and therefore improve outcomes. Guidelines for asthma management are not being adhered to and inappropriate prescribing of ICS–LABA combination therapy may be putting children at unnecessary risk of adverse effects. Innovative educational strategies such as PACE Australia and GASP are important for promoting asthma management guidelines and reducing asthma morbidity and mortality in children.

[Series] Strengthening of accountability systems to create healthy food environments and reduce global obesity

To achieve WHO’s target to halt the rise in obesity and diabetes, dramatic actions are needed to improve the healthiness of food environments. Substantial debate surrounds who is responsible for delivering effective actions and what, specifically, these actions should entail. Arguments are often reduced to a debate between individual and collective responsibilities, and between hard regulatory or fiscal interventions and soft voluntary, education-based approaches. Genuine progress lies beyond the impasse of these entrenched dichotomies.

Medical cannabis: time for clear thinking

Australia is behind the times on the medical use of cannabis

The debate about the medical use of cannabis in Australia has become confused with the proposal for a formal clinical trial instead of proceeding to legislation in New South Wales, the Australian Capital Territory and Victoria. Debates about prohibition of cannabis have a long history,1 as has the proposal for medical cannabis in Australia.2 Politicians are nervous about being “soft on drugs”, especially before an election. The clinical trial proposed, if successful, presumes that cannabis would then be approved and regulated as a pharmaceutical substance.

We need to be across the facts and options. Cannabis can never be a pharmaceutical agent in the usual sense for medical prescription, as it contains a variety of components of variable potency and actions, depending on its origin, preparation and route of administration. Consequently, cannabis has variable effects in individuals. It will not be possible to determine universally safe dosage of cannabis for individuals based on a clinical trial.

Extreme views in the debate about any form of cannabis decriminalisation are advanced with almost religious fervour. On the one hand, some assert that cannabis is a dangerous, highly addictive drug which causes schizophrenia, and that any move to relax prohibition would be a disaster. This view defies published evidence. On the other hand are those who have used cannabis for years, swearing it causes no trouble. They see prohibition as a totally inappropriate curb on individual freedom.

Facts about cannabis

The assertion that cannabis is highly addictive ignores firm evidence. The most authoritative review comparing addictiveness of drugs rates physical dependence on a scale of 0–3.3 Heroin is ranked 3; tobacco, barbiturates and benzodiazepines, 1.8; alcohol, 1.6; and cannabis, 0.8. Cannabis may, of course, be a pathway to more addictive drugs if obtained from illegal sources that also offer powerful alternatives.

The view that cannabis carries no risk likewise ignores much published evidence.4 Recent Australian and New Zealand longitudinal studies show significant social, behavioural, educational and mental problems with frequent use of cannabis by young people (aged 15–25 years). Psychosis occurred more frequently following long-term heavy use than among non-users, but no schizophrenia was noted in this study.5 A recent review of the evidence implicating cannabis in the development of schizophrenia found only that it can accelerate its expression at an earlier age and may aggravate existing schizophrenia. Of course, non-users also develop schizophrenia.6 Others have identified heavy cannabis use in the young as a possible factor in later psychosis, without specifying schizophrenia.7

Australians, together with citizens in the United States and New Zealand, are the world’s greatest users of cannabis per head of population.8 Prohibition has failed to prevent widespread use and young people report that they can readily access it.9 Young people need to be strongly dissuaded, on health grounds, from frequent or even regular use of cannabis, but this has little relevance to cannabis used for medical purposes or the debate surrounding it. Potential medical users are often, for example, in the later stage of a battle with painful cancer, finding problems with morphine, other analgesics and nausea with chemotherapy. Others seek relief from painful conditions such as muscle spasm in multiple sclerosis. Cannabis is believed to reduce seizures in Dravet syndrome, a rare genetic myoclonic epileptic encephalopathy beginning in infancy.10 Most parents of affected children (84%) report much lessened frequency or abolition of seizures with medical cannabis. They should have continuing access to it until trials using purified cannabidiol (CBD), believed to be the active component for these children, provide a superior agent.

We are behind the times on medical cannabis. Currently, 23 states in the US have legalised use of cannabis for medical conditions, as has Canada since 2001. Other countries approving it include Israel, Holland and the Czech Republic. Portugal, in 2001, removed penalties for personal possession and use of all illicit drugs, but with rigorous administrative processes to handle problem use. Eliminating prohibition is not a disaster if there are sensible processes to control drug-related harms.11

An Australian and US study found that removal of legal action and possible imprisonment for possession and use makes no difference to the patterns of use of cannabis.12 World Health Organization mental health surveys of 17 countries found that “countries with stringent user-level illegal drug policies did not have lower levels of use than countries with liberal ones”.13 There is no rational basis for the view that weakening prohibition to permit use for medical conditions would lead to a surge in general use.

Cannabis has at least two important active elements: δ-9-tetrahydrocannabinol (THC) and CBD. The former is responsible for the high of intense comfort and pleasure when presented to the brain in sufficient quantum. Its presence is greatly enhanced by heating marijuana above 170°C, as in a bong, converting the inactive precursor THC-A to THC. THC infused at high dose can produce a powerful euphoria but also hallucinations and other psychotic effects in some normal individuals, followed by complete recovery.14 CBD, on the other hand, does not give a high but has other effects including suppression of nausea and pain. It counteracts some of the effects of THC.15 The plant Cannabis sativa has more than 100 alkaloids with potential to influence the cannabis receptors CB1 and CB2, which respond to normal cannabinoids.16

Response to cannabis varies from person to person, partly due to genetic variation among users.17 The content of THC and CBA varies among different strains of marijuana. Some users vary the type of plant they use to benefit from these different effects.

What would a clinical trial entail?

Cannabis as such cannot be subjected to a double-blind clinical trial. Participants would have to agree to be treated with it, hoping to gain relief from distressing pain or nausea. Each would become aware whether they are receiving cannabis or a placebo. Dose would have to be adjusted for each individual. Any trial would use cannabis with multiple active constituents, varying with the source of marijuana used and its preparation.

If a person in the late stages of painful cancer seeks the euphoria of THC, why should they not have it? They must have a right to withdraw from a trial if it does not suit them. Participants in the control group may demand to transfer to the active arm on seeing others feeling better. Cannabis should supplement morphine for pain as necessary, not replace it.

Are there barriers in principles of medical practice?

There may be medicolegal issues if a medical practitioner prescribes a preparation of unquantified potency or with an incomplete description of its constituents and without full knowledge of side effects and their extent. But this has not proved to be a problem in those US states where the patient makes the choice to use cannabis following a medical consultation. A recent readership survey conducted by the New England Journal of Medicine sought comment on a published case report of a cancer patient where a senior psychiatrist and a pain management specialist had both recommended against use of cannabis. Seventy-six per cent of respondents from several countries responded that they would recommend use of cannabis in such a case.18 Medical marijuana is now widely used. A recent US study found that the states with medical cannabis use over 10 years had a lower death rate from opioid overdose than those without.19

Why not go ahead with legislative approval?

The real question is whether a person who is suffering pain and distress can access cannabis on their own initiative, following medical consultation as to their symptoms. They can access other herbal remedies from authorised providers such as health food stores or a pharmacist. If legislation permits sale to people suffering from a condition diagnosed by a doctor and scheduled in legislation, there should be no problem with provision of cannabis by this route without waiting for completion of a clinical trial. This is especially the case with Dravet syndrome patients where a formal clinical trial with a proprietary CBD concentrate20 may take several years to complete.

We should ensure that cannabis is provided only to approved users who should be registered. As there is no legal supplier, users should have permission to grow their own plants — up to 10 at any one time — but be forbidden from selling their product. Any proposal for commercial production should be subject to strict control, with analysis of THC, THC-A and CBD content by a government toxicology laboratory for both cannabis oil and the leaf product. Venues for sale, presumably pharmacies or health food shops, should be registered. People aged between 15 and 25 years should be excluded as recipients, except where it is provided specifically for a cause covered by legislation. The legislation should also make cannabis available for medical research.

In summary, use of cannabis should be decided by the patient, following medical advice about the condition from which they seek relief, with patients being registered under state legislation. If there is to be a nationally approved trial, it should be one of documenting clinical experience from cannabis use under state legislation of the kind foreshadowed by recently elected Victorian Premier Daniel Andrews.21

The Australian Medical Schools Assessment Collaboration: benchmarking the preclinical performance of medical students

Since 2000, the number of medical schools in Australia has expanded rapidly. Seven new schools have been established in the past 15 years, so there are now 19 medical schools. The schools differ with regard to entry point, curricula, course duration and teaching methods. Schools may identify themselves as aiming to achieve specific graduate attributes, for instance, producing future specialists, rural health practitioners or medical researchers, while others are more general in their aims.

Medical schools need a process that allows them to measure changes in their students’ and graduates’ performance relative to other medical schools, so they can evaluate changes to their selection criteria, curricula and teaching methods.

The Australian Medical Schools Assessment Collaboration (AMSAC) was established by a group of seven medical schools in 2008. It aims to allow Australian medical schools to share assessment items and performance statistics within an anonymous framework. While other assessment collaborations exist for item sharing, there has been no previous sharing of Australian student performance data. The formation principles guard against the construction of league tables. In 2013, the AMSAC collaboration comprised 12 Australian medical schools (Appendix 1).

The collaboration assesses preclinical medical education, in the sense that schools generally administer the items at the point where students make the transition from predominantly campus teaching to mainly clinical settings. This division is more clear cut in some schools than others. Almost all AMSAC collaborators have embedded the items in second-year examinations, irrespective of the total length of their programs.

AMSAC assessment generation

The project creates an agreed set of 50 items for participating schools to include in summative assessments. A multiple choice format with one correct answer is used. This is the most widely used written item type in assessment of basic and clinical sciences1,2 and, if well designed, assesses reasoning as well as factual recall.3,4 We have used the five-option format standardised by the United States National Board of Medical Examiners,4 although we acknowledge that varying the option number has little effect on item performance.5,6 The items are mapped to a blueprint (Appendix 2) that covers two broad basic science domains — function and structure — and are managed through the Sydney Medical School’s assessment database.7 All participating schools contribute items, which are reviewed at an annual collaborators’ meeting. A short list of 60 items is circulated and items nominated by multiple schools as problematic are eliminated to produce the final set of 50. About half the items have been used previously with good performance and serve as “anchors” for interyear comparison.

Including the items in assessments

The chosen items are delivered to a single student cohort in the collaborating schools as part of one or more summative assessments over a calendar year. Schools vary in terms of the number of items they include in their assessments (Appendix 3), as assessment and curriculum timing affect item relevance. The time allowed for each item varies between collaboration members; from a low of 60 seconds to a high of 120 seconds.8

The performance of individual students on the AMSAC items is collated and analysed by an independent consultancy, so schools can preserve their anonymity through the use of confidential identifiers. The data are analysed using the Rasch model which, unlike classical test theory, accounts for missing data in estimates of item difficulty and student performance, enabling valid comparisons to be made across the cohort, irrespective of which of the 50 items are administered. Rasch analysis has been applied widely in medical assessment.9,10

Study objectives

Institutional variation in the quality of assessments in other countries has been noted,11,12 but there have been few reports comparing medical school assessment outcomes in Australia.13 Our aim in this study was to report participation by medical schools and their students in AMSAC and to determine whether there were differences in student performance related to medical school characteristics and test administration methods.

Methods

We used Medical Deans of Australia and New Zealand (MDANZ) data on year two enrolments at schools outside the collaboration to calculate the equivalent-year population base for 2009–2013. (Box 1).

The Rasch measure (Winsteps, version 3.80.1; Winstep Software Technologies) for each student was used to investigate differences related to medical schools and variations in implementation. Although Rasch estimates were derived for both domains (structure and function), some schools implemented too few questions to provide a reliable basis for analysis of individual domains.

We used a general linear model analysis of variance (ANOVA) in SPSS Version 21 (IBM). Five independent variables (year of administration, entry requirement, school size, number of assessments and time per item) were applied to the models. Significance was defined at P < 0.01 to account for Type I errors. Effect size was assessed using the F test and partial η2, multiple interactions using the Scheffé test and reliability using the Kuder-Richardson Formula 20 index (KR20).

Results

Participation in AMSAC

The representation of Australian medical schools and students in AMSAC more than doubled between 2009 and 2013. In 2013 it included 12 of 19 medical schools (Box 1) and 68% of medical students.

Although the initial collaboration was formed by seven medical schools, one was unable to field questions in 2009, and another was unable to in 2010. Two medical schools participated for 2 years and withdrew owing to difficulty in matching the agreed blueprint within a single cohort; one recently rejoined.

The proportion of graduate-entry schools grew from half of the participating schools in 2009 to two-thirds in 2013. The proportion of students who attended a graduate-entry school and participated in AMSAC was relatively stable; 69% in 2009, 62% in 2011 and 67% in 2013. The proportion of AMSAC schools that could be classified as large (intake of 150 or more students) remained at about half, with the corresponding student representation being 61% in 2009, 74% in 2011 and 73% in 2013.

In 2013, AMSAC comprised six of the 10 small schools and six of the nine large schools. In terms of entry requirement, it comprised eight of the 11 schools with graduate entry and four of the eight schools admitting school leavers.

Statistical analysis

Rasch analysis found the item set to be psychometrically sound with a good fit of items to the model (Box 2), and the ability estimates for student performance are robust. The KR20 score for the 2013 AMSAC question cohort was 0.85. The average student performance varied slightly across the five implementations.

Our statistical analysis was performed only on the 2011–2013 data owing to variations in item difficulty, fewer participating schools in the early years of the collaboration and increased availability of reliable marker questions. As the number of reliable marker questions has increased over the years, the performance of the question set has stabilised.

Effect of independent variables

The ANOVA showed significant differences (P < 0.001) for four of the five independent variables. Entry type was the most significant main effect (F test and partial η2), followed by school size, year of implementation and number of assessments (Appendix 4). The effect of time allowed per multiple choice question was not significant (P = 0.681). The interaction of year and each of the four independent variables was also significant on ANOVA. The mean and, to a lesser extent, the standard deviation of student performance for each interaction clarifies the strength and direction of the significant differences (Box 4).

The set of test items for the 2013 implementation was significantly harder (Scheffé test) than the 2011 and 2012 sets (2011 mean difference (MD) = − 0.22; P < 0.001; 2012 MD = − 0.18; P < 0.001). The mean scores for 2011 and 2012 were not significantly different (MD = 0.04; P = 0.29). Although the difference in the means was statistically significant, the magnitude was less than 0.5 logit, the definition of a substantive difference14 in the Rasch model. There was a large overlap between the interquartile ranges of student performance in each year (Box 3).

Students from large schools performed better than students from small schools. The difference in performance increased over time and was significant in 2012 and 2013 (Appendix 4); however, the difference attributable to school size explained only 2.3% of variation. The interaction with year of implementation explained a further 0.5%. Even at its greatest (2013; − 0.38), the difference due to school size was still less than 0.5 logit.

Graduate-entry students performed better than those entering medicine directly from school (ANOVA P < 0.001; Appendix 4). The proportion of variance attributable to entry type was 4.5%. The interaction of entry type with year of implementation was not as strong (η2 = 2.3) due to the variation over the 3 years for the two options (Box 4).

The time allowed per item was not significantly associated with performance (P = 0.681). While the number of assessments had a significant effect on performance (P < 0.001), the effect size was too low to be meaningful (partial η2 = 0.003) (Appendix 4). The frequency of summative assessments increased each year of the collaboration, so some medical schools were reclassified over time (Box 4).

There was no interdependence between the independent variables explored in this study. The strongest association was between size of medical school and use of AMSAC questions in more than one assessment (r = 0.44). The multiple regression with all five independent variables explained only 12% of total variance (R2 = 0.12). The standardised beta weights were 0.28 for entry type, 0.26 for size of school, 0.14 for time per item, − 0.10 for year and − 0.07 for number of assessments. Thus, 88% of variation in medical student performance was due to factors outside of our model.

Discussion

The AMSAC project demonstrates the viability of linking assessments across medical schools. As few as 25 common items enable reliable interschool comparisons. Individual medical schools can use AMSAC data to assess the effect of changes in their curriculum or entry requirements and to evaluate the need for change; however, fitting all questions into all school curricula for a single cohort is challenging.

AMSAC is a broad collaboration of medical schools that vary in size, selection criteria, course duration and syllabus content. The overall sampling of Australian medical school students has grown from one-third of the preclinical cohort in 2009 to over two-thirds in 2013 and includes 14 schools in 2015. Two schools have left the collaboration due to difficulty with curricula mapping, though one has recently rejoined.

A key outcome of this process has been the collegiate interaction of the medical school representatives. The schools involved have acquired a better understanding of the structure and content of other schools’ syllabuses and assessment strategies. The increase in the quality and stability of the items during the project is a reflection of the broad engagement of course leaders in the question collection and review process, a phenomenon which has also been found in overseas collaborations.15

Rasch analysis allows valid comparisons between schools using less than the full set of test items and has enabled valid comparisons to be made by medical school and implementation methods. The slightly better performance of graduate-entry students in the early years of medical school may reflect their increased maturity and previous success but is also likely to reflect the substantial proportion of candidates with a medical science degree (eg, 27% of entrants to Sydney Medical School, 2011–2013). It would be surprising if an additional 3 years of study in the medical sciences did not confer any advantage in a preclinical medical science examination. A previous study from Melbourne Medical School found a similar small advantage for graduate-entry students.16

The small but significant difference in performance by size of school probably reflects the small size of all but one of the new Australian medical schools. The new schools are unlikely to have the depth of resources in the preclinical sciences of the established schools and are also in a stage of course stabilisation as their early cohorts graduate. Most variation in student performance on AMSAC items is due to other factors, most likely individual student ability.

AMSAC provides an opportunity for comparison of assessment strategies across schools. Over time there has been an increase in schools using multiple assessments as opposed to a single end-of-year exam. This pattern is particularly strong among the larger schools, perhaps reflecting better resourcing. The use of multiple small assessments did not improve student performance.

The project allows participating schools some ability to compare their students’ knowledge base and reasoning skills with those of other schools and with a national average. This project does not assess other graduate attributes and only looks at mid-course performance, but other national collaborations are in process to examine clinical skills and knowledge and reasoning in the pregraduation phase.

The project has demonstrated that medical schools can collaborate on a benchmarking process without the need for external regulation. Early fears about data being misused to create league tables or unique syllabus content being damaged have not been realised. The AMSAC project is a model for national collaboration between medical schools to meet government and community demands for accountability without loss of school autonomy.

1 Participation in the Australian Medical Schools Assessment Collaboration

	Year of administration
	2009	2010	2011	2012	2013

No. of medical schools (n = 19)	6	6	8	11	12
No. of students assessed	1035	1293	1666	2358	2377
Proportion of all medical students in equivalent year*	33%	39%	51%	65%	68%

* Data were obtained from Medical Deans of Australia and New Zealand 2013 medical student statistics (http://www.medicaldeans.org.au/wp-content/uploads/Website-Stats-2013-Table-2.pdf); Table 2(a): Total student enrolments 2013 by year of course (Australia).

2 Australian Medical Schools Assessment Collaboration student and item Rasch distributions, 2013

3 Rasch measure* for each year

* Each box displays the median score (horizontal line within the box) and the interquartile range.

4 Mean Rasch scores by school type and implementation method

		Year of implementation
		2011	2012	2013	Total

School type
Small school	Mean (SD)	0.94 (0.82)	0.67 (0.71)	0.51 (0.63)	0.68 (0.73)
	No. of students	431	420	638	1489
Large school	Mean (SD)	1.03 (0.64)	1.03 (0.86)	0.89 (0.70)	0.98 (0.75)
	No. of students	1235	1938	1739	4912
School leaver entry	Mean (SD)	0.82 (0.70)	0.61 (0.68)	0.73 (0.71)	0.71 (0.70)
	No. of students	635	985	775	2395
Graduate entry	Mean (SD)	1.12 (0.66)	1.23 (0.85)	0.82 (0.69)	1.03 (0.77)
	No. of students	1031	1373	1602	4006
Implementation method
< 90 seconds per item	Mean (SD)	0.92 (0.59)	1.03 (0.95)	0.79 (0.73)	0.91 (0.81)
	No. of students	556	1219	1205	2980
≥ 90 seconds per item	Mean (SD)	1.05 (0.74)	0.91 (0.70)	0.79 (0.67)	0.91 (0.71)
	No. of students	1110	1139	1172	3421

Single assessment	Mean (SD)	1.24 (0.76)	1.00 (0.72)	0.68 (0.68)	0.98 (0.75)
	No. of students	575	791	588	1954
Multiple assessments	Mean (SD)	0.88 (0.62)	0.95 (0.90)	0.82 (0.71)	0.88 (0.76)
	No. of students	1091	1567	1789	4447
Total
	Mean (SD)	1.01 (0.69)	0.97 (0.84)	0.79 (0.70)	0.91 (0.76)
	No. of students	1666	2358	2377	6401

Childhood food allergy and anaphylaxis: an educational priority

The challenge of higher rates of food allergy must be met through development of better models of care and education

IgE-mediated food allergy (FA) and anaphylaxis have become an increasing public and personal health burden in developed countries over the past decade, contributing to increased demand for specialty services, significant economic cost of care, and reduced quality of life for children with FA and their families.1 In the most accurate estimate in Australia to date, the Victorian HealthNuts study found the prevalence of challenge-proven FA at age 12 months to be 10% overall.2 Effective strategies for primary prevention of FA are lacking, and secondary prevention is limited to strategies to reduce the risk of unintentional exposure. Although food-specific immunotherapy appears promising, it remains at the investigational stage because of the infrastructure required, high rates of adverse reactions and lack of persistent tolerance when treatment ceases.3 While several risk factors for childhood FA have been proposed — such as early-onset atopic eczema, timing of solids introduction, vitamin D status and intestinal bacterial load3 — this area remains an active area of research.

Although other triggers for anaphylaxis exist (insect venom, medication or latex), the major strategies for avoidance focus on FA, due to its relatively high prevalence in childhood and higher rates of accidental exposure, particularly in school and childcare settings.4 Risk management requires patient and carer education on reducing the risk of exposure to allergic triggers, providing an emergency action plan if reactions occur, dealing with higher-risk situations (eg, exposure to unlabelled food, attendance at parties, school excursions and camps), and providing an adrenaline autoinjector to individuals considered to be at higher risk. As children age and approach their teenage years, self-management and concerns about parties (exposure to unlabelled food), alcohol exposure (reduced vigilance) and risks of exposure to food allergens by kissing5 should also be discussed.

The demand for evidence-based and nationally consistent education across jurisdictional boundaries on how best to care for individuals with FA and anaphylaxis continues to outstrip the current resources available for face-to-face training by community and hospital-based FA and anaphylaxis trainers. With most specialist services located in major cities, alternative models for education delivery are required to service the needs of rural areas.

To meet the challenge of increasing FA prevalence and demand for education, the Australasian Society of Clinical Immunology and Allergy (ASCIA) has developed a number of educational resources including national standardised emergency action plans, adrenaline autoinjector prescription guidelines (http://www.allergy.org.au/health-professionals/anaphylaxis-resources), and allergy prevention guidelines for schools and child care.4 ASCIA has also partnered with various state education and health departments to develop childcare and school e-training courses, which are available without charge from the ASCIA website (http://www.allergy.org.au). The content of these educational programs was developed after extensive consultation, with childcare versions approved by the Australian Children’s Education and Care Quality Authority. Since launching in March 2010, 178 000 school and childcare staff have registered for the e-training.

Additional separate modules on anaphylaxis and FA management have been specifically designed to meet the needs of medical practitioners, pharmacists, dietitians, first aid providers and the broader community, with Royal Australian College of General Practitioners accreditation of a 6-hour active learning module on allergy and anaphylaxis worth 40 (Category 1) continuing medical education points (https://alm.ascia.org.au).

Education of patients, caregivers and health professionals is recommended in FA and anaphylaxis guidelines, with the aims of improving patient care and reducing the risk of adverse outcomes.6 While the clinical outcome from provision of emergency action plans is yet to be investigated in controlled studies,7 educational training has been shown to result in more accurate recognition of symptoms of anaphylaxis by health professionals,8 and to improve knowledge of FA and change practice in catering staff.9 Finally, an evaluation of ASCIA pharmacist e-training demonstrated improved knowledge after training compared with baseline or no training, and long-term retention of knowledge 7 months after completion.10

Until specific strategies are available to reduce the health burden of FA and anaphylaxis, the challenges for our health care systems will be how best to develop evidence-based policies to reduce the risk of FA development, care for younger children presenting with new cases of FA or anaphylaxis, and manage the shifting burden on older teenagers and young adults, who carry the highest relative risk for fatal anaphylaxis. There will be an ongoing need to develop models of care to enhance access to specialist medical services, improve acute management and educate those charged with delivering care both within and outside the health care sector. We encourage health professionals involved in the care of patients with FA and anaphylaxis to update their skills in this area.

Reporting rural workforce outcomes of rural-based postgraduate vocational training

To the Editor: Following calls to bridge the evidence gap regarding rural exposure and uptake into rural medical practice,1 Rural Clinical Schools (RCS) regularly report graduate rural career outcomes. This permits comparison of approaches and quality improvement of the program.

Comparatively little is reported from the postgraduate rural-based vocational training programs. Just as the evidence gap for RCS required bridging, a similar approach should be adopted as standing key performance outcome indicators of regional training providers.

Ministerial review of general practice training previously identified a chronic undersupply of rural doctors as a “pressing concern” for government.2 Rural vocational training needs were determined as a priority in establishing the regionalised Australian General Practice Training (AGPT) program in 2002. The program requires 50% of vocational training to be conducted in rural areas to improve distribution of general practitioners into rural and regional areas.3 Yet, unlike RCS, in the AGPT program, training providers are not required to routinely report their rural workforce outcomes.

Two key performance outcome indicators are proposed: rural retention rate (RRR) and advanced rural skills proportion (ARSP). RRR reflects the number of registrars in rural practice 1 or more years after completing training. Advanced rural skill training acquisition is not available to RCS, but has been identified as increasing rural retention,4 and is intimately related to rural retention and workforce outcomes. ARSP is the proportion of all completing registrars who achieved Fellowship in Australian College of Rural and Remote Medicine or Fellowship in Advanced Rural General Practice.

These are both reasonable and appropriate measures of rural workforce contribution. Such sentinel measures would permit comparison between programs, leading to further improvement of vocational rural medical education.

In one dedicated rural medical vocational training program in Queensland, the RRR is 75% (38/51 registrars since the exclusive rural pathway was delivered) and the ARSP is 49% (25/51).

Dedicated rural medicine training contributes to the short- and intermediate-term rural medical workforce. This contribution should be measured using key sentinel measures in addition to detailed multivariate analyses.

The importance of surgeons teaching anatomy, especially by whole-body dissection

To the Editor: The reduction in anatomy teaching by whole-body dissection in medical education is a critical matter that has received substantial attention in the medical education literature.1,2 Where anatomy teaching by whole-body dissection has remained, there has been a marked move away from the tradition of such courses being taught by surgeons. A recent review of anatomy education in Australia and New Zealand showed that teaching of gross anatomy is now predominantly undertaken by non-clinical staff, including medical students, science graduates, physiotherapists and technical staff.2 Speculation has arisen that the teaching of anatomy by non-clinical staff may lead to a lack of depth in understanding of topographical clinical anatomy among medical graduates.2

The importance of providing clinical relevance to medical teaching is frequently highlighted. In fact, the importance of being taught by clinicians and surgeons in the anatomy dissection courses is perhaps more relevant to the modern medical curricula, which have limited time for imparting essential clinical anatomy. Anatomical knowledge is still important to safe clinical practice; the range of possible surgery has increased dramatically; and sophisticated technological advances such as modern imaging require a sophisticated knowledge of topographical anatomy.3

The reintroduction of both undergraduate and postgraduate courses in anatomy by whole-body dissection at Sydney Medical School has re-established the tradition of anatomy dissection taught by surgeons. Senior surgeons, both currently working and retired, provide guidance in their area of expertise, and are able to contribute their anecdotes and experiences to provide a relevant clinical perspective.4 Having surgeons from different specialties present when their areas of interest are being dissected provides a propitious environment for acquisition of students’ knowledge and skills.4

In recent years, the demands of the health care system have placed increased strains on clinicians’ commitments to teaching. The amalgamation of basic science departments into medical faculties has affected the design of curricula, resulting in non-medical, non-clinical personnel teaching widely within medical schools.5 With their wealth of clinical experience, surgeons who teach anatomy dissection offer a valuable, rare resource, essential to the provision of a clinical context to students.3 Recruitment mechanisms that attract surgeons to teach anatomy would ensure a high-quality anatomical learning experience for medical students.

Full medical program fees and medical student career intention

Admission to Australian medical schools is highly competitive, despite an increase in capacity from about 1200 places in 1999 to 3500 places in 2013.1 Most of these places are Commonwealth supported; in 2013, students paid A$9450 for each of the 4–6 years of medical tuition via the HECS-HELP scheme (Higher Education Contribution Scheme, Higher Education Loan Program).2

Tuition fees can be paid in advance or deferred until an annual income threshold is reached (A$51 309 in the 2013–14 financial year); deferred payments are interest-free but adjusted according to the consumer price index.3 In 2011, 56% of medical school entrants had a prior degree that may have also generated HECS-HELP debt.4

Medical students enrolled in a Commonwealth-supported place (CSP) may accrue a debt of A$36 000 to A$63 000, depending on course structure and prior degrees (4–7 years of fees), plus living expenses (about A$15 000 per year if away from home2). Concerns have been raised about the potential inequity of pricing medical education beyond the range that is practical for students from lower socioeconomic backgrounds.5,6

Subsidies for tuition fees are available through Bonded Medical Places (18.8% of students), Medical Rural Bonded Scholarships (3.0%), Australian Defence Force (ADF) scholarships (0.2%),4 and state-based rural scholarships, all of which require return of service in areas of need (usually non-metropolitan communities or the ADF). CSP students can also reduce HECS-HELP debts by one year’s fees for each year of work in an area of need.

Between 2005 and 2009, some universities introduced additional places that required payment of the full cost of medical education.7 Bond University commenced a full-fee paying (FFP) undergraduate medical course7 and some other medical schools offered small numbers of domestic FFP places to cater for surplus student demand.

Most medical schools also offer FFP courses for international students, providing a valuable source of income and contributing to export of higher education.8 About 700 international places were available annually until recent competition for intern places reduced this to about 550 places.

While fees for international FFP students vary (A$30 000 to A$60 000 per year), the financial investment by graduation by these students is much higher than that for domestic FFP students. Domestic FFP students may access partial loans under the FEE-HELP loan scheme (a lifetime maximum of A$116 507 in 2013)9 and may apply for ADF scholarships and state-based rural scholarships. International FFP students do not have these options.

FFP students (domestic and international) can therefore graduate with substantial debts, raising concerns about workforce outcomes. The debts can be comparable to those in the United States, where a private education system is well established.10–12 In 2012, 86% of US medical graduates reported substantial debts, 30% as high as US$200 000.11 Follow-up studies show a clear association between debt, anticipated income, personal value placed on money and choice of higher paid specialties.11,13,14

Choice of specialty is a complex decision, influenced by extrinsic and intrinsic factors.15 Extrinsic factors include work culture, postgraduate work experience, opportunities for flexible hours and perceived prestige of certain specialties.15 Prestige is characterised by longer and more intensive training periods, more competitive selection, higher income, and perceived greater societal status.16 These perceptions remain constant from undergraduate training through to early postgraduate training, although they may be challenged by clinical experiences during clerkships and residency.16

Intrinsic factors include student demographics, personal attributes and preferences, and the clinical work environment. Student demographic profiles have significant influences on specialty choice.17 Socioeconomic status and background appear to be important; students from less wealthy families place greater weight on debt and pursuing higher incomes. Students from a rural background are more likely to pursue a rural career.12,18 Sex is associated with differences in motivation for particular career choices, with women more likely to pursue general practice careers because of shorter, more flexible training and better working conditions.15 Men who place added value on personal lifestyle factors also prefer general practice.19

The three most influential personal determinants of specialty choice appear to be “appraisal of own skills and aptitudes”, “intellectual content of the specialty”, and “interest in helping people”.15 Lifestyle and finances are increasingly reported as major considerations by graduates.10–12,18 While debt load may influence students towards a preference for higher-paying careers, this may be more significant only for students who place greater importance on socioeconomic status as overall career preferences between FFP students and their publicly subsidised counterparts are similar.12

Although privately funded medical education continues to grow overseas, the influence of financial burden on career choice in Australia (where the geographic and specialty distribution of graduates is of greater concern than total numbers) has not been studied in depth. We compared the geographic and specialty career intentions of CSP and FFP medical students, domestic and international.

Methods

Data were accessed from the Medical Schools Outcomes Database and Longitudinal Tracking (MSOD) Project, a project of Medical Deans Australia and New Zealand that is funded by Health Workforce Australia as a means of evaluating rural medical education initiatives.19 Questionnaires are administered to all medical students on entry to and graduation from Australian medical schools. We collected data from these questionnaires for the period 2008 (when the MSOD Project commenced, with four participating medical schools) to 2011 (when 18 medical schools participated).

Dependent variables

Work location preference data were collected in five categories: small community; smaller town; regional city or large town; major urban centre; and capital city. The first three and last two categories were collapsed to create a binary variable for preference for rural practice versus urban practice.

Preferences for future medical specialty were analysed according to:

first choice selection of one of the five highest paid specialties in Australia — identified by the 2010 Medicine in Australia: Balancing Employment and Life study20 of specialty income (emergency medicine; surgery; radiology; obstetrics and gynaecology; intensive care medicine)21
selection of any of the top six in-need specialties — those predicted by Health Workforce Australia to be in short supply in 2025 (general practice; psychiatry; obstetrics and gynaecology; pathology; ophthalmology; radiology)22
first choice selection of any of the top six in-need specialties
first, second or third choice selection of any of the top six in-need specialties.

Independent variables

A binary variable was created to represent whether each student was a domestic FFP student or a CSP student (the latter was defined as a student receiving Commonwealth, state or university support). This variable excluded international FFP students, and a second binary variable was created to contrast international FFP students with CSP students. Additional binary variables were created for sex, marital status (single versus married or living with a partner) and rural background. Age at entry to medical school, in whole years, was also included.

Statistical analysis

Logistic regression models were run initially to analyse (i) rural future practice intentions, (ii) preferences for the top five income specialties and (iii) preferences for the top six in-need specialties. Two models were run for each: for domestic FFP students versus CSP students, and for international FFP students versus CSP students. Another six logistic regression models were then run to further analyse preferences for the top six in-need specialties, for domestic FFP students versus CSP students only.

Sex, age, marital status and rural background were initially included in all regression models together with the independent variable of whether students were domestic FFP or international FFP. Two-way interaction terms were included for interactions between the control variables and the independent variable of interest, and then removed using a backwards stepwise approach until the model contained only statistically significant interaction effects (those contributing a significant improvement in the model [a 2 log likelihood]).

Results

Data were available for 5688 students who graduated from 2008 to 2011: 262 in 2008; 894 in 2009; 1978 in 2010; and 2554 in 2011. The overall response rate was 83% (4704/5688) for those who completed the entrance questionnaire and 80% (4461/5568) for those who completed both entrance and exit questionnaires, although there were missing data for each of the variables, in particular specialty preferences.

A summary of the data collected from the exit questionnaires is shown in Box 1. A majority of students were young (mean age, 22 years), female, single and from urban backgrounds, and a minority were domestic FFP students (9.1%) and international FFP students (14.7%).

Preference for rural versus urban future practice

Domestic FFP students were significantly more likely than CSP students to prefer an urban future practice location (OR, 5.58; 95% CI, 2.04–15.26; P < 0.001). However, there was a significant domestic FFP student by marital status interaction effect, such that domestic FFP students who were married or partnered on exit from medical school were more likely to prefer a rural location (OR, 0.64; 95% CI, 0.44–0.95; P < 0.05).

Having a rural background had a strong effect on preference for a rural future practice (OR, 0.18), as did being older on entry to medical school (OR, 0.96). International FFP students were more likely to state a preference for urban practice (OR, 1.79). These data are shown in Box 2.

Preferences for medical specialty

Students who were married or partnered were less likely to select one of the top five income specialties as their first preference (OR, 0.77) and domestic FFP students were more likely to select one of the top five income specialties as their first preference (OR, 1.37). International FFP students were not more likely to select one of the top five income specialties as their first preference (OR, 1.18). These data are summarised in Box 3.

Domestic FFP students, but not international FFP students, were less likely than CSP students to have a first preference for an in-need specialty (OR, 0.72; 95% CI, 0.52–1.00; P < 0.05). All of the control variables were significant in the models as main effects: men were less likely to select an in-need specialty (OR, 0.44; 95% CI, 0.37–0.53; P < 0.001), while older (OR, 1.03; 95% CI, 1.01–1.04; P < 0.01), married or partnered (OR, 1.23; 95% CI, 1.14–1.34; P < 0.001) and rural background (OR, 1.28; 95% CI, 1.04–1.57; P < 0.05) graduates were more likely to select one of the in-need specialties.

Analyses of each of the predicted top six in-need specialities for 2025 were performed separately and focused on first preferences. Domestic FFP students were less likely than CSP students to select general practice (OR, 0.71), but domestic FFP students were no more or less likely than CSP students to select the remaining five in-need specialties. The results of the analysis of preference for general practice are shown in Box 4.

However, there was no significant difference between domestic FFP students and CSP students in terms of including any of the top six in-need specialties in their first three preferences (OR, 0.89; 95% CI, 0.71–1.11).

Discussion

We found that Australian domestic FFP students as a whole were more likely to state a preference for higher-paid specialties in urban locations, and were less likely to state a first choice preference for one of the six specialties predicted to be in need in 2025. However, the only specialty that was less popular was general practice; other associations were not uniform throughout the cohort.

Domestic FFP students who were married or partnered were notably different in that they were more likely to prefer rural practice settings. Further, when students’ first three specialisation preferences were analysed, there were no significant differences between domestic FFP and CSP students in preference for a top six in-need specialty.

These differences might be partly explained by student demographics and medical school locations. A higher proportion of FFP students, both domestic and international, are from urban backgrounds and most medical schools are in metropolitan areas or large urban centres. The outcomes may, therefore, be similar to those for other urban background students in urban medical schools.

On the other hand, rural clinical school experience in one metropolitan medical school program has been shown to be at least as influential as rural background,23 suggesting that rural initiatives may be effective for FFP students.

The implications of our findings for Australia’s medical workforce planning could be relatively minor. Domestic FFP students currently comprise a small minority of Australia’s medical students. For international students, a majority of whom want to stay in Australia for at least some postgraduate experience and training, encouragement can be drawn from the finding that specialty choice is similar to that for CSP students. If the number of FFP student places is increased through changes in government policy or establishment of more private medical schools, strategies to increase the focus on rural and other underserved populations might be needed. Unless rural initiatives are extended across public and private medical schools, FFP student places (domestic or international) are unlikely to address the current rural and regional medical workforce shortages or affect the intention to further develop primary care medicine.

The possibility of increased fees for CSP students, and therefore increased debt levels, begs consideration of the potential impact on career preferences. Higher fees might drive interest towards higher-paid, metropolitan specialties. Such an effect might, however, be mitigated by continuing the apparently successful rural medical education initiatives that, although costly, are effective in promoting rural recruitment.23,24

Our study has some limitations. Several initiatives may influence choice of rural locations in the early graduate period. For example, CSP students with rural scholarships are required to work at least initially in non-metropolitan communities, and may also reduce HECS-HELP debt by working in a defined area of need, usually non-metropolitan. Hence it is difficult to be confident that any changes in career preference relate to fee levels or to the existence of fewer rural medical education initiatives for FFP students. Also, we were not able to collect data on debt, and it is possible that students paying high fees could graduate with no debt. Finally, career preference takes several years to become final, so longer follow-up (at least 10 years) is required to produce a more robust analysis based on final career outcomes.

Our data show differences in specialty and location preferences between domestic FFP and CSP students. Consideration should be given to extending rural medical education initiatives across public and private medical school places to ensure that all medical students are exposed to rural and more generalist career attractions.

1 Descriptive statistics for study variables for students who completed the Medical Schools Outcomes Database and Longitudinal Tracking Project exit questionnaire, 2008–2011*

Domestic FFP students (n = 408)

International FFP students (n = 655)

CSP students (n = 3398)

Age in years at entry to medical school, mean (range; SD)

22 (16–53; 4.6)

21 (15–36; 3.0)

22 (15–68; 5.0)

Women

219/408 (53.7%)

371/654 (56.7%)

1924/3398 (56.6%)

Marital status single

318/408 (77.9%)

527/655 (80.5%)

2325/3229 (72.0%)

Urban background

371/408 (90.9%)

596/655 (91.0%)

2650/3398 (78.0%)

Preference for urban future practice

364/390 (93.3%)

481/521 (92.3%)

2686/3258 (82.4%)

First preference for any of the top five income specialties

153/322 (47.5%)

235/552 (42.6%)

1115/2929 (38.1%)

First preference for any of the top six in-need specialties†

54/322 (16.8%)

129/552 (23.4%)

737/2929 (25.2%)

First to third preference for any of the top six in-need specialties†

151/322 (46.9%)

243/552 (44.0%)

1377/2929 (47.0%)

* Data are number/denominator (%) unless otherwise indicated. † Top six specialties predicted to be in need in 2025.

2 Logistic regression analysis of preference on exit from medical school for rural versus urban future practice (n = 3314)*

Odds ratio (95% CI)†

Age at entry to medical school

0.96 (0.95–0.98)

< 0.001

Sex

1.24 (1.01–1.53)

< 0.05

Marital status

1.91 (0.70–5.23)

Not significant

Rural background

0.18 (0.15–0.22)

< 0.001

Domestic FFP student by marital status interaction

0.35 (0.14–0.90)

< 0.05

Domestic FFP student

3.36 (1.75–6.46)

< 0.001

International FFP student‡

1.79 (1.19–2.72)

< 0.01

CSP = Commonwealth-supported place. FFP = full fee-paying. * Independent variable: CSP students versus domestic FFP students (CSP = 0, FFP = 1). Control variables: age at entry to medical school, sex (female = 1, male = 2), marital status (unmarried = 0, married = 1) and rural background of the student (no = 0, yes = 1). † Higher odds ratio indicates preference for urban future practice. ‡ International students were entered into a separate model with the control variables.

3 Logistic regression analysis of first preference on exit from medical school for any of top five income specialties (n = 2945)*

Odds ratio (95% CI)†

Age at entry to medical school

1.00 (0.98–1.02)

Not significant

Sex

1.55 (1.33–1.80)

< 0.001

Marital status

0.77 (0.64–0.92)

< 0.01

Rural background

0.93 (0.77–1.12)

Not significant

Domestic FFP student

1.37 (1.07–1.75)

< 0.05

International FFP student‡

1.18 (0.96–1.47)

Not significant

CSP = Commonwealth-supported place. FFP = full fee-paying. * Independent variable: CSP students versus domestic FFP students (CSP = 0, FFP = 1). Control variables: age at entry to medical school, sex (female = 1, male = 2), marital status (unmarried = 0, married = 1) and rural background of the student (no = 0, yes = 1). † Higher odds ratio indicates greater likelihood of choosing high-income specialty. ‡ International students were entered into a separate model with the control variables.

4 Logistic regression analysis of first preference on exit from medical school for working in general practice (n = 2945)*

Odds ratio (95% CI)†

Age at entry to medical school

1.03 (1.01–1.05)

< 0.01

Sex

0.44 (0.37–0.53)

< 0.001

Marital status

1.55 (1.28–1.89)

< 0.001

Rural background

1.28 (1.04–1.57)

< 0.05

Domestic FFP student

0.71 (0.52–0.99)

< 0.05

International FFP student‡

0.99 (0.76–1.26)

Not significant

CSP = Commonwealth-supported place. FFP = full fee-paying. * Independent variable: CSP students versus domestic FFP students (CSP = 0, FFP = 1). Control variables: age at entry to medical school, sex (female = 1, male = 2), marital status (unmarried = 0, married = 1) and rural background of the student (no = 0, yes = 1). † Higher odds ratio indicates greater likelihood of choosing general practice. ‡ International students were entered into a separate model with the control variables.

Roadmap for physician trainees’ Everest

ALTHOUGH NOT DIRECTLY endorsed by the Royal Australasian College of Physicians (RACP), Examination medicine is widely considered to be the definitive manual for approaching the exam that many physicians describe as the most stressful experience of their careers. The 7th edition retains the overall structure of its previous incarnation, with the early chapters providing an overview of physician training in Australia and New Zealand and touching briefly on the FRACP written exam. The book remains dedicated to how candidates for the FRACP examination should approach the long and short case formats that make up the exam.

This new edition makes even greater use of tables and figures to present key information in ways that are relatively simple to absorb. Clinical images abound and are now predominantly in colour. Useful tips and potential pitfalls for the unwary candidate are flagged. A welcome new chapter has been added that contains examples of potential long cases — highlighting how an examiner may approach a case and what discussion points are likely to arise. Additional online video content is included with this edition in the form of a model long and short case.

The 7th edition builds on the strengths of previous editions and hence remains an invaluable reference, not only for FRACP candidates but also for advanced trainees and consultants looking to refresh and revise their clinical skills. Professor Talley and Dr O’Connor are well placed to comment on the standard expected at the exam being, at the time of publication, the President of the RACP and a member of the Senior Examination Panel, respectively. Medical students and clinicians from other specialties will also benefit from the systematic and thorough approach to clinical assessment and diagnosis presented in this book, although they may find the level of detail surplus to requirement.