Measles alert in Brisbane

Queensland Health has issued a measles alert in Brisbane after a student from Taringa was diagnosed with the disease.

The man was infected with the disease while travelling and returned to Australia last Wednesday.

Public Health Physician Dr James Smith said: “Although this person didn’t get measles in Australia, he would still have been very infectious when he was out in the community between Wednesday and Saturday last week.”

The man was in the following locations while infectious:

Brisbane Airport – Domestic Terminal on Wednesday 15 July. He was a passenger on Qantas flight QF524 from Sydney.
University of Queensland, St Lucia between Thursday 16 July and Saturday 18 July
Indooroopilly Shopping Centre on either 16 or 17 July

Queensland Health is urging anyone who develops these symptoms to isolate themselves from school, work and social activities and to seek medical advice.

“It’s very important to call the medical practice first to say you could have measles, so that staff can take precautions to avoid spreading the disease to others,” Dr Smith said.

Anyone born during or since 1966, who has not had two documented doses of measles, mumps, rubella (MMR) vaccine or had proven measles, should visit their family doctor to get vaccinated for measles. The vaccine is free for anyone who requires it.

Visit Queensland Health for more information.

Vale Dr David Game, distinguished GP and medicSA editor

Dr David Aylward Game was born in Adelaide on 31 March 1926, the fourth son of a bank manager and a nurse. On 14 May, in his 90th year and having played bridge at the Adelaide Club that morning, he died suddenly at his desk while attending to computer tasks. The table was, as usual, meticulously set for dinner.

David was educated at St Peter’s College, Adelaide, and the University of Adelaide, where on his first day he met fellow medical student Patricia Jean Hamilton. They married immediately after graduation and were the first married couple to receive their MBBS degrees on the same day. In 1953, David commenced general practice from their first home on Payneham Road, but as the family grew to include their four children – Ann, Philip, Timothy and Ruth, they moved to Rokeby in Royston Park.

From his early years as a family doctor, David became an advocate for general practice as a specialty in its own right, a cause which became an abiding passion and the source of great achievement. He was a founding member of the Royal Australian College of General Practice, in which he held a number of key roles, including that of President from 1974 to 1976.

In 1980, he received the college’s highest accolade, the Rose Hunt Award. He represented the College at a number of international meetings, and in 1970 became involved in the formation of the World Organisation of National Colleges, Academies and Academic Associations of General Practitioners/Family Physicians, with its somewhat peculiar acronym WONCA, and was its President from 1983 to 1986.

Among the many anecdotes about David’s experiences in these roles with various dignitaries, there is a wonderful story about Prince Philip confusing WONCA with wombat, leading to the establishment of the Honorary Wombat Award for retiring presidents, David’s having pride of place in his office.

David was a pioneer for the involvement of GPs in public and teaching hospital work, holding positions at the Adelaide Children’s, Modbury and Royal Adelaide hospitals. He is the only GP to have been granted an emeritus appointment at the RAH.

Early in his career, he involved students and family medicine program graduates in his private practice, and between 1991 and 1998 was medical director of the South Australian Postgraduate Medical Education Association. In 1983, he was appointed an Officer in the Order of Australia for service to general practice.

He was a Fellow and Life Member of AMA South Australia, filled many important roles for the SA Branch, and was editor of medicSA from 2004 to 2012, during which time it won the award for best State publication twice. His significant contributions saw him awarded the AMA(SA) President’s Award in 2006.

This exceptionally generous and caring man is greatly missed, not only by his four children, six grandchildren and four great-grandchildren, but by his colleagues and many friends.

In the weeks since his death, tributes have arrived from around the world and, in particular, from his WONCA colleagues in countries including the United States, UK, Singapore, South Africa, Holland, Nepal, India, Jordan and Ireland.

The AMA honours the work of this distinguished South Australian general practitioner.

* This article was supplied by medicSA, where it was first published last month.

AMA in the News – 21 July

Your AMA has been active on policy and in the media on a range of issues crucial to making our health system better. Below is a snapshot of recent media coverage.

Print/Online

Doctors, teachers face gags under immigration laws, Sydney Morning Herald, 4 June 2015
Doctors and teachers working in immigration detention facilities could face up to two years in prison if they speak out against conditions in the centres or provide information to journalists. AMA President Professor Brian Owler said this was the first time doctors had been threatened with jail for revealing inadequate conditions.

Medical research fund could be ‘slush’ fund: Labor, The Age, 5 June 2015
The Abbott Government could raid its Medical Research Future Fund to pay for election promises and “pet projects” under proposals before federal Parliament, Labor has claimed. AMA President Professor Brian Owler said decisions about which research projects would be funded needed to be made at arm’s length from the minister.

Help for violence victims, Northern Territory News, 5 June 2015
A new resource to assist doctors in providing better support for victims of family violence was launched by the AMA at the AMA National Conference. AMA President Professor Brian Owler said the medical profession had a key role to play in the early detection, intervention and treatment of patients who has experience family violence.

Experts fear flu season shaping as the worst on record, The Saturday Age, 6 June 2015
The first five months of 2015 have been the worst on record for influenza, with experts warning Australia could be in for a rotten flu season. AMA Chair of General Practice Dr Brian Morton said Australia tended to follow the northern hemisphere’s flu season, which had been severe due to the emergence of new flu strains.

Banned flu drug still being given to children, Sunday Mail Brisbane, 7 June 2015
A disturbing number of doctors have ignored multiple warnings against administering the flu vaccine Fluvax to children younger than five years, even though there are safe alternatives. AMA President Professor Brian Owler said this risked undermining an otherwise safe vaccine schedule.

Leaked trade deal terms prompt fears for Pharmaceutical Benefits Scheme, The Guardian, 11 June 2015
The leak of new information on the Trans-Pacific Partnership agreement (TPP) shows the mega-trade deal could provide more ways for multinational corporations to influence Australia’s control of its pharmaceutical regulations. AMA president Professor Brian Owler said while doctors were very concerned at the possible effects on Australia’s health care system, their fears were routinely dismissed by Trade Minister Andrew Robb.

Save the planet for better health, The Canberra Times, 24 June 2015
The biggest boost to public health this century could come from action to tackle climate change, such as shutting down coal-fired power plants and designing better cities, according to a Lancet Commission report. AMA President Professor Brian Owler said the Australian health system was not prepared for climate change.

‘Whistleblowers’ challenge Australia’s law on reporting refugee conditions, CNN, 2 July 2015
More than 40 doctors, nurses, teachers, and other humanitarian workers have signed an open letter to the Australian government, challenging a new bill that could put whistleblowers in jail for disclosing the conditions of Australian detention centres. AMA President Professor Brian Owler said the act puts doctors in a dilemma when treating detainees and asylum seekers if they have concerns about the provision of their health care.

Medibank dust-up sparks care debate, The Saturday Age, 11 July 2015
AMA President Professor Brian Owler said the contract clauses being pushed by Medibank Private that put financial risk for unplanned patient readmissions and preventable falls back on private hospitals are evidence the newly listed market leader has shifted its priority to shareholders.

Radio

Professor Brian Owler, 666 ABC Canberra, 28 May 2015
AMA President Professor Brian Owler talked about the issues surrounding the bulk billing of GPs. Professor Owler said a doctor can bulk bill and this means they can accept the amounts from Medicare.

Dr Brian Morton, 5AA, 3 June 2015
AMA Chair of General Practice Dr Brian Morton discussed medicines on the drug subsidy scheme will rise in price on July 1. Dr Morton said that any medicine that currently costs consumers less than $36 will be hit by the rise.

Professor Brian Owler, 702 ABC Sydney, 4 June 2014
AMA President Professor Brian Owler talked about Medicare. Professor Owler said there have been a number of reviews but, these have never really been dealt with the schedule as a whole.

Professor Brian Owler, ABC Classic FM, 11 June 2014
AMA President Professor Brian Owler discussed health issues including the “Don’t Rush” road safety campaign, neurosurgery, and vaccinations.

Dr Brian Morton, 3AW, 29 June 2015
AMA Chair of General Practice Dr Brian Morton talked about issues with Dr Google. Dr Morton said it could be beneficial when trying to understand a treatment a patient is undergoing.

Professor Brian Owler, 612, 13 July 2015
AMA President Professor Brian Owler discussed diabetes in Australia. Professor Owler said the majority of type 2 diabetes cases were preventable and encouraged people to eat healthier food and get regular exercise.

Television

Prof Brian Owler, ABC Brisbane, 29 May 2015
The AMA has warned that doctors’ fees could go up if the freeze on Medicare rebates for GP visits continues, and that even patients with private health insurance could end up paying more

Prof Brian Owler, Channel 9, 31 May 2015
A new online tool to help doctors identify and respond to family violence has been rolled out. The resource launched by the AMA allows doctors to provide information on support services.

Dr Stephen Parnis, Channel 7, 13 June 2015
AMA Vice President Dr Stephen Parnis discussed warnings Victoria was on the verge of a whooping cough epidemic. Dr Parnis said deaths from whooping cough were not common but were entirely avoidable.

Dr Brian Morton, Channel 10, 20 June 2015
AMA Chair of General Practice Dr Brian Morton warned of a spike in emergency department admissions, with the price of some of the most common Pharmaceutical Benefits Scheme prescription medications set to rise.

AMA Family Doctor Week

This week is AMA Family Doctor Week, a celebration of the hard work and dedication of GPs across Australia and a reminder to the community of the vital role played by local family doctors in keeping Australians healthy.

This year’s theme is You and Your Family Doctor: the best partnership in health. It promotes the important and unique role that family doctors play in the provision of patient centred care. The AMA Family Doctor Week 2015 poster highlighting this year’s theme is available to download and display in your reception areas and consulting rooms, and on your websites.

Book your seat now to attend the AMA President’s National Press Club Address in Canberra on Wednesday 22 July 2015. Professor Brian Owler will use his speech to outline priorities to strengthen the Australian health system. Acknowledging the political and economic realities that confront Governments, Professor Owler will set out practical, affordable, and achievable policies and actions that the AMA believes will best serve the health needs of the Australian population.

Additional events and activities planned during Family Doctor Week, include:

AMA Family Doctor Week 2015 youtube videos.
Daily media releases highlighting general practice issues.
A general practice themed edition of the Medical Journal of Australia.
General practice themed articles in Australian Medicine.

For more information about Family Doctor Week 2015 and its events and to download your poster, visit the AMA’s Family Doctor Week Landing Page.

Follow all the Family Doctor Week action on Twitter by using #amafdw15

Geographical mobility of general practitioners in rural Australia

Key to improving the poorer health status that characterises people in rural areas is ensuring equitable access to appropriate health care.1–3 However, this requires recruiting and retaining an adequate supply of appropriate health workers, which is known to be difficult in rural and remote areas.4,5 While considerable research has been conducted on the factors and barriers that facilitate and impede medical workforce supply in rural areas, there is a dearth of quantitative empirical evidence relating to the dynamics of general practitioner mobility patterns — specifically, which doctors move where, at what frequency, and why.

Understanding GP mobility is important because of its impact on workforce availability — both in the origin area (place from which the doctor moved) and the destination area. Considerable investment is made by governments into health programs specifically oriented towards improving the recruitment and retention of doctors in rural areas, with the goal of maximising movement into and minimising movement away from rural areas.

Despite a large body of social sciences literature on both inter- and intraregional migration, its applicability to the health workforce is not clear. Unfortunately, research literature focusing specifically on medical and health workforce mobility is scant. Internationally, sentinel works related to doctors include one 20-year national study in the United States on the volume and location of rural moves, although covariate analysis was not reported.6 Subsequent publications from the same dataset have focused on mobility in and out of areas of high need and between four major regions of the US.7,8 Similarly, a few Canadian studies have focused specifically on interregional (large distance) migration patterns of doctors without a focus on rural areas per se.9,10 Much of the extant health mobility literature has concentrated on the international migration of doctors from developing to developed countries,11 focusing particularly on ethical issues, the impact of the loss of doctors on reduced access to health care in origin countries, and the roles of these international medical graduates (IMGs) in destination countries.12–14

Associations between mobility and covariates have rarely been quantified,9,15,16 with younger age being the dominant common factor linked with increased mobility. Much less has been written about the mobility of Australian doctors,17,18 and no specific mobility data have been published for the non-medical health workforce. The reasons for this lack of literature include limited access to data at a suitable geographical scale; lack of longitudinal studies from which to monitor doctors’ movements; inherent difficulties of tracking individual doctors without linked datasets; and insufficient numbers of moves to generate valid and reliable results.

In an attempt to redress this paucity of evidence, we aimed to describe the geographical mobility of GPs in Australia both within rural areas and between rural and metropolitan areas. We describe where doctors are moving to and from, how many doctors are moving, and the characteristics of doctors who move. Such research helps to provide the basis for better understanding the role of push and pull factors behind why doctors move and what has influenced their decision to move. This in turn assists policymakers to design policies targeting medical workforce maldistribution in rural and remote areas.

Methods

We used data from the large Medicine in Australia: Balancing Employment and Life (MABEL) survey, conducted within the Centre for Research Excellence in Medical Workforce Dynamics. MABEL is Australia’s national longitudinal survey of doctors, which collects similar data in annual waves from mostly the same panel of doctors (https://mabel.org.au). MABEL was approved by the University of Melbourne Faculty of Business and Economics Human Ethics Advisory Group (Reference 0709559) and the Monash University Standing Committee on Ethics in Research Involving Humans (Reference CF07/1102 – 2007000291).

Study participants

The first wave of the MABEL survey, in 2008, invited the participation of the entire medical workforce, and 3906 GPs (19% of Australia’s GP workforce) completed the initial survey. Subsequent annual waves of previous respondents saw a 70%–80% retention rate, including the annual addition of new GPs to the dataset and returning participants who missed at least 1 year. This study used data from waves 1–5 (2008 to 2012), comprising 3502 (wave 2), 3514 (wave 3), 3287 (wave 4) and 3361 (wave 5) responses. Detailed non-response bias was conducted for waves 1 and 2.19,20 The most notable observable bias was a significant increase in the number of responses from doctors in remote areas, attributable to a financial incentive ($100 honorarium) to maximise participation of these GPs. GP registrars were excluded, because many do not have autonomy over their work location during their fellowship training.

Locational measures

Locational data were geocoded to a specific town or suburb. Each GP’s self-reported work location (< 1% missing data) was used to calculate mobility, by comparing their location between each annual wave. Mobility was classified using the seven-category Modified Monash Model scale,21 which combines population size of settlements (< 5000; 5000–15 000; >15 000–50 000; and > 50 000) with the Australian Statistical Geography Standard — Remoteness Areas (ASGS-RA) classification, to define a geographical classification of most relevance to Australian GPs.22 Locational changes within the same rural town or within metropolitan areas were all classified as “no change”.

Statistical analysis

Analysis was conducted in two distinct parts. First, all GP respondents were analysed using only their origin location and destination location, aggregated using the Modified Monash Model. GPs who participated in all five waves thus contributed four origin–destination pairs. Second, mobility outcomes were assessed for their association with additional key covariates of age (< 40, 40–54, ≥ 55 years), sex, having a life partner, IMG status and location restrictions as part of their registration, business relationship within the practice, and length of stay in that location. For this analysis, mobility was categorised as no change (metropolitan), no change (rural), change from rural to metropolitan, change from metropolitan to rural and change within rural areas (where “rural” encompasses all six non-metropolitan categories, from regional to very remote). Annual “risk” of moving between rural and metropolitan locations was measured using total number of observed years. Panel (clustered) logit models were additionally used to measure the associations between these risk factors and either leaving rural areas (models 1 and 2) or leaving metropolitan areas (models 3 and 4). Length of stay was removed from models 2 and 4 because of its strong multicollinearity. All calculations were performed using StataSE 12 (StataCorp) with a 5% significance level.

Results

Between wave 1 and wave 5, a total of 5844 GPs completed at least one MABEL survey. Of these, 1810 GPs completed all five waves, providing 7240 mobility observations. A further 805 GPs missed one survey (2415 mobility observations), 786 completed three out of five waves (1572 observations) and 887 completed only two waves. Additionally, 1470 GPs completed only one MABEL survey, contributing no mobility data. In total, there were 12 114 mobility observations, which decreased to 10 900 after GP registrars were removed from the dataset.

Overall, fully trained GPs were observed to have a mobility rate of about 4.6% (507/10 900). In comparison, GP registrars had a mobility rate of 21% (253/1214).

Box 1 summarises the number of locational changes for the five waves (2008–2012). Cells along the main diagonal represent GPs who did not change their location between waves. This approximation of retention within each category shows a decreasing rate as the degree of geographical rurality or remoteness increases. In cells to the right of the diagonal, the destination location is increasingly remote compared with the origin location (eg, large rural to remote), and cells to the left of the diagonal capture GPs who have moved to decreasingly remote locations (eg, small rural to medium rural). The first row captures all GPs (103) who moved from a metropolitan origin to a non-metropolitan destination during the five-wave period; 98.6% (7015) stayed within a metropolitan location. The first column of Box 1 captures all GPs who moved from a regional, rural or remote origin to a metropolitan destination (133). Just under half of all observed location changes were between non-metropolitan and metropolitan locations (236). There were 478 observations originating from a remote or very remote location, with 417 (87%) GPs remaining within the same location in the next year, and most (45 [74%]) of the 61 movers remaining within a non-metropolitan area.

Aggregate counts of GPs and the characteristics of the movers and stayers are summarised in Box 2. The observed risk (per observed year) of moving to a non-metropolitan area was 1 in 75 for metropolitan GPs. In contrast, the risk of losing non-metropolitan GPs to metropolitan areas was 1 in 31. Of the 271 GPs who moved within non-metropolitan Australia, 77 moved to regional centres (population over 50 000), but only 24 left regional centres for a smaller rural or remote location. A further 18 GPs moved from a rural to a remote location and 35 moved from remote practice to small or large rural locations.

Box 2 also shows the characteristics of GPs who moved compared with GPs who stayed in their original location. There was a small increased risk of moving for the youngest group of GPs, while sex and having a life partner had minimal association with increased mobility. IMGs had an increased risk of moving; even more so for the subgroup who were restricted in their location choice. GPs who were also principals of their practice were much less likely to move, while contract employees were highly mobile away from regional, rural and remote areas.

Box 3 shows the association between observed significant location changes and GP characteristics, with two binary outcomes tested (leaving rural and leaving metropolitan practice). Younger rural GPs were significantly more likely to leave rural practice than older rural GPs. There were no other significant associations between GP mobility and age or between GP mobility and sex and family status. The risk of moving to a metropolitan area was 2.5 to three times higher for rural GPs in their first 3 years in a location than for those who had been in a location for 4 years or more. Both contract employees and salaried employees were highly likely to leave rural practice, while salaried employees were most likely to leave metropolitan areas. Compared with GPs in regional centres, those in small and medium rural towns were significantly more likely to leave rural practice, while GPs in very remote areas had a lower risk of moving to a metropolitan area. The omission of length of stay strengthened the mobility odds ratio of all employment types, compared with practice principal or partners, and the association between small population size and an increased risk of turnover in rural areas. Additionally, IMGs restricted in their practice location had a higher risk of moving than Australian-trained, unrestricted GPs.

Discussion

This study provides the first national evidence of rural GP mobility over an extended period. Moreover, we investigated whether individual- and practice-level covariates were associated with the propensity to move. We used the seven-category Modified Monash Model to show which groups of GPs exhibit the highest mobility and are most at risk of leaving rural practice, or most likely to leave metropolitan areas for rural practice.

GPs in small rural towns and remote areas had higher mobility rates. While remote and very remote GPs had the highest mobility rate, this group was not significantly at increased risk of leaving non-metropolitan practice completely. Rural GPs practising in small towns (less than 5000 residents) and in medium-sized towns (up to 15 000 residents) were most at risk of moving to metropolitan areas. These results further support the need for policies to better target GPs in small rural communities and differentiate them from GPs in large regional centres.21–23

GPs most at risk of moving, both from and to rural areas, are those who have only been in their current location for up to 3 years, similar to recent findings in rural New South Wales.24 That is, once a GP has been settled in either a rural or metropolitan location for at least 3 years they are less likely to move.

Additionally, younger GPs (under 40 years) and those working as either salaried or contract employees are more likely to be mobile. Sex and family status were not associated with mobility.

When more data become available, we plan to investigate whether there is any association between mobility and GPs’ satisfaction with the schools that are available for their dependents.

Unrestricted rural IMGs had a slightly but non-significantly increased risk of leaving rural practice compared with locally trained unrestricted GPs. Further investigation of the strength of association between mobility and changed restriction (overseas trained) or bonding (Australian trained) status is also planned.

Our study was strengthened by the removal of GP registrars. GP registrars frequently have minimal control over their training locations, and so their moves are not equivalent to observed moves of GPs who have independently chosen to practise in a specific location. GP registrars are highly mobile, both between metropolitan and rural areas as well as between different rural areas. In this study, GP registrars were observed to have a mobility rate about five times higher than the annual mobility rate for fully trained GPs.

The main limitation of this study was our use of a self-selected cohort. Annually, the MABEL survey includes about 16%–19% of all Australian GPs, with 75%–80% of participants returning each year (potential selection or attrition bias). Despite having five annual waves of data, the number of GPs observed changing work location was still relatively small. In total, only 236 GPs were observed moving in either direction between rural and metropolitan areas. Larger numbers of moves are observable using more complete datasets like the Australian Health Practitioner Regulation Agency dataset,18 but this approach only provides very limited covariate information and includes large bias from the highly mobile GP registrar subgroup. The true mobility rate of rural–urban relocations for Australia’s GP population may be different to the 3.2% (rural origin) and 1.3% (urban origin) observed annual rates in our study. More observed moves and sophisticated panel data analysis will be possible as additional MABEL data become available.

Increasing workforce supply and maintaining the existing rural medical workforce remains a key health issue in improving rural health in Australia. For several decades now, the Australian Government has made considerable investment in training more medical graduates, exposing these new doctors to more rural experience during their training, and increasing GP fellowships, rural bonded scholarships and rural retention payments.25 Nonetheless, little longitudinal evidence exists on how long to expect GPs to remain in different locations, what locations GPs move from and to, and personal and organisational factors associated with mobility. Most existing evidence comprises only cross-sectional data on retrospectively identified factors and prospective intention.

Using the best available GP data, this study helps to understand who is most likely to move each year, how often moves occur and where they might move to and from. In particular, these results both highlight and quantify the strong association between mobility propensity and increasing rurality and remoteness of practice locations. Such evidence is useful in guiding more effective targeting of rural health policies and workforce planning and incentives.

1 Summary of origin–destination work location changes* for all non-registrar general practitioners (annual survey, 2008–2012)

	Destination location, no. (%)
Origin location	Metropolitan	Regional centre	Large rural	Medium rural	Small rural	Remote	Very remote	Total observations (n = 10 900)

Metropolitan	7015 (98.6%)	38 (0.5%)	9 (0.1%)	11 (0.2%)	30 (0.4%)	10 (0.1%)	5 (0.1%)	7118 (100%)
Regional centre	15 (2.0%)	695 (94.7%)	4 (0.5%)	6 (0.8%)	7 (1.0%)	4 (0.5%)	3 (0.4%)	734 (100%)
Large rural	28 (3.5%)	20 (2.5%)	741 (91.6%)	6 (0.7%)	10 (1.2%)	2 (0.3%)	2 (0.3%)	809 (100%)
Medium rural	26 (3.7%)	21 (3.0%)	5 (0.7%)	633 (89.3%)	17 (2.4%)	3 (0.4%)	4 (0.6%)	709 (100%)
Small rural	48 (4.6%)	27 (2.6%)	14 (1.3%)	13 (1.2%)	943 (89.6%)	4 (0.4%)	3 (0.3%)	1052 (100%)
Remote	14 (4.0%)	3 (0.9%)	5 (1.4%)	7 (2.0%)	5 (1.4%)	311 (89.1%)	4 (1.2%)	349 (100%)
Very remote	2 (1.6%)	6 (4.7%)	2 (1.6%)	4 (3.1%)	3 (2.3%)	6 (4.7%)	106 (82.2%)	129 (100%)

* There were an additional 51 work location changes observed within non-metropolitan areas where the location category was unchanged.

2 Characteristics of general practitioners who remain in or change their work location (annual survey, 2008–2012)

						Per-year “risk”
Origin location characteristic	No change: metropolitan	Metropolitan to rural*	Rural to metropolitan	No change: rural	Moved within rural	Rural to metropolitan	Metropolitan to rural

Total observations	7015	103	133	3378	271	3.20% (1 in 31)	1.34% (1 in 75)
Age group
< 40	751 (11%)	16 (16%)	28 (21%)	335 (10%)	44 (17%)	6.3% (1 in 16)	1.9% (1 in 53)
40–54 years	3171 (46%)	41 (40%)	68 (52%)	1722 (52%)	136 (52%)	3.2% (1 in 31)	1.2% (1 in 85)
55+ years	3006 (43%)	45 (44%)	35 (27%)	1281 (38%)	84 (32%)	2.3% (1 in 44)	1.4% (1 in 73)
Sex and family circumstances
Male and partner	3007 (45%)	40 (42%)	64 (50%)	1835 (58%)	136 (54%)	2.9% (1 in 35)	1.2% (1 in 83)
Female and partner	2783 (42%)	38 (40%)	51 (40%)	1024 (32%)	87 (35%)	4.0% (1 in 25)	1.3% (1 in 79)
Male and no partner	306 (5%)	8 (8%)	5 (4%)	141 (4%)	17 (7%)	2.7% (1 in 37)	2.4% (1 in 42)
Female and no partner	517 (8%)	10 (10%)	8 (6%)	180 (6%)	10 (4%)	3.8% (1 in 27)	1.8% (1 in 57)
Training location and place restriction†
Local, unrestricted	5282 (80%)	66 (71%)	70 (54%)	2226 (70%)	145 (56%)	2.6% (1 in 38)	1.1% (1 in 87)
IMG, restricted	295 (4%)	11 (12%)	35 (27%)	416 (13%)	60 (23%)	6.2% (1 in 16)	3.3% (1 in 30)
IMG, unrestricted	1022 (15%)	16 (17%)	24 (19%)	519 (16%)	54 (21%)	3.6% (1 in 28)	1.4% (1 in 72)
Business relationship
Principal, partner	2119 (33%)	15 (16%)	16 (13%)	1211 (39%)	38 (18%)	1.2% (1 in 87)	0.6% (1 in 155)
Associate	664 (10%)	11 (12%)	13 (11%)	469 (15%)	20 (9%)	2.4% (1 in 41)	1.5% (1 in 67)
Salaried employee	371 (6%)	13 (14%)	15 (13%)	307 (10%)	36 (17%)	3.9% (1 in 26)	3.1% (1 in 32)
Contract employee	3261 (51%)	52 (57%)	76 (63%)	1086 (35%)	119 (56%)	5.4% (1 in 19)	1.5% (1 in 68)
Length of stay in origin location
≤ 1 year	533 (8%)	24 (26%)	40 (33%)	416 (13%)	68 (29%)	6.8% (1 in 15)	3.8% (1 in 26)
2–3 years	722 (11%)	18 (19%)	32 (26%)	414 (13%)	50 (21%)	5.8% (1 in 17)	2.2% (1 in 45)
4–6 years	894 (14%)	14 (15%)	11 (9%)	406 (13%)	47 (20%)	2.2% (1 in 46)	1.4% (1 in 70)
7–10 years	917 (14%)	8 (9%)	12 (10%)	396 (13%)	25 (11%)	2.6% (1 in 39)	0.8% (1 in 125)
11+ years	3491 (53%)	30 (32%)	26 (21%)	1521 (48%)	48 (20%)	1.5% (1 in 67)	0.8% (1 in 125)

IMG = international medical graduate. * Rural includes regional, rural or remote. † Locally trained and restricted doctors (that is, Australian-trained graduates who are bonded to initially work in a rural area) have been removed from this analysis because there were very few observations in this group.

3 Panel logit models of general practitioners who move between metropolitan and rural work locations (annual survey, 2008–2012)

Origin location characteristic

Leaving rural,* model 1† (OR [95% CI])

Leaving rural, model 2† (OR [95% CI])

Leaving metropolitan, model 3‡ (OR [95% CI])

Leaving metropolitan, model 4‡ (OR [95% CI])

Age group (reference: 55+ years)

< 40 years

2.06 (0.79–5.34)

2.85 (1.09–7.43)**

0.62 (0.30–1.27)

1.11 (0.57–2.14)

40–54 years

1.62 (0.75–3.48)

1.68 (0.76–3.72)

0.61 (0.35–1.04)

0.76 (0.45–1.26)

Sex and family status (reference: male and partner)

Female and partner

1.07 (0.54–2.10)

1.13 (0.56–2.27)

0.97 (0.57–1.63)

0.90 (0.54–1.50)

Male and no partner

1.35 (0.35–5.27)

1.51 (0.37–6.14)

1.32 (0.50–3.46)

1.56 (0.64–3.79)

Female and no partner

0.62 (0.15–2.47)

1.07 (0.29–3.91)

1.26 (0.56–2.80)

1.20 (0.54–2.65)

Training location and place restriction§ (reference: Australia, unrestricted)

International, restricted

0.91 (0.41–2.05)

1.57 (0.73–3.36)

1.59 (0.74–3.41)

2.65 (1.29–5.43)††

International, unrestricted

1.39 (0.58–3.32)

1.92 (0.79–4.66)

1.02 (0.54–1.92)

1.33 (0.73–2.41)

Business relationship (reference: principal, partner)

Associate

1.18 (0.39–3.61)

1.76 (0.58–5.40)

1.83 (0.76–4.37)

2.43 (1.05–5.60)**

Salaried employee

3.89 (1.15–13.16)**

7.23 (1.94–26.89)††

3.22 (1.33–7.82)††

4.94 (2.14–11.40)††

Contract employee

5.18 (1.98–13.56)††

8.38 (2.72–25.78)††

1.47 (0.74–2.92)

2.20 (1.16–4.19)**

Length of stay in origin location (reference: 11+ years)¶

≤ 1 year

3.40 (1.34–8.62)††

—

4.46 (2.11–9.42)††

—

2–3 years

3.73 (1.41–9.85)††

—

2.63 (1.25–5.53)**

—

4–6 years

1.03 (0.36–2.94)

—

2.16 (1.04–4.48)**

—

7–10 years

0.86 (0.30–2.48)

—

1.24 (0.54–2.85)

—

Modified Monash rural scale (reference: regional centre)

Large rural

2.25 (0.78–6.50)

2.68 (0.88–8.20)

Medium rural

3.04 (1.02–9.09)**

3.46 (1.09–10.99)**

Small rural

3.96 (1.41–11.14)††

5.03 (1.61–15.78)††

Remote

1.22 (0.34–4.34)

1.27 (0.34–4.81)

Very remote

0.20 (0.01–3.03)

0.23 (0.01–4.17)

* Rural includes regional, rural and remote. † Dependent variable outcome = moves from rural/remote to metropolitan (n = 133). ‡ Dependent variable outcome = moves from metropolitan to rural/remote (n = 103). § Locally trained and restricted doctors (that is, local graduates who are bonded to initially work in a rural area) have been removed from this analysis because there were very few observations in this group. ¶ Length of stay was removed from Models 2 and 4 because of its strong multicollinearity. ** P < 0.05. †† P < 0.01.

General practice after-hours incentive funding: a rationale for change

After-hours incentive funding was made available to accredited general practices in 1998 as a foundation component of the Practice Incentives Program (PIP). The PIP after-hours practice incentive payment was intended to “help resource a quality after hours service and compensate practices that make themselves available for longer hours, in recognition of the additional pressures this entails”.1 Funding for each participating practice was based on the formula shown in Box 1. The model thus predominantly focused on access to after-hours care and comprised four main components:

a practice’s standardised whole patient equivalent (SWPE) — the sum of the fractions of care provided to practice patients weighted for the age and sex of each patient
how that practice ensured 24/7 care, from arranged external provision (stream 1) to self-provision only (stream 3)
the location of the practice, based on its Rural, Remote and Metropolitan Areas (RRMA) classification
the value per SWPE ($2).

In 2010, the PIP was audited by the Australian National Audit Office (ANAO).2 In an analysis of data provided by Medicare, the ANAO estimated that 14.9% of practices were non-compliant with respect to after-hours incentive payments between the financial years 2005–06 and 2008–09, the highest level of non-compliance across 12 PIP components. The Practice Nurse Incentive Program payments, at 9.5% non-compliance, were second highest. The ANAO investigated the potential of identifying practices at high risk of non-compliance for after-hours incentive payments in 34 practices deemed “high risk”. These practices were deemed high risk because of little evidence of actual after-hours service provision based on Medicare billings, while as stream 3 practices under PIP (Box 1), they were supposed to provide 24/7 care. On further investigation of these practices by random after-hours calls, only half provided at least a phone number at which a practice doctor could be contacted. The ANAO considered that secondary sources of information were imperative in ensuring practice compliance.

After-hours incentive funding and Medicare Locals

Under the aegis of the Commonwealth Government’s 2011 national health reforms to promote local decision making, Medicare Locals were delegated responsibility for the funding and delivery of after-hours services in their constituencies from 1 July 2013. Each Medicare Local, including Tasmania Medicare Local (TML), had the opportunity to develop and/or implement the most applicable and relevant mechanism for their locale.

For TML, the local situation is complex as its constituency encompasses large urban practices through to small isolated practices across an entire state that is geographically challenging. Three factors led to TML’s decision to continue the existing PIP after-hours funding arrangements in the 2013–14 financial year while simultaneously developing a preferred mechanism to be implemented in subsequent years: the complexities of the service environment; the desire to implement a fair, transparent and auditable mechanism; and the immediate need to provide after-hours incentive funding.

As part of the development process of the new after-hours incentive funding model, the PIP mechanism was interrogated to gain an understanding of the groundswell of disaffection for it among Tasmanian general practitioners. In this article, we describe the determination of the drivers of the PIP after-hours incentive funding model and the implications of this mechanism when viewed in context of the available (objective) Tasmanian after-hours data.

Drivers of the Practice Incentives Program mechanism: practice size, funding stream and location

For a given-sized practice, the primary determinant of after-hours PIP was its stream as reflected in PIP payments calculated for a practice of 2000 SWPE by RRMA classification and stream (Box 2). The practice size of 2000 SWPE was chosen for simplicity and consistency with subsequent calculations. Stream could make up to a threefold difference in after-hours incentive payments for practices of the same SWPE and RRMA levels, as compared with a 1.5-fold difference for practices of a given SWPE and a given stream level located in the most disparate locales (RRMA 1/2 and RRMA 7).

Together, stream and location could give rise to a potential 4.5-fold difference in payments — in other words, the impacts are additive. For example, a practice with 2000 SWPE classified at RRMA 7 and stream 3 will have a PIP of $18 000 as compared with $4000 for the same-sized practice classified at RRMA 1/2 and stream 1.

The greatest impact on after-hours PIP, however, was practice size, with payments directly proportional to individual practice SWPE as reflected in PIP payments calculated for practices in RRMA category 1 by SWPE and stream (Box 3). For example, the after-hours PIP for a stream 1 practice classified at RRMA 1/2 with 2000 SWPE is $4000 as compared with $20 000 for a similarly classified practice with 10 000 SWPE; a fivefold difference in practice size giving rise to a fivefold difference in after-hours PIP.

Thus, the PIP after-hours incentive funding mechanism was a multiplicative model primarily driven by practice size (SWPE), and in which the impacts of the claimed method of provision of after-hours care (stream) and location were additive, but of decreasing importance.

Implications

For the PIP after-hours incentive funding mechanism to fulfil its stated aim, practice size should therefore be the primary determinant of the burden and pressures faced by practices after hours, followed by stream and location. Given that the role of SWPE in PIP after-hours funding has been a major source of contention among Tasmanian general practices, the relative importance of practice size to after-hours burden is open to debate. Core questions include:

how much does SWPE matter to after-hours on-call requirements and after-hours service provision?
is it really the individual practice SWPE that matters?
does one extra patient make that much difference during the on-call period or is the number of doctors available to share the burden of after-hours care a more relevant consideration?

Does size really matter? Insights from the 2013–14 Tasmanian After-Hours Practice Funding Scheme

The average full-time GP has been attributed a value of 1000 SWPEs annually.3 Given this accepted workload and to expedite subsequent analysis, the 92 Tasmanian practices in receipt of an after-hours incentive payment within the 2013–14 Tasmanian After-Hours Practice Funding Scheme (as at 31 December 2013), have been categorised into one of five SWPE bands, as specified in Box 4. The choice of SWPE bands in part reflects feedback received during the development of the Tasmanian General Practice After Hours Incentive Funding Model for 2014–15 that sustainable on-call care requires the availability of 4 or 5 full-time doctors. The breakdown was also supported by the distribution of Tasmanian general practices by practice size (SWPE) (individual data not shown due to commercial-in-confidence reasons). The average SWPE for Tasmanian practices was 3693.

Practices have also been classified under a new Tasmanian General Practice Location Classification (TGPLC), which was developed as a foundational element of the funding model given concerns about the applicability of the RRMA and other classifications in the Tasmanian context. The TGPLC is an eight-level classification: 1, major metropolitan centre; 2, major urban centre; 3, other urban centres; 4, urban fringe; 5, rural locations; 6, remote locations; 7, very remote locations; and 8, isolated.

Practice characteristics

In Tasmania, practice size becomes more restricted as level of remoteness increases. Large practices (SWPE bands 4 and 5) are only located in major urban locations (locations 1–3) under the TGPLC, whereas isolated areas only support small practices (SWPE band 1). Detailed data are not provided (due to commercial-in-confidence reasons). It is also evident that as practices become increasingly remote and isolated, the provision of 24/7 care becomes a necessity, with all practices in locations 7 and 8 of the TGPLC classified as stream 3. This observation arguably reflects the intent of stream 3, which was to support those practices that had no option but to provide 24/7 care.1 However, stream 3 practices occur in each TGPLC location category (1–8) and thus this categorisation does not of itself identify practices with unavoidable after-hours burden. In contrast, unavoidable after-hours burden is at least partially captured through a comprehensive and accurate location mechanism.

There was no obvious relationship between stream and practice size in Tasmanian practices providing after-hours care, with at least one practice from each SWPE band (1–5) represented in each stream (1–3). While any practice in SWPE band 3 or higher theoretically has the in-house capacity to provide sustainable 24/7 care (at least 4 or 5 full-time equivalent GPs), 23 of 35 stream 3 practices fall within SWPE band 1 or 2. These practices unquestionably face excessive on-call burden. Whether this burden is avoidable largely depends on the availability of viable alternative providers — that is, the existence of practices in the near vicinity to share the load.

Together, these data indicate the importance of determining the specific objectives of any after-hours incentive funding scheme and ensuring that the mechanism embodies those objectives — for example, support for (unavoidable) burden.

Performance by key determinants of Practice Incentives Program funding: practice size, funding stream and location

An analysis of objective data of after-hours service provision by general practices receiving after-hours incentive funding through TML provides further insights into the functioning of the 1998–2013 PIP after-hours funding scheme in relation to practice size, stream and location, and type of after-hours care.

Urgent after-hours attendances

Over the period 1 July 2013 to 31 December 2013, there is clear evidence that practice location, based on the TGPLC, has the strongest association with the number of urgent after-hours attendances per practice (Medicare item numbers 597 and 599), followed by stream. As assessed through simple linear regression, location explained 27% of the difference in urgent after-hours attendances between practices (P < 0.001) as compared with 9% for stream (P = 0.003). Practice size (SWPE band) had no explanatory value (R2 = 0.01; P = 0.39) (individual practice data not shown due to commercial-in-confidence reasons). The importance of practice location in the provision of urgent after-hours care is also reflected in the fact that the 18 practices located in non-urban localities (locations 5–8) accounted for almost two-thirds (926 of 1404) of urgent after-hours attendances.

On the basis of these results, and the fact that the most remote practices are smaller in size and stream 3 (on-call 24/7), rural and remote practices are, in general, facing greater burdens than urban practices after hours.

After-hours services to registered aged care facilities: a distinct form of after-hours activity

An interesting and marked contrast exists in relation to practice performance in the provision of care to immobile patients — for example, patients in residential aged care facilities (RACFs). First, the vast majority (2139 of 2423 [88.3%]) of after-hours RACF visits (Medicare item numbers 5010, 5028, 5049 and 5067) occurred in urban localities (locations 1–4) a finding consistent with the distribution of RACF bed numbers. Second, no relationship was found between increasing remoteness and number of after-hours RACF visits per practice (R2 = 0.00, P = 0.92), nor was a relationship found between number of after-hours RACF visits and a practice’s stream (R2 = 0.01, P = 0.36). Some stream 1 practices gave rise to some of the highest levels of RACF visits, while otherwise ensuring urgent on-call access. For some practices, this activity may be arising due to formal arrangements with a nearby RACF. A relationship was, however, observed between number of RACF visits per practice and SWPE band, although it was limited, with practice size explaining 6% of the difference in number of RACF visits per practice between practices (P = 0.02). Some of the smallest practices gave rise to some of the highest levels of RACF visits (data not shown due to commercial-in-confidence reasons). Again, this could be due to formal arrangements.

Summary

Tasmanian data indicate that practice location is the primary predictor of on-call burden — that is, the burden increases as remoteness increases. Conversely, RACF visits, which are greater in number than after-hours attendances, predominantly occur in urban locations, but location is not a predictor of individual practice activity. Neither practice size (SWPE band) nor practice stream appear to be strong independent predictors of the provision of any form of after-hours care, although there are small positive trends for numbers of RACF visits and urgent on-call attendances. This trend reflects the fact that across SWPE bands and streams, there is a spectrum of providers (those that do and do not provide urgent care) and practices (ranging from those that provide minimal after-hours RACF visits to those that provide extensive after-hours RACF visits). These results were underpinned by relationships between location and stream (all very remote and isolated practices being stream 3), and between location and practice size (large practices > 6000 SWPE only being located in major urban locations).

Conclusion

The PIP after-hours incentive funding mechanism operating as at 30 June 2013 did not preferentially support practices that provide after-hours care. An after-hours incentive funding mechanism that recognises those practices that have no alternative but to provide 24/7 care is needed. Use of streams or tiers in the mechanism is considered inappropriate, potentially amounting to a perverse incentive. RACF visits should be considered an important but distinct form of after-hours care in an incentive funding mechanism. Finally, demands for transparency and use of auditable data are well justified.

1 Calculation of the Practice Incentives Program AHPIP

AHPIP = $2.00 × SWPE × stream × (1.00 + RL)

Stream = 1 means that the practice ensures access to 24/7 care

Stream = 2 means that the practice ensures access to 24/7 care and provides minimum specified levels of care (based on SWPE and hours of after-hours care provision)

Stream = 3 means that the practice provides 24/7 care

RL1 = 0; RL2 = 0; RL3 = 0.15; RL4 = 0.20; RL5 = 0.40; RL6 = 0.25; RL7 = 0.50

AHPIP = after-hours practice incentive payment. SWPE = standardised whole patient equivalent (practice based). RL = rural loading (based on the Rural, Remote and Metropolitan Areas classification).

2 After-hours incentive payments for 2000 standardised whole patient equivalents by stream and Rural, Remote and Metropolitan Areas (RRMA) classification

3 After-hours incentive payments for Rural, Remote and Metropolitan Area 1 by stream and standardised whole patient equivalent (SWPE)

4 Proportion of Tasmanian general practices in the After Hours Practice Funding Scheme by standardised whole patient equivalent (SWPE) band

SWPE band	SWPEs	No. (%) of general practices (n = 92)

1	≤ 2000	31 (33.7%)
2	2001–4000	30 (32.6%)
3	4001–6000	15 (16.3%)
4	6001–8000	10 (10.9%)
5	8001 +	6 (6.5%)

State-based legal requirement for Schedule 8 prescriptions: why so complicated?

Inconsistent prescription requirements between Australian states and territories create unnecessary complexity for health professionals

In Australia, medicines defined as Schedule 8 (S8) under the Standard for the Uniform Scheduling of Medicines and Poisons are strictly regulated because of the high risk of misuse and/or physical and psychological dependence associated with them.1 They have to be prescribed, dispensed, documented and destroyed in specific ways that are in compliance with each state and territory’s different drug regulations. S8 medicines are under stricter control than Schedule 4 (S4) medicines (other prescription-only drugs), for which requirements have been standardised between states and territories.2,3

Australia has no central body to regulate the handling of S8 drugs. Although the Therapeutic Goods Administration (TGA) is the national body for the regulation of medicines, each state and territory self-regulates under the general principles established by the TGA and has its own interpretation and legislation regarding S8 drugs, resulting in varied prescribing requirements. The legal requirements for obtaining authority and writing prescriptions for S8 medicines are listed in Box 1 and Box 2: they are often difficult to find and are long and daunting to read.

Impact on practice

The establishment of a national registration agency, the Australian Health Practitioner Regulation Agency (AHPRA), in 2010 meant that Australian health professionals were allowed to freely practise in any state or territory. Greater mobility of health practitioners between jurisdictions has been accompanied by new problems.

First, to the best of our knowledge, prescribers newly relocated to a different state or who practise across more than one jurisdiction have no single, clear resource that documents the slight nuances in each state or territory’s regulations. Legal requirements for prescribing S8 drugs are not accessible in a prescriber-friendly manner. Pharmacists can guide prescribers on the regulations and legality of prescriptions; yet the same confusion applies to pharmacists who move interstate.

Second, travelling patients bringing an S8 prescription interstate might discover that a legal prescription in one state is not legal in another. The dispensing pharmacist would need to contact the medical practitioner in the patient’s home state to find a solution. If this could not be done, treatment would be delayed until a local prescription was obtained from a medical practitioner in the state the patient was visiting.

What can we do?

It may be impractical to unify health care legislation in Australia to eliminate the complexity. However, all states and territories could maintain individual regulations but unify the S8 legal requirements. Given that S4 requirements are standardised between the different states and territories, why are S8 requirements treated differently?

For the moment, resources highlighting state-based S8 requirements for prescribers should be made readily available. A comprehensive quick-reference guide, such as the table we provide here, minimises the ambiguity in legal requirements for health practitioners, and its use may also reduce the amount of time spent by pharmacists and doctors in correcting non-compliant prescriptions.

1 Current requirements of Australian states and territories for obtaining authority to prescribe Schedule 8 medicines

State or territory

Required authority

Australian Capital Territory4

Write “Standing short term approval” for treatment of less than 2 months. For treatment of longer than 2 months, write “CHO approval number” followed by approval number from the ACT Chief Health Officer

New South Wales5

From Director-General NSW Health for psychostimulants, alprazolam, methadone, buprenorphine, flunitrazepam and hydromorphone

Northern Territory6

None

Queensland7

None

South Australia8

From SA Minister for Health for more than 2 months of treatment13

Tasmania9

From Tas Secretary for Health for more than 2 months of treatment14,15 (1 month for alprazolam, prior approval for psychostimulants, fentanyl and hydromorphone)

Victoria10,11

May need a Drugs and Poisons Regulation Group permit to prescribe to drug-dependent patients

Western Australia12

From WA Department of Health Chief Executive Officer for more than 2 months of treatment

2 Current legal requirements for prescribing Schedule 8 medicines in each state of Australia

Australian Capital Territory4

New South Wales5

Northern Territory6

Queensland7

South Australia8

Tasmania9

Victoria10,11

Western Australia12

Prescriber

Name

✓

Address

✓

Phone no.

✓

Qualification

✓

Signature

Patient

Name

✓

H (with initials)

✓

Address

✓

Date of birth

✓

Medicine

Name

✓

H (description of the medicine)

✓

H (description of the medicine)

Form

✓

Not specified

✓

Not specified

Strength

✓

Not specified

Quantity

✓

H (in words and figures)

✓ (in words and figures)

H (in words and figures)

✓ (in words and figures)

H (in words and figures)

Direction

✓

No. of repeats

✓

H (in words and figures)

Interval for repeats

✓

Date

✓

Only one S8 drug per prescription*

Multiple items allowed

✓

Not specified

✓

Multiple items allowed

✓

✓ = required. x = not required. H = information that must be written in the doctor’s own handwriting. * Exceptions apply: different forms of the same drug are acceptable.

Supporting the family doctor

At the recent AMA National Conference, during the Funding quality general practice – is it time for change? policy session, a number of speakers talked about the need to better support general practice, including through the adoption of different models of payment.

Some ideas were more radical than others, but all speakers emphasised the need to better reward and support the ‘usual GP’, that is, the family doctor, in providing quality, comprehensive and long-term care.

The policy session concluded with members of National Conference recognising that, while fee-for-service should remain the primary funding model for general practice, the AMA should remain open to other payment models that could complement this. This will guide the AMA’s contribution to the Primary Care Review that has been established by the Federal Government.

As GPs, we are facing a number of challenges, both now and into the future.

Our patients are ageing and developing multiple chronic conditions, and they want greater access to personalised health care.

Simultaneously, GPs are seeking a better work/life balance, increasingly working in larger practices and in multidisciplinary teams, and our traditional role is under threat from other health professionals that want to expand their scope of practice.

Practice viability is under threat with each funding cut and inadequate indexation – let alone the current four-year freeze on indexation. Quality care is poorly remunerated, and we are under ongoing pressure to deliver more with less, and for less.

We need to be able to spend the time on patients that they need, including to educate them on the benefits of good nutrition and being active, as well as informing them how to implement the lifestyle changes that will enable them to lead healthy lives. To identify and manage their risk factors. To hear their concerns and work with them in treating or managing a health issue. To plan and coordinate their care.

GPs need the comprehensive care they provide to be recognised and rewarded. We need to be remunerated in a way that supports and encourages us to continually do better.

The valuable role that we play as family doctors will be once again honoured by the profession, and highlighted to the community and Government in the coming weeks as we approach AMA Family Doctor Week (19-25 July).

Join us in this endeavour by downloading the Family Doctor Logo and using it on your signature block or web profile. Members can download it here: article/ama-family-doctor-logo.

You can also download the Family Doctor Week poster for printing or displaying on your website. It can be downloaded from here: family-doctor-week-2015.

The AMA will take advantage of a number of opportunities in the coming months to advocate for improved funding arrangements to support both the profession and our patients. These include in providing input to the MBS Review Taskforce, the Primary Health Care Advisory Group and the House of Representatives Standing Committee on Health inquiry into Chronic Disease Prevention and Management in Primary Health Care.

Our key objective will be to ensure that the outcomes of these reviews support, not devalue, the family doctor in caring for patients.

Ensuring safe exercise participation in clinical populations: who is responsible?

An overview of recent advances and ongoing challenges in exercise participation-related risk

The benefits of regular physical activity are well established, and the advice to “move more” can be offered to most individuals with little risk. Exercise, where there is a structured movement and activity plan, is recommended as cornerstone management for people with many chronic conditions, but it carries inherent risks that must be considered.1 The responsibility for managing this risk should be shared between primary health providers, patients and exercise professionals, but how well does this work in practice?

The best available evidence suggests the absolute risk of adverse events during exercise in an apparently healthy individual is very low at 0.1–1 adverse events for every 10 000 hours of exercise.2 However, this risk is higher in people with many common chronic conditions.1 In a study of commercial fitness centres, 52% of new members were identified as “higher risk” and 17% as “moderate risk” and in need of a modified exercise prescription,3 yet there is an alarming lack of capacity and effective processes within the fitness industry to manage the increased risk in clients who present with chronic diseases. The highest level of fitness or exercise qualification commonly found in gymnasiums and fitness centres is certifications held by exercise instructors and personal trainers, but they have little or no capacity to manage increased risk (Box).

Historically, a common feature of exercise risk stratification systems is that anyone who is deemed to be at risk is encouraged to obtain clearance from their doctor before they commence exercise. This has placed general practitioners in a difficult position where they are asked to provide a “medical clearance to exercise”, without standardised guidelines. In the general practice setting, it is usually not feasible to establish a patient’s response to an exercise challenge or stress test, and making a judgement about risk on the basis of the available medical history is not always appropriate. Further, the GP may have limited information about the intended exercise program, and who will be responsible for the patient’s wellbeing. Indeed, patients themselves may not know the answer to these questions. GPs have been actively discouraged from providing clearance-to-exercise certificates on the basis that such a clearance represents a transfer of medicolegal responsibility from the exercise or fitness professional to the GP.4

In 2011, a new adult pre-exercise screening system (APSS) was developed by Exercise and Sports Science Australia, Sports Medicine Australia, and Fitness Australia. This system removes the requirement for higher-risk clients to seek a medical clearance. It has been replaced with an instruction to seek “guidance” from an appropriate medical or allied health professional. This reflects a shared responsibility for client care where exercise practitioners have a responsibility to satisfy themselves that they have sufficient information to provide a safe service for the client. However, problems with the use of the tool remain that require interprofessional collaboration and resolution to achieve further progress towards this goal.

Notably, a recent survey of fitness centres suggests that, in practice, the uptake of the new screening tool within the fitness industry has been poor. Of those fitness centres that responded (~10%), only 55% regularly applied the APSS tool, with only 65% regularly using any form of pre-screening at all.5 It is also unclear what type of “guidance” should be sought from medical or allied health professionals. For example, should a GP be providing instruction, and particularly restrictions, on the mode, intensity, duration and frequency of exercise? Or are they simply to provide an indication of the current clinical status of an individual? The former is likely beyond a medical practitioner’s scope and training; the latter beyond the expertise of the non-clinically trained exercise practitioner to safely interpret.

It is clear that an integrated risk-mitigation process remains to be developed. In the interim, it is necessary that GPs have some insight into the goals and limitations of the current system to support their decision making when asked to provide a medical clearance or guidance; or indeed when referring or advising a patient toward engagement in exercise. As a minimum, it is worthwhile for GPs to become aware of the risk-screening protocols and staffing profiles of fitness centres in their communities and to direct patients toward the most appropriate options. GPs can manage the many uncertainties around this process by actively engaging their clinical allies in this field — in accredited exercise physiologists and physiotherapists.

The best model ultimately involves strong referral networks, and shared responsibility for patient risk and outcomes between the medical, allied health and fitness sectors. To ensure the integration of safe and effective exercise services within primary health care, there is a need for relevant professional bodies to work together to establish clearer referral pathways and universal assessment and decision-making guidelines for the identification and management of higher-risk individuals when commencing exercise.

Professionals who work across the fitness industry and exercise health sector

Exercise instructors and personal trainers

Registration with Fitness Australia or an equivalent body requires a relevant fitness qualification (Certificate III in Fitness or higher) and current first aid and CPR certification. Exercise instructors and personal trainers are able to plan, demonstrate and supervise exercise programs for healthy clients, on both individual and group levels.

Exercise scientists

Exercise science is a bachelor level university qualification. University programs accredited by Exercise and Sports Science Australia (ESSA) enable exercise scientists to design and deliver exercise programs and assessments to meet the specific needs of apparently healthy clients, and to deliver exercise programs for clients with illness or injury that have been prescribed by an accredited exercise physiologist (AEP), physiotherapist or an appropriately qualified health professional.

Accredited exercise physiologists

AEPs are recognised allied health professionals who have completed university training in exercise science, pathophysiology and advanced clinical exercise practice. Exercise physiology university programs are accredited by ESSA; AEPs specialise in clinical exercise interventions for people at high risk of developing, or with existing, chronic and complex conditions or injuries.

Australia good, but can do better, on heart disease and stroke

Australia has one of the lowest mortality rates from cardiovascular disease in the developed world, but the nation has been told it needs to consider taxes on sugar-rich and unhealthy foods to combat rising obesity and diabetes.

Australia’s cardiovascular disease (CVD) mortality rate fell to 208 per 100,000 people in 2011, 30 per cent below the average among Organisation for Economic Co-operation and Development member countries of 299 per 100,000, and the potential years of life lost to circulatory diseases dipped to 372 per 100,000, 36 per cent below the OECD average of 581 per 100,000.

In a report released overnight, the OECD attributed the nation’s success in driving down deaths from heart attacks and stroke to accessible, high quality health care and effective public health policies, particularly in reducing smoking.

The Organisation said comprehensive tobacco control measures, including a hefty excise, mass media campaigns, advertising and smoking bans and, most recently, tobacco plain packaging laws, had helped drive the smoking rate down to 12.8 per cent last year, one of the lowest in the OECD and well below the average of 20.9 per cent among member countries in 2012.

But the OECD warned the nation needed to overcome several challenges if it was to cement and build upon its success in reducing CVD mortality.

It cautioned that Australia’s high obesity rate – 28.3 per cent, almost double the OECD average of 18 per cent – threatened to drive up the incidence of CVD unless it was addressed, and noted that the nation’s spending on preventive health measures had slipped to just 1.8 per cent of total health expenditure, well below the OECD average of 2.9 per cent.

In its first Budget, the Abbott Government abolished the Australian National Preventive Health Agency and absorbed its functions with the Health Department, heightening concerns of a loss of national focus and leadership on preventive health measures.

The OECD has also echoed warnings from the AMA about the dangers of deterring patients from seeing their doctor by imposing out-of-pocket costs.

AMA President Professor Brian Owler said the Government’s four-year freeze on Medicare rebates would create a patient co-payment “by stealth” by forcing doctors to reduce bulk billing and charge out-of-pocket (OOP) expenses.

The OECD said that Australian patients already faced higher than average out-of-pocket costs, and cautioned that “higher OOP costs will lead to a lower use of primary care services, particularly among the poor”.

Nonetheless, the Organisation said access to primary care in Australia was “generally good”, and the nation’s heavy use of cholesterol-lowering drugs – the highest in the OECD – showed there was ready access to medication.

The observation came two days after research was published estimating that 60,000 patients stopped taking cholesterol-lowering statins after the ABC television program Catalyst questioned their safety.

The OECD said Australians with CVD had access to good quality acute care. The 30-day case-fatality rate for acute myocardial infarction patients was 4.4 per cent, one of the lowest rates in the OECD, while case-fatality for stroke patients was around the OECD average and the proportion of stroke patients treated in dedicated facilities was higher than many other comparable countries.

The OECD said the country needed to curb the rise in obesity if it was to make further inroads into CVD fatality rates, and suggested it consider measures adopted in other countries, such as taxes on unhealthy or sugar-rich food and drinks and the development of nationally-co-ordinated health promotion programs.

Adrian Rollins