New prostate cancer clinical guidelines launched

Australian health professionals will now have access to evidence-based recommendations for using the prostate specific antigen (PSA) blood test to assess prostate cancer risk in patients.

The PSA Testing and Early Management of Test-detected Prostate Cancer: Guidelines for health professionals were developed in partnership with the Prostate Cancer Foundation of Australia (PCFA) and Cancer Council Australia and have now been approved by the National Health and Medical Research Council (NHMRC).

PCFA Chief Executive Officer, Associate Professor Anthony Lowe said contention about the PSA test has made it difficult for health professionals to take a consistent, evidence based approach to the test.

“The guidelines cut through the contention and provide guidance in relation to an individual man’s circumstances and on how to manage a patient if he requests and consents to taking the test,” he said.

The recommendations include:

Men considering a PSA should be given information about the benefits and harms of testing.
Men with an average risk who have decided to undergo regular testing after being informed of the benefits and harms should be offered PSA testing every 2 years from age 50-69. If the total PSA concentration is greater than 3ng/mL then further investigation should be offered.
Men over 70 who have been informed of the benefits and harms of testing and who wish to start or continue regular testing should be informed that the harms of PSA testing may be greater than the benefits of testing in their age group.
Men with a father or one brother who has been diagnosed with prostate cancer has 2.5 – 3 times higher than average risk of developing the disease. If these men have decided to undergo regular testing after being informed of the benefits and harms, they should be offered PSA testing every 2 years from age 45 to 69.
Men with a father and two or more brothers who have been diagnosed with prostate cancer have at least 9 to 10 times higher than average risk of developing the disease. If these men have decided to undergo regular testing after being informed of the benefits and harms, they should be offered PSA testing every 2 years from age 40 to 69.
In a primary care setting, digital rectal examination is not recommended for asymptomatic men in addition to PSA testing however this may be an important assessment procedure if referred to a urologist or other specialist for further investigation.
Mortality benefit due to an early diagnosis of prostate cancer due to PSA testing isn’t seen within less than 6-7 years of testing so PSA testing isn’t recommended for men who are unlikely to live another 7 years (subject to health status).
A PSA testing decision aid for men and their doctors is under development by PCFA and Cancer Council Australia.

Other recommendations also include further investigations if the PSA concentration is above 3 ng/mL; prostate biopsy and multiparametric MRI; active surveillance and watchful waiting.

The report says there is no evidence to support a national PSA screening program to all men of a certain age group.

Cancer Council Australia CEO, Professor Sanchia Aranda says use of the guidelines will hopefully reduce the level of over-treatment.

“The NHMRC’s Information Document for health professionals, recommended as a companion document to the guidelines, estimates that for every 1000 men aged 60 with no first degree relatives affected by prostate cancer who take the test annually for ten years, two will avoid a prostate cancer death before the age of 85 as a result. Yet 87 men will receive a false-positive PSA test result and have an invasive biopsy that they didn’t require –28 will experience side-effects, including impotence and incontinence, as a result of this biopsy, and one will require hospitalisation.”

PSA Testing and Early Management of Test-detected Prostate Cancer: A guideline for health professionals is available for download at www.pcfa.org.au and wiki.cancer.org.au/PSAguidelines.

Latest news:

Stillbirth risk twice as high for disadvantaged women

Women from low socio-economic families have twice the risk of delivering a stillborn baby than those from wealthier backgrounds, an Australian-led international study has found.

The Lancet’s Ending Preventable Stillbirths series reports that over 200,000 stillbirths worldwide could have been prevented in 2015.

Although Australia ranks 15th lowest in the world, it has a stillborn rate that is 2.7/1000 total births, double the rate of Iceland which comes in at the lowest rate of 1.3 stillbirths/1000.

Experts in the field believe that more can be done to help prevent stillbirth and over 200 stillbirths each year could be prevented in Australia.

Philippa Middleton from the University of Adelaide said migrants, Indigenous peoples, people on low income, those with low education and early teenagers all were found to have double the risk of stillbirth.

“During pregnancy it might be about how good your access to antenatal care is, whether you have to travel to get good care and whether your mental health is all that it might be,” she said.

The causes are varied, including the fact that some disadvantaged women aren’t as empowered to make choices.

Associate Professor Vicki Flenady from the Mater Research Institute at the University of Queensland said the lack of appropriate care is a big factor.

“The lack of provision of culturally sensitive care that results in women not attending for care and complications not being picked up. We know poor antenatal care is certainly a risk factor for stillbirth.”

There are other major risk factors that are also at play, including smoking, being overweight or obese and fetal growth restriction which many care providers don’t know enough about.

Professor David Ellwood, a Professor of Obstetrics & Gynaecology at Griffith University, said an increased understanding of risk factors among care providers and the community could help the stillbirth rate.

He said surveys have demonstrated there is an underestimation of risk on certain risk factors including increased maternal age, multiple births and an increased risk of pregnancies attached to IVF.

A third of the population attributable risk comes from three risk factors which are maternal age, maternal overweight or obesity and smoking.

While smoking has become less of a burden, Dr Ellwood said it’s being replaced by overweight or obesity.

“It’s important to emphasise when we’re talking about risk factors, it doesn’t mean that everybody of a certain age is at high risk, it is characterising a group that collectively is at increased risk and require some additional surveillance or some other form of antenatal care,” he said.

The researchers also highlighted the role health care providers can play in helping a family who is dealing with stillbirth.

Associate Professor Fran Boyle from the School of Public Health at the University of Queensland said one thing that GPs can do is to acknowledge the loss.

“To understand that parents will be grieving their baby, to understand that recovery is a very long term process. It’s not something that happens in just 6 to 8 weeks.”

There are also issues in caring for women in subsequent pregnancies who may be anxious, and referring families to additional support services and parent organisations if needed

“It’s about recognising the loss and hearing from parents what they need,” she said.

Sands CEO, Andre Carvalho applauded the call to action on stillbirth prevention and said more needs to be done to support healthcare professionals.

“Sands will be developing new services to support this aim, including the development of new national care guidelines and training for front line staff,” he said.

Read the executive summary of the Lancet study or the full study.

Latest news:

Changes to PIP eHealth initiative

Following stakeholder consultation, the Department of Health has advised the new eligibility criteria for the Practice Incentives Programme (PIP) eHealth Incentive. The changes aim to encourage GP uptake and to increase the meaningful use of the My Health Record system.

Despite advice from the AMA and other members of the PIP Advisory Group that the My Health Record is not yet fit for purpose, the Government has decided to link the incentive to use of the My Health Record. From 1 May, general practices will be required to upload a Shared Health Summary (SHS) to the My Health Record system for 0.5% of the practice’s standardised whole patient equivalent (SWPE) to be eligible for their payment. This contribution equates to about five shared health summaries per full-time equivalent GP per quarter.

Practices will be advised at the start of a quarter of the SWPE count. They will need to keep a tally of shared health summaries uploaded to be certain of meeting their target.

To assist general practices to meet the new requirements, there will be online training available nationally from February and on demand face to face training from March/April. PIP participating general practices will be advised of the changes to the eligibility criteria for the ePIP through regular communication channels such as the PIP newsletter, websites and through Primary Health Networks.

Further consultation with the PIP Advisory Group and the broader general practice community will be undertaken in the near future regarding a tiered performance-based incentive arrangement, targeted for possible introduction in the August 2016 quarter. Under this approach, incentive payments would be linked to levels of use, such as numbers of SHSs uploaded.

Andrew Knight: e-Health revolution

Following AMA advice, the Department is considering transitioning existing PIP eHealth recipients to the new PIP eHealth arrangements as an alternative to requiring re-registration. Further advice on this matter will be provided to the PIP Advisory Group in February.

During consultations with the Department, the AMA, along with other stakeholders on the PIP Advisory Group, have repeatedly advised that the introduction of an MBS item and Service Incentive Payment for creating, uploading and updating a SHS would drive greater usage of the My Health Record. This view will be considered as part of the MBS Review.

This article was first published on GP Network News.

Latest news:

[Correspondence] Perinatal depressive symptoms preceded by mental health problems – Authors’ reply

Kelsey Hegarty and Laura Tarzia comment on the role of intimate partner violence in depression in young women and the scope for intervention through primary care.

Are general practice characteristics predictors of good glycaemic control in patients with diabetes? A cross-sectional study

Finding ways to better care for people with diabetes and other chronic conditions is a priority for the Australian health system. It is notable that five of the nine national health priority areas established by Australian governments1 are chronic conditions (diabetes, mental health, asthma, arthritis, obesity and dementia). Increasing survival of patients with cancer (one of the three other priority areas, together with cardiovascular health and injury prevention) means that this could also be considered a chronic condition.

Diabetes is one of the fastest growing chronic conditions in Australia, with National Health Survey reports showing an increase in prevalence from 1.3% in 1989–90 to 4.5% in 2011–12.2 This increase is probably linked with the ageing of our population, rising levels of obesity, and greater life expectancy for those with diabetes.2 Diabetes expenditure is also growing rapidly, with the annual costs (after adjusting for inflation) rising from $811 million in 2000–01 to $1507 million in 2008–09, an average annual growth rate of 10%.2

Recent studies have shown that there are opportunities for improving care for those with diabetes. For example, the CareTrack Australia study, which explored the appropriateness of the care provided in general practice, found that only 63% of patients with diabetes received optimal care.3 Further, data from the Australian Institute of Health and Welfare Institute indicate that in 2009–10 only 18% of patients with diabetes had completed the recommended annual cycle of care (ACC).4

It is clear that there are many possible reasons why an individual patient might not receive optimal care. For example, a patient might have several comorbid conditions that militate against the use of a recommended medication. Patients themselves might not adhere to the recommended therapy, or be able to afford a prescribed medication. The workloads of individual general practitioners differ, and the amount of training in chronic disease management is variable.

Practice characteristics, such as the employment of a practice nurse or the use of medical software, might also affect the appropriateness of care. Studies of the relative contributions of these factors have produced mixed results. For example, a study of 422 general practices providing care for 154 945 patients with diabetes in the United Kingdom found no relationship between practice size and the quality of diabetes management (defined as achieving HbA_1c levels of 53 mmol/mol or less).5

An American study of 40 medical groups found that the practice health systems (including formal quality assurance activities and data feedback), clinical information systems (including a diabetes registry), and decision support (including clinical guidelines, clinician prompts for diabetes) were all associated with patients with diabetes having HbA_1c levels of 64 mmol/mol or less.6 It is notable that they found no association between glycaemic control and the practice having a diabetic educator, a dedicated specialist diabetic nurse, a primary care team, patient reminders, or self-management training for patients.

A systematic review of the impact on glycaemic control of 11 different categories of practice quality improvement found that most produced small to modest benefits for glycaemic control.7

A study of 10 health centres in the Netherlands (45 GPs) found that the quality of care for patients with diabetes was higher if the centre had a diabetes education program, yearly medical check-ups by both the GP and a nurse practitioner, and structured follow-ups.8

A 2009 Australian study found that a GP service incentive payment (SIP) scheme for improving chronic disease management increased the probability of a GP requesting an assessment of HbA_1c levels by 20%.9 A similar study found that practices receiving practice nurse support were more likely to claim SIP payments for diabetes care, whereas practice size, diabetes activities, and the sex and age of the GPs were not associated with SIP payments.10

In this article, we present the results of our analysis of baseline data collected as part of the Diabetes Care Project (DCP), a federal government-funded project conducted between 2011 and 2014 to evaluate whether changes to the way in which primary care is organised and funded might improve care for people with diabetes.11 The DCP was a pragmatic clustered, three-armed, randomised controlled trial that evaluated the efficacy of coordinated patient care and flexible funding for GPs in the management of patients with diabetes. Clustering was at the level of the general practice. The three arms of the study were the control group (usual care), intervention group 1 (installation of the online chronic disease management support tool cdmNet12 and access to training and capability building), and intervention group 2 (installation of cdmNet, altered funding arrangements, provision of a care facilitator, and access to training and capability building). The primary outcome measure was defined as a change in patient HbA_1c levels at the end of the trial. Participants were included if they were at least 18 years old, had established type 1 diabetes mellitus (diagnosed at least 12 months ago) or newly diagnosed or established type 2 diabetes mellitus, and had the capacity to provide informed consent. Exclusion criteria included having a terminal illness or dementia, being pregnant or planning to become pregnant, and participating in the Coordinated Veterans Care program.

Our aim was to assess whether the characteristics of GP practices were associated with good glycaemic control in patients with diabetes and with completing an ACC. The dataset for our cross-sectional study, in contrast to that used in the DCP, was not risk-stratified, and we excluded newly diagnosed patients. In addition, our study includes the results of a separate survey of GP practices that was not part of the DCP study protocol.

Methods

A full medical history was obtained and patient demographic data were collected at baseline, as well as data on a number of clinical indicators, including HbA_1c levels. This information was obtained from the medical records in each practice. Practice characteristics were collected by telephone interview with the relevant staff of each practice (Box 1). Glycaemic control was defined as having an HbA_1c level of 53 mmol/mol or less.

The ACC is a measure of the clinical management of diabetes according to Australian national guidelines.4 Completion of the ACC enables GPs to submit a claim to Medicare for the costs of managing a patient with diabetes. For the ACC to be complete, all of the following actions need to have been undertaken: annual measurement of HbA_1c level; comprehensive eye examination every two years; twice yearly assessments of body mass index, blood pressure and feet; annual measurement of total cholesterol, triglyceride and high-density lipoprotein cholesterol levels; and annual test for microalbuminuria. Information on whether the ACC had been completed in the 18 months before starting the DCP was also available from Medicare as part of the baseline dataset.

The original sample size for the DCP was based on its being a three-armed, clustered, randomised controlled trial that compared changes in HbA_1c levels in the three groups during the study period. We excluded all newly diagnosed patients in this sample, as they would not have had time to have a completed ACC, leaving a sample size of 5455 patients. Logistic regression of a binary response variable (Y) on a binary independent variable (X) with a sample size of 1835 observations (of which 50% are in the group X = 0 and 50% are in the group X = 1) would achieve 80% power at P < 0.05 for detecting a difference corresponding to an odds ratio of 1.3. To allow for the clustered design, we assumed an intraclass correlation coefficient of 0.05, providing a design effect of approximately 3; this was equivalent to a required sample size of 5505 (ie, 3 × 1835) individuals, close to the actual sample size.

Practice predictors of good glycaemic control were assessed at an unadjusted univariate level, and after adjustment for patient age, sex, duration of diabetes, patient complexity (a dichotomous variable based on macro- and microvascular complications of diabetes, and comorbid renal disease and depression), and the Australian Bureau of Statistics Socio-Economic Indexes for Areas (SEIFA) score for relative socio-economic disadvantage.13 Odds ratios and 95% confidence intervals were calculated using clustered logistic regression models.

Practice predictors of a completed ACC were initially assessed at the univariate level, and then in a multivariate model that included all variables significant at P ≤ 0.05 in the univariate analyses. Adjustment for age, sex, duration of diabetes, patient complexity and SEIFA score was undertaken for all models, including the multivariate model, but these adjustments had little effect on the results; these analyses are therefore not presented in this article. All models involving patient-level data were adjusted for clustering by practice. Stata 14 (StataCorp) was used for all statistical analyses.

The study protocol was approved by the human research ethics committees of the Department of Health and Ageing (application number 15/2011), the Department of Human Services (2010/Co09591), the Australian Institute of Health and Welfare (EC 2011/4/38), SA Health (HREC 474/09/2014) and Queensland Health (HREC/11/QTDD/65), and by the Aboriginal Health Research Ethics Committee (Aboriginal Health Council of South Australia; reference 04-11-471). On the basis of the above approvals, the Department of Health, Victoria, determined that the study did not need review by their Human Research Ethics Committee.

Results

Data were available for 5455 patients and for 147 of 150 medical practices (98%). The mean age of the patients was 65.3 ± 11.6 years; 55.9% were men. The median time since diagnosis of diabetes was 9 years (interquartile range, 4–15 years). In general, these data were consistent with data for the general Australian population of people with diabetes. The enrolled GP practices had fewer solo GPs and more practice nurses than the national average.11

Of the 5455 patients, 55.0% (95% CI, 53.7%–56.4%) had good glycaemic control (HbA_1c ≤ 53 mmol/mol); 37.0% (95% CI, 35.8%–38.3%) had completed an ACC in the past 18 months.

Using logistic regression of glycaemic control on practice identification number treated as a dummy variable, the McKelvey and Zavoina pseudo-R² indicated that GP practice accounted for 5% of the variability in glycaemic control. The patient characteristics of age, sex, duration of diabetes, condition complexity and SEIFA score together accounted for 13.5% of variability in glycaemic control.

Box 2 presents data on the relationship between each of the practice characteristic variables and glycaemic control. Although the patient having a completed ACC is, strictly speaking, a patient characteristic, it is nonetheless a measure of practice quality and has therefore been included in this table.

In the unadjusted analysis, only the practice having regular multidisciplinary team meetings (odds ratio [OR], 1.16; 95% CI, 1.03–1.31) and the patient having completed an ACC (OR, 1.21; 95% CI, 1.07–1.37) were significantly associated with patients being in glycaemic control. After adjustment for age, sex, duration of diabetes, condition complexity and SEIFA, only the association with the patient having completed an ACC remained statistically significant.

Data for predictors of the patient having completed an ACC in the past 18 months are shown in Box 3. At the univariate level, the practice having a chronic disease-focused nurse (OR, 2.01; 95% CI, 1.07–3.77), the practice having regular staff educational events (OR, 1.68; 95% CI, 1.03–2.73), and the practice offering diabetes education events for patients (OR, 1.92; 95% CI, 1.21–3.06) were all statistically significantly associated with completion of an ACC. In the multivariate analysis, however, only the practice having a chronic disease-focused nurse and the practice running diabetes education events for patients were statistically significant.

Discussion

It is notable that neither having at least one practice nurse nor a chronic disease-focused practice nurse were directly associated with good glycaemic control in patients with diabetes. A review of the literature identifies mixed findings about the value of practice nurses. For example, a 2003 Cochrane review concluded that the availability of a diabetes specialist nurse or nurse case manager may improve patients’ diabetic control for short periods, but there was not enough evidence to demonstrate this effect in the longer term.14 On the other hand, a retrospective cohort study of 397 patients with type 2 diabetes recruited from five general practices in the Netherlands found that delegating diabetes care to a practice nurse led to improvements in diabetes care, including a statistically significant drop in HbA_1c levels.15 Finally, an observational study of 193 Danish general practices and 12 960 patients with type 2 diabetes found that the proportion of patients with HbA_1c levels of 64 mmol/mol or more was lower in practices with well implemented, nurse-led type 2 diabetes consultations.16

Having completed an ACC was the only variable that was significantly associated with glycaemic control after adjustment for patient characteristics. It is interesting that the only published study that examined the association between the completion of an ACC and health outcomes found that the physical functioning of women with diabetes who had completed an ACC was poorer than in women who had only had their HbA_1c levels measured.17 Our finding that patients who had completed an ACC were more likely to be in glycaemic control is the first to indicate the usefulness of this quality indicator.

The practice having a chronic disease-focused practice nurse, the practice offering diabetes education sessions for staff, and the practice organising self-management activities for patients with diabetes were features significantly associated with completing an ACC in the univariate model, although the relationship with staff education was not significant in the multivariate model. This highlights the need to have practice nurses trained in chronic disease management. This recommendation is also supported by the finding of a Cochrane review that the addition of patient education or elevating the role of the nurse to involvement in complex intervention strategies seems important for improving both patient outcomes and process outcomes.18

It would appear that practice characteristics, apart from those described above, are only weak predictors of the patient having completed an ACC. It is unfortunate that we could not obtain information about individual GPs in each practice, and it is likely that their individual characteristics would have a greater influence on the completion of the ACC than information about the practice as a whole, just as patient characteristics explained more of the variability in glycaemic control than did practice characteristics.

As with all cross-sectional studies, it is unwise to attribute causality to any of the detected associations. Practices nominated themselves to participate in the program, and were thus possibly more interested in diabetes management than those that did not. Finally, practice data, including whether the nurse was a practice nurse or a chronic disease-focused nurse, were self-reported, introducing the possibility of bias; further, the analysed data were based on responses to a checklist of practice attributes completed by practice staff, rather than a direct assessment of these features.

The findings of this study underline the importance of having practice nurses trained in chronic disease management, as well as the practice providing education to its diabetic patients. It is also important that this is the first study to find an association between completion of an ACC and good glycaemic control, and GP practices are therefore encouraged to ensure that their patients with diabetes complete an ACC.

Box 1 –
Practice characteristics assessed for this study

Practice location
Practice size
Practice has a practice nurse
Practice has a chronic disease-focused practice nurse
Practice currently uses chronic disease management software
Corporate practice (ie, part of a larger group of practices)
Allied health professionals located in the practice
Practice participated in the Australian collaborative quality improvement program in the past 24 months
Practice takes part in audit and feedback
Practice has dedicated staff member who coordinates care or manages cases
Practice has regular multidisciplinary team meetings
Practice has regular staff education events
Practice uses shared electronic medical records with care team
Practice has education events for patients with diabetes
Practice has formal motivation and self-management education activities for patients with chronic diseases

Box 2 –
Practice characteristics associated with good glycaemic control: univariate models

Variable	Category	HbA_1c > 53 mmol/mol		HbA_1c ≤ 53 mmol/mol		Odds ratio	95% CI for odds ratio	P*	P^†
Variable	Category	n	%	n	%	Odds ratio	95% CI for odds ratio	P*	P^†

Metropolitan practice	No	706	46.3%	820	53.7%	1.00
Yes	1743	44.4%	2186	55.6%	1.08	0.93–1.25	0.310	0.470
Practice size	1–2 GPs	559	45.5%	670	54.5%	1.00
≥ 3 GPs	1882	44.7%	2327	55.3%	1.03	0.88–1.21	0.704	0.413
Practice nurse	No	408	44.7%	504	55.3%	1.00
Yes	2002	44.9%	2462	55.1%	1.00	0.82–1.21	0.965	0.575
Chronic disease-focused nurse	No	440	48.1%	474	51.9%	1.00
Yes	2009	44.2%	2532	55.8%	1.17	0.95–1.44	0.135	0.375
Chronic care planning software already used	No	1589	45.3%	1918	54.7%	1.00
Yes	830	44.3%	1042	55.7%	1.04	0.90–1.20	0.593	0.383
Corporate practice	No	2142	45.1%	2612	54.9%	1.00
Yes	240	43.2%	316	56.8%	1.08	0.91–1.29	0.392	0.466
Co-located allied health professionals	No	1375	45.3%	1660	54.7%	1.00
Yes	1074	44.4%	1346	55.6%	1.04	0.90–1.19	0.596	0.634
Practice involved in quality improvement collaboration	No	1626	45.6%	1939	54.4%	1.00
Yes	816	43.7%	1051	56.3%	1.08	0.93–1.26	0.329	0.839
Practice has audit and feedback	No	1184	44.4%	1483	55.6%	1.00
Yes	1255	45.5%	1502	54.5%	0.96	0.83–1.09	0.512	0.692
Practice has dedicated case management	No	1146	44.2%	1448	55.8%	1.00
Yes	1293	45.7%	1537	54.3%	0.94	0.82–1.08	0.376	0.436
Practice has regular multidisciplinary team meetings	No	1726	46.0%	2028	54.0%	1.00
Yes	618	42.4%	839	57.6%	1.16	1.03–1.31	0.027	0.226
Practice has regular staff education	No	1067	45.2%	1291	54.8%	1.00
Yes	1372	44.8%	1694	55.2%	1.02	0.89–1.17	0.774	0.877
Practice uses shared electronic medical records	No	1551	44.9%	1901	55.1%	1.00
Yes	894	44.9%	1099	55.1%	1.00	0.86–1.16	0.969	0.944
Practice has patient diabetes education events	No	1719	44.8%	2117	55.2%	1.00
Yes	703	45.2%	852	54.8%	0.98	0.83–1.16	0.851	0.198
Practice has self-management activities	No	1518	45.2%	1840	54.8%	1.00
Yes	921	44.6%	1145	55.4%	1.03	0.89–1.18	0.729	0.913
Completed annual cycle of care	No	1603	46.6%	1833	53.4%	1.00
Yes	846	41.9%	1173	58.1%	1.21	1.07–1.37	0.002	0.011

* Based on clustered logistic regression. † Adjusted for age, sex, duration of diabetes, Socio-Economic Indexes for Areas (SEIFA) score and level of condition complexity.

Box 3 –
Practice characteristics associated with a completed annual cycle of care (ACC)

Variable	Category	ACC completed		ACC not completed		Odds ratio	95% CI for odds ratio	P*	P^†
Variable	Category	n	%	n	%	Odds ratio	95% CI for odds ratio	P*	P^†

Metropolitan practice	No	890	58.3%	636	41.7%	1.00
Yes	2546	64.8%	1383	35.2%	0.76	0.46–1.24	0.202
Practice size	1–2 GPs	854	69.5%	375	30.5%	1.00
≥ 3 GPs	2568	61.0%	1641	39.0%	1.46	0.82–2.59	0.202
Practice nurse	No	654	71.7%	258	28.3%	1.00
Yes	2739	61.4%	1725	38.6%	1.60	0.89–2.88	0.120
Chronic disease-focused nurse	No	690	75.5%	224	24.5%	1.00
Yes	2746	60.5%	1795	39.5%	2.01	1.07–3.77	0.029	0.036
Chronic care planning software already used	No	2216	63.2%	1291	33.3%	1.00
Yes	1151	61.5%	721	34.5%	1.08	0.63–1.84	0.792
Corporate practice	No	2922	61.5%	1832	38.5%	1.00
Yes	436	78.4%	120	21.6%	0.44	0.18–1.08	0.073
Co-located allied health professionals	No	1951	64.3%	1084	35.7%	1.00
Yes	1485	61.4%	935	38.6%	1.13	0.69–1.86	0.623
Practice involved in quality improvement collaboration	No	2326	65.3%	1239	34.8%	1.00
Yes	1093	58.5%	774	41.5%	1.33	0.77–2.31	0.312
Practice has audit and feedback	No	1707	64.0%	960	36.0%	1.00
Yes	1698	61.6%	1059	38.4%	1.11	0.68–1.80	0.677
Practice has dedicated case management	No	1548	59.7%	1046	40.3%	1.00
Yes	1857	65.6%	973	34.4%	0.78	0.48–1.26	0.301
Practice has regular multidisciplinary team meetings	No	2499	66.6%	1255	33.4%	1.00
Yes	803	55.1%	654	44.9%	1.62	0.97–2.72	0.068
Practice has regular staff education	No	1639	69.5%	719	30.5%	1.00
Yes	1766	57.6%	1300	42.4%	1.68	1.03–2.73	0.038
Practice uses shared electronic medical records	No	2239	65.0%	1213	35.0%	1.00
Yes	1187	59.6%	806	40.4%	1.25	0.76–2.08	0.381
Practice has patient diabetes education events	No	2591	67.5%	1245	32.5%	1.00
Yes	808	52.0%	747	48.0%	1.92	1.21–3.06	0.006	0.004
Practice has self-management activities	No	2193	65.3%	1165	34.7%	1.00
Yes	1212	58.7%	854	41.3%	1.33	0.81–2.17	0.262

* Based on clustered logistic regression. † Multivariate model including two variables significant at P < 0.05 in univariate models.

Cost-effectiveness of screening for bowel cancer

Increasing bowel cancer testing rates through a general practitioner-organised health care package would reduce incidence and prove cost-effective

Treating bowel cancer is expensive, and the cost is rising rapidly. In the past decade, costs have increased for treating cancers at all stages (in particular, Stages 3 and 4), largely due to increased chemotherapy options and the introduction of more effective but expensive drug regimens.1 Increased treatment costs are a stimulus for the considerable effort in the areas of prevention and early detection.

The National Bowel Cancer Screening Program (NBCSP), based on a faecal occult blood test (FOBT), was introduced in mid 2006 to people aged 55 and 65 years, and was extended in 2009 to include people aged 50 years. It is due to be further expanded to biennial testing in 2020, with gaps filled annually until then.2 This delay in full implementation is related to the perceived cost of the NBCSP as well as infrastructure and logistical difficulties.3

There are concerns with aspects of the structure of the NBCSP, such as the target age group and screening intervals.3 Incidence of bowel cancer for people aged 40 to 50 years is rising,4 and recent evidence suggests that the incidence for people aged under 40 years is also increasing.5 This is important given that people aged under 50 years are relatively productive contributors to the Australian economy.6

The screening interval in the NBCSP is 2 years but some studies have shown greater benefit from shorter screening intervals. Studies of FOBT and subsequent colonoscopy for a positive test result in patients aged 55–64 years show a reduction in mortality of 19% from biennial screening and 29% from annual screening.1 As this study was limited to patients aged 55–64 years, caution should be used when extrapolating these results to other age cohorts. A recent study emphasised that with biennial screening the NBCSP will result in 35 000 fewer deaths in the next 40 years.2

The Gut Foundation, in conjunction with Deloitte Access Economics, performed a cost-effectiveness study of screening between the ages of 40 and 70 years.7 The study is publicly available and contains details on the methodology, data and results. Three interventions were studied:

Biennial immunochemical FOBT (iFOBT) starting at age 40 years and ceasing at age 70 years
Annual iFOBT for the same period
Colonoscopy at age 40 years, then at age 50 years, and 5-yearly intervals thereafter until age 70 years.

The comparator was no screening and standard care when diagnosed symptomatically. The NBCSP was not used as a comparator due to a lack of publicly available data when the study was undertaken.

Three techniques were used to examine the proposed interventions:

Cost-effective analyses (CEAs): these compare the monetary cost of achieving a particular non-monetary objective; eg, deaths averted or life-years saved. All CEAs of the screening interventions involved an analysis of program costs, eg, costs of screening kits, and diagnostic and pathology tests; screening results, eg, number of bowel cancer cases detected (true positives), missed (false negatives) or otherwise (false positives and true negatives); bowel cancer stage incidence rates for true-positive and false-negative test results; treatment costs and health outcomes per person associated with each pathway (true positive, false positive, true negative, false negative); and overall outcomes on health care cost savings and avoidance of disability-adjusted life-years (DALYs) from earlier detection and treatment. Costs are not discounted to present values, since they are assumed to be incurred in a single year. The incremental cost-effectiveness ratios (ICERs) presented in the analysis have been calculated from the non-rounded estimates of costs and DALYs.
Estimated DALYs: some DALYs would be incurred as a result of annual and biennial iFOBT screening due to complications and, very rarely, as a result of deaths from colonoscopy procedures.8 However, these are outweighed by the DALYs that would be averted as a result of screening.
The World Health Organization recommendations: the WHO makes recommendations in relation to cost-effectiveness benchmarks. A highly cost-effective intervention is determined as costing less than the gross domestic product per capita which, in Australia, was about $60 000 per DALY averted in 2011.9

Results

The results of the cost-effectiveness modelling are presented in the Box (note that some results may not add up due to rounding). The results are expressed for:

Total financial costs: these include costs such as mail-outs and kits, pathology tests, general practitioner appointments, colonoscopies for participating patients with positive test results and patients in the colonoscopy intervention program, and perforations from colonoscopies. The financial costs in the model are limited to health care costs only.
Total financial benefits: these include benefits from better survival and cases of bowel cancer averted, and health care cost savings from earlier treatment and cases of bowel cancer averted.
Total costs: these include financial costs, as well as economic costs from DALYs lost, such as from patient non-participation or from false-negative test results.
Total benefits: these include financial benefits as well as economic benefits from fewer cases of bowel cancer and improved survival rates.
Net DALYs averted by the intervention.
ICER (societal perspective): net financial costs divided by net DALYs averted.
ICER (health care perspective): net financial health care costs divided by net DALYs averted.

Additional modelling results are available in the report.7 This report demonstrates that annual and biennial iFOBT and colonoscopy screening are all highly cost-effective. From a societal perspective, the annual iFOBT is the most cost-effective ($9510 per DALY averted), followed by the biennial iFOBT ($21 490) and colonoscopy ($40 978).

However, the financial costs of the annual iFOBT program are the highest ($273.8 million), followed by colonoscopy ($251.2 million) and the biennial iFOBT ($141.2 million). The annual iFOBT costs are about twice as high compared with the biennial iFOBT costs, because about twice as many tests are carried out. The colonoscopy costs are higher than the biennial iFOBT costs due to the higher costs associated with colonoscopy screening compared with screening via mail-outs.

The key to success of any screening program (eg, the NBCSP) is the uptake of the program. The participation rate needs significant improvement to reduce the incidence of bowel cancer in Australia.

A solution to this dilemma could be to include bowel cancer screening and prevention in a health care package organised by GPs. The package could be based on the annual iFOBT intervention (this includes colonoscopy for participants who receive a positive result, followed up by their GP). Based on the results of this report,7 this program has the potential to save $2.6 billion (including financial and economic savings). Note that the study did not include additional administrative, staff and system costs of GPs, eg, issuing invitations for appointments, sending reminders and following up results.

The Gut Foundation has successfully undertaken an iFOBT study via GPs in the Riverina region of New South Wales to assess the results of screening people aged ≥ 40 years. The regional population aged ≥ 40 years was encouraged to visit their GP for an iFOBT kit. From a total of 1409 kits, 203 were positive, including 51 positive test results for the 40–49 year age group.10 The positive test results included 14 cancers, 59 adenomas (including multiple adenomas) and 13 hyperplastic polyps. The study notes that the small sample size limits its impact, and that the high positivity rate may be due to the location of the study. The Gut Foundation plans to enlarge this study in the Port Macquarie area of NSW (in conjunction with the Rural Medical School at the University of New South Wales and local GPs) to identify how participation and outcomes can be improved.

While this article has focused on the cost-effectiveness of age-based population screening, it is important to note that bowel cancer has been identified as having the strongest genetic links of all the common cancers.5 Patients with a genetic predisposition to bowel cancer have a higher risk of contracting the disease across all age groups, and genetic links among young bowel cancer patients may be more common than among older bowel cancer patients.5 The cost-effectiveness of screening patients < 40 years with genetic predispositions to bowel cancer could be the subject of further research.

Bowel cancer kills an Australian every 2 hours.2 The polyp–cancer sequence and NBCSP screening data suggest many cancers could be prevented or at least diagnosed early.2 We need to act now.

Box –
Bowel cancer screening for people aged 40–70 years

	Biennial iFOBT	Annual iFOBT	Colonoscopy

Total financial costs (health care only, $m)	141.2	273.8	251.2
Total financial benefits (health care only, $m)	8.7	26.1	11.4
Net financial costs (health care only, $m)	132.5	247.7	239.7
Total financial costs ($m)	141.2	273.8	251.2
Total financial benefits ($m)	38.1	124.0	54.2
Net financial costs ($m)	103.1	149.8	196.9
Total costs ($m)	182.6	353.7	541.6
Total benefits ($m)	902.8	2,907.5	1169.2
Net total benefit ($m)	720.2	2,553.9	627.7
Net DALYs averted	4798	15 756	4805
ICER (societal perspective)	21 490	9510	40 978
ICER (health care perspective)	27 620	15 719	49 894

iFOBT = immunochemical faecal occult blood test. DALY = disability-adjusted life-years. ICER = incremental cost-effectiveness ratios.

Low stress resistance leads to type 2 diabetes: study

A recent study published in Diabetologia (the journal of the European Association for the Study of Diabetes) has found 18-year-old men with low stress resistance have a 50% higher risk of developing type 2 diabetes in their lifetime.

The population based study examined all 1,534,425 military conscripts in Sweden during 1969–1997 who underwent psychological assessment to determine stress resilience. They had to have had no previous diagnosis of diabetes.

They were followed up for type 2 diabetes from 1987–2012 with the maximum attained age being 62.

After adjusting for body mass index, family history of diabetes, and individual and neighbourhood socioeconomic factors, the research found 34,008 men had been diagnosed with type 2 diabetes.

The study found the 20% of men with the lowest resistance for stress were 51% more likely to have been diagnosed with diabetes than the 20% with the highest resistance to stress.

Authors Dr Casey Crump, Department of Medicine, Stanford University, Stanford, CA, USA, and colleagues in Sweden and the USA admit lifestyle behaviours related to stress including smoking, unhealthy diet and lack of physical activity could be related to the increased risk of diabetes. The study also could not make any assertions about women as it only included male army cadets.

The authors conclude: “These findings suggest that psychosocial function and ability to cope with stress may play an important long-term role in aetiological pathways for type 2 diabetes. Additional studies will be needed to elucidate the specific underlying causal factors, which may help inform more effective preventive interventions across the lifespan.”

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Long courses, confusion and culture: why we’re losing the fight against antibiotic resistance

Doctors often tell patients to take a “course” of antibiotics, because a partially treated infection may result in relapse with antibiotic-resistant bacteria. But where does this advice come from?

As Lyn Gilbert has pointed out on The Conversation, there isn’t good evidence behind many of these recommendations. For GPs, the main determinant of the duration of antibiotics is the size of the pack they come in.

In hospitals, we also have some odd rules about antibiotics:

Prime numbers for durations of up to a week (three, five or seven days)
Even numbers for more serious infections that take weeks to eradicate (two, four or six weeks)
Multiples of three for really tenacious infections such as bone infections (three months) or TB (six months).

Of course, there is nothing magical about these numbers. I doubt anyone was harmed by stopping their treatment on day 89 instead of day 90.

Although this seems rather silly, it highlights the serious point that we often don’t know exactly how long is necessary to treat many infections.

The evidence base for these recommended durations comes from the duration used in previous studies. But shorter courses often haven’t been tested. Clinical trials that test shorter durations of treatment aren’t as sexy as those testing a new antibiotic, but are also important.

If we could safely treat infections with shorter courses of antibiotics, this might help reduce the risk of antibiotic resistance developing in bacteria. On the other hand, inadequate treatment of infections can increase the risk of resistance, so the optimal treatment length is “just enough”.

Grey areas in clinical diagnosis

One of the most difficult areas for new doctors is dealing with uncertainty. It is easy to catastrophise: every headache could possibly be meningitis, every cough could be pneumonia, every fever could be the harbinger of an overwhelming infection. The problem is, sometimes they are. The junior (and senior) doctor’s worst nightmare is to miss a serious diagnosis, be responsible for a patient’s death and end up in court.

Given this uncertainty, it isn’t surprising that doctors sometimes over-prescribe antibiotics. Despite clinical guidelines not to prescribe antibiotics for viral infections – and knowledge that antibiotics don’t benefit patients who have bronchitis – it is easy to rationalise why “my” patient might be different.

Patients don’t present to their doctors with a diagnosis; when doctors make the decision to prescribe antibiotics they rarely have the results of a test for viral flu, or a chest x-ray to diagnose pneumonia. Even in hospitals, where access to diagnostic tests isn’t really a problem, the results of the test may not be available until well after the decision to prescribe antibiotics is made.

Another example is in sinusitis. The clinical trials that looked at the role of antibiotics in sinusitis largely focused on those presenting to GPs in the community. They show little or no benefit for patients given antibiotics compared to those who did not receive antibiotics.

But what about patients who need to be hospitalised with sinusitis? What about a patient with sinusitis who responded well to antibiotics last time? What about a patient with sinusitis who had a heart transplant and is on medication to heavily suppress her immune system? Or the frail elderly patient with multiple chronic illnesses who probably wouldn’t survive a serious infection?

One way we have been combating this problem in hospitals is to have “post-prescription” reviews. A team of pharmacists and infectious diseases specialists checks the notes and tests of patients who are prescribed broad spectrum antibiotics two to three days after they are started, with the sole aim to see if something better could be used.

This recognises that simple rules for prescribing don’t account for how complicated patients can be, and that not all the information may be available when the initial decision is made.

Benefits for the individual, harm to others

Antibiotic resistance is, in many ways, a lot like global warming. We want to be warm and well fed, live comfortably in large houses and take holidays in exotic locations, but don’t want to think about the consequences for the environment.

As Alex Broom wrote on The Conversation, doctors want the best for their patient, and giving antibiotics to treat or prevent infection provides a potential benefit for the patient. It is hard enough deciding on the balance of benefits and harms for the patient in front of you, let along the potential “harms” to the wider community.

Cultural factors may be particularly important in clinical decision-making. When I worked in the United States, there was a strong feeling among many doctors that the individual being treated was the patient, and the impact on other patients was very much a secondary consideration. I once heard a doctor saying he used new, broad spectrum antibiotics because he wanted his patient to benefit from them before the bacteria became resistant to it.

On the other hand, the northern Europeans are well known for their low rates of antibiotic use and resistance.

I once worked in a hospital in Denmark and had a patient who was rather unwell with sinusitis, which had caused fever for more than two weeks. I explained to him that while the evidence generally didn’t support the use of antibiotics for sinusitis, prolonged illness was a situation where we might consider using antibiotics. He said to me that he would prefer to wait a few more days, just to see if he might avoid the need to take antibiotics.

In addition to the obvious cultural differences between Americans and Europeans, this suggests that education is required for both doctors and patients. Australia’s National Prescribing Service is running a Resistance Fighter campaign to raise awareness of the dangers of unnecessary antibiotic use.

Research findings that antibiotic use actually increases the risk of resistance in the patient, and isn’t just a hypothetical problem in a far-off future, is also an important message.

It is easy to make excuses for poor prescribing and no doubt a significant proportion of antibiotics are not required. We could do more by researching the optimal durations of treatment for different infections, setting up systems to deal with clinical uncertainty and educating both doctors and patients about the trade-off between antibiotic use and resistance.

Allen Cheng, Professor in Infectious Diseases Epidemiology, Monash University

This article was originally published on The Conversation. Read the original article.

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Potato consumption linked to gestational diabetes

A study published in the BMJ has found a link between a woman’s pre-pregnancy consumption of potatoes and her chances of suffering gestational diabetes.

The researchers from the Eunice Kennedy Shriver National Institute of Child Health and Human Development and Harvard University tracked 15,632 women over a 10-year period, which resulted in 21,693 singleton pregnancies.

Of these pregnancies, 854 were affected by gestational diabetes.

After taking into account risk factors such as age, family history of diabetes, diet quality, physical activity and BMI, researchers found that higher total potato consumption was significantly associated with a risk of gestational diabetes.

The researchers found that if women substituted two servings of potatoes a week with other vegetables, wholegrains or legumes, there is a 9-12% lower risk of contracting gestational diabetes.

They say one explanation of the findings is that potatoes have a high glycaemic index which can trigger a rise in blood sugar levels thanks to the high starch content.

The most recent Australian dietary guidelines released in 2015 say Australians need to eat less starchy vegetables.

The authors of the study admit that the observational nature of their study means no definite conclusions can be drawn about cause and effect.

However, they conclude: “Higher levels of potato consumption before pregnancy are associated with greater risk of GDM, and substitution of potatoes with other vegetables, legumes, or whole grain foods might lower the risk.”

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Government policy, not consumer behaviour, is driving rising Medicare costs

By Professor Stephen Duckett, Director, Health Program, Grattan Institute

This article first appeared in The Conversation on 2 December, 2015, and can be viewed at: https://theconversation.com/governmentpolicynotconsumerbehaviour…

Announcing the ill-fated 2014 budget initiative to introduce a consumer co-payment for general practice visits, the-then Health Minister, Peter Dutton, lamented that annual Commonwealth health costs had increased from $8 billion to $19 billion over a decade.

He described the increase as “unsustainable”, and used it to justify the Budget’s bitter pill.

The implication of his announcement was that consumers were driving the increase in costs, and that action to change consumer behaviour was necessary to rein them in.

The growth numbers were presented as part of the government’s then mantra of a “debt and deficit disaster”, and massaged to create maximum shock and awe. The minister’s numbers did not adjust either for population growth or inflation.

Nonetheless, a more legitimate set of growth numbers would still show Medicare Benefits Schedule (MBS) payments growing at an annual rate of 2.3 per cent in real per head terms, faster than growth in Government expenditure overall (1.8 per cent).

But this still leaves open the question of whether consumer behaviour is driving rising costs, or whether there may be other causes.

A report released in late November by the Parliamentary Budget Office shows that Government policy has driven a significant proportion of the growth in MBS costs. In fact, of the $325 real increase in MBS spending per head since 1993-94, all but $74 has been the result of explicit government decisions.

MBS spending per head is the product of the rebate for each MBS item and the per head use of those items. Both elements of this calculation have been tinkered with as part of policy change over the last two decades.

A significant proportion of the growth in Medicare costs has been driven by Government policies such as items for new services and larger rebates.

Governments have increased rebates for some items faster than inflation. This has been done, for example, to encourage an increased rate of bulk billing.

New item numbers have also been added as part of major policy reviews. (Each MBS service involves one or more item numbers and an associated description. For example, an ordinary consultation with a general practitioner is item number 24.) The single largest cost impact ($51 per head) came from changes to diagnostic imaging items, including new items for magnetic resonance imaging (MRI).

But implementation of policies to expand magnetic resonance imaging and reform diagnostic imaging items more generally has been poor. It is questionable whether consumers are getting value for money from this investment. Also, some diagnostic imaging tests appear to be overused.

Policies designed to increase bulk billing accounted for an extra $70 per head: increasing the GP rebate from 85 per cent of the schedule fee to 100 per cent accounted for $42 per head; targeted increases in the rebate to increase bulk billing rates accounted for the rest.

When did Medicare spending soar?

In the decade to 2003-044, Medicare spending grew by $53 per head. Just over half of that was attributable to the addition of new diagnostic imaging items to the schedule. In the next decade, spending grew at five times that rate – by $272 per head.

Most of the growth was due to decisions taken when Tony Abbott was Health Minister, between 2003 and 2007. In fact, almost half (47 per cent) of the growth in Medicare spending over the last two decades is the result of policy decisions taken when he was running the health portfolio.

The changes were introduced over the years for a mix of policy and political reasons.

The decline in bulk billing was associated with public dissatisfaction with Medicare and was clearly having political impacts. This led to new bulk billing incentives and increases to the rebates for general practitioner fees.

The increasing prevalence of chronic diseases, such as diabetes and heart disease, led to new assessment and care planning items.

A decline in the proportion of GPs providing after-hours care led to new items to redress that as well.

General practitioners got more rebate income (in real terms) for seeing the same number of patients, so it was actually changes initiated by Government that led to the increase in spending.

What does this mean for Medicare reform?

Two main lessons can be drawn from the Parliamentary Budget Office report.

First, the Government must be clear about what is driving growth in expenditure. The co-payment proposal sank like a lead balloon partly because it was seen as inefficient and unfair, but also because the public didn’t have any ownership of the “problem” the changes sought to address. The way the problem was initially presented was wrong, causing confusion between Medicare services (which include diagnostic tests) and GP visits. The vast majority of the population, who have few visits, refused to accept that per head use was going up.

Second, the report shows how much governments have relied on tinkering with the Medicare Benefits Schedule to drive system change in the last decade. “Here a new item, there a new item, everywhere a new item”, became the Canberra policy song sheet.

Health Minister Sussan Ley wiped the slate clean when she was appointed in December, setting up a raft of reviews to look at everything from primary care to disinvestment.

Importantly, reviews must consider whether the Medicare Schedule is still “fit for purpose” in the context of the increase in chronic disease and the impact this is having on clinical practice.

It must be hoped new policies developed in response will be both more sophisticated and less profligate than we have seen over recent decades.