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AMA list of medical services and fees

The 1 November 2015 edition of the AMA Fees List will soon be available both in hard copy and electronic format.

The hard copy for those members listed as being in private practice or with rights of private practice, and salaried members who have requested a book will commence being dispatched on 14 October 2015.

The AMA Fees List is available in the following electronic formats; a PDF version of the hard copy book, a CSV file for importing into practice software, as well as an Online database where members can view, print or download individual items or groups of items to suit their needs. 

The PDF and CSV versions of the AMA Fees List will be available to all members via the Members Only area of the AMA website http://www.ama.com.au/resources/fees-list from 21 October 2015. The Fees List Online Database will be updated on 2 November 2015.

To access this part of the website simply enter your username and password by clicking on the  symbol in the right corner of the blue task bar at the top of the AMA homepage and follow these steps.

1)   From the home page hover over Resources at the top of the page. A drop down box will appear. Under this, select Fees List.
2)   For the PDF and CSV – Select first option, AMA List of Medical Services and Fees – 1 November 2015 (Members Only).
3)   Download either or both the CSV (for importing into practice software) and PDF (for viewing) versions of the AMA Fees List.
4)   For the Fees List Online Database – Select AMA Fees List Online Database (Members Only)
5)   Click on the link to open the AMA Fees List Online Database, or alternatively the database can be accessed directly via http://feeslist.ama.com.au.

Also available to members is the AMA Fees Indexation Calculator, this allows you to calculate your own fee increase based on your individual cost profile. To access the AMA Fees Indexation Calculator, follow these steps:

1)   From the home page hover over Resources at the top of the page. A drop down box will appear. Under this, select Fees List.
2)   Select AMA Fees Indexation Calculator (Members Only)

Members who do not currently have a username and password should email their name, address and AMA member services number to memberservices@ama.com.au requesting a username and password.

If you do not receive your hard copy of the 1 November 2015 AMA Fees List or would like one, please contact the AMA on 02 6270 5400 or email feeslist@ama.com.au.

You are not Robinson Crusoe

A huge undertaking, but is it about improving outcomes or cutting costs?

Dean of Medicine at the University of Sydney, Bruce Robinson, is leading the Medicare Benefits Schedule (MBS) Review Taskforce in its examination of how more than 5500 listed services can be aligned with contemporary clinical evidence and improve health outcomes for patients.1

It would be informative if the federal government had the Department of Finance provide a figure indicating how much money it wants to save. Disguising a rationing exercise by saying it is about improving outcomes will cut little ice unless the level of rationing is acceptable to the medical profession.

Pricing MBS items is a cost-accounting exercise. Trying to evaluate whether a particular service, based on the Medicare price, improves health outcomes could lead the taskforce into a paper chase seeking clinical evidence, when the intent of the exercise is all about increasing cost efficiencies.

Advances in technology improve efficiency. Pathology services were an early target because the original MBS items were based on tests undertaken manually. Once tests became automated, throughput increased and pathology service providers made substantial windfall gains before the MBS prices were adjusted.

On the other hand, the pricing for cataract removal has been largely immune from any recognition of the advances in technology that have occurred since the first medical benefits table for each Australian state was established in the early 1970s.2 When ophthalmologists protested strongly and publicly about a proposed cut in the fee for the Medicare benefit in 2010, the cut never eventuated; a compromise was reached in the government price.3

Determining fees for benefits

Trying to alter the relativities between the different medical tribes is thus a challenge. In determining the original MBS, advice was sought from the various groups on what were considered “fair and reasonable” fees. Because of the way they assessed their original fees, ophthalmologists have always been considered as being at the top of the relativity scale.

In the early years, the Australian Medical Association (AMA) and the federal government participated in regular enquiries into medical fees for medical benefits. This had the effect of reinforcing the acceptance of relativities between the services provided by different groups and specialties, because each submitted data to the AMA. As the AMA bore the cost of making the submission, it certainly was in its interests not to question the accepted relativities unless there were obvious shifts, as occurred with pathology services. The AMA was successful in having the prices for the services raised with every successive enquiry. The submissions were argued from an industrial perspective. There was no attempt to try to evaluate the effectiveness of individual procedures or consultations. With every enquiry, there was a sense within the AMA that the results were not as successful as the enquiry before. The last enquiry into medical fees for medical benefits was held in 1984.

Since the end of those periodic enquiries, and with increasing specialisation, the AMA’s role in the area of medical fees for medical benefits has diminished. The AMA releases a list of recommended fees annually, but the formula has not been updated. It is the MBS pricing that counts. Specialty groups sought recognition of the cost of advances in their fields in the Medicare benefits item descriptors. With no unifying force, it became a time when specialties strove for their own gain.

One example was in radiotherapy (radiation oncology). When the relativities were first determined, most radiotherapists, as they were then known, were salaried and their equipment was the most expensive item. There was little private radiotherapy. However, by the mid-1980s, there was considerable interest in providing a private service. In radiotherapy, it was crucial to recognise and differentiate the service price into three components: professional, technical and capital.

In terms of pricing, the professional component always dominated. The AMA had always asserted that all procedural pricing should embody the professional component of the price, taking into account office and car costs. Hospitals paid the cost of the technical staff and the imputed capital costs of using the facility. This resulted in cost shifting onto the state governments or private hospitals.

Radiation oncologists who saw a future in private practice knew that the price for the service was totally inadequate. There was no mechanism to handle the capital expenditure required, which depended on the international value of the Australian dollar. The technical component, comprising the staff and other non-capital costs, was measurable. The professional component was essentially a normative distillation of time to undertake the service (which is measurable) and the required level of skill and knowledge, often defined as complexity (a matter of opinion).

The end result, after long negotiation, was that radiation oncology in private practice was rendered viable. Based on detailed costing, the government separated the capital component of the Medicare benefit into a specific payment for major equipment that could be updated regularly to reflect actual costs.4

At the same time, calculations to establish the new radiation oncology benefits also identified the most efficient number of linear accelerators per site. Unless there were two to three linear accelerators per facility, services were inefficient, but that did not stop the states paying for stand-alone facilities in regional Australia. The states tried to justify this by repeatedly reviewing the viability of stand-alone radiation oncology facilities. In the end, communities that wanted a single linear accelerator got it, which may have been good politics, but was bad economics.5

Thus, the MBS establishes the most efficient use of time and equipment; in other words, it establishes service capacity. Having determined capacity, what is a reasonable daily throughput of services? Getting the throughput figure wrong either enables the situation that occurred in the early days of pathology service pricing, or makes unreal demands so that the only viable option is a publicly provided service with consequent rationing; namely, waiting lists. At the same time, all jurisdictions add multiple layers of extra requirements for many medical services in the name of quality, regulation and reporting, all of which add complexity and cost, but receive scant recognition in the pricing formulae.

Whether it be radiotherapy or general practice, the same rules apply. The MBS has grown enormously since the radiation oncology example. In the absence of countervailing forces, the government can just set the prices; it can ration, irrespective of any outside advice. Look at the Relative Value Study of the MBS, which ran for a number of years up to 2000;6 for what outcome? It was widely acknowledged that the time taken to complete the Relative Value Study delayed MBS fee increases by several years and saved the government a considerable amount of money.

The taskforce faces no easy task

The MBS Review Taskforce must consider clinical outcomes. Improvements in technology have influenced Medicare pricing, but whether technology improves clinical outcomes may be the subject for a different forum. Adam Elshaug, a member of the Taskforce and Director of the Value in Health Care Division at the Menzies Centre for Health Policy, may well be the person to chair such a forum. He seems to know what he is talking about, having led a study that identified at least 150 health care procedures of low value.7

Bruce Robinson, you are not alone in dealing with the Medicare behemoth; it is just that the medical profession would like to be considered. They would like a dividend, be it financial, organisational or social. Without this, doctors may well keep increasing their fees, which will become increasingly distant from the government price, the so-called fee for Medicare benefit paid for the same item of service.

Being marooned with a ration of hard tack is not politically palatable, especially for a patient with cataracts, a dodgy hip and a heart in search of a pacemaker.

Can a medical researcher have too many publications?

The most prolific researchers may not be adhering to authorship guidelines

Medical research is a very competitive business, with a low success rate for grants and fellowships. To survive the competition, a researcher needs strong performance indicators, chief of which is the number of publications and associated citations. With publications, more is generally seen as better. However, I argue that very high publication rates should be seen as indicating poor authorship practices and should be discounted in evaluating track record.

The reason is that some researchers are claiming authorship on an extraordinary number of publications. To illustrate, using Publish or Perish software (Harzing, http://www.harzing.com/pop.htm), I did a publication count of the 27 Australian health and medical researchers listed on the Highly Cited Researchers 2014 website (Thomson Reuters, http://www.highlycited.com). In 2014, their median number of publications was 32, with eight individuals having more than 50 publications (more than one per week) and one author having more than 100 publications (more than two per week). I question whether it is possible to meaningfully participate as an author on one or more publications per week.

How many publications are feasible?

The Australian Code for the Responsible Conduct of Research, which is endorsed by the National Health and Medical Research Council (NHMRC), the Australian Research Council and Universities Australia, states:

Attribution of authorship depends to some extent on the discipline, but in all cases, authorship must be based on substantial contributions in a combination of:

  • conception and design of the project

  • analysis and interpretation of research data

  • drafting significant parts of the work or critically revising it so as to contribute to the interpretation.

The right to authorship is not tied to position or profession and does not depend on whether the contribution was paid for or voluntary. It is not enough to have provided materials or routine technical support, or to have made the measurements on which the publication is based. Substantial intellectual involvement is required.1

To get an indication of how many publications per year might be feasible while still adhering to the Code, I conducted a straw poll of 10 full professors at the University of Melbourne who are active in clinical or public health research. I asked them: “Imagine a person who is a full-time researcher funded by an NHMRC Research Fellowship. This person is named as an author on a certain number of publications per year. Let the person’s average number of publications per year be X. What do you think is the maximum feasible value of X if the person adheres to the authorship criteria above?” Answers ranged from 10 to 30, with a mean of 17.5. While this is based only on a straw poll, it has been shown that averaged estimates of experts can be surprisingly accurate.2

Based on these figures, and allowing considerable latitude for differences between disciplines and extremes of productivity, I suggest that it is not plausible that a researcher could author 50 or more publications a year and still adhere to the NHMRC authorship criteria.

Why should we be concerned?

Claiming authorship that is not due is on the spectrum of scientific misconduct. If an author has not contributed at the required level, we cannot trust that there has been adequate oversight of the quality of the work. Unfortunately, such behaviour is likely to be rewarded, except in rare instances where the research is found to be fraudulent or incompetent. There may also be a misuse of power. It has been pointed out that senior researchers can achieve high publication rates by exerting pressure on more junior researchers, who may do most of the work, to be listed as an author.3

What should be done to promote more responsible authorship?

First, I propose that producing an implausibly large number of publications per year should be counted negatively by grant review, appointment and promotion committees. This should be made explicit in the criteria for awarding grants and positions. Sometimes researchers are asked to list their “best X publications”, emphasising quality rather than quantity, but this is not enough, because a person with a large number of publications has more to choose from.

Second, employing institutions should do spot audits on the authorship contributions of staff, particularly those exceeding feasible publication rates for their discipline, similar to what occurs with medical overservicing.

Third, journals could do more to check the role of authors in producing a publication. Some require that each author state what his or her specific contribution is, but this is not universal and editors may not query whether the stated contribution is sufficient.

If action is not taken on this issue by the medical research community, funding bodies, institutions and journals, we are in danger of seeing an escalation of implausible authorship claims as researchers compete with each other for scarce resources.

Suboptimal medication-related quality of care preceding hospitalisation of older patients

Chronic diseases are the leading cause of death and disability worldwide, and their prevalence is increasing, particularly in the older population.1 In Australia, chronic diseases account for 70% of total health expenditure, costing $91.2 billion in the 2010–11 financial year.2 Optimal management of chronic disease therefore has significant potential to reduce health care expenditure, as well as to improve health outcomes for individuals.

In Australia, it is estimated that between 2% and 3% of all hospital admissions are medication related.3 There were 9.3 million hospital separations in Australia during 2011–2012 at an average cost of $5204 per separation; this suggests that there are about 232 500 medication-related admissions per year at an annual cost of $1.2 billion.4 Many of these hospitalisations could potentially be prevented by delivery of appropriate primary care.3

To facilitate the reduction of medication-related morbidity, clinical indicators have been developed that assess processes of care associated with medication use and ensuing adverse outcomes of hospitalisation.5,6 These medication-related clinical indicator sets were originally developed more than 10 years ago by expert panels in the United States, United Kingdom and Canada, based on the principles that medication-related problems are recognisable, that the adverse outcomes are foreseeable, and that their causes and outcomes are identifiable and controllable. On the basis of these clinical indicators, it has been reported that between 3% and 20% of hospitalised patients had suboptimal care before admission, depending on the country and population studied.79

Clinical indicators have been widely adopted as a measure of health system performance and quality of care provided to patients, ranging from the acute care to primary care settings, across a number of disease states.10 Use of clinical indicators to determine the appropriateness and timeliness of care for patients with chronic disease and associated medication use is a potentially underused measure for assessing health system performance. Such indicators may facilitate the identification of areas with potential for improving health care and health outcomes, as well as reducing the frequency of adverse events.

We have developed evidence-based medication-related indicators of suboptimal processes of care before hospitalisation that are specific to the Australian health care setting.11 The indicators are based on Level III or greater evidence, and were validated by an expert panel as aspects of medication use that clinicians should be able to identify and resolve in primary care.12 The aim of this study was to apply these medication-related clinical indicators to investigate the prevalence of suboptimal medication-related processes of care preceding hospitalisation of older patients.

Methods

Ethics approval for this study was obtained from the Human Research Ethics Committees of the University of South Australia (protocol number 0000025588) and the Department of Veterans’ Affairs (DVA) (protocol number E012/003).

Data source

We analysed DVA administrative health claims data to determine the prevalence of clinical indicators of suboptimal medication-related processes of care before hospitalisation in a treatment population of about 300 000 veterans during the study period (1 July 2007 to 30 June 2012). The DVA claims database contains patient-specific demographic data, including date of birth, date of death, sex, level of entitlement and residential status, as well as details of all prescription medicines, medical and allied health services, and hospitalisations provided to veterans for which the DVA pays a subsidy. Medicines are coded in the dataset according to the World Health Organization anatomical and therapeutic chemical (ATC) classification13 and the Pharmaceutical Benefits Schedule (PBS) item codes.14 Services are coded according to the Medicare Benefits Schedule (MBS),15 and hospitalisations are coded according to the World Health Organization International Classification of Diseases, 10th revision, Australian modification (ICD-10-AM).16

Prevalence of clinical indicators in the DVA database

Details of the development of the clinical indicators of suboptimal medication-related processes of care before hospitalisation have been published elsewhere.11 As an example of an indicator where the outcome of interest is hospitalisation for acute coronary syndrome, the associated process of care is defined as the combination of “patient has coronary artery stent (in 1 year before admission)” and “no use of aspirin or clopidogrel (in 12 months before admission)”.11

We reviewed the clinical indicators to identify those that were suitable for testing with the DVA administrative health claims data. As the DVA database is an administrative claims dataset, it contains records only for medicines and health services that attract a subsidy. Health care activities that do not have an individual funding item number, such as blood pressure measurement, are not recorded in the administrative claims database. While the use of health services (such as testing for glycated haemoglobin [HbA1c] levels) can be determined from the claims data, the test results are not available. The criteria for appropriate use of health services as part of the process of care adopted by the indicators were based on practice recommendations in Australian evidence-based guidelines.11 Some of the validated indicators included processes of care that could not be identified in the administrative claims database, and therefore had to be excluded from this analysis. A total of 21 of the 29 validated indicators included medication-related processes of care that could be identified in the claims database and were therefore included in this analysis. They were drawn from six disease groupings: cardiovascular disease, respiratory disease, gastrointestinal disease, osteoporosis or fracture, renal disease, and diabetes. Of these 21 indicators, 13 are based on Level I evidence.11 Indicators that could not be included related to conditions that could not be accurately identified in the data: moderate to severe chronic obstructive pulmonary disease with frequent exacerbations, dyspepsia, and positive test results for Helicobacter pylori; influenza and pneumococcal vaccinations are not recorded in the database, nor are the doses of medicines used (corticosteroids) or the measurement of vitamin D or calcium levels.11

Data rules were developed for identifying each pattern of care and hospitalisation outcome for each indicator in the administrative claims dataset. These data rules included ICD-10-AM codes that identified each hospitalisation outcome, ATC or PBS item codes that identified medications, and MBS codes that identified testing procedures or claims related to the process of care. DVA administrative health claims between 1 July 2007 and 30 June 2012 were analysed to identify all hospitalisations with a primary diagnosis for the outcomes, and all MBS and PBS claims were analysed for patterns of care for the clinical indicator set.

We calculated the prevalence of hospitalisations with suboptimal medication-related processes of care before hospitalisation, as defined by the clinical indicator set. The prevalence was defined as the proportion of individuals with both the pattern of care and the associated hospitalisation divided by the total number of hospitalisations for that indicator. Demographic data were obtained for patients at study entry. All analyses were undertaken with SAS for Windows, v9.4 (SAS Institute).

Results

There were 164 813 hospitalisations for the conditions included in the clinical indicator set over the 5-year study period, encompassing 83 430 patients. The median age of the study population was 81 years (interquartile range, 78–84 years); 54.5% were men, and 6.9% resided in an aged care facility at the time of admission (Box 1).

Box 2 contains the final list of clinical indicators included in the study and the prevalence of suboptimal medication-related processes of care preceding hospitalisation. More than one-third (34.5%) of the study population had at least one hospitalisation and 10.4% had two or more hospitalisations where there had been suboptimal medication-related processes of care before admission (Box 1). The overall proportion of hospitalisations that were preceded by suboptimal medication-related processes of care was 25.2% (41 546 hospitalisations). The most common hospitalisations were for cardiovascular disease (including acute coronary syndromes and heart failure), fracture and gastrointestinal conditions. Fracture and congestive heart failure (CHF) caused the highest numbers of hospitalisations that were preceded by suboptimal medication-related processes of care (Box 2). Of the fracture hospitalisations, 85.4% were for patients aged 65 years or older who had been dispensed a falls-risk medicine before admission; 19.7% and 17.2% of fracture hospitalisations were for men and women, respectively, who had a history of fracture or osteoporosis but had not received a medicine for osteoporosis. There were 4744 CHF admissions (17.1%) of patients with a history of CHF who had not been dispensed an angiotensin-converting enzyme inhibitor (ACEI) or an angiotensin receptor blocker (ARB) in the 3 months before admission. More than one in 10 admissions for gastrointestinal bleeding or ulcer were associated with long-term use of non-steroidal anti-inflammatory drugs (NSAIDs). About one in 10 admissions for renal failure occurred in patients with a history of diabetes who had not received a renal function test in the year before admission and were not dispensed an ACEI or ARB (Box 2).

Although there were more than 33 363 hospitalisations for acute coronary syndromes during the study period, less than 2% involved individuals with a history of myocardial infarction or who had received cardiac stents and had not been dispensed acute coronary syndrome medicines recommended by the guidelines. Similarly, although there were more than 17 149 hospitalisations for gastrointestinal bleeding, ulcer or gastritis during the study period, less than 1% involved patients with a prior history of gastrointestinal bleeding or ulcer who had been dispensed an NSAID without a concurrent gastroprotective agent (Box 2). There were 1751 admissions for hyperglycaemia or hypoglycaemia; only 209 of these patients (11.9%) were prescribed insulin and had not received an HbA1c test in the 6 months before admission.

Discussion

This is the first study to examine suboptimal medication-related processes of care before hospitalisation. We applied newly developed evidence-based clinical indicators specific to the Australian health care setting and found that 25.2% of hospitalisations for conditions identified in the clinical indicator set were preceded by suboptimal medication-related processes of care. Of the 28 807 patients in the study who had hospitalisations preceded by suboptimal medication-related processes of care, 30% (8640 patients) had multiple such hospital admissions. At least one in 10 hospitalisations for CHF, ischaemic stroke, asthma, gastrointestinal ulcer or bleeding, fracture, renal failure or nephropathy, hyperglycaemia or hypoglycaemia were preceded by suboptimal medication-related processes of care that clinicians should be able to identify and avoid. The frequency of falls-risk medicine use before hospitalisation for a fracture was particularly high (85.4%), highlighting the need to review appropriate prescribing of these medications for older people, who may be particularly vulnerable to their adverse effects.

A recent Australian study (CareTrack) examined the provision of appropriate health care. The investigation was based on medical records from health care practices (primary and secondary care) and hospitals, and it found that 43% of Australian patients had not received appropriate care.17 The CareTrack study examined process indicators only, and these were not linked to outcome measures, such as hospitalisation. The indicators included in the study were either consensus or evidence-based in nature, and were related to individual patient data. Gaps in the provision of appropriate care for specific conditions were identified (including for diabetes, osteoporosis, asthma and stroke), consistent with the results of our study.

Many of the conditions for which suboptimal processes of care were identified by our study fall within National Health Priority Areas for Australia or are associated with a high disease burden in Australia.18 This highlights the potential suitability of the medication-related indicators for monitoring appropriate provision of health care in Australia.

Other studies have highlighted the suitability of clinical indicators as quality indicators for monitoring health system performance and assessing the quality of patient care.5,7,10 Our study showed that administrative health databases can be used to investigate suboptimal medication-related processes of care before hospitalisation through the application of clinical indicators, and to assess the appropriateness of health care in current clinical practice. Routine prospective monitoring of trends in suboptimal processes of care associated with medicine use, and using the indicators in administrative health datasets or as data-mining tools in primary care, could provide a valuable tool for both monitoring and improving health system performance. Primary care interventions, such as patient-specific feedback to medical practitioners, could be focused on improving processes of care that have known and significant risks for patient outcomes and health care expenditure.

The suboptimal processes of care associated with the medication-related indicators applied in our study were validated by an expert panel as problems that clinicians should be able to recognise as suboptimal, with adverse outcomes that are foreseeable, and which could be both identified and controlled. Collaborative home medicines reviews that involve the patient, the pharmacist and the general practitioner have been shown to increase the identification and resolution of medication-related problems,19 and to reduce hospitalisation of patients with heart failure20 and those taking warfarin.21 The suboptimal care processes leading to hospitalisation outcomes in our study are the types of problems that could be identified and potentially resolved with a medication review (eg, reviewing the use of laxatives by chronic users of opioids or of falls-risk medications). Future research could be conducted to confirm whether such reviews are effective in reducing the incidence of suboptimal medication-related processes of care.

A limitation of our study is that we did not assess whether implementation of appropriate care processes would have avoided hospitalisation. It may be that hospitalisations would still have occurred even if the appropriate pattern of care had been implemented. Of interest for future studies would be an examination of the occurrence and effect on hospital admissions of the care processes defined by the indicator set. In addition, there could have been a subset of patients in the study population for whom certain medications were contraindicated, possibly related to comorbid conditions that we were not able to identify. An additional limitation was the inability to distinguish between individuals with diastolic and systolic heart failure on the basis of the available data; we acknowledge that the evidence base for the efficacy of ACEIs and ARBs in reducing long-term morbidity and mortality in those with diastolic heart failure is currently lacking.22 Furthermore, we were unable to assess the use of over-the-counter medicines.

Our study analysed DVA administrative data, which cover an older population of patients with a median age of 81 years. However, our results are probably applicable to other older Australians. Age-specific comparisons of DVA Gold Card holders (those eligible for all health services subsidised by the DVA) without service-related disability with the wider Australian population have found similar rates of GP visits, filling of prescriptions, and hospitalisations per year.23

Although differences in the definitions of clinical indicators may limit their applicability to other population groups, the indicators we employed are based on high-level evidence for common chronic conditions and are linked to patient outcomes. More than 60% of the indicators examined were based on Level I evidence, which, where applicable, included clinical studies of those aged 75 years or older (eg, the use of anti-osteoporosis medicines to reduce the incidence of fractures).11

In summary, this study highlights conditions associated with suboptimal medication-related processes of care in the primary care setting. The patterns of care on which the indicators are based incorporate high-level evidence and are therefore likely to be applicable internationally. Failure to implement appropriate patterns of care suggests that an opportunity to improve health care outcomes is being missed. Routine prospective monitoring of the prevalence of suboptimal processes of care and adverse outcomes in the Australian health care system using clinical indicators may provide a means for assessing the appropriateness of care for common chronic conditions, and for identifying evidence–practice gaps in primary care. The results could be used to inform and focus the development of interventions and efforts to improve the quality of health care delivery, potentially reducing morbidity and health care costs.

Box 1 
Demographics of the study population: hospitalisation for diagnoses in the medication-related clinical indicator set (n = 83 430)

Age, median (interquartile range)

81 years (78–84 years)

Sex, n (%)

Male

45 456 (54.5%)

Female

37 974 (45.5%)

Location of residence, n (%)

Residential aged care facility

5725 (6.9%)

Community

77 705 (93.1%)

Hospitalisations with suboptimal processes of care before admission, n (%)

0

54 623 (65.5%)

1

20 167 (24.2%)

≥2

8640 (10.4%)

Box 2 
Prevalence of hospitalisations after suboptimal processes of care as defined by the medication-related clinical indicator set

No.

Hospitalisation outcome

Process of care (preceding hospitalisation)

Total hospitalisations (TH)

Hospitalisations after suboptimal care [% TH, 95% CI]


Cardiovascular disease indicators

1

Acute coronary syndrome

  1. History of myocardial infarction (in 2 years before admission)
  2. Not on aspirin, β-blocker, ACEI or ARB and statin (in 3 months before admission)

33 363

567 [1.69%, 1.56%–1.84%]

2

Acute coronary syndrome

  1. Patient has coronary artery stent (in 1 year before admission)
  2. No use of aspirin or clopidogrel (in 12 months before admission)

33 363

640 [1.91%, 1.75%–2.05%]

3

CHF

  1. History of CHF (in 2 years before admission)
  2. Not on an ACEI or ARB (in 3 months before admission)

27 828

4744 [17.05%, 16.66%–17.54%]

4

CHF or heart block

  1. History of CHF and heart block or advanced bradycardia (in 2 years before admission)
  2. Use of digoxin (in 6 months before admission)

31 039

195 [0.63%, 0.54%–0.72%]

5

Ischaemic stroke

  1. History of chronic atrial fibrillation or ischaemic stroke (in 2 years before admission)
  2. No use of warfarin or aspirin (in 3 months before admission)

6637

677 [10.20%, 9.47%–10.93%]

Respiratory disease indicators

6

Asthma

  1. History of asthma
  2. Use of short-acting β-agonist more than three times per week
  3. No use of inhaled corticosteroids

1335

214 [16.03%, 14.13%–18.07%]

7

Asthma

  1. History of asthma
  2. Use of long-acting β-agonist
  3. No use of inhaled corticosteroids

1335

10 [0.75%, 0.32%–1.28%]

Gastrointestinal disease indicators

8

Gastrointestinal bleed, perforation or ulcer or gastritis

  1. History of gastrointestinal ulcer or bleeding
  2. NSAID use for at least 1 month
  3. No use of gastroprotective agent (eg, proton pump inhibitor)

17 149

107 [0.62%, 0.48%–0.72%]

9

Chronic constipation or impaction

  1. Regular use of a strong opioid analgesic (fentanyl, oxycodone, morphine)
  2. No concurrent use of a laxative

6780

604 [8.91%, 8.22%–9.58%]

10

Gastrointestinal ulcer or bleed

  1. Patient with osteoarthritis
  2. Dispensed long-term NSAID therapy (including cyclooxygenase-2 inhibitors)

17 125

2166 [12.65%, 12.20%–13.20%]

Osteoporosis or fracture indicators

11

Fracture

  1. Female patient
  2. History of osteoporosis or fracture
  3. No use of hormone replacement therapy, bisphosphonate, teriparatide, selective oestrogen receptor modulators or strontium

20 213

3467 [17.15%, 16.68%–17.72%]

12

Fracture

  1. Male patient
  2. History of osteoporosis or fracture
  3. No use of bisphosphonate or teriparatide

12 231

2406 [19.67%, 18.98%–20.38%]

13

Fracture

  1. Patient aged 65 years or older
  2. Use of a falls-risk medicine6,7,24 (eg, long-acting hypnotic or anxiolytic, tricyclic antidepressant)

31 486

26 892 [85.41%, 85.01%–85.79%]

Renal disease indicators

14

Renal failure or nephropathy

  1. History of diabetes
  2. Microalbuminuria and plasma creatinine not monitored in previous 12 months
  3. Patient not on ACEI or ARB

7335

665 [9.07%, 8.44%–9.76%]

15

Renal failure

  1. NSAID use for >&nbsp3 months
  2. Serum creatinine not monitored in the previous 12 months

7113

102 [1.43%, 1.13%–1.67%]

Diabetes indicators

16

Hyperglycaemia

  1. Use of an oral hypoglycaemic agent
  2. HbA1c level not monitored in previous 6 months

223

42 [18.83%, 13.67%–23.93%]

17

Hypoglycaemia

  1. Use of a long-acting oral hypoglycaemic agent (glibenclamide or glimepiride)
  2. HbA1c level not monitored in the previous 6 months

1528

67 [4.38%, 3.37%–5.43%]

18

Hyperglycaemia or hypoglycaemia

  1. Use of insulin
  2. HbA1c level not monitored in the previous 6 months

1751

209 [11.94%, 10.38%–13.42%]

19

Hyperglycaemia or hypoglycaemia

  1. Use of insulin or oral hypoglycaemic medicines
  2. Use of medicines that may alter blood glucose concentration
  3. HbA1c level not monitored in the previous 6 months

1751

103 [5.88%, 4.80%–7.01%]

20

Hypoglycaemia

  1. Use of glibenclamide or glimepiride
  2. Renal function not monitored in the previous year

1528

42 [2.75%, 1.97%–3.63%]

21

Cardiovascular disease

  1. History of diabetes
  2. Not on lipid-lowering drug

67 177

2541 [3.78%, 3.66%–3.94%]


ACEI = angiotensin-converting enzyme inhibitor; ARB = angiotensin receptor blocker; CHF = congestive heart failure; HbA1c = glycated haemoglobin; NSAID = non-steroidal anti-inflammatory drug.

Medicare Local–Local Health Network partnerships in South Australia: lessons for Primary Health Networks

Medicare Locals (MLs) were one of the shortest-lived features of the Australian health care landscape, existing for just 4 years. In 2011, the federal government established 61 MLs. The major reasons for their establishment were to strengthen the multidisciplinary aspects of primary health care (PHC) and to improve population health planning — features identified as important in recent proposals for Australian health reform.1 Contractual requirements for MLs included population health planning; needs assessments; and working with general practices, other health providers, and state and territory health networks. A 2014 review of MLs criticised their performance, noting that they “failed to appropriately involve and engage GPs” and that there was “lack of clarity in what many Medicare Locals are trying to achieve” and “variability in both the scope and delivery of activities”.2 The government responded by replacing MLs with a smaller number of Primary Health Networks (PHNs) that commenced operating in July 2015.

Inter-organisational networks are increasingly recognised in the literature as a useful approach for complex problems, and for sharing knowledge and resources.3,4 Such networks require leadership, careful planning, time and resources, and their value is more evident in the longer than in the shorter term.3,5

Local Health Networks (LHNs) are state-based entities partially funded by the federal government under the 2011 National Health Reform Agreement.6 One area emphasised in this agreement was the partnership between LHNs and MLs in delivering coordinated services.68 Despite the emphasis on collaboration, little is known about how MLs have negotiated with LHNs in population health planning. An evaluation of nine MLs across Australia revealed examples of specific links, such as ML representatives being appointed to LHN governing councils. This evaluation identified a need for a framework that ensured that the funding and governance of LHNs did not undermine the goals of MLs.9 To enable high-quality and coordinated PHC, further efforts to make ML and LHN policies and protocols more consistent were recommended.10

This article examines whether MLs made any significant contributions to improving PHC services, with a specific focus on the effectiveness of their partnerships with state-funded LHNs in population health planning. Here, we report on partnerships between South Australian MLs and LHNs. We examined factors that facilitated or constrained collaborations, with the aim of providing lessons and recommendations for LHNs and the new PHNs.

Methods

We conducted interviews with between two and five key informants from each of the five South Australian MLs and the five South Australian LHNs (a total of 34 people) between March and July 2014 (Box 1). Chief executive officers were asked to nominate key executive or program leader staff for interviewing. With the exception of the Women’s and Children’s Health Network, which is a statewide network, the other LHNs cover specific geographical areas.

The interviews explored population health planning processes, examples of successful collaboration, and participants’ perceptions of political and contextual factors that facilitated or constrained collaboration between MLs and LHNs. We specifically discussed needs assessment and population health planning processes in MLs, the scope and areas of collaboration between MLs and LHNs, features that made the collaborations work, and factors that would contribute to effective and sustainable working relationships between PHNs and LHNs in the future.

Interviews were audio-recorded and transcribed. We developed a coding structure, and three interviews were double-coded by two researchers to establish the usefulness of the coding structure in terms of concept validity and coding consistency.

Ethics approval was granted by the Southern Adelaide Clinical Human Research Ethics Committee.

Results

Quotes in this section have been included to illustrate our findings; we have identified the participants by number (P1–P34) and health care role.

Considerable work in needs assessment and population health planning has been undertaken by MLs

We found that all MLs in this study had completed a comprehensive needs assessment and instituted population health planning processes (including collecting, collating and synthesising health and social data), engaged with local stakeholders (including community engagement to identify needs), set priorities according to the needs assessment data and, to a lesser extent, undertaken program and outcome evaluations.

We’ve taken a detailed look at the quantitative and qualitative data, and engaged with communities, health providers and key stakeholders, [to] identify health needs, prioritise those and determine strategies to assist in addressing those in the future, a significant work (ML representative, P17).

The process was also reported as a capacity-building process for the ML workforce that brought together a variety of skills (eg, health informatics, statistics, population health planning) to synthesise data.

We first outsourced our population health planning and data analysis, but we have tried to build that capacity within the organisation around research and analysis, mapping and interpreting data (ML representative, P16).

Population health planning and program implementation facilitated positive collaborations between MLs and LHNs

The participants described a range of interactions between MLs and LHNs, including data sharing, joint community consultation sessions, program evaluation, and joint training activities. These were undertaken in different contexts, including steering committees, working groups and informal relationships. Having to deal with five MLs was seen as more difficult for the statewide Women’s and Children’s LHN. Box 2 lists areas and examples of collaboration between MLs and LHNs.

Participants noted the establishment of the Southern Adelaide Health Alliance (SAHA) — drawing together the Southern Adelaide–Fleurieu–Kangaroo Island ML, the Southern Adelaide LHN, the Health Consumers Alliance of SA and the SA Ambulance Service in southern Adelaide — as an example of a strategic partnership that generated opportunities to enhance collaborative planning and fostered trust and reciprocity between the key stakeholders.

Through SAHA we have been able to develop resources and share ideas and plan jointly, that’s [ie, the establishment of SAHA] been a very good thing to formalise partnership (ML representative, P11).

The focus of LHNs on hospital services constrains engagement in broader population health planning

Participants described the importance of the ML–LHN partnership in population health planning. Participants from both organisation types noted, however, that the focus of LHNs on hospital management and the associated pressures of dealing with acute care demands limited their opportunity for stronger engagement in the population health planning work of the MLs.

LHN is missing the mark in that it’s still a sickness-focus rather than a wellness-focus … the focus is on providing hospital services, not preventing the need for hospital services (LHN representative, P31).

The new funding model was reported as a factor moving LHNs away from population health activities. For example, the shift to activity-based funding (ie, funding allocated to specific, mainly clinical activities) within the LHNs raised concerns that LHNs were becoming less involved in population and preventive care.

The withdrawal of funding for most health promotion programs and the reorientation of state-funded PHC services towards chronic disease management in South Australia in recent years11 resulted in LHNs and state-funded PHC services moving further away from a population health approach.

What was PHC in the [region] has been devolved into hospitals within the past few years, so it is a very different agenda to the agenda that the MLs are working on (LHN representative, P34).

MLs were successful in engaging with a broad range of local PHC stakeholders

One of the major strengths of MLs mentioned by all study participants was their strong focus on engagement with a wide range of stakeholders, including general practitioners, allied health professionals, pharmacies, local community members, non-government organisations, local governments and state-funded PHC services. This engagement assisted in identifying local health needs, and in prioritising and determining strategies that focused on those needs. The time and effort invested by MLs in establishing working relationships with local stakeholders was particularly appreciated by people working in LHNs. Most participants saw the broader community focus, multidisciplinary work and better integration of allied health services into the PHC system as a major accomplishment of MLs that further distinguished them from the previous Divisions of General Practice.

MLs have a broader focus on population health, are more inclusive of non-general practice services, have the ability to pull in private and non-government organisations in a way that general practice divisions didn’t have. It is a positive addition for the PHC landscape, it’s important that more voices are heard than just those voices of the general practitioners (LHN representative, P20).

Health promotion and social determinants of health attracted little attention in action and collaborations between MLs and LHNs

We found no specific examples of collaboration between MLs and LHNs that were directed towards social determinants of health. Although some MLs had strategies that focused on such factors (eg, links with the transport and education sectors, employment of outreach workers), there was considerable variability in terms of funding, resources and capabilities that affected the capacity of MLs to attend to social determinants of health.

In the current policy environment, there is much confusion about who is responsible for health promotion in the PHC sector. Recent state policy changes have led to an emphasis on acute and intermediate care, with extensive cuts to funding of health promotion and community-based programs in LHNs. Most ML participants believed that they had neither the capacity nor the funding to fill the gaps in health promotion.

There had been a thought from LHNs that health promotion fell within MLs’ mandate, but we’re not funded to do that type of work, and that’s still not clearly defined with the State Primary Health Care Plan (ML representative, P17).

Strong leadership and systematic support are required to initiate and sustain collaboration

There was general consensus among participants that, in most cases, opportunities for collaboration between MLs and LHNs relied on individual leadership rather than on systemic support and organisational structures. Both ML and LHN staff felt the lack of formalised collaboration strategies was particularly challenging, given that state and federal governments had different strategy directions and priorities.

[opportunities for collaborative engagement] depended so much more on personality rather than systems. With a system support it’s easy to integrate two different agencies, but, because the cultures of the two agencies are so different and more dependent on individual leadership, it’s hard to progress at any pace faster than what it is now (ML representative, P3).

The meetings and relationship that I had with the ML have changed over time depending on personality and management style … I don’t believe the systems were there to set up the relationship (LHN representative, P30).

Continual policy changes and uncertainty in the PHC landscape constrained collaboration

Continual policy changes, restructuring, and uncertainty in both the state and federal PHC landscapes were frequently mentioned by ML and LHN participants as a barrier to collaboration.

Uncertainty around the structure of MLs means that some of the things that we might have progressed haven’t been able to go forward as confidently as we wanted to, we don’t want to be in a situation where we’re compromising the ability to deliver health care, we’re not certain about the funding or the structural future of MLs (LHN representative, P23).

One ML participant noted that workforce movement caused by the restructuring of PHC hindered retaining expertise and maintaining collaborations.

Losing or shuffling of key staff with historical knowledge has been a real barrier … when you lose the people, you lose the knowledge and you lose the relationship, and that is very much what’s occurred in SA Health (ML representative, P1).

Discussion

During the short period of their existence, MLs in South Australia were successful in identifying local needs and building good relationships with a range of stakeholders and health providers, particularly GPs and allied health professionals. Our study reports examples of such collaborations, and provides some lessons that may assist PHNs during and after their establishment (Box 3).

The findings of this study in South Australia may not be generalisable to other Australian states and territories. We acknowledge that the extent of implementation and the sustainability of some of our examples are unknown. Moreover, our study is unable to compare the relative achievements of MLs in developing partnerships and those of the previous Divisions of General Practice.

The Public Health Association of Australia and the Australian Healthcare and Hospitals Association convened a series of PHC roadshows to identify opportunities, challenges and recommendations for the new PHNs. Some of our findings are consistent with the points raised in their report, including that “community needs assessment data should be utilised effectively”, “partnerships should be formalised”, and “PHNs must play a role as a change agent for health promotion, working with enabling organisations”.12

It is essential that the good work of MLs in establishing trust and working relationships is not lost, especially given the possible cost to the Australian Government of dismantling the MLs has been estimated by the Opposition as being more than $200 million.13 Effective and sustainable collaboration is more likely when supported by strategic planning, strong leadership, stable organisational structures and effective networks that draw on strong personal relationships. Individual networking opportunities and the importance of personal working relationships must also be exploited to boost effective partnerships. Inter-organisational networks have shown early promise in facilitating collaboration (eg, the SAHA) but need evaluation and long-term commitment to ensure the sustainability that will increase their chances of contributing to improved health outcomes.3,14

Health promotion and action on the social determinants of health are integral components of comprehensive PHC.15,16 Reviews of the health system in Australia have reinforced the importance of health promotion in reducing the impact of chronic diseases and mental illnesses, as well as demands on hospital services and the costs of the health system.1720 The World Health Organization Commission on Social Determinants of Health has also emphasised the role of PHC in taking action on social determinants of health at a local level.21 Despite strategies in some South Australian MLs to support this area of activity, they were patchy and financially not well supported. The PHNs do not appear to regard health promotion and disease prevention as being within their area of responsibility, but our study suggests that it is important that they do.

Finally, planning for population health, building trust and relationships, implementing programs and evaluating outcomes all require long-term investment, support and commitment that should be explicitly clarified in the objectives, contractual requirements and outcome measurement strategies of PHC organisations. As PHC operates in an unstable environment in which it is affected by constant policy changes, political influences and repeated restructuring of the health system, it is difficult to achieve its long-term objectives of improving health equity and population health.

The short lifespan of the MLs has prevented evaluation of their long-term impact and effectiveness. As noted in the Public Health Association of Australia and Australian Healthcare and Hospitals Association report,12 “stability is required in the system”. Fostering networks of the kind that MLs established in the past few years is a complex and time-consuming venture. A further round of reorganisation risks paralysing activity because of continuing uncertainty about the form and function of population health planning and the fear that the new structures may again be transitory. In this case, the gains and investments made will be lost to our health systems. This underlines the need for rigorous evaluation of any health care reforms, and for assessing the extent to which the reforms have helped to improve levels of equity, effectiveness, efficiency, quality and sustainability.

Box 1 
Roles and locations of the 34 study participants, South Australia

Organisation

Participants interviewed (number)


Medicare Locals

Central Adelaide and Hills

Northern Adelaide

Southern Adelaide–Fleurieu–Kangaroo Island

CEO/deputy CEO (3)

Country North SA

Senior executive (9)

Country South SA

Program manager (7)

Local Health Networks

Central Adelaide

Northern Adelaide

CEO (1)

Southern Adelaide

Director/manager (10)

Country Health SA

Former director (1)

Women’s and Children’s

Project officer (3)


CEO = chief executive officer.

Box 2 
Areas and examples of collaboration between Medicare Locals (MLs) and Local Health Networks (LHNs) in South Australia

Area of collaboration

Examples


Data sharing and interpretation

LHN providing health data to corresponding ML; eg, data on after-hours care, emergency department admissions, and general population health data (in all five MLs)Discussions and meetings about data interpretation and use

Community consultation

Joint consultation sessions, or LHN or ML members attending consultation sessions as invitees, sharing information derived from consultation sessions (in four sites)

Collaboration in program planning and implementation

General support and referring clients to programs; eg, diabetes management, physical health fitness and men’s health programsCollaboration between Aboriginal ML health staff and hospital Aboriginal liaison officers to identify and assist Aboriginal people leaving hospital to navigate primary health care services, and to provide broader social support (in four sites)

Monitoring and program evaluation

Development of an evaluation framework and key performance indicators to manage and monitor respiratory disease in the region (in one site)

Sharing the load of clinical care

Patient referrals from GP Plus centres (state-funded primary health care services) to ML, and vice versa, for mental health consultations (in two sites)

Training

Joint professional development sessions to train people in residential aged care facilities on emergency admissions; staff training in mental health (in two sites)

Funding support

ML provided funding to LHN to run an Aboriginal community event program or to implement outreach programs (in one site)


Box 3 
Lessons for Primary Health Networks (PHNs) drawn from our analysis

PHNs should:

  • acknowledge, utilise and apply the comprehensive work undertaken by Medicare Locals (MLs) in local needs assessments and priority setting;
  • seek to retain the population health workforce built during the brief existence of the MLs;
  • view general practice as a key stakeholder but also build networks with other primary health care providers, and balance the views of general practitioners with those of other stakeholders who may have diverse or conflicting views regarding the role of primary health care organisations;
  • devote resources to promoting engagement with Local Health Networks (LHNs) and other stakeholders, to develop strategic partnerships in planning and program implementation; and
  • ensure that network activity achieves measurable short- and long-term benefits.

LHNs should:

  • accept and welcome PHNs as essential community partners in an integrated health care system;
  • develop joint understanding of the roles and responsibilities of PHNs and LHNs, including their roles in health promotion and addressing social determinants of health as key elements of comprehensive primary health care; and
  • seek to form strategic partnerships with PHNs that aim to overcome differences in focus and culture and improve the coordination of primary health care.

State and federal governments should:

  • recognise that PHNs and LHNs require long-term investment, funding, and organisational stability and support to ensure they have adequate time and certainty to build and maintain collaborations, and to evaluate the impact of collaborative work on population health equity and outcomes.

[Correspondence] Methodology of the SEYLE trial on suicide prevention in schools

Over the past decade, UK Child and Adolescent Mental Health Services (CAMHS) have faced a rising tide of ever-increasing demand, coupled with diminishing funding. Cost-effective interventions to target suicide attempts in adolescents are needed urgently. In this bleak context, the SEYLE trial1 could chart a course to safer waters.

[Editorial] India—small progress in health care, decline in rural services

As the second most populated nation in the world, with 1·2 billion people, India is a complex society, with wide ethnic, religious, and cultural variations; and deeply entrenched inequalities in wealth distribution, education, and access to health-care services. In 2011, the Lancet India Series called for the implementation of a universal Indian Health Service by 2020, accompanied by structural, educational, and political changes. The authors recommended that government overall health spend be increased from the current 1·04% to 4% of gross domestic product by 2015, and to 6% by 2020.

[Correspondence] Tackling obesity: challenges ahead

As highlighted by William Dietz and colleagues1 in the recent Lancet Obesity Series, the obesity pandemic is no longer a problem only for the developed world, and clinical care for obese patients must be addressed. We are concerned that increasing obesity in women in developing countries might impact negatively on existing maternal health services in low-resource settings. Women with obesity have greater risk of pre-eclampsia, gestational diabetes, premature delivery, macrosomia, dystocia, post-partum haemorrhage, and miscarriage,2 and their babies are at a 62% increased risk of dying within 48 hours after birth compared with newborn babies of mothers without obesity.

National Social Housing Survey: detailed results 2014

This report provides an overview of the national findings of the 2014 National Social Housing Survey. The report shows that the majority of tenants are satisfied with the services provided by their housing organisation, with community housing tenants the most satisfied. Tenants report a range of benefits from living in social housing and the majority live in dwellings of an acceptable standard.