Why are knee replacement rates in Australia over four times higher than they are in Israel? Or the rate for caesarean deliveries nearly twice as high as in Finland? These findings come from an Organisation for Economic Co-operation and Development report that highlighted substantial variation in the rates of several common health care interventions both across and within 13 countries.1 These types of geographic variations in health care use have been consistently demonstrated over long periods of time and for a vast range of clinical interventions.2–6

Variation in health care use across Australia has now been mapped in the recently published Australian atlas of healthcare variation, produced by the Australian Commission on Safety and Quality in Health Care (ACSQHC) and the National Health Performance Authority.7 Health care use by location of patient residence is mapped using standard geographic regions. Rates are standardised by age to adjust for age differences between different geographic populations. Data used to produce the Atlas have come from three datasets: the Admitted Patient Care National Minimum Data Set (APC NMDS), covering patients admitted to public and private hospitals; the Medicare Benefits Scheme (MBS) claims database (use of medical services, procedures and tests covered under this scheme); and the Pharmaceutical Benefits Scheme (PBS) claims database (use of subsidised prescription medicines). This is the first time that data from all these datasets have been used to explore variation across health care settings.

Information on dispensing of antimicrobials, use of diagnostic investigations, interventions for chronic disease, mental health interventions (including use of psychotropic medicines), opioid dispensing and use of surgical procedures are presented in the Atlas. For most hospital admissions, the data are from the 2012–13 financial year. MBS and PBS data are for 2013–14. In Australia, there is high overall use of some drugs, such as antimicrobials and antidepressants, and considerable variation in the rates of some interventions, even when outliers are excluded (Box). Marked regional variation is apparent in rates of surgical interventions such as hysterectomy, endometrial ablation and MBS-funded cataract surgery. There are differences between states in use of psychotropic medicines. The patterns of hospital admission for chronic conditions, with higher rates in rural and regional Australia, contrast with the patterns seen for many elective surgical admissions. Some interventions are used more in areas of higher socio-economic status or, like knee arthroscopy, are known from previous work to be provided mainly in private settings.2 There is no public/private breakdown provided in the Atlas — this would be a useful next step in order to explore the extent to which there are discrepancies in access because of people’s ability or willingness to pay for health care.

Reasons for observed variation

Some variation will reflect differences in need for health care because of differing disease prevalence or severity. Studies of variation aim to account for demographic differences in disease prevalence by standardising results for age and sex. Variation in disease severity is more difficult to adjust for at the population level or to determine using routinely collected health care data. The same limitation applies to risk factors for disease.

Some observed variation may be explained by differences in patient preferences for type of care; for example, choice of medical rather than surgical treatment or for “aggressive” rather than “conservative” management.

Variation may reflect problems with datasets such as incomplete capture of information or inconsistency in coding practices. It may also be random variation — a particularly important consideration when analysing small populations.

Use of health services is clearly related to their supply and accessibility.1,8 High intervention rates for some types of care may reflect poor access to alternatives. One reason for the marked variation in dispensing of psychotropic medicines noted in the Atlas may be a lack of access to alternative mental health care. Similarly, decreased access to community care among rural and remote populations may explain some of the higher rates of hospitalisation in these communities for chronic diseases examined in the Atlas. Less use of elective surgery may be due to lack of local service capability or the inability of patients to pay for private care. Methods for funding or reimbursing costs of health care can markedly influence service provision. Remuneration methods that reward greater volumes of procedures provide incentives to both individual health care providers and organisations for higher rates of servicing.

Clinical decisions are a key driver of health care variation. Practice patterns of individual doctors are influenced by their knowledge, skills, experiences and differences in beliefs about the benefits or harms of specific interventions.9 Even when robust evidence on effectiveness is widely disseminated and well publicised, practices that are at variance with the evidence may remain entrenched in some areas. The personal preference of surgeons for certain types of procedures, irrespective of published literature on effectiveness, can exert a marked effect on rates of use.10–13 Thousands of Australians aged 55 and over continue to have knee arthroscopy, with markedly different rates across the country, despite evidence that arthroscopy for treatment of uncomplicated degenerative disease is no better than placebo and potentially harmful.7,14–16 Practices known to be effective, such as foot care for people with diabetes, are not consistently employed.17 Such variation highlights problems with the way research on effectiveness is translated into routine practice.

Variation may also result from “indication creep” when a treatment shown to be beneficial within a narrow set of indications (eg, for younger patients with severe disease and few co-morbidities) becomes used in patients with a broader set of indications (eg, for people with less severe disease or older patients with multimorbidity) where there is little or no evidence of effectiveness.

While there is general agreement about the usefulness of operations such as total knee replacement in patients with severe osteoarthritis, there are controversies in the literature about how some patient characteristics affect operative outcomes. Doctors differ in their opinions about which patients will benefit most, leading to different patient selection and different practice patterns.13,18 While studies comparing the long term results of different treatment strategies for the same condition in “real world” patients are starting to be reported,19 the lack of use of routine measures of patient outcome, and the risk of confounding by selection bias, mean considerable uncertainty remains about the true effects on patients of these differences in practice.

Differential use of new therapies with uncertain or unproven benefit also drives variation. The need for a system for controlled introduction and evaluation of new surgical techniques and medical technologies in Australia has been recently highlighted.20

Warranted versus unwarranted variation

Substantial variation in health care use that cannot be explained by patient needs or preferences is often referred to as unwarranted variation.1 It may reflect both underuse of care of proven benefit, raising concerns about equity and the unrealised potential for better health, or overuse of care that is ineffective or likely to confer net harm, thus posing a needless threat to patients and an opportunity cost to a society with limited resources.

Identifying the rate of use of an intervention that is most appropriate within a defined patient population is a major challenge in studying warranted versus unwarranted variation. Routine data collection currently captures a large amount of information about what care is delivered in the health care system, and how long people wait to receive it, but very little about the indications for care and patient outcomes achieved as a result.

Patient-reported outcome measures are mandated for some types of surgery in the United Kingdom21 but are not routinely used in Australia. Linkage of data from different sources to follow up patient health status (while ensuring privacy protection) is another means of determining information on outcome, but while there are some state-based systems for record linkage — for example, in Western Australia data linkage has been undertaken for several decades22 — such linkage is not routine at the national level.

Accurate measurement of the outcomes for people who undergo common or costly interventions would help clarify which types of patients (outside of research settings) are most or least likely to benefit from care. It would also help determine the appropriate population rate of intervention use for specific clinical indications, and would allow for comparisons of variation in outcomes, in addition to variation in use, of interventions.

Defining benefit thresholds is also particularly important in avoiding the natural inclination to assume that, when confronted with a range of low or high use outliers, the mid-point or average value is necessarily the one that reflects the most appropriate rate of use.

Analysing variation

Datasets used to explore variation should satisfy certain requirements. Comprehensive population coverage provides confidence that any observed variation is not due to differential capture of information across geographic areas. Age, sex and residence of the person receiving care are required for standardisation and mapping. The geographical regions used to report variation must have a population of sufficient size to prevent identification of individual patients and health care providers.

The three datasets used for analysis (APC NMDS, MBS, PBS) were established for administration and reimbursement purposes and currently have some limitations when used to investigate geographic variations in health care use. MBS and PBS data do not contain diagnostic information or the reason for provision of the service. Information on most public hospital drug usage, private prescribing or over-the-counter sales is not captured by the PBS data, nor is information on some medicines dispensed by Aboriginal health services. Pathology testing data are only captured on the three most expensive tests ordered for each patient and, as with medicines, information on most of the tests provided free of charge to public patients in hospitals is not captured. The APC NMDS contains detailed diagnostic and procedural information on admissions to a public or private hospital in Australia, but does not include details of tests ordered or drugs prescribed.

As a result, some types of care provided in the system are not consistently captured by any of these three datasets. For example, it is not possible to obtain an accurate picture of variation in total use of magnetic resonance imaging across public and private sectors. The lack of standardised hospital admission policy means some observed variations may be due to differences in admission practices rather than differences in care provided.

Despite their limitations, these three datasets provide the best available information in Australia for identifying variations in health care use. They could be rendered even more useful if some of the issues noted were remedied. Linking individual-level data across these datasets, and with death registries and other clinical or population datasets (while ensuring patient confidentiality), would provide better information about outcomes. It would also help highlight areas where care could be improved; for example, whether there is variation in secondary preventive care for specific conditions after discharge from hospital.

Responses to evidence of variation

The aim of publishing data showing variation in health care is to prompt investigation into why variation is occurring and to ensure that patients receive appropriate care. Reasons for variation need to be examined at a local level using information about service provision that is not available nationally and data sources such as registries that contain clinically richer collections of information about patient care delivery and its outcomes. Within the Atlas, there are 67 recommendations for action. States and local health care organisations should review data and practices in their region, particularly where they are outliers. Some findings have been referred for review by national bodies such as the Pharmaceutical Benefits Advisory Committee; for example, the use of topical quinolones and access to amoxicillin-clavulanate on the PBS. For some items, review of the need for evidence-based guidelines or for new Clinical Care Standards23 is identified; for example, a clinical care standard for the management of osteoarthritic knee pain. Mandated adherence to the National Safety and Quality Health Service Standards24 provides a mechanism for increasing use of evidence-based practice. The Australian Health Practitioner Regulation Agency and national boards are asked by the Commission to consider what can be done to ensure registered health professionals have up-to-date knowledge of prescribing guidelines.

Some recommendations focus on improving patients’ understanding of their care options. Evidence suggests shared decision-making approaches enable people to better choose among different options with associated benefits in terms of better knowledge and more accurate expectations of the likely effects.25,26

Medical colleges and clinical groups may investigate and respond to the data in the Atlas in a variety of ways, including via guidelines, performance measures, audit and feedback and various behavioural incentives.27

Researchers have documented large and persistent variations in health care use, far beyond that explainable by patient need or preference, for many decades.28,29 Research into causes and consequences of variation has been less prolific and linking research to action on unwarranted variation has been problematic. The involvement of policy agencies and clinical organisations in the generation and use of the Australian Atlas offers the opportunity to link investigation of variation with policy levers and actions by health care organisations and clinical groups to reduce unwarranted variation.

The idea of paying more for better quality care and paying less (or not at all) for poor quality care appears inherently sensible, and has motivated several attempts to introduce financial incentives for improving the quality of health care. These range from bonus payments to hospitals that meet specified clinical indicators for particular conditions (Queensland and Western Australia are currently implementing such schemes) or paying for structures that encourage quality (including higher payments for achieving accreditation), to penalties for poor quality, such as withholding payment for “never ever events” or shocking medical errors, such as wrong site surgery (as applied in the United Kingdom and by the United States Centers for Medicaid and Medicare Services).1,2 Activity-based funding for hospital care is widely used across the world, and quality payments are generally applied as adjustments to the case payments. Financial incentives that reward quality are also applied in primary care, but this article will focus on hospitals.

Two key questions must be considered when thinking about paying for quality. The first is whether the standard case payment is inadequate for providing quality care; that is, whether appropriate quality care, even when supplied efficiently, simply costs more than the case payment. The second is whether the use of rewards (and penalties) will encourage more appropriate or higher quality care. Any use of payments or other incentives obviously requires a clear definition of appropriate quality.

The first question involves the concern that quality could be actively constrained by not paying enough for care. There can be no sensible argument in support of paying too little to achieve appropriate quality; the question is whether it is likely to happen. In Australia, the casemix price paid through activity-based funding is based on the analysis of existing cost data supplied by public hospitals in all states and territories. Unless the present quality of care is significantly lower than appropriate, the national price will therefore reflect adequate care. This could change with technological advances or new evidence about clinical effectiveness. Incremental change is incorporated by regular revisions of casemix classifications and price. Even a major shock in terms of technological progress or additional evidence is likely to be focused on a particular case type, so that the impact on total hospital revenue would be marginal and corrected within a short period of time. While arbitrary cuts can be made by funders to the national price, these would not be a cost-based determination.

The second question is both more interesting and more challenging. Financial incentives that target health care use are generally effective, consistent with economic theory. It should follow that aligning incentives with quality improvement should enhance the quality of care. Evidence collected over the past decade has been disappointing in this respect,3,4 and more recent critiques are no more encouraging in terms of their finding improved health outcomes.5 One reason for these disappointing findings is that financial incentives are not precise, and there are wide differences in the characteristics and the contexts of the different programs. For example, incentives may be positive (extra payments) or negative (reducing or withholding payments). The incentives might apply at the hospital level, benefiting the hospital budget as a whole; at a clinical department level, benefiting the departmental budget; or be directed to individual clinicians, in cash or in kind. The size of the incentive ranges from token payments to substantial funding. This would make it difficult to generalise findings about outcomes, even if there were a series of rigorous evaluations. Any design or evaluation should therefore start by considering whether the financial incentive is well targeted and appropriate for the behaviour it is trying to change.

Financial incentives can be applied to hospital-level indicators that encompass all conditions, or be targeted at particular conditions. Targeting a particular condition is more precise, but loses the scope of the entire patient population. Even a high volume condition affects a small proportion of the patient population, so that a targeted program will achieve only a limited overall impact.

Incentives can be directed to reward either better outcomes or improved processes of care. While better health outcomes for patients are undoubtedly the desired end, good quality care does not guarantee a better outcome for the individual. Many factors other than the processes of care influence outcomes, and there is always an element of chance. Further, some outcomes may not be experienced until years after care has been delivered.

The economic principle underlying the design of payment schemes is that the funder should reward effort that promotes the interests of the funder. This requires that the hospital, department or clinician is rewarded for what they do and for how they manage factors within their control. Not surprisingly, most financial incentives are therefore applied to improving processes of care. However, to avoid losing sight of the desired better outcomes, evidence that improving the specified processes leads to better outcomes is generally required.

Establishing the evidence base is challenging. Hospitals are complex organisations and hospital care typically involves a variety of clinicians and diagnostic and treatment modalities. The links between incentive, process and health outcome depend on the actions and interactions of many different players.

As stated earlier, a performance payment alone does not achieve anything. Generally, a specific payment is grafted onto an existing payment scheme; and, unsurprisingly, what works in one context or in one organisational and funding model cannot necessarily be extrapolated to another. For example, whether funders and hospitals are operating in a competitive market or in a centrally controlled system will affect how a pay-for-performance model works. Additional payments grafted onto a population-funded model would be expected to have a different impact to paying the same reward as an adjustment of activity-based funding. Further, incentives are complex and encompass more than financial rewards. Professional status, striving for excellence, and effective leadership can each influence behaviour.6

Evidence of no benefit is not the same as no evidence of benefit. The first means that there is evidence that an intervention is not effective; the second that the necessary research has not been undertaken. Even without strong evidence of improved outcomes, some people would argue that rewarding good quality processes is, in itself, valuable because quality should be encouraged, and higher quality is more likely to improve than to harm outcomes. However, it is important to first ask whether there could be unintended consequences of payment schemes, and the answer is unequivocally: yes.

The initial effect of a payment incentive is to focus attention. Some reward payments are too small or too cumbersome for potential recipients to claim, making them ineffective. Where the incentive is sufficiently strong, the attention of management will be focused on how to maximise the rewards. While this will improve the measured processes of care, it will also draw attention away from other problems. It is difficult to establish what the opportunity cost will be, but improved performance in one aspect of care may come at the expense of foregone improvements, or even deteriorations, elsewhere.

Incentives can also have perverse effects by encouraging gaming. This can involve changing how treatment processes are counted, such as coding conditions as more complex case types; raising the threshold for recognising hospital-acquired conditions; re-defining a multidisciplinary case conference. This effect can be mitigated by monitoring and auditing processes. One of the more undesirable effects is patient selection: if there is a strong incentive to choose less complex patients, an unintended effect is that hospitals may favour easier cases, so that patients in greater need find it difficult to receive treatment. This is more challenging to monitor.

More significant is the problem of intrinsic and extrinsic motivation, which tends to be little discussed in this context. Intrinsic motivation is complex and powerful, and is vital in health care: care providers are motivated by doing their job well, caring for their patients, and gaining the respect of their peers. Extrinsic motivation relates to behaviour that is driven by external rewards; financial incentives are clearly an important form of extrinsic motivation. Not only do extrinsic motivators lose their effectiveness over time, however, they can “crowd out” or displace intrinsic motivation. As a result, the rewarded behaviour is likely to fade once the reward is removed, even among those who were doing the right thing before the incentive is introduced.7

Any discussion of financial incentives should also address the notion of purchasing health gains. This is not as simple as it first seems. Let us assume that the Australian social value, or willingness to pay for a degree of health gain as measured in quality-adjusted life-years (QALYs), is about $75 000 (a reasonable estimate based on Pharmaceutical Benefits Advisory Committee determinations8). It does not follow that the Australian health care system should spend $75 000 for every QALY gained; this would certainly not maximise the health outcomes achieved by its budget.9 Specific health gains are delivered at a range of prices; for example, if it cost $15 000 per QALY for a particular treatment, paying $75 000 represents an overpayment of $60 000, or a loss of 4 QALYs. Maximising health outcomes requires starting with the lowest cost per QALY, and adding more expensive treatments until the upper budgetary limit, or the maximum social willingness to pay for a QALY, is reached.

Translated into hospital funding, this means not paying the same price for each unit of health gain. It means paying the efficient price for each treatment for each case type, up to the maximum social willingness to pay. It requires an umpire to set the efficient price for a case type, and a different perspective for determining whether this represents value for money. According to this argument, the price paid should reflect the efficient cost of production, but the volume of cases should be managed separately. The efficient price is intended to provide the incentive for better cost control, particularly in high cost hospitals. It is aimed at improving technical efficiency; that is, maximising the output for a given input.

Finally, getting the incentives to be consistent with the desired ends is only part of the challenge. Managers, clinicians and others involved in health care may be offered the “right” incentives, but, if they lack the skills and tools to identify what and how to effect change, they are powerless to respond.10

Financial incentives used alone are a blunt instrument. Their effectiveness will depend on the size and design of the reward or penalty, and also on how they reinforce (or are inconsistent with) other signals in the operating environment. It is therefore not surprising that it is difficult to reach general conclusions about their usefulness. It is even more difficult to reach conclusions about their relative cost-effectiveness compared with alternative approaches. Further, financial incentives have an opportunity cost, diverting funds and attention from other problems. Given what is known and what is still uncertain, it would be unwise to rush into their widespread use as a strategy for improving the quality of health care in Australia. Instead, they should be applied cautiously, with careful consideration of design and context and of the potential for unintended effects, and with evaluation of outcomes.

Australian practice data from clinical audits and other research have clearly shown that dissemination of high quality clinical practice guidelines is not enough to ensure everyone with a particular clinical condition receives appropriate care.1–3 Even for clinical conditions with established networks of care, such as acute coronary syndromes (ACS), variations in care persist, not all of which can be explained by patient needs or preferences. In this article, we explore the features and underlying principles of clinical care standards (looking at the example of ACS) and the improvements in delivery of appropriate care that a clinical care standard may help to make.

The National Health Reform Agreement signed by the Council of Australian Governments in 2011 (http://www.federalfinancialrelations.gov.au/content/npa/health/_archive/national-agreement.pdf) determined that clinical standards would be developed by the Australian Commission on Safety and Quality in Health Care (the Commission) to help ensure appropriateness of care for specific clinical conditions nationally. Clinical care standards are small sets of concise recommendations (quality statements) that focus on specific gaps in evidence-based practice for a clinical condition. Their aim is to drive delivery of appropriate care, reduce unwarranted variation and to promote shared decision making between patients, carers and clinicians.

What’s different about a clinical care standard?

Unlike a clinical practice guideline, a clinical care standard is not a comprehensive management guide. Instead, it targets areas of care where both divergence from evidence and the opportunity for improvement are greatest. In collaboration with a working group of clinicians, researchers, health care organisations and consumers, the Commission uses practice data to identify key areas for improvement, which become the focus of each quality statement.

Clinical care standards are developed using a process designed to optimise the uptake and reach of the care they describe. First, each topic requires the agreement of representatives of state and territory health departments. Second, before public consultation, the draft standard is considered by representatives from private and public health sectors. Third, each draft is released for broad public consultation, with feedback sought from all levels of the health system as well as from key organisations. Finally, before it is released, the standard is submitted to the Australian Health Ministers Advisory Council and then to Australian Health Ministers. This highly collaborative and consultative method of development not only assists in ensuring the relevance of the standard to the health care system but builds engagement of both clinical and policy decision makers at multiple levels within the system. In prompting review of existing initiatives, the standard acts as a focus for integrated whole-of-system efforts to improve the quality of care.

Putting patients at the centre of care is an integral part of clinical care standards and is ensured in several ways:

• the quality statements are written from the patient’s perspective, describing the care that patients can expect to be offered by the health care system;

• a consumer fact sheet accompanies each standard describing in lay terms what the quality statement means; and

• the standards align understanding and expectations of patients, clinicians and health services about what good care is, how it should be delivered, and what needs to be put in place to ensure it happens.

Indicators are an important part of implementation support for each clinical care standard. Each standard has a set of indicators for local use by health services to monitor adherence and to identify areas for improvement. The National Stroke Foundation’s 2015 national audit recently showed how the process indicators from a standard can be used to track performance over time.2 The indicators can also be used by health services to show they are providing high quality evidence-based care, a requirement of the National Safety and Quality Health Service Standards.4 The indicators are not mandatory, as some services may have other measures in place to demonstrate they are delivering the care described within a standard.

Australia is the second country to develop national clinical standards. In 2009, the National Institute for Health and Care Excellence (NICE) established a program to develop quality standards across health care, public health and social care, for use in England. As of December 2015, NICE had developed over 100 quality standards. The Commission’s Clinical Care Standard program began in 2013. Standards on ACS, antimicrobial stewardship, acute stroke, delirium and hip fracture care have been released. Standards for osteoarthritis of the knee and heavy menstrual bleeding are under development.

Improving care for patients with acute coronary syndromes

The ACS Clinical Care Standard was developed to address substantial heterogeneity in the use of treatments known to reduce risk of cardiac events, which could not be explained by clinical complexity or patient needs.1 Research into the sources of this variation offers insights into potential targets for improving ACS care throughout Australia, and was used to inform the quality statements of the Standard (Box 1).

Practice-related factors

Translation of knowledge into practice has been identified as a major practice-related issue affecting quality of ACS care.6 In a 2009 survey, Australian clinicians reported high levels of agreement with, and adherence to, the existing (2006) ACS guidelines. However, these views correlated poorly with observed practice, with often striking overestimation by clinicians of their use of treatments recommended in the guidelines.6

Clinician misperception about patient risk of recurrent cardiovascular events and uncertainty about applying evidence for patients with complex clinical needs appear to be contributors to the variation. Cardiovascular risk stratification is a critical decision point in the appropriate provision of cardiac care. Compared with assessment using validated cardiovascular risk tools, clinical intuition more frequently overestimates the risk for low risk patients and underestimates that for high risk patients.7,8 Underappreciation of cardiovascular risk is worse for females with myocardial infarction (MI) than for males with MI and is associated with delays in providing invasive management, lower use of evidence-based drugs and an increase in the risk of late mortality.9

Even when risk is accurately estimated, challenges remain in applying the ACS evidence base among patients with complex clinical needs. Australian data show that patients with comorbidities are less likely to receive evidence-based treatments than patients at the same level of cardiovascular risk without comorbidities.10 Age and clinical comorbidities, such as prior cerebrovascular disease, lung disease and impaired renal function, elevate the risk of adverse events from invasive management (eg, reperfusion) and cardiovascular therapies (eg, antiplatelet drugs). However, the marked divergence in care for these patients suggests that intervention-related risks are not being objectively weighed up against treatment benefits (Box 2).10

Risk stratification and discussion of these risks and the benefits of coronary angiography for non-ST-segment-elevation ACS are the focus of quality statements 4 and 5 of the Standard (Box 1).

System factors

There are several important system-related contributors to ACS practice variation. The absence of systematic processes to improve the timely provision of reperfusion in ST-segment-elevation MI (STEMI) results in longer “door to balloon time” and is associated with increased rates of mortality and recurrent MI.11,12 In a survey of 35 hospitals examining implementation strategies for reducing time to reperfusion, those with at least one strategy delivered reperfusion on average 21 minutes faster than those without any strategy, and this was associated with a reduced rate of 12-month death or MI (12.8% v 22.1%, respectively; P = 0.006).12

The need for systematic processes to improve the timeliness and accuracy of diagnosis is highlighted in quality statements 1 and 2 of the Standard; quality statement 3 focuses on systems to support the timely provision of reperfusion (Box 1).

The vastness of Australia’s geography and the nation’s cultural diversity are both possible contributors to ACS practice variation and to patient outcomes. Mortality and complication rates due to MI are higher in rural and regional areas than in metropolitan areas;1,13 lack of access to clinical expertise and to timely invasive management for non-ST-segment-elevation ACS may contribute to variation in these areas of care.14 Variation in prescription of secondary prevention medications and lifestyle modifications, and in the engagement of patients to adhere to them, are likely to be particularly challenging gaps to address in the diverse demographic profile of modern Australia, yet they are important targets for well-designed interventions.

Quality statement 6 of the Standard focuses on use of an individualised care plan to improve the transition of care, including the ongoing need for secondary prevention measures (Box 1).

Impact of reducing variation

Attempts to estimate the impact of quality initiatives suggest there are substantial gains associated with making system-wide improvements to ACS care.15 Several observations are worth highlighting:

• The gains to be had from rectifying omissions of care (eg, missed opportunities in timely reperfusion) far exceed the benefits to be gained from choices between therapies (eg, immediate fibrinolysis versus transfer for percutaneous coronary intervention in STEMI).

• Improving the application of secondary prevention therapies is likely to have a much greater impact on late clinical outcomes than a focus on invasive management.

• The incremental benefit of new treatments and strategies applied to patients who are already optimally treated is relatively small and is dwarfed by the gains to be had for all by small improvements in the delivery and reach of evidence-based care across the whole system.11,12

Economic evaluation of strategies to improve the quality of ACS care in Australia are limited. Yet the fact that half of all cardiovascular events occur in patients with prior documented coronary artery disease, and that the estimated yearly costs of MI to the Australian community is $1.14 billion dollars, suggests that even modest systems improvements in ACS care are likely to be highly efficient.16

Efforts to redesign the provision of care in various parts of Australia have been promising, showing meaningful improvements in patient outcomes. For example, several health networks have sought to move the identification of STEMI into the ambulance, through the transmission of initial echocardiographic data to the emergency department, ensuring patients are brought to hospitals with appropriate clinical teams and facilities, as well as shortening the time to response when these teams are on remote call.17,18

Similarly, clinical networks that provide remote clinical support combined with access to metropolitan-based invasive services have been shown to reduce heterogeneity in clinical care and improve short term outcomes for patients residing in rural areas.14

Complementary to these initiatives, approaches to secondary prevention that embrace the individuality of patient needs and tailor education and care to these have shown significant promise in improving adherence, as well as the achievement of risk factor targets known to lower overall risk of future cardiovascular events.19,20

The uptake of the ACS Clinical Care Standard is not yet known, and neither is that of the UK’s corresponding quality standard, also released in 2014. However, substantial improvements in the care and survival for older people with hip fracture in England have been attributed to initiatives underpinned by a national clinical standard, including a national registry to support audit and feedback, and a financial incentives program.21 In December 2014, NICE reported on the uptake of 28 published quality standards. While data were limited, uptake of care could be tracked over time for many quality standards using selected process indicators.22

What the ACS Clinical Care Standard adds

The ACS Clinical Care Standard is a significant step forward in supporting clinicians and health services to realise all of the gains promised by the ACS evidence base.23 It focuses on the areas of care that are known to be most associated with variation in outcome. It supports patient involvement in critical decisions that affect their care, refocuses clinicians on the priority areas of ensuring appropriate ACS care, and informs health services about the systems required to deliver evidence-based care. The revised ACS clinical practice guidelines released in August 2016 remain consistent with the ACS Clinical Care Standard and specifically support its use for quality improvement.24

Ensuring effective and equitable care of patients with ACS across Australia is complex. For the first time, a common vision for care of patients with ACS provides an opportunity for alignment and coordination of local, state and national efforts to improve consistency of care. In doing so, the ACS Clinical Care Standard may just represent the keystone for evidence translation in Australian ACS care.

Box 2 –
Impact of cardiac risk and comorbid risk on the likelihood of angiography in acute coronary syndromes10

Health systems around the world are facing the twin pressures of increasing demand for services, caused by the impact of ageing populations and medical science developments, and a lack of resources as a consequence of economic slowdown in many countries.1 In these circumstances, it should not be surprising that there is an increased focus on using available resources to deliver high quality care and addressing variation in the provision, uptake and costs of health care2 with a view to identifying and reducing unwarranted variation.

The ubiquity of recognition of variation3–5 continues to raise the profile of variation, capturing the imagination of researchers and policy makers6 to pose a challenge to those planning and delivering health care. That challenge runs much deeper than the undemanding observation and recording of variation, to one which must stimulate clinicians, managers and patient groups across the health care system into urgent and necessary action to identify and reduce unwarranted variation. That action is essential, not only as a means of enabling the health care systems to close their funding shortfalls, but more importantly to reduce harm to patients, improve the quality of services and increase value from resources. This is the focus of the NHS Right Care initiative (www.rightcare.nhs.uk) and the genesis of the NHS Atlas of Variation series in England.

The NHS Atlas of Variation series

The NHS Atlas series is a comprehensive view of health care from a geographic perspective, principally using formal NHS administrative organisations to measure a range of indicators including spend and outcomes. The work to produce the NHS Atlas series was greatly influenced by the philosophy and experience of Professor John Wennberg of Dartmouth College in the United States, who knew the full impact of publishing variation and the concept of unwarranted variation, which he defined as “variation in the utilization of health care services that cannot be explained by variation in patient illness or patient preferences”.7

The first Atlas was produced in 2010, and was followed by a series of themed Atlases and two other compendium Atlases (Box 1). NHS England is not alone in producing an atlas of variation; a number of other countries are following the lead from America, Canada and Spain, including Australia, Germany, the Netherlands, Norway and New Zealand.

Preparation phase

There are as many lessons to learn from the pre-publication phase of the Atlas series as there are in the post-publication phase. The first lesson is the need for engagement and sponsorship from the very “top of the office”, from both policy makers and senior clinicians. That support is critical to the credibility and sustainability of Atlas production and necessary to mitigate any undue political or managerial interference regarding the main purpose of the Atlases. The Atlas editorial team was convinced that the publication of the Atlas series was much more than just about assisting the NHS deal with the increasing need and demand, which is rising faster than the resources available or the political challenges of the day; namely, meeting targets too frequently designed around organisational objectives not patient need. As important as they may be, it was considered that the publication of the Atlas series is an essential process to jolt the culture of health care away from assuming that existing patterns of care are right and that more resources are always required to improve outcomes. We knew that the culture of the medical and nursing professions, and the behaviours within the NHS, would need to change. The Atlases were designed for emotional impact as well as the transmission of information to prompt all clinicians in primary and secondary care to work together with their population to agree what services should look like, what needs to stop and what services need to start doing to provide higher value health care.

The second lesson from this phase is to remember that the purpose of sharing data on variation is not to claim what is the right or wrong rate of, say, an intervention, but to stimulate the discussion and to prompt the search for unwarranted variation, where resources are being wasted and shift those resources to more appropriate care where patients and the population achieve better outcomes. Indeed, we are reminded that it is not right to use variation data alone to determine which rate is “right” but should acknowledge that the presence of too much variation is a sign of health service delivery problems.8 These are two fundamental concepts and the Atlas production team frequently challenges itself about the use of data, how those data should be presented and to be clear about what it signals.

A way of mitigating that issue introduces the third lesson. It is critical to engage and maintain a constructive relationship with the most senior clinical leaders — in the case of NHS England, the National Clinical Directors (NCDs). This is important when selecting the indicators and agreeing the commentary for the Atlas. The leadership shown from NCDs in NHS England cannot be underestimated and should never be undervalued as an important step in the process of deciding which indicators and which dataset should be applied and what narrative to transmit. This positive relationship also enhances the credibility of the Atlas and increases the focus of attention to those indicators that have been declared as being of such importance by the NCDs, which can also lead to improved uptake and use of the Atlas series through the medium of both the printed versions and the interactive Atlases. These early lessons endorse the notion that stimulating interest and curiosity is the first step toward action and a reduction in unwarranted variation.

Publication phase

It is important to be clear that the publication of the Atlas of Variation is not a blunt performance tool, and the Atlas team is careful not to use any data that the health system does not already have access to. Therefore, available data are always used, in a novel way, to produce commentaries and illustrations, with maps, about the extent of variation for all sorts of provision, spend and outcome. The lesson is that the publication of the maps needs to be both stimulating and dramatic to draw a response from the health care system to investigate the known variation in each area of health care; an objective which appears to be achieved by organisations’ inquisitiveness to understand their position in relation to their peers and then to use that information as formative learning9 for future planning and decision making.

A key message from this phase is the involvement and engagement of other stakeholders, beyond the NCDs, in both the preparation and participation of the launch of the Atlas. It has previously been declared that the engagement of senior clinicians and policy makers is an important part of the whole process, particularly during the publication process. There are other key stakeholders to engage here too; perhaps the most important are patient representative groups and third sector organisations that can create a powerful and positive narrative about what the Atlas is displaying, remembering the message that not all variation is bad — if it were, it would be easier to take action.10 The involvement of patient representatives also helps the shared decision making (SDM) agenda, which is an important part of the transformation process, enabling the active involvement of patients with their clinicians to make the right decision about the choice of treatment.

NHS Right Care has long advocated and continues to promote the use of SDM as a way of empowering patients to become part of the solution to the challenge of delivering high quality care. The transformational program has developed and published 35 patient decision aids (PDAs) to complement the Atlas series. PDAs are specially designed resources to help patients make informed decisions about their care. People who have used the PDAs report that they understand their problem and the choices they have more clearly.

The ambition of NHS Right Care is to use the Atlas of Variation to stimulate a search for unwarranted variation in the NHS and its underlying causes, by providing a tool for learning and exploration of potential deficits in local resource allocation. That ambition is amplified when using the PDAs as a tool to engage and support patients in decision making about what is right and appropriate for them.

Public services, including health services, are under pressure to control increasing costs, and the NHS has been challenged to adapt to evolving demands and “shine a light on variation in care and unacceptable practice”11 to improve the quality and safety of care. A significant lesson is that the production and publication of an atlas of variation is not an end in itself but an essential component of a large scale transformation initiative to increase value, improve quality and reduce harm.

Next phase

The domains of quality and safety have strongly influenced the shape and delivery of the NHS for more than a decade, but is this the right paradigm for the next decade and beyond? We ask this as we are reminded that the issue of variation in health care is not a new phenomenon. Indeed, it could be argued that variation has been met with a level of inertia and confusion for many years and by raising the awareness of variation, through the publication of the NHS Atlas of Variation series, we aim to stimulate the search for unwarranted variation but also to further advance the focus of attention toward value.

If health care systems are to meet rising demand with reducing resources, there needs to be a shift from traditional patterns of planning and contracting around established organisations and clinical processes to one that is focused on “doing the right thing — for the right patient — at the right time”, where we need to think about value. The Right Care initiative has set out to promote value by encouraging organisations to aim for optimal care, declaring that it is not a process that can be done in isolation of other organisations, and to remember that no one professional group has all the necessary information or knowledge to plan and deliver optimal care.

Rather, health care systems need to look at their processes, working with their populations to decide if the balance is right between prevention, screening, diagnosis, intervention and long term care. The search for unwarranted variation plays an important part in that quest and the time has arrived for us to enter the “value era”, in which a population perspective and patient views of value are adopted to improve the health outcomes for both populations and individual patients.

Reducing variation to increase value

Possibly the simplest way to think of value is from an economic perspective. The word “value” is, like many words, slippery to define and can have a range of meanings to different people. In the plural, as in the terms “values”, the word has a moral meaning — for example, “we value diversity and equality.” In the singular, however, the meaning is largely economic.

The Right Care approach identifies three types of value:

• Allocative value — to optimise allocative efficiency by taking responsibility for the resources allocated.

• Technical value, or efficiency — it is essential that all organisations work across the health care system to maintain a good understanding of what is being delivered, including whether some services are now being delivered at a rate that could be classified as overuse.

• Personalised value — determined by the degree to which the outcome relates to the particular problem that the individual brought to the health service, where shared decision making becomes the norm for that population.

The primary focus of the Atlas series has been to create a tool to raise the profile of variation, at a population level, as part of a much bigger transformation initiative. What quickly emerged was the need to think of both population and personalised health care as being two sides of the one coin. The agenda now is to focus on increasing the value of health care to the whole population as well as on the optimal care for the individual patient. This is summarised in the Right Care approach (Box 2), which clearly offers an insight into why atlases of variation are important, but recognises that they cannot be the singular answer to transforming health care.

Conclusion

This article has demonstrated how the production and publication of an atlas of variation can be an important step in the journey toward increasing value in health care — for patients, for populations and by directing resources to higher value health care, for tax payers. The article has described how the preparation stage, which includes many conversations, negotiations and lengthy discussions (eg, deciding the indicators and narrative) leads to improved engagement of all stakeholders. Working hard to build a positive relationship at the preparation stage pays dividends during the publication phase, where all stakeholders can contribute to the overall message and purpose of the Atlas. It is not sufficient, however, to publish an atlas of variation in isolation from other tools (eg, patient decisions aids) and expect it to have remarkable impact. An atlas of variation needs to be an integral part of a larger transformational change program.

Box 2 –
NHS Atlas of Variation series illustrated as an essential part of a large scale transformation initiative to increase value and reduce unwarranted variation

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CfV = Commissioning for Value. PDAs = Patient Decision Aids. STAR = Socio-Technical Allocation of Resources.

Understanding variation in care is an important step in improving patient health outcomes through appropriate care

Variation in health care usage is a troubling feature of contemporary medicine. For similar populations, usage of medications, interventions and procedures may be very different and lead to variation in outcomes. The following articles discuss why exploring unwarranted variation is a priority for health care systems; how atlases of health care variation act as catalysts of change and what health care systems can do to increase appropriate care. In this context, the Australian health care systems’ response to the problem of unwarranted health care variation is considered.

In November 2015, the Hon Sussan Ley, federal Minister for Health, launched the Australian atlas of healthcare variation.1 The Atlas, the first in a series, looks at variation in health care use at population level for 36 clinical activities including medication dispensing, diagnostic and surgical interventions and interventions for chronic diseases. International data, where available, are included and provide context. For example, Australia’s rate of dispensing of antibiotics is almost double that of Canada. This variation is consistent with a large body of evidence including that from a recent Organisation for Economic Co-operation and Development report, which included Australian data.2,3

In a number of countries, variation is being explored as a way to define and promote appropriate care and thereby value in the health care system. In this Supplement, DaSilva and Gray argue that atlases of clinical variation are catalysts for change by stimulating debate, engaging all participants in the health system so that patient-focused care can be achieved.4 The authors argue that no one group has all the necessary information, knowledge or capacity to plan and deliver appropriate care. For this reason, the Australian Commission on Safety and Quality in Health Care (the Commission) and the National Health Performance Authority developed the Australian atlas with input from the states and territories, and clinician and consumer groups. The Atlas’s recommendations require action from many parts of the health care system.

Variation is not bad per se. As Buchan and colleagues note, some variation in health care delivery is warranted and desirable, such as meeting differences in patients’ health needs or health preferences.2 For example, patients with knee pain from osteoarthritis may choose physiotherapy, knee replacement or lifestyle changes. The focus must be on variation that is inexplicable by either patient need or preference and is therefore unwarranted, such as would occur in the above example if treatment options were not offered. Unwarranted variation means people are exposed to real harm from not receiving care that they need or potential harm from receiving care that they do not need and cannot benefit them.

Atlases as such do not demonstrate the impact of unwarranted variation on patient outcomes. Atlases highlight variation such as, in this case, the seven-fold variation in dispensing rates of antipsychotics in people aged over 65 years. Clinical experts, for example, can analyse the data for unwarranted variation, distil the evidence for change into a clinical care standard and thereby effect widespread reduction in unwarranted variation and increase appropriate care.5

Research literature often focuses on the harms of not receiving evidence-based care. However, there is increasing awareness that people can be harmed from overdiagnosis and overtreatment, an example being antibiotic treatment of all infections.6 “Winding back the harms of too much medicine” (http://www.preventingoverdiagnosis.net) and “choosing wisely” (http://www.choosingwisely.org.au) are two recent catchphrases.

In the era of evidence-based medicine, defining what is right should be easier but remains challenging. Evidence of effectiveness is limited and can change over time, particularly for emerging technology, pharmaceuticals and patients with multiple comorbidities. Where evidence exists, implementation science needs improving. Glasziou, a recognised evidence-based medicine expert, describes a leaking evidence-to-practice pipeline.7 For evidence-based care to occur, evidence needs to be available, applicable and accepted, and able to be implemented, acted upon and agreed to by the patient. Achieving this requires multiple strategies; organisational prioritisation of the issue as important; resources to achieve the objective; systems to support clinician and consumer adoption of best practice; outcome measurement; and feedback for improvement, as Turnidge and colleagues describe in relation to antimicrobial use in Australian hospitals.8 The Commission’s work to support clinician and consumer adoption of best practice includes developing clinical care standards, clinical quality registries and patient-reported outcome measures (PROMs). Articles in this Supplement discuss the emerging evidence for these initiatives.9,10 For example, mechanisms to measure patient outcomes such as PROMs can assess the effectiveness of care.10,11 Clinical quality registries can improve clinical appropriateness and clinical care standards reduce unwarranted variation in treatment, such as for acute coronary syndromes.9,10

There is urgency for improving appropriate care because of increasing demand for services from an ageing population, medical science developments and cost escalators.4 Mechanisms to define, communicate and continually measure value to the patient may improve patient outcomes, and thereby increase the appropriateness of individual care and the sustainability of health care for populations. Future atlases that provide time-trended data will help. Exploring variation is the first step.