Hospital utilisation in Australia, 1993-2020, with a focus on use by people over 75 years of age: a review of AIHW data.

OBJECTIVES: To assess Australian hospital utilisation, 1993-2020, with a focus on use by people aged 75 years or more. DESIGN: Review of Australian Institute of Health and Welfare (AIHW) hospital utilisation data. SETTING, PARTICIPANTS: Tertiary data from all Australian public and private hospitals for the financial years 1993-94 to 2019-20. MAIN OUTCOME MEASURES: Numbers and population-based rates of hospital separations and bed utilisation (bed-days) (all and multiple day admissions) and mean hospital length of day (multiple day admissions), overall and by age group (under 65 years, 65-74 years, 75 years or more). RESULTS: Between 1993-94 and 2019-20, the Australian population grew by 44%; the number of people aged 75 years or more increased from 4.6% to 6.9% of the population. The annual number of hospital separations increased from 4.61 million to 11.33 million (146% increase); the annual hospital separation rate increased from 261 to 435 per 1000 people (66% increase), most markedly for people aged 75 years or more (from 745 to 1441 per 1000 people; 94% increase). Total bed utilisation increased from 21.0 million to 29.9 million bed-days (42% increase), but the bed utilisation rate did not change markedly (1993-94, 1192 bed-days per 1000 people; 2019-20, 1179 bed-days per 1000 people), primarily because the mean hospital length of stay for multiple day admissions declined from 6.6 days to 5.4 days; for people aged 75 years or more it declined from 12.2 to 7.1 days. However, declines in stay length have slowed markedly since 2017-18. Total bed utilisation was 16.8% lower than projected from 1993-94 rates, and was 37.3% lower for people aged 75 years or more. CONCLUSION: Hospital bed utilisation rates declined although admission rates increased during 1993-94 to 2019-20; the proportion of beds occupied by people aged 75 years or more increased slightly during this period. Containing hospital costs by limiting bed availability and reducing length of stay may no longer be a viable strategy.

In search of professional consensus in defining and reducing low-value care.

Care that confers no benefit or benefit that is disproportionately low compared with its cost is of low value and potentially wastes limited resources. It has been claimed that low-value care consumes at least 20% of health care resources in the United States - the comparable figure in Australia is unknown but there is emerging evidence of overuse of diagnostic tests and therapeutic procedures. Very few clinical interventions are of no value in every clinical circumstance, and efforts to label interventions as being so will meet with professional resistance. In the context of complex and highly individualised clinical decisions, nuanced clinical judgements of experienced and well informed clinicians are likely to outperform any service-level measurement and incentive program aimed at recognising and reducing low-value care. Public policy interventions should focus on supporting clinician-led efforts to seek professional consensus on what constitutes low-value care and the best means for reducing it.

Identifying and acting on potentially inappropriate care.

OBJECTIVE: To develop a model to measure potentially inappropriate care in Australian hospitals. DESIGN: Secondary analysis of computerised hospital discharge data for all Australian hospitals for the 2010-11 financial year. MAIN OUTCOME MEASURE: Hospital-specific incidence of selected diagnosis-procedure pairs identified as inappropriate in other literature. RESULTS: Five hospital procedures that are not supported by clinical evidence happened more than 100 times a week, on average. The most frequent of these do-not-do treatments was hyperbaric oxygen therapy for a range of specific conditions (4659 admissions in 2010-11). The rate of do-not-do procedures varied greatly, even among comparator hospitals that provided the procedure and that treated the relevant patient group. Among comparator hospitals, an average of 3.3% of patients with osteoarthritis of the knee received arthroscopic lavage and debridement of the knee (a do-not-do treatment), but four hospitals had rates of over 20%. There was also great variation in hospital-specific rates of procedures that should not be done routinely. CONCLUSION: Hospital-specific rates of do-not-do treatments vary greatly. Hospitals should be informed about their relative performance. Hospitals that have sustained, high rates of do-not-do treatments should be subject to external clinical review by expert peers.

Activity-based funding of hospitals and its impact on mortality, readmission, discharge destination, severity of illness, and volume of care: a systematic review and meta-analysis.

BACKGROUND: Activity-based funding (ABF) of hospitals is a policy intervention intended to re-shape incentives across health systems through the use of diagnosis-related groups. Many countries are adopting or actively promoting ABF. We assessed the effect of ABF on key measures potentially affecting patients and health care systems: mortality (acute and post-acute care); readmission rates; discharge rate to post-acute care following hospitalization; severity of illness; volume of care. METHODS: We undertook a systematic review and meta-analysis of the worldwide evidence produced since 1980. We included all studies reporting original quantitative data comparing the impact of ABF versus alternative funding systems in acute care settings, regardless of language. We searched 9 electronic databases (OVID MEDLINE, EMBASE, OVID Healthstar, CINAHL, Cochrane CENTRAL, Health Technology Assessment, NHS Economic Evaluation Database, Cochrane Database of Systematic Reviews, and Business Source), hand-searched reference lists, and consulted with experts. Paired reviewers independently screened for eligibility, abstracted data, and assessed study credibility according to a pre-defined scoring system, resolving conflicts by discussion or adjudication. RESULTS: Of 16,565 unique citations, 50 US studies and 15 studies from 9 other countries proved eligible (i.e. Australia, Austria, England, Germany, Israel, Italy, Scotland, Sweden, Switzerland). We found consistent and robust differences between ABF and no-ABF in discharge to post-acute care, showing a 24% increase with ABF (pooled relative risk  = 1.24, 95% CI 1.18-1.31). Results also suggested a possible increase in readmission with ABF, and an apparent increase in severity of illness, perhaps reflecting differences in diagnostic coding. Although we found no consistent, systematic differences in mortality rates and volume of care, results varied widely across studies, some suggesting appreciable benefits from ABF, and others suggesting deleterious consequences. CONCLUSIONS: Transitioning to ABF is associated with important policy- and clinically-relevant changes. Evidence suggests substantial increases in admissions to post-acute care following hospitalization, with implications for system capacity and equitable access to care. High variability in results of other outcomes leaves the impact in particular settings uncertain, and may not allow a jurisdiction to predict if ABF would be harmless. Decision-makers considering ABF should plan for likely increases in post-acute care admissions, and be aware of the large uncertainty around impacts on other critical outcomes.

Can Alberta's primary care networks provide any lessons for Medicare Locals?

Australia's Medicare Locals are in a formative period, and any comparison so far has focused on the United Kingdom.

An improvement focus in public reporting: the Queensland approach.

In many settings, public reporting of health care outcomes still reflects the "name-shame-blame" culture that has permeated large areas of the health care sector for decades. A new approach to public reporting in Queensland, based on statistical process control, emphasises the dynamic nature of performance against specified outcome measures by focusing on the actions that hospitals are taking if their indicators vary from the average. The aim is for public reporting to contribute to, rather than detract from, the creation of an internal culture that emphasises rigorous investigation and improvement rather than merely assigning blame for problems.

The acute-aged care interface: exploring the dynamics of 'bed blocking'.

OBJECTIVE: To understand the dynamics underlying 'bed-blocking' in Australian public hospitals that is frequently blamed on older patients. METHODS: Analysis of primary and secondary data of utilisation patterns of hospital and aged care services by older Australians. RESULTS: A model of the dynamics at the acute-aged care interface was developed, in which the pathway into permanent high-care Residential Aged Care (RAC) is conceptualised as competing queues for available places by applicants from the hospital, the community and from within RAC facilities. The hospital effectively becomes a safety net to accommodate people with high-care needs who cannot be admitted into RAC in a timely manner. CONCLUSION: The model provides a useful tool to explore some of the issues that give rise to access-block within the public hospital system. Access-block cannot be understood by viewing the hospital system in isolation from other sectors that support the health and well-being of older Australians.

The Australian health care system: reform, repair or replace?

A Festshrift gives us the opportunity to look both backwards and forwards. Ken Donald's career stretches back to his intern days in 1963 and has encompassed clinical and population health, academe, clinical settings and the bureaucracy, and playing sport at state and national levels. There has been considerable change in the health care system over the period of Ken's involvement in the sector with more change to come -- where have those changes left us? This paper discusses these changes in relation to performance criteria.

Developing 'robust performance benchmarks' for the next Australian Health Care Agreement: the need for a new framework.

If the outcomes of the recent COAG meeting are implemented, Australia will have a new set of benchmarks for its health system within a few months. This is a non-trivial task. Choice of benchmarks will, explicitly or implicitly, reflect a framework about how the health system works, what is important or to be valued and how the benchmarks are to be used. In this article we argue that the health system is dynamic and so benchmarks need to measure flows and interfaces rather than simply cross-sectional or static performance. We also argue that benchmarks need to be developed taking into account three perspectives: patient, clinician and funder. Each of these perspectives is critical and good performance from one perspective or on one dimension doesn't imply good performance on either (or both) of the others.The three perspectives (we term the dimensions patient assessed value, performance on clinical interventions and efficiency) can each be decomposed into a number of elements. For example, patient assessed value is influenced by timeliness, cost to the patient, the extent to which their expectations are met, the way they are treated and the extent to which there is continuity of care.We also argue that the way information is presented is important: cross sectional, dated measures provide much less information and are much less useful than approaches based on statistical process control. The latter also focuses attention on improvement and trends, encouraging action rather than simply blame of poorer performers.

Design of price incentives for adjunct policy goals in formula funding for hospitals and health services.

BACKGROUND: Hospital policy involves multiple objectives: efficiency of service delivery, pursuit of high quality care, promoting access. Funding policy based on hospital casemix has traditionally been considered to be only about promoting efficiency. DISCUSSION: Formula-based funding policy can be (and has been) used to pursue a range of policy objectives, not only efficiency. These are termed 'adjunct' goals. Strategies to incorporate adjunct goals into funding design must, implicitly or explicitly, address key decision choices outlined in this paper. SUMMARY: Policy must be clear and explicit about the behaviour to be rewarded; incentives must be designed so that all facilities with an opportunity to improve have an opportunity to benefit; the reward structure is stable and meaningful; and the funder monitors performance and gaming.

Identifying variations in quality of care in Queensland hospitals.

Identifying and acting on variations from good practice is one of the critical tasks of clinical governance. We describe one aspect of Queensland's post-Bundaberg clinical governance arrangements: the use of variable life-adjusted displays (VLADs) to monitor outcomes of care in the 87 largest public and private hospitals in Queensland, which together account for 83% of all hospital activity. VLAD control charts were created for 31 clinical indicators using routinely collected data, and are disseminated monthly. About a third of hospitals had a run of cases in the 3-year period that flagged at the 30% level (local level investigation). For three indicators, about one in five hospitals had sufficiently cumulatively more deaths than statistically expected that the hospital was highlighted for state-wide review. VLADs do not provide definitive answers about the quality of care. They are used to develop ideas about why variations in reported outcomes occur and suggest possible solutions, be they ways of improving data quality, improving casemix adjustment, or implementing system changes to improve quality of care. Critical to the approach is that there is not just monitoring - the monitoring is tied in with systems that ensure that investigation, learning and action occur as a result of a flag.

A new approach to clinical governance in Queensland.

Clinical governance approaches in Queensland health were trenchantly criticised in 2005 by two external reviews. In designing the new approach to clinical governance it was recognised that clinical governance should not be seen as only being about traditional safety and quality policies. A range of levers and policy instruments have been used in Queensland health to effect a new approach to clinical governance.