The Australian health workforce has changed dramatically over the last 4 years, growing in size and changing composition. However, more changes will be needed in the future to respond to the epidemiological and demographic transition of the Australian population. A critical issue will be whether the supply of health professionals will keep pace with demand. There are current recorded shortages of most health professionals, but this paper argues that future workforce planning should not be based on providing more of the same. Rather, the roles of health professionals will need to change and workforce planning needs to place a stronger emphasis on issues of workforce substitution, that is, a different mix of responsibilities. This will also require changes in educational preparation, in particular an increased emphasis on interprofessional work and common foundation learning.
Objectives: To determine the incidence of adverse events in patients admitted in the year 2003–04 to selected Victorian hospitals; to identify the main hospital‐acquired diagnoses; and to estimate the cost of these complications to the Victorian and Australian health system. Design: The patient‐level costing dataset for major Victorian public hospitals, 1 July 2003 – 30 June 2004, was analysed for adverse events by identifying C‐prefixed diagnosis codes denoting complications, preventable or otherwise, arising during the course of hospital treatment. The in‐hospital cost of adverse events was estimated using linear regression modelling, adjusting for age and comorbidity. Main outcome measures: Cost of each patient admission (“admitted episode”), length of stay and mortality. Results: During the designated timeframe, 979 834 admitted episodes were in the sample, of which 67 435 (6.88%) had at least one adverse event. Patients with adverse events stayed about 10 days longer and had over seven times the risk of in‐hospital death than those without complications. After adjusting for age and comorbidity, the presence of an adverse event adds $6826 to the cost of each admitted episode. The total cost of adverse events in this dataset in 2003–04 was $460.311 million, representing 15.7% of the total expenditure on direct hospital costs, or an additional 18.6% of the total inpatient hospital budget. Conclusion: Adverse events are associated with significant costs. Administrative datasets are a cost‐effective source of information that can be used for a range of clinical governance activities to prevent adverse events.
BackgroundActivity-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.MethodsWe 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.ResultsOf 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.ConclusionsTransitioning 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.
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.
Australia suffered two waves of the COVID-19 pandemic in 2020: the first lasting from February to July 2020 was mainly caused by transmission from international arrivals, the second lasting from July to November was caused by breaches of hotel quarantine which allowed spreading into the community. From a second wave peak in early August of over 700 new cases a day, by November 2020 Australia had effectively eliminated community transmission. Effective elimination was largely maintained in the first half of 2021 using snap lockdowns, while a slow vaccination program left Australia lagging behind comparable countries. This paper describes the interventions which led to Australia's relative success up to July 2021, and also some of the failures along the way.
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