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Background & Objectives: Significant research conducted in New South Wales (NSW) hospitals' indicated that about 30% of red cell transfusions in stable adult patients was inappropriate. Of the total Australian government blood product budget in 2009-2010 (i.e. $878·8 million dollars) was spent on fresh blood products and plasma collection. The Clinical Excellence Commission (CEC) launched a systematic intervention called Blood Watch (BW) aiming to reduce inappropriate red cell transfusions in all NSW hospitals. An evaluation of BW was undertaken to measure the effectiveness of the programme and to estimate the associated potential cost-saving., Materials & Methods: Through the deterministic linkage of the four population-based administrative databases, three outcome indicators and four process indicators were developed. The analyses were of five elective surgical groups as they were the focus of the interventions. Three-level logistic regression and three-level linear regression were used to explore the time trend of the study process and outcome indicators. Modelling of the possible avoided red cell transfusions was also undertaken using a quadratic regression technique., Results: Overall, there was a 27·4% reduction of the blood usage after the introduction of the BW programme and the reductions were consistent across five elective surgical groups. Such a reduction was associated with annual cost-savings of over $8·5 million., Conclusions: The BW programme which was based on collaborative improvement methods and implemented at scale led to significant reduction of blood usage, consistently across five elective surgical groups and significant cost-saving., (© 2015 International Society of Blood Transfusion.)

Objective: To better understand the differences between two iatrogenic injury studies of hospitalized patients in 1992 which used ostensibly similar methods and similar sample sizes, but had quite different findings. The Quality in Australian Health Care Study (QAHCS) reported that 16.6% of admissions were associated with adverse events (AE), whereas the Utah, Colorado Study (UTCOS) reported a rate of 2.9%., Setting: Hospitalized patients in Australia and the USA., Design: Investigators from both studies compared methods and characteristics and identified differences. QAHCS data were then analysed using UTCOS methods., Main Outcome Measures: Differences between the studies and the comparative AE rates when these had been accounted for., Results: Both studies used a two-stage chart review process (screening nurse review followed by confirmatory physician review) to detect AEs; five important methodological differences were found: (i) QAHCS nurse reviewers referred records that documented any link to a previous admission, whereas UTCOS imposed age-related time constraints; (ii) QAHCS used a lower confidence threshold for defining medical causation; (iii) QAHCS used two physician reviewers, whereas UTCOS used one; (iv) QAHCS counted all AEs associated with an index admission whereas UTCOS counted only those determining the annual incidence; and (v) QAHCS included some types of events not included in UTCOS. When the QAHCS data were analysed using UTCOS methods, the comparative rates became 10.6% and 3.2%, respectively., Conclusions: Five methodological differences accounted for some of the discrepancy between the two studies. Two explanations for the remaining three-fold disparity are that quality of care was worse in Australia and that medical record content and/or reviewer behaviour was different.

Objective: To examine the causes of adverse events (AEs) resulting from healthcare to assist in developing strategies to minimise preventable patient injury., Design: Descriptions of the 2353 AEs previously reported by the Quality in Australian Health Care Study (QAHCS) were reviewed. A qualitative approach was used to develop categories for human error and for prevention strategies to minimise these errors. These categories were then used to classify the AEs identified in the QAHCS, and the results were analysed with previously reported preventability and outcome data., Results: 34.6% of the causes of AEs were categorised as "a complication of, or the failure in, the technical performance of an indicated procedure or operation", 15.8% as "the failure to synthesise, decide and/or act on available information", 11.8% as "the failure to request or arrange an investigation, procedure or consultation", and 10.9% as "a lack of care and attention or failure to attend the patient". AEs in which the cause was cognitive failure were associated with higher preventability scores than those involving technical performance. The main prevention strategies identified were "new, better, or better implemented policies or protocols" (23.7% of strategies), "more or better formal quality monitoring or assurance processes" (21.2%), "better education and training" (19.2%), and "more consultation with other specialists or peers" (10.2%)., Conclusion: The causes of AEs or errors leading to AEs can be characterised, and human error is a prominent cause. Our study emphasises the need for designing safer systems for care which protect the patient from the inevitability of human error. These systems should provide new policies and protocols and technological support to aid the cognitive activities of clinicians.

A review of the medical records of over 14,000 admissions to 28 hospitals in New South Wales and South Australia revealed that 16.6% of these admissions were associated with an "adverse event", which resulted in disability or a longer hospital stay for the patient and was caused by health care management; 51% of the adverse events were considered preventable. In 77.1% the disability had resolved within 12 months, but in 13.7% the disability was permanent and in 4.9% the patient died.