The Medical journal of Australia
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Although difficult to quantify, there is known widespread variation in the way that best available evidence is applied in clinical practice. The reasons for gaps between evidence and practice are complex, and efforts to improve uptake are unlikely to be successful if they are one-dimensional or focus on individual health professionals. This article provides contextual reference for articles in this Supplement in addressing how and why clinical variation exists, the importance of reducing it and strategies to drive a more streamlined approach to evidence-based care in Australian health care systems.
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The variable life-adjusted display is a graphical, statistical methodology used in Queensland to monitor patient outcomes of clinical indicators. The quality improvement cycle is a systematic approach employed by patient safety and quality programs worldwide to improve patient care. ⋯ Indicators with definitional issues that are not subject to the quality improvement cycle may initially prompt quality improvement opportunities, but are more likely to potentially lead to unnecessary chart and clinical reviews, which will disengage coders and clinicians. Queensland recently used the quality improvement cycle to refine the laparoscopic cholecystectomy complications of surgery indicator definition and several maternity definitions.
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This article reports the experience of the Victorian Department of Health in seeking clinician engagement in the testing of 11 quality-of-care indicators in 20 health services in Victoria. The Department previously developed a suite of 18 core indicators and seven subindicators known as the AusPSI set. We used routinely collected administrative data from the Victorian Admitted Episodes Dataset to produce variable life-adjusted display (VLAD) control charts for 11 selected indicators. ⋯ Although using readily available and inexpensive routinely collected administrative data to measure clinical performance has a certain appeal, the use of administrative data and VLADs to identify apparent variations has posed significant challenges due to concerns about the quality of the data and resource requirements. When clinicians at a major Melbourne hospital were engaged, it resulted in an improvement in clinical practice. Investigating apparent variation in patient care provides an ideal opportunity for emerging clinical leaders to take local ownership and develop expertise in investigating apparent variation in processes of care and implementing change as required.