2012
DOI: 10.1093/bja/aes173
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Using quality indicators in anaesthesia: feeding back data to improve care

Abstract: After recent UK policy developments, considerable attention has been focused upon how clinical specialties measure and report on the quality of care delivered to patients. Defining the right indicators alone is insufficient to close the feedback loop. This narrative review aims to describe and synthesize a diverse body of research relevant to the question of how information from quality indicators can be fed back and used effectively to improve care. Anaesthesia poses certain challenges in the identification o… Show more

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Cited by 80 publications
(91 citation statements)
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“…Various QI endeavours have been shown to reduce operating room inefficiencies, improve antibiotic compliance, and reduce postoperative pneumonias. 3 An understanding of the barriers to implementation is paramount to the success of these QI enterprises. Simply monitoring data without providing feedback, lack of trust in data, and lack of motivation have all been cited as reasons for ineffective QI buy-in and implementation.…”
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confidence: 99%
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“…Various QI endeavours have been shown to reduce operating room inefficiencies, improve antibiotic compliance, and reduce postoperative pneumonias. 3 An understanding of the barriers to implementation is paramount to the success of these QI enterprises. Simply monitoring data without providing feedback, lack of trust in data, and lack of motivation have all been cited as reasons for ineffective QI buy-in and implementation.…”
mentioning
confidence: 99%
“…Simply monitoring data without providing feedback, lack of trust in data, and lack of motivation have all been cited as reasons for ineffective QI buy-in and implementation. 3 The study by Görges et al addresses such common barriers by providing feedback through the use of statistical control processes. Nevertheless, unlike a traditional audit that examines snapshot data over a brief amount of time, the use of a continuous form of data created through run charts (which display observed data over a set time sequence -typically a year), creates a data-rich environment for assessing current practice over time and evaluating the impact of changes to the care system.…”
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confidence: 99%
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