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Despite consensus that preventing patient safety events is important, measurement of safety events remains challenging. This is, in part, because they occur relatively infrequently and are not always preventable. There is also no consensus on the ‘best way‘ or the ‘best measure’ of patient safety. The purpose of all safety measures is to improve care and prevent safety events; this can be achieved by different means. If the overall goal of measuring patient safety is to capture the universe of safety events that occur, then broader measures encompassing large populations, such as those based on administrative data, may be preferable. Acknowledging the trade-off between comprehensiveness and accuracy, such measures may be better suited for surveillance and quality improvement (QI), rather than public reporting/reimbursement. Conversely, using measures for public reporting and pay-for-performance requires more narrowly focused measures that favour accuracy over comprehensiveness, such as those with restricted denominators or those based on medical record review.
There are at least two well-established patient safety measurement systems available for use in the inpatient setting, namely the administrative data-based Agency for Healthcare Research and Quality (AHRQ) Patient Safety Indicators (PSIs) and the medical record-based National Surgical Quality Improvement Programme (NSQIP) measures.1–3 The AHRQ PSIs, publicly released in 2003, are evidence-based measures designed to screen for potentially preventable medical and surgical complications that occur in the acute care setting. Since they use administrative data, they were originally designed as tools for use in case finding for local QI efforts and surveillance, as well as for internal hospital comparisons. They were developed using a rigorous process beginning with a thorough review of the literature for existing administrative data-based indicators, review by clinical expert panels, consultation with coding experts and empirical analyses to assess the statistical properties of the measures, such as reliability and predictive and …
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