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Patient safety indicators for England from hospital administrative data: case-control analysis and comparison with US
Veena S Raleigh1, Jeremy Cooper, Stephen A Bremner
1Healthcare Commission, London EC1Y 8TG. veena.raleigh@healthcarecommission.org.uk
BMJ (Clinical Research Ed.)
|October 22, 2008
Summary
Routine hospital data can identify patient safety events in England, showing higher mortality and longer hospital stays for affected patients. These indicators, though lower than US rates, highlight areas for improved patient safety monitoring.
Area of Science:
- Healthcare quality and safety research.
- Health services research.
Background:
- Assessing patient safety is crucial for improving healthcare outcomes.
- Routine hospital data offers a potential source for patient safety indicators.
Purpose of the Study:
- To evaluate the feasibility of using routine hospital data to derive patient safety indicators in England.
- To determine if these indicators can effectively signal adverse patient outcomes.
Main Methods:
- Nine patient safety indicators from the US Agency for Healthcare Research and Quality (AHRQ) were applied to English hospital episode statistics (2003-2006).
- A case-control analysis compared length of stay and mortality between patients experiencing safety events (cases) and matched controls.
- Comparisons were made with data from the United States.
Main Results:
- Consistent national rates for the nine indicators were observed across three years.
- Cases consistently showed significantly longer hospital stays and higher mortality rates compared to controls (P<0.001), except for obstetric trauma indicators.
- Postoperative hip fracture and sepsis demonstrated the greatest excess length of stay and mortality in cases.
Conclusions:
- Hospital administrative data are a feasible, low-cost source for patient safety event monitoring.
- Derived indicators demonstrate poorer outcomes for patients experiencing safety events, indicating potential for monitoring.
- Further validation and improved event recording are necessary; observed differences with US data may stem from coding variations and healthcare system disparities.
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