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Systematic review of discharge coding accuracy
E M Burns1, E Rigby, R Mamidanna
1Department of Surgery, Imperial College, St Mary's Hospital, Praed Street, W21NY London, UK.
Journal of Public Health (Oxford, England)
|July 29, 2011
Summary
Routinely collected health data in Great Britain show improving accuracy, with a median accuracy of 83.2% compared to case notes. These datasets are robust enough for research and health service management.
Area of Science:
- Health Informatics
- Data Quality Assessment
- Healthcare Management
Background:
- Routinely collected data are vital for research, financial reimbursement, and health service planning.
- High-quality data are essential for reliable analysis and decision-making.
- Assessing the accuracy of these datasets is crucial for their effective utilization.
Purpose of the Study:
- To systematically assess the published accuracy of routinely collected data sets in Great Britain.
- To evaluate the reliability of routinely collected data for various healthcare applications.
Main Methods:
- Systematic literature searches were conducted across major databases (EMBASE, PUBMED, OVID, Cochrane) from 1989 to present.
- Included studies compared routinely collected data against case notes or clinical registries.
- Data extraction focused on accuracy metrics for diagnoses and procedures.
Main Results:
- Thirty-two studies met the inclusion criteria.
- The overall median accuracy of routinely collected data compared to case notes was 83.2%.
- Accuracy rates demonstrated considerable variation (50.5-97.8%), with improvements noted since the introduction of Payment by Results in 2002.
Conclusions:
- Accuracy rates for routinely collected data are demonstrably improving.
- The current reported accuracy levels suggest these datasets are sufficiently robust for research and managerial decision-making.
- Continued monitoring and quality improvement initiatives are warranted.
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