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Systematic review of discharge coding accuracy

Open access
Burns, E. M., Rigby, E., Mamidanna, R., Bottle, A., Aylin, P., Ziprin, P., Faiz, O. D.·2012·Journal of Public Health

Abstract

INTRODUCTION: Routinely collected data sets are increasingly used for research, financial reimbursement and health service planning. High quality data are necessary for reliable analysis. This study aims to assess the published accuracy of routinely collected data sets in Great Britain. METHODS: Systematic searches of the EMBASE, PUBMED, OVID and Cochrane databases were performed from 1989 to present using defined search terms. Included studies were those that compared routinely collected data sets with case or operative note review and those that compared routinely collected data with clinical registries. RESULTS: Thirty-two studies were included. Twenty-five studies compared routinely collected data with case or operation notes. Seven studies compared routinely collected data with clinical registries. The overall median accuracy (routinely collected data sets versus case notes) was 83.2% (IQR: 67.3-92.1%). The median diagnostic accuracy was 80.3% (IQR: 63.3-94.1%) with a median procedure accuracy of 84.2% (IQR: 68.7-88.7%). There was considerable variation in accuracy rates between studies (50.5-97.8%). Since the 2002 introduction of Payment by Results, accuracy has improved in some respects, for example primary diagnoses accuracy has improved from 73.8% (IQR: 59.3-92.1%) to 96.0% (IQR: 89.3-96.3), P= 0.020. CONCLUSION: Accuracy rates are improving. Current levels of reported accuracy suggest that routinely collected data are sufficiently robust to support their use for research and managerial decision-making.

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Metadata

Authors
Burns, E. M., Rigby, E., Mamidanna, R., Bottle, A., Aylin, P., Ziprin, P., & Faiz, O. D.
Venue
Journal of Public Health
Published
2011-07-27
Volume
34
Issue
1
Pages
138-148
ISSN
  • 0943-1853 (ISSN-L)
  • 1741-3842
  • 1741-3850
OpenAlex
W2146417320
Cited by
690
References
0
FWCI
3.91
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Systematic review of discharge coding accuracy. https://app.cochat.ai/papers/10.1093/pubmed/fdr054
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Burns, E. M., Rigby, E., Mamidanna, R., Bottle, A., Aylin, P., Ziprin, P., & Faiz, O. D. (2012). Systematic review of discharge coding accuracy. Journal of Public Health. https://doi.org/10.1093/pubmed/fdr054

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.