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Comparative Study
. 2008;12(4):R95.
doi: 10.1186/cc6969. Epub 2008 Jul 29.

Reliability of diagnostic coding in intensive care patients

Affiliations
Comparative Study

Reliability of diagnostic coding in intensive care patients

Benoît Misset et al. Crit Care. 2008.

Abstract

Introduction: Administrative coding of medical diagnoses in intensive care unit (ICU) patients is mandatory in order to create databases for use in epidemiological and economic studies. We assessed the reliability of coding between different ICU physicians.

Method: One hundred medical records selected randomly from 29,393 cases collected between 1998 and 2004 in the French multicenter Outcomerea ICU database were studied. Each record was sent to two senior physicians from independent ICUs who recoded the diagnoses using the International Statistical Classification of Diseases and Related Health Problems: Tenth Revision (ICD-10) after being trained according to guidelines developed by two French national intensive care medicine societies: the French Society of Intensive Care Medicine (SRLF) and the French Society of Anesthesiology and Intensive Care Medicine (SFAR). These codes were then compared with the original codes, which had been selected by the physician treating the patient. A specific comparison was done for the diagnoses of septicemia and shock (codes derived from A41 and R57, respectively).

Results: The ICU physicians coded an average of 4.6 +/- 3.0 (range 1 to 32) diagnoses per patient, with little agreement between the three coders. The primary diagnosis was matched by both external coders in 34% (95% confidence interval (CI) 25% to 43%) of cases, by only one in 35% (95% CI 26% to 44%) of cases, and by neither in 31% (95% CI 22% to 40%) of cases. Only 18% (95% CI 16% to 20%) of all codes were selected by all three coders. Similar results were obtained for the diagnoses of septicemia and/or shock.

Conclusion: In a multicenter database designed primarily for epidemiological and cohort studies in ICU patients, the coding of medical diagnoses varied between different observers. This could limit the interpretation and validity of research and epidemiological programs using diagnoses as inclusion criteria.

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Figures

Figure 1
Figure 1
Number of codes per patient selected by the initial coder (x-axis) and the two external coders (y-axis). The dotted line represents identity.
Figure 2
Figure 2
Distribution of codes according to the three coders. Each coding is symbolized by a circle. Only 18% of the codes (intersection of the three circles) were selected by all three coders.
Figure 3
Figure 3
Distribution of the codes for shock (beginning with R57) according to the three coders. Each coding is symbolized by a circle. Only 29% of the codes (intersection of the three circles) were selected by all three coders.

Comment in

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