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Assessment of the Accuracy of Using ICD-10 Codes to Identify Systemic Sclerosis
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Assessment of the Accuracy of Using ICD-10 Codes to Identify Systemic Sclerosis
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Assessment of the Accuracy of Using ICD-10 Codes to Identify Systemic Sclerosis
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Journal Article
Assessment of the Accuracy of Using ICD-10 Codes to Identify Systemic Sclerosis
2020
Overview
With the increased use of data from electronic medical records for research, it is important to validate in-patient electronic health records/hospital electronic health records for specific diseases identification using International Classification of Diseases, Tenth Revision (
) codes.
To assess the accuracy of using
codes to identify systemic sclerosis (SSc) in the French hospital database.
Electronic health record database analysis. The setting of the study's in-patient database was the Toulouse University Hospital, a tertiary referral center (2880 beds) that serves approximately 2.9 million inhabitants. Participants were patients with
discharge diagnosis codes of SSc seen at Toulouse University Hospital between January 1, 2010, and December 31, 2017.
The main outcome was the positive predictive value (PPV) of discharge diagnosis codes for identifying SSc. The PPVs were calculated by determining the ratio of the confirmed cases found by medical record review to the total number of cases identified by
code.
Of the 2766 hospital stays, 216 patients were identified by an SSc discharge diagnosis code. Two hundred were confirmed as SSc after medical record review. The overall PPV was 93% (95% CI, 88-95%). The PPV for limited cutaneous SSc was 95% (95% CI, 85-98%).
Our results suggest that using
codes alone to capture SSc is reliable in The French hospital database.
