Assessment of the Accuracy of Using ICD-10 Codes to Identify Systemic Sclerosis

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 th...

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Bibliographic Details
Published in:Clinical epidemiology 2020-01, Vol.12, p.1355-1359
Main Authors: De Almeida Chaves, Sébastien, Derumeaux, Hélène, Do Minh, Phuong, Lapeyre-Mestre, Maryse, Moulis, Guillaume, Pugnet, Grégory
Format: Article
Language:English
Subjects:
Accuracy
Classification
Clinical medicine
Codes
Connective tissue diseases
Electronic health records
Electronic records
Epidemiology
Hospital patients
Hospitals
Medical records
Medical research
Medicine, Experimental
Patients
Scleroderma
Scleroderma (Disease)
Short Report
Systemic scleroderma
Systemic sclerosis
systemic sclerosis international classification of diseases positive predictive value sensitivity hospital database
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Summary: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.
ISSN:1179-1349
1179-1349
DOI:10.2147/CLEP.S260733