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

• Main Authors: De Almeida Chaves S, Derumeaux H, Do Minh P, Lapeyre-Mestre M, Moulis G, Pugnet G
• Format: Article
• Language: English
• Published: Dove Medical Press 2020-12-01
• Series: Clinical Epidemiology
• Subjects: systemic sclerosis international classification of diseases positive predictive value sensitivity hospital database
• Online Access: https://www.dovepress.com/assessment-of-the-accuracy-of-using-icd-10-codes-to-identify-systemic--peer-reviewed-article-CLEP

Sébastien De Almeida Chaves,1 Hélène Derumeaux,2 Phuong Do Minh,1 Maryse Lapeyre-Mestre,3– 5 Guillaume Moulis,1,4,5 Grégory Pugnet1,4,5 1Department of Internal Medicine, CHU Toulouse, Toulouse, France; 2Department of Medical Information, CHU Toulouse, Toulouse, France; 3Department of Medical and Clinical Pharmacology, CHU Toulouse, Toulouse, France; 4UMR 1027 Inserm-University of Toulouse, Toulouse, France; 5Clinical Investigation Center 1436, CHU Toulouse, Toulouse, FranceCorrespondence: Grégory PugnetService de Médecine Interne, CHU Toulouse Purpan, 1 Place du Dr Joseph Baylac, TSA 40031, 31059, Toulouse Cedex 9, FranceTel [phone]Fax [phone]Email [e-mail]: 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 (ICD-10) codes.Objective: To assess the accuracy of using ICD-10 codes to identify systemic sclerosis (SSc) in the French hospital database.Design, Setting, and Participants: 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 ICD-10 discharge diagnosis codes of SSc seen at Toulouse University Hospital between January 1, 2010, and December 31, 2017.Main Outcomes and Measures: 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 ICD-10 code.Results: 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%).Conclusions and Relevance: Our results suggest that using ICD-10 codes alone to capture SSc is reliable in The French hospital database.Keywords: systemic sclerosis, International Classification of Diseases, positive predictive value, sensitivity, hospital database