Positive Predictive Value of International Classification of Diseases, Ninth Revision, Clinical Modification , and International Classification of Diseases, Tenth Revision, Clinical Modification , Codes for Identification of Congenital Heart Defects

Author:

Ivey Lindsey C.1,Rodriguez Fred H.12ORCID,Shi Haoming3ORCID,Chong Cohen45ORCID,Chen Joy6ORCID,Raskind‐Hood Cheryl L.4ORCID,Downing Karrie F.7ORCID,Farr Sherry L.7ORCID,Book Wendy M.14ORCID

Affiliation:

1. Division of Cardiology Emory University School of Medicine Division of Cardiology Atlanta GA USA

2. Children’s Healthcare of Atlanta Cardiology Atlanta GA USA

3. Department of Biomedical Engineering Georgia Institute of Technology and Emory University Atlanta GA USA

4. Emory University Rollins School of Public Health Atlanta GA USA

5. Now with Philadelphia College of Osteopathic Medicine Philadelphia PA USA

6. PicnicHealth San Francisco CA USA

7. National Center on Birth Defects and Developmental Disabilities Centers for Disease Control and Prevention Atlanta GA USA

Abstract

Background Administrative data permit analysis of large cohorts but rely on International Classification of Diseases, Ninth Revision, Clinical Modification ( ICD‐9‐CM ), and International Classification of Diseases, Tenth Revision, Clinical Modification ( ICD‐10‐CM ) codes that may not reflect true congenital heart defects (CHDs). Methods and Results CHDs in 1497 cases with at least 1 encounter between January 1, 2010 and December 31, 2019 in 2 health care systems, identified by at least 1 of 87 ICD‐9‐CM / ICD‐10‐CM CHD codes were validated through medical record review for the presence of CHD and CHD native anatomy. Interobserver and intraobserver reliability averaged >95%. Positive predictive value (PPV) of ICD‐9‐CM / ICD‐10‐CM codes for CHD was 68.1% (1020/1497) overall, 94.6% (123/130) for cases identified in both health care systems, 95.8% (249/260) for severe codes, 52.6% (370/703) for shunt codes, 75.9% (243/320) for valve codes, 73.5% (119/162) for shunt and valve codes, and 75.0% (39/52) for “other CHD” (7 ICD‐9‐CM / ICD‐10‐CM codes). PPV for cases with >1 unique CHD code was 85.4% (503/589) versus 56.3% (498/884) for 1 CHD code. Of cases with secundum atrial septal defect ICD‐9‐CM / ICD‐10‐CM codes 745.5/Q21.1 in isolation, PPV was 30.9% (123/398). Patent foramen ovale was present in 66.2% (316/477) of false positives. True positives had younger mean age at first encounter with a CHD code than false positives (22.4 versus 26.3 years; P =0.0017). Conclusions CHD ICD‐9‐CM / ICD‐10‐CM codes have modest PPV and may not represent true CHD cases. PPV was improved by selecting certain features, but most true cases did not have these characteristics. The development of algorithms to improve accuracy may improve accuracy of electronic health records for CHD surveillance.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Cardiology and Cardiovascular Medicine

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