Farhan Zafar1, Philip Allen2, Roosevelt Bryant3, James S Tweddell4, Hani K Najm5, Brett R Anderson6, Tara Karamlou5. 1. The Heart Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio. Electronic address: farhan.zafar@cchmc.org. 2. Columbia University Mailman School of Public Health, New York, NY. 3. Division of Cardiac Surgery, Phoenix Children's Hospital, Phoenix, Ariz. 4. The Heart Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio. 5. Department of Pediatric Cardiac Surgery, Heart, Vascular, and Thoracic Institute, Cleveland Clinic, Cleveland, Ohio. 6. Division of Pediatric Cardiology, NewYork-Presbyterian/Columbia University Irving Medical Center, New York, NY.
Abstract
BACKGROUND: Administrative billing data are critical to many initiatives in congenital heart surgery. Mapping algorithms for International Classification of Disease, 10th Revision diagnosis and procedure codes to clinical registry procedure definitions will allow identification of surgical cases and account for patient and procedural factors within administrative data. Our objectives were to develop mapping logic to crosswalk International Classification of Disease, 10th Revision procedure codes to 10 Society of Thoracic Surgeons Congenital Heart Surgery Database benchmark and beta-test the algorithm. METHODS: Patients undergoing Society of Thoracic Surgeons Congenital Heart Surgery Database benchmark procedures from 2015 to 2019 were identified and served as the gold standard. Cases were linked on direct identifiers to cases from the Pediatric Health Information System Database. Two independent teams developed International Classification of Disease, 10th Revision-based algorithms for cases capture. Algorithms were compared and iteratively refined to optimize sensitivity and specificity. Operative mortalities for cases identified in the administrative versus registry data were compared. RESULTS: Overall sensitivity was 91% and specificity was 99% for capture of benchmark operations using International Classification of Diseases 10th Revision codes. Sensitivity was more than 90% in identifying 6 of the 10 individual benchmark procedures and more than 98% sensitive in identifying Fontan, Glenn, and arterial switch with ventricular septal defect procedures. Specificity was more than 98% for all benchmark operations. There were no statistical differences in operative mortality between cases identified in the administrative versus the registry data. CONCLUSIONS: Novel mapping algorithm for International Classification of Disease, 10th Revision procedure codes enables identification of congenital heart benchmark procedures within administrative billing data. This crosswalk facilitates population-based congenital heart surgical research and quality assessment.
BACKGROUND: Administrative billing data are critical to many initiatives in congenital heart surgery. Mapping algorithms for International Classification of Disease, 10th Revision diagnosis and procedure codes to clinical registry procedure definitions will allow identification of surgical cases and account for patient and procedural factors within administrative data. Our objectives were to develop mapping logic to crosswalk International Classification of Disease, 10th Revision procedure codes to 10 Society of Thoracic Surgeons Congenital Heart Surgery Database benchmark and beta-test the algorithm. METHODS: Patients undergoing Society of Thoracic Surgeons Congenital Heart Surgery Database benchmark procedures from 2015 to 2019 were identified and served as the gold standard. Cases were linked on direct identifiers to cases from the Pediatric Health Information System Database. Two independent teams developed International Classification of Disease, 10th Revision-based algorithms for cases capture. Algorithms were compared and iteratively refined to optimize sensitivity and specificity. Operative mortalities for cases identified in the administrative versus registry data were compared. RESULTS: Overall sensitivity was 91% and specificity was 99% for capture of benchmark operations using International Classification of Diseases 10th Revision codes. Sensitivity was more than 90% in identifying 6 of the 10 individual benchmark procedures and more than 98% sensitive in identifying Fontan, Glenn, and arterial switch with ventricular septal defect procedures. Specificity was more than 98% for all benchmark operations. There were no statistical differences in operative mortality between cases identified in the administrative versus the registry data. CONCLUSIONS: Novel mapping algorithm for International Classification of Disease, 10th Revision procedure codes enables identification of congenital heart benchmark procedures within administrative billing data. This crosswalk facilitates population-based congenital heart surgical research and quality assessment.
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