Open Access

ARTICLE

Identification of adults with congenital heart disease of moderate or great complexity from administrative data

by

1 Division of Cardiology, University of Washington, Seattle, Washington, USA
2 Department of Epidemiology, University of Washington, Seattle, Washington, USA
3 Cambia Center for Palliative Care, Harborview Medical Center, Seattle, Washington, USA

* Corresponding Author: Jill M. Steiner, MD, 1959 NE Pacific St., Division of Cardiology, HSB AA522, Box 356422, Seattle, Washington. Email:

Congenital Heart Disease 2018, 13(1), 65-71. https://doi.org/10.1111/chd.12524

Abstract

Introduction: There is relatively sparse literature on the use of administrative datasets for research in patients with adult congenital heart disease (ACHD). The goal of this analysis is to examine the accuracy of administrative data for identifying patients with ACHD who died.
Methods: A list of the International Classification of Diseases codes representing ACHD of moderate- or great-complexity was created. A search for these codes in the electronic health record of adults who received care in 2010–2016 was performed, and used state death records to identify patients who died during this period. Manual record review was completed to evaluate performance of this search strategy. Identified patients were also compared with a list of patients with moderate- or great-complexity ACHD known to have died.
Results: About 134 patients were identified, of which 72 had moderate- or great-complexity ACHD confirmed by manual review, yielding a positive predictive value of 0.54 (95% CI 0.45, 0.62). Twenty six patients had a mild ACHD diagnosis. Thirty six patients had no identified ACHD on record review. Misidentifications were attributed to coding error for 19 patients (53%), and to acquired ventricular septal defects for 11 patients (31%). Diagnostic codes incorrect more than 50% of the time were those for congenitally corrected transposition, endocardial cushion defect, and hypoplastic left heart syndrome. Only 1 of 21 patients known to have died was not identified by the search, yielding a sensitivity of 0.95 (0.76, 0.99).
Conclusion: Use of administrative data to identify patients with ACHD of moderate or great complexity who have died had good sensitivity but suboptimal positive predictive value. Strategies to improve accuracy are needed. Administrative data is not ideal for identification of patients in this group, and manual record review is necessary to confirm these diagnoses.

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