Your browser doesn't support javascript.
loading
Identification of adults with congenital heart disease of moderate or great complexity from administrative data.
Steiner, Jill M; Kirkpatrick, James N; Heckbert, Susan R; Habib, Asma; Sibley, James; Lober, William; Randall Curtis, J.
Afiliação
  • Steiner JM; Division of Cardiology, University of Washington, Seattle, Washington, USA.
  • Kirkpatrick JN; Division of Cardiology, University of Washington, Seattle, Washington, USA.
  • Heckbert SR; Department of Epidemiology, University of Washington, Seattle, Washington, USA.
  • Habib A; Division of Cardiology, University of Washington, Seattle, Washington, USA.
  • Sibley J; Cambia Center for Palliative Care, Harborview Medical Center, Seattle, Washington, USA.
  • Lober W; Cambia Center for Palliative Care, Harborview Medical Center, Seattle, Washington, USA.
  • Randall Curtis J; Cambia Center for Palliative Care, Harborview Medical Center, Seattle, Washington, USA.
Congenit Heart Dis ; 13(1): 65-71, 2018 Jan.
Article em En | MEDLINE | ID: mdl-28736836
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.
Assuntos
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Atestado de Óbito / Guias de Prática Clínica como Assunto / Registros Eletrônicos de Saúde / Cardiopatias Congênitas Tipo de estudo: Diagnostic_studies / Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Atestado de Óbito / Guias de Prática Clínica como Assunto / Registros Eletrônicos de Saúde / Cardiopatias Congênitas Tipo de estudo: Diagnostic_studies / Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2018 Tipo de documento: Article