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Cross sectional study to assess the accuracy of electronic health record data to identify patients in need of lung cancer screening.
Cole, Allison M; Pflugeisen, Bethann; Schwartz, Malaika R; Miller, Sophie Cain.
Afiliación
  • Cole AM; Department of Family Medicine, University of Washington, Box 354696, Seattle, WA, 98195-4696, USA. acole2@uw.edu.
  • Pflugeisen B; MultiCare Institute for Research and Innovation, 314 Martin Luther King Jr. Way Suite 402, Tacoma, WA, 98405, USA.
  • Schwartz MR; Department of Family Medicine, University of Washington, Box 354696, Seattle, WA, 98195-4696, USA.
  • Miller SC; University of Washington School of Medicine, Box 354696, Seattle, WA, 98195-4696, USA.
BMC Res Notes ; 11(1): 14, 2018 Jan 10.
Article en En | MEDLINE | ID: mdl-29321038
ABSTRACT

OBJECTIVE:

Lung cancer is the leading cause of cancer death in the United States [Siegel et al. in CA Cancer J Clin 667-30, 1]. However, evidence from clinical trials indicates that annual low-dose computed tomography screening reduces lung cancer mortality [Humphrey et al. in Ann Intern Med 159411-420, 2]. The objective of this study is to report results of a study designed to assess the sensitivity, specificity, and positive and negative predictive value of an electronic health record (EHR) query in comparison to patient self-report, to identify patients who may benefit from lung cancer screening. Cross sectional study comparing patient self report to EHR derived assessment of tobacco status and need for lung cancer screening. We invited 200 current or former smokers, ages 55-80 to complete a brief paper survey. 26 responded and 24 were included in the analysis.

RESULTS:

For 30% of respondents, there was not adequate EHR data to make a lung cancer screening determination. Compared to patient self-report, EHR derived data has a 67% sensitivity and 82% specificity for identifying patients that meet criteria for lung cancer screening. While the degree of accuracy may be insufficient to make a final lung cancer screening determination, EHR data may be useful in prompting clinicians to initiate conversations with patients in regards to lung cancer screening.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Fumar / Detección Precoz del Cáncer / Registros Electrónicos de Salud / Autoinforme / Neoplasias Pulmonares Tipo de estudio: Diagnostic_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Límite: Aged / Aged80 / Female / Humans / Male / Middle aged Idioma: En Revista: BMC Res Notes Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Fumar / Detección Precoz del Cáncer / Registros Electrónicos de Salud / Autoinforme / Neoplasias Pulmonares Tipo de estudio: Diagnostic_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Límite: Aged / Aged80 / Female / Humans / Male / Middle aged Idioma: En Revista: BMC Res Notes Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos