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Tracking Substance Use Complications: A Collaborative Analysis of Public Health and Academic Medical Center Records on Drug Use-Associated Infective Endocarditis.
de Gijsel, David; DesBiens, Martha; Talbot, Elizabeth A; Laflamme, David J; Conn, Stephen; Chan, Benjamin P.
Afiliación
  • de Gijsel D; Dartmouth-Hitchcock Medical Center, Section of Infectious Disease and International Health, Lebanon, New Hampshire, USA.
  • DesBiens M; Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA.
  • Talbot EA; Dartmouth-Hitchcock Medical Center, Section of Infectious Disease and International Health, Lebanon, New Hampshire, USA.
  • Laflamme DJ; Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA.
  • Conn S; Dartmouth-Hitchcock Medical Center, Section of Infectious Disease and International Health, Lebanon, New Hampshire, USA.
  • Chan BP; Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA.
J Infect Dis ; 222(Suppl 5): S437-S441, 2020 09 02.
Article en En | MEDLINE | ID: mdl-32877542
BACKGROUND: Healthcare systems and public health agencies use different methods to measure the impact of substance use (SU) on population health. We studied the ability of systems to accurately capture data on drug use-associated infective endocarditis (DUA-IE). METHODS: We conducted a retrospective analysis of patients with IE discharge diagnosis from an academic medical center, 2011-2017, comparing data from hospital Electronic Health Record (EHR) to State Uniform Hospital Discharge Data Set (UHDDS). To identify SU we developed a composite measure. RESULTS: EHR identified 472 IE discharges (430 of these were captured in UHDDS); 406 (86.0%) were correctly coded based on chart review. IE discharges increased from 57 to 92 (62%) from 2012 to 2017. Hospitalizations for the subset of DUA-IE identified by any measure of SU increased from 10 to 54 (440%). Discharge diagnosis coding identified 128 (60.7%) of total DUA-IE hospitalizations. The composite measure identified an additional 65 (30.8%) DUA-IE hospitalizations and chart review an additional 18 (8.5%). CONCLUSIONS: The failure of discharge diagnosis coding to identify DUA-IE in 40% of hospitalizations demonstrates the need for better systems to capture the impact of SU. Collaborative data sharing could help improve surveillance responsiveness to address an emerging public health crises.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: United States Dept. of Health and Human Services / Trastornos Relacionados con Sustancias / Endocarditis / Centros Médicos Académicos Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans / Male / Middle aged País/Región como asunto: America do norte Idioma: En Revista: J Infect Dis Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: United States Dept. of Health and Human Services / Trastornos Relacionados con Sustancias / Endocarditis / Centros Médicos Académicos Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans / Male / Middle aged País/Región como asunto: America do norte Idioma: En Revista: J Infect Dis Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos