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A comparison of two structured taxonomic strategies in capturing adverse events in U.S. hospitals.
Austin, John M; Kirley, Erin M; Rosen, Michael A; Winters, Bradford D.
Afiliação
  • Austin JM; Armstrong Institute for Patient Safety and Quality, Johns Hopkins Medicine, Baltimore, Maryland.
  • Kirley EM; Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
  • Rosen MA; Armstrong Institute for Patient Safety and Quality, Johns Hopkins Medicine, Baltimore, Maryland.
  • Winters BD; Armstrong Institute for Patient Safety and Quality, Johns Hopkins Medicine, Baltimore, Maryland.
Health Serv Res ; 54(3): 613-622, 2019 06.
Article em En | MEDLINE | ID: mdl-30474108
ABSTRACT

OBJECTIVE:

To compare the Agency for Healthcare Research and Quality's Quality and Safety Review System (QSRS) and the proposed triadic structure for the 11th version of the International Classification of Disease (ICD-11) in their ability to capture adverse events in U.S. hospitals. DATA SOURCES/STUDY

SETTING:

One thousand patient admissions between 2014 and 2016 from three general, acute care hospitals located in Maryland and Washington D.C. STUDY

DESIGN:

The admissions chosen for the study were a random sample from all three hospitals. DATA COLLECTION/EXTRACTION

METHODS:

All 1000 admissions were abstracted through QSRS by one set of Certified Coding Specialists and a different set of coders assigned the draft ICD-11 codes. Previously assigned ICD-10-CM codes for 230 of the admissions were also used. PRINCIPAL

FINDINGS:

We found less than 20 percent agreement between QSRS and ICD-11 in identifying the same adverse event. The likelihood of a mismatch between QSRS and ICD-11 was almost twice that of a match. The findings were similar to the agreement found between QSRS and ICD-10-CM in identifying the same adverse event. When coders were provided with a list of potential adverse events, the sensitivity and negative predictive value of ICD-11 improved.

CONCLUSIONS:

While ICD-11 may offer an efficient way of identifying adverse events, our analysis found that in its draft form, it has a limited ability to capture the same types of events as QSRS. Coders may require additional training on identifying adverse events in the chart if ICD-11 is going to prove its maximum benefit.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Classificação Internacional de Doenças / United States Agency for Healthcare Research and Quality / Documentação / Dano ao Paciente / Administração Hospitalar Tipo de estudo: Prognostic_studies Limite: Adult / Aged / Female / Humans / Male / Middle aged País/Região como assunto: America do norte Idioma: En Revista: Health Serv Res Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Classificação Internacional de Doenças / United States Agency for Healthcare Research and Quality / Documentação / Dano ao Paciente / Administração Hospitalar Tipo de estudo: Prognostic_studies Limite: Adult / Aged / Female / Humans / Male / Middle aged País/Região como assunto: America do norte Idioma: En Revista: Health Serv Res Ano de publicação: 2019 Tipo de documento: Article