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A Computational Framework to Evaluate Emergency Department Clinician Task Switching in the Electronic Health Record Using Event Logs.
Moy, Amanda J; Cato, Kenrick D; Kim, Eugene Y; Withall, Jennifer; Rossetti, Sarah C.
Afiliação
  • Moy AJ; Columbia University (CU) Department of Biomedical Informatics, NY, NY.
  • Cato KD; CU Irving Medical Center Department of Emergency Medicine, NY, NY, USA.
  • Kim EY; CU School of Nursing, NY, NY, USA.
  • Withall J; Children's Hospital of Philadelphia Department of Biomedical and Health Informatics, Philadelphia, PA, USA.
  • Rossetti SC; CU Irving Medical Center Department of Emergency Medicine, NY, NY, USA.
AMIA Annu Symp Proc ; 2023: 1183-1192, 2023.
Article em En | MEDLINE | ID: mdl-38222361
ABSTRACT
Workflow fragmentation, defined as task switching, may be one proxy to quantify electronic health record (EHR) documentation burden in the emergency department (ED). Few measures have been operationalized to evaluate task switching at scale. Theoretically grounded in the time-based resource-sharing model (TBRSM) which conceives task switching as proportional to the cognitive load experienced, we describe the functional relationship between cognitive load and the time and effort constructs previously applied for measuring documentation burden. We present a computational framework, COMBINE, to evaluate multilevel task switching in the ED using EHR event logs. Based on this framework, we conducted a descriptive analysis on task switching among 63 full-time ED physicians from one ED site using EHR event logs extracted between April-June 2021 (n=2,068,605 events) which were matched to scheduled shifts (n=952). On average, we found a high volume of event-level (185.8±75.3/hr) and within-(6.6±1.7/chart) and between-patient chart (27.5±23.6/hr) switching per shift worked.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Médicos / Registros Eletrônicos de Saúde Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Médicos / Registros Eletrônicos de Saúde Idioma: En Ano de publicação: 2023 Tipo de documento: Article