Study of EHR-mediated workflows using ethnography and process mining methods.

Rapid ethnography and data mining approaches have been used individually to study clinical workflows, but have seldom been used together to overcome the limitations inherent in either type of method. For rapid ethnography, how reliable are the findings drawn from small samples? For data mining, how...

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Publicado en:Health Informatics Journal Vol. 27; no. 2; pp. 1 - 15
Autores principales: Grando, M Adela, Vellore, Vaishak, Duncan, Benjamin J, Kaufman, David R, Furniss, Stephanie K, Doebbeling, Bradley N, Poterack, Karl A, Miksch, Timothy, Helmers, Richard A
Formato: pictorial research tables/charts Journal Article
Publicado: Sage Publications Inc. Apr-Jun2021
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Apr-Jun2021
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        atl: Study of EHR-mediated workflows using ethnography and process mining methods.
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        au:
          Grando, M Adela
          Vellore, Vaishak
          Duncan, Benjamin J
          Kaufman, David R
          Furniss, Stephanie K
          Doebbeling, Bradley N
          Poterack, Karl A
          Miksch, Timothy
          Helmers, Richard A
        affil: Mayo Clinic, USA
      sug:
        subj:
          Electronic Health Records
          Workflow
          Data Mining
          Human
          Ethnographic Research
          Documentation
          Hospitals
          Descriptive Statistics
          Health Informatics
      ab: Rapid ethnography and data mining approaches have been used individually to study clinical workflows, but have seldom been used together to overcome the limitations inherent in either type of method. For rapid ethnography, how reliable are the findings drawn from small samples? For data mining, how accurate are the discoveries drawn from automatic analysis of big data, when compared with observable data? This paper explores the combined use of rapid ethnography and process mining, aka ethno-mining, to study and compare metrics of a typical clinical documentation task, vital signs charting. The task was performed with different electronic health records (EHRs) used in three different hospital sites. The individual methods revealed substantial discrepancies in task duration between sites. Specifically, means of 159.6(78.55), 38.2(34.9), and 431.3(283.04) seconds were captured with rapid ethnography. When process mining was used, means of 518.6(3,808), 345.5(660.6), and 119.74(210.3) seconds were found. When ethno-mining was applied instead, outliers could be identified, explained and removed. Without outliers, mean task duration was similar between sites (78.1(66.7), 72.5(78.5), and 71.7(75) seconds). Results from this work suggest that integrating rapid ethnography and data mining into a single process may provide more meaningful results than a siloed approach when studying of workflow.
      pubtype: Academic Journal
      doctype:
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        research
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      ougenre: Article
    language: English
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