A process mining model to detect adverse patient safety events: Blood products watch.

Introduction: Patient safety incidents and adverse events are reported voluntarily by healthcare staff. The Global Trigger Tool, developed by the Institute for Healthcare Improvement, is used to capture unreported events. The objective of the new model is to use process mining in the context of adve...

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Publicado en:Journal of Patient Safety & Risk Management Vol. 29; no. 5; pp. 248 - 257
Autores principales: Sumer, Ahmet Murat, Ceylan, Cemil
Formato: research tables/charts Journal Article
Publicado: Sage Publications Inc. Oct2024
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Oct2024
      vid: 29
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      pub: Sage Publications Inc.
      place: Thousand Oaks, California
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        10.1177/25160435241282041
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        atl: A process mining model to detect adverse patient safety events: Blood products watch.
      aug:
        au:
          Sumer, Ahmet Murat
          Ceylan, Cemil
        affil: Industrial Engineering Department, 52971Istanbul Technical University, Istanbul, Turkey
      sug:
        subj:
          Adverse Health Care Event
          Patient Safety
          Blood Transfusion
          Incident Reports
          Data Mining
          Human
          Descriptive Statistics
          Turkiye
          Documentation
          Medical Records
          Record Review
          Automation
          Clinical Assessment Tools
          Surgery, Operative
      ab: Introduction: Patient safety incidents and adverse events are reported voluntarily by healthcare staff. The Global Trigger Tool, developed by the Institute for Healthcare Improvement, is used to capture unreported events. The objective of the new model is to use process mining in the context of adverse event detection to increase reporting efficiency. Methods: In the first phase, the process mining model is used to discover the actual process map by querying inpatient processes using the provided log data. Transfusions of blood or blood products within 24 h after surgery, a subset of The Transfusion of Blood or Use of Blood Products trigger of Institute for Healthcare Improvement (GTT-C1) was deployed as a process pattern within the actual process map. Only detected patients were reviewed in the last phase. Results: The model ran on a single hospital data set, which included 2870 patients, 1048 of which included surgeries. The model reduced the analyzed data to 57 patients. The expert group analyzed these 57 patients and defined 12 adverse events. The calculated adverse event ratio was 1.1%, comparable with other manual Global Trigger Tool studies. In addition, the reviewers' time required decreased by 94.6%, from 138.28 to 7.52 h. Two reviewers validated the model by reviewing a sample of patients. Conclusions: Process mining can be used in healthcare institutions to conduct routine surveillance and detect unreported safety events. This allows healthcare providers to allocate financial and human resources to more urgent needs and increase efficiency. Further research is needed to evaluate the model with other triggers.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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