Analyzing the trajectories of patients with sepsis using process mining

F. Mannhardt, D. Blinde

    Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

    33 Citaten (Scopus)
    277 Downloads (Pure)

    Samenvatting

    Process mining techniques analyze processes based on event data. We analyzed the trajectories of patients in a Dutch hospital from their registration in the emergency room until their discharge. We considered a sample of 1050 patients with symptoms of a sepsis condition, which is a life-threatening condition. We extracted an event log that includes events on activities in the emergency room, admission to hospital wards, and discharge. The event log was enriched with data from laboratory tests and triage checklists.
    We try to automatically discover a process model of the patient trajectories, we check conformance to medical guidelines for sepsis patients, and visualize the flow of patients on a de-jure process model. The lessons-learned from this analysis are: (1) process mining can be used to clarify the patient flow in a hospital; (2) process mining can be used to check the daily clinical practice against medical guidelines; (3) process discovery methods may return unsuitable models that are difficult to understand for stakeholders; and (4) process mining is an iterative process, e.g., data quality issues are often discovered and need to be addressed.
    Originele taal-2Engels
    TitelRADAR+EMISA 2017, Essen, Germany, June 12-13, 2017
    UitgeverijCEUR-WS.org
    Pagina's72-80
    Aantal pagina's9
    StatusGepubliceerd - 2017
    EvenementRADAR + EMISA 2017 - Essen, Duitsland
    Duur: 12 jun 201713 jun 2017

    Publicatie series

    NaamCEUR Workshop Proceedings
    Volume1859
    ISSN van geprinte versie1613-0073

    Congres

    CongresRADAR + EMISA 2017
    LandDuitsland
    StadEssen
    Periode12/06/1713/06/17

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