Mining Sepsis Treatment careflow Logs Using Disco
In a healthcare context the trajectory of a patient from arrival in the emergency ward to the admission to a hospital ward and up to the discharge can be seen as a process (sometimes also known as careflows). Often the execution of such a processes is supported by information systems. For example, the hospital may record medical information such as symptoms, the condition upon arrival of the patient, and the results of blood tests. Moreover also logistical information are recorded such as the movement of patients between wards and different types of discharge.
Process mining has been used by healthcare providers to understand and optimize their care pathways of patients[1].
In [2] Felix et al. have looked at the problem of discovering sepsis treatment process from logged ERP data [3]. They have created an event log containing data compiled from various sources (e.g lab/triage documents, financial records). see figure 2.
About the dataset:
we collected the event data and consolidated it into a single anonymized event log covering the traces that were recorded for 1050 patients over the course of 1.5 years in the hospital information systems. The resulting event log (see [3]) is made available for further process mining research purposes.The events were recorded by the ERP (Enterprise Resource Planning) system of the hospital. There are about 1000 cases with in total 15,000 events that were recorded for 16 different activities. Moreover, 39 data attributes are recorded, e.g., the group responsible for the activity, the results of tests and information from checklists.
The event log contains events for 16 activities:
- 3 activities regarding the registration and triaging in the emergency ward;
- 3 activities regarding measurement of leukocytes, CRP, and lactic acid;
- 2 activities regarding admission or transfer to normal care or intensive care;
- 5 activities for variants of discharge from the hospital; and
- an activity concerned with returning patients at a later time
The final process model shows 16 activities some of which are administrative (figure 3). We believe the aspect thats interesting is medical activities and provides the greatest room for process re-engineering/optimisation(measured here by patient well being and number of days till discharge) and showcasing our techniques.
Full process of management of the disease and associated decision making policy is fairly complicated where Treatment can include administration of antibiotics, source control, intravenous fluid therapy and organ system support with vasopressor drugs, mechanical ventilation, and renal replacement therapy as required[4].
results:
but they also concluded by saying ‘Unfortunately, little actionable results were obtained’
Their data ‘lack of data quality regarding the time when antibiotics were given and the general lack of data that could explain the returning patients’
Disclaimer: I blog mainly to document my learnings. I appolgize if I don’t provide all the references and borrow sentences as is.
[1] https://bmjopen.bmj.com/content/bmjopen/8/12/e019947.full.pdf
[2] http://ceur-ws.org/Vol-1859/bpmds-08-paper.pdf
[3] https://data.4tu.nl/repository/uuid:915d2bfb-7e84-49ad-a286-dc35f063a460
[4] Dellinger RP, Levy MM, Carlet JM, Bion J, Parker MM, Jaeschke R, Reinhart K, Angus DC, Brun-Buisson C, Beale R, Calandra T, Dhainaut JF, Gerlach H, Harvey M, Marini JJ, Marshall J, Ranieri M, Ramsay G, Sevransky J, Thompson BT, Townsend S, Vender JS, Zimmerman JL, Vincent JL (2008) Surviving sepsis campaign: international guidelines for management of severe sepsis and septic shock. Intensive Care Med 34:17–60
