Appl Clin Inform 2018; 09(03): 654-666
DOI: 10.1055/s-0038-1668089
Research Article
Georg Thieme Verlag KG Stuttgart · New York

Mapping the Flow of Pediatric Trauma Patients Using Process Mining

Ashimiyu B. Durojaiye
1  Division of Health Sciences Informatics, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States
2  Armstrong Institute Center for Health Care Human Factors, Johns Hopkins Medicine, Baltimore, Maryland, United States
,
Nicolette M. McGeorge
2  Armstrong Institute Center for Health Care Human Factors, Johns Hopkins Medicine, Baltimore, Maryland, United States
,
Lisa L. Puett
3  Department of Pediatric Nursing, Johns Hopkins Hospital, Baltimore, Maryland, United States
,
Dylan Stewart
4  Department of Pediatric Surgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States
,
James C. Fackler
5  Division of Pediatric Anesthesiology and Critical Care Medicine, Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States
,
Peter L. T. Hoonakker
6  Center for Quality and Productivity Improvement, University of Wisconsin, Madison, Wisconsin, United States
,
Harold P. Lehmann
1  Division of Health Sciences Informatics, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States
,
Ayse P. Gurses
1  Division of Health Sciences Informatics, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States
2  Armstrong Institute Center for Health Care Human Factors, Johns Hopkins Medicine, Baltimore, Maryland, United States
7  Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University, Baltimore, Maryland, United States
8  Malone Center for Engineering in Healthcare, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States
9  Department of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, United States
› Author Affiliations
Funding This study was supported by the Agency for HealthCare Research and Quality (R01HS023837; PI: Gurses). The study sponsor was not involved in the study design, the writing, and the decision to submit the manuscript for publication.
Further Information

Publication History

01 March 2018

27 June 2018

Publication Date:
22 August 2018 (online)

Abstract

Background Inhospital pediatric trauma care typically spans multiple locations, which influences the use of resources, that could be improved by gaining a better understanding of the inhospital flow of patients and identifying opportunities for improvement.

Objectives To describe a process mining approach for mapping the inhospital flow of pediatric trauma patients, to identify and characterize the major patient pathways and care transitions, and to identify opportunities for patient flow and triage improvement.

Methods From the trauma registry of a level I pediatric trauma center, data were extracted regarding the two highest trauma activation levels, Alpha (n = 228) and Bravo (n = 1,713). An event log was generated from the admission, discharge, and transfer data from which patient pathways and care transitions were identified and described. The Flexible Heuristics Miner algorithm was used to generate a process map for the cohort, and separate process maps for Alpha and Bravo encounters, which were assessed for conformance when fitness value was less than 0.950, with the identification and comparison of conforming and nonconforming encounters.

Results The process map for the cohort was similar to a validated process map derived through qualitative methods. The process map for Bravo encounters had a relatively low fitness of 0.887, and 96 (5.6%) encounters were identified as nonconforming with characteristics comparable to Alpha encounters. In total, 28 patient pathways and 20 care transitions were identified. The top five patient pathways were traversed by 92.1% of patients, whereas the top five care transitions accounted for 87.5% of all care transitions. A larger-than-expected number of discharges from the pediatric intensive care unit (PICU) were identified, with 84.2% involving discharge to home without the need for home care services.

Conclusion Process mining was successfully applied to derive process maps from trauma registry data and to identify opportunities for trauma triage improvement and optimization of PICU use.

Protection of Human and Animal Subjects

This study was performed in compliance with the World Medical Association Declaration of Helsinki on Ethical Principles for Medical Research Involving Human Subjects and was reviewed by Johns Hopkins Medicine Institutional Review Board.