This paper is in the following e-collection/theme issue:

Clinical Information and Decision Making (1915) Health Services Research (557) Health Care Quality and Health Services Research (337) Health Services Research and Health Care Utilization in Older Patients (138) Involvement of Elderly Populations in Health and Health Services Research (60) Frailty Detection, Assessment and Prediction (62) Design of Processes and Workflows (187)

Published on in Vol 23, No 10 (2021): October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/27499, first published .
Identifying Frequent Health Care Users and Care Consumption Patterns: Process Mining of Emergency Medical Services Data

Identifying Frequent Health Care Users and Care Consumption Patterns: Process Mining of Emergency Medical Services Data

Identifying Frequent Health Care Users and Care Consumption Patterns: Process Mining of Emergency Medical Services Data

Authors of this article:

Laura Maruster1 Author Orcid Image ;   Durk-Jouke van der Zee1 Author Orcid Image ;   Erik Buskens1, 2 Author Orcid Image
Article Authors Cited by (12) Tweetations (4) Metrics

Journals

  1. Scott J, Pakpahan E, Marlow B, Daxner N. Defining a threshold above which an adult can be considered to frequently use ambulance services: a retrospective cross-sectional study of emergency calls to an ambulance service in England. British Paramedic Journal 2023;7(4):35 View
  2. Olivier A, Adams M, Mohammadi S, Smyth A, Thomson K, Kepler T, Dadlani M. Data analytics for improved closest hospital suggestion for EMS operations in New York City. Sustainable Cities and Society 2022;86:104104 View
  3. Furia G, Vinci A, Colamesta V, Papini P, Grossi A, Cammalleri V, Chierchini P, Maurici M, Damiani G, De Vito C. Appropriateness of frequent use of emergency departments: A retrospective analysis in Rome, Italy. Frontiers in Public Health 2023;11 View
  4. Yang X, Huang W, Zhao W, Zhou X, Shi N, Xia Q. Exploring Acute Pancreatitis Clinical Pathways Using a Novel Process Mining Method. Healthcare 2023;11(18):2529 View
  5. Cyrino C, Castro M, Nunes H, Deodato S, Dell’Acqua M, Juliani C. Factors related to readmissions to the Mobile Emergency Care Service. Escola Anna Nery 2023;27 View
  6. Cyrino C, Castro M, Nunes H, Deodato S, Dell’Acqua M, Juliani C. Fatores relacionados às readmissões ao Serviço de Atendimento Móvel de Urgência. Escola Anna Nery 2023;27 View
  7. Weil L, Zwerwer L, Chu H, Verhoeff M, Jeurissen P, van Munster B. Identifying future high healthcare utilization in patients with multimorbidity – development and internal validation of machine learning prediction models using electronic health record data. Health and Technology 2024;14(3):433 View
  8. Gehrt T, Laursen C, Lock M, Bossen C, Huibers L, Væggemose U. Frequent callers to the emergency medical services: A mixed-methods study of call patterns, reasons for calling, and wellbeing. Social Science & Medicine 2025;382:118326 View
  9. Harring A, Kjærgaard M, Gehrt T. Frequent callers vs. frequent users – a scoping review of frequent contacts to the emergency medical services. International Journal of Emergency Medicine 2025;18(1) View
  10. Kjærgaard M, Valås Harring A, Gehrt T. How to Define a Frequent Caller to the Prehospital Emergency Medical Services? Literature-Based vs. Data-Driven Approach. Prehospital Emergency Care 2025:1 View
  11. Pouw M, Dijkstra H, Kőntőș E, de Jonghe A, Dercksen B, Maruster L, van der Zee D, van Munster B. Frequent Emergency Medical Services Utilization Among Older Patients: Exploration and Automatic Identification Using Natural Language Processing. Journal of the American Medical Directors Association 2025;26(11):105814 View
  12. Furia G, Vinci A, Lombardo P, Papini P, Barbara A, Mataloni F, Di Martino M, Davoli M, Maurici M, Damiani G, De Vito C. Frequent Users of Emergency Departments: Analysis of the Characteristics and Geographical Distribution in a Local Health Authority in Rome, Italy. Healthcare 2025;13(20):2609 View