Literature DB >> 18487792

Process mining techniques: an application to stroke care.

Ronny Mans1, Helen Schonenberg, Giorgio Leonardi, Silvia Panzarasa, Anna Cavallini, Silvana Quaglini, Wil van der Aalst.   

Abstract

In a competitive health-care market, hospitals have to focus on ways to streamline their processes in order to deliver high quality care while at the same time reducing costs. To accomplish this goal, hospital managers need a thorough understanding of the actual processes. Diffusion of Information and Communication Technology tools within hospitals, such as electronic clinical charts, computerized guidelines and, more generally, decision support systems, make huge collections of data available, not only for data analysis, but also for process analysis. Process mining can be used to extract process related information (e.g., process models) from data, i.e., process mining describes a family of a-posteriori analysis techniques exploiting the information recorded in the event logs. This process information can be used to understand and redesign processes to become efficient high quality processes. In this paper, we apply process mining on two datasets for stroke patients and present the most interesting results. Above all, the paper demonstrates the applicability of process mining in the health-care domain.

Entities:  

Mesh:

Year:  2008        PMID: 18487792

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  14 in total

1.  Data analysis and data mining: current issues in biomedical informatics.

Authors:  R Bellazzi; M Diomidous; I N Sarkar; K Takabayashi; A Ziegler; A T McCray
Journal:  Methods Inf Med       Date:  2011       Impact factor: 2.176

2.  The Lombardia Stroke Unit Registry: 1-year experience of a web-based hospital stroke registry.

Authors:  Giuseppe Micieli; Anna Cavallini; Silvana Quaglini; Giancarlo Fontana; Michela Duè
Journal:  Neurol Sci       Date:  2010-03-26       Impact factor: 3.307

Review 3.  Computerization of workflows, guidelines, and care pathways: a review of implementation challenges for process-oriented health information systems.

Authors:  Phil Gooch; Abdul Roudsari
Journal:  J Am Med Inform Assoc       Date:  2011-07-01       Impact factor: 4.497

4.  Latent treatment pattern discovery for clinical processes.

Authors:  Zhengxing Huang; Xudong Lu; Huilong Duan
Journal:  J Med Syst       Date:  2013-02-08       Impact factor: 4.460

5.  Inferring Clinical Workflow Efficiency via Electronic Medical Record Utilization.

Authors:  You Chen; Wei Xie; Carl A Gunter; David Liebovitz; Sanjay Mehrotra; He Zhang; Bradley Malin
Journal:  AMIA Annu Symp Proc       Date:  2015-11-05

6.  Process Mining of Incoming Patients with Sepsis.

Authors:  Renee M Hendricks
Journal:  Online J Public Health Inform       Date:  2019-09-19

7.  Discovery of outpatient care process of a tertiary university hospital using process mining.

Authors:  Eunhye Kim; Seok Kim; Minseok Song; Seongjoo Kim; Donghyun Yoo; Hee Hwang; Sooyoung Yoo
Journal:  Healthc Inform Res       Date:  2013-03-31

8.  Building Data-Driven Pathways From Routinely Collected Hospital Data: A Case Study on Prostate Cancer.

Authors:  Joao H Bettencourt-Silva; Jeremy Clark; Colin S Cooper; Robert Mills; Victor J Rayward-Smith; Beatriz de la Iglesia
Journal:  JMIR Med Inform       Date:  2015-07-10

9.  Development, Implementation, and Evaluation of a Telemedicine Service for the Treatment of Acute Stroke Patients: TeleStroke.

Authors:  Carlos Parra; Francisco Jódar-Sánchez; M Dolores Jiménez-Hernández; Eduardo Vigil; Alfredo Palomino-García; Francisco Moniche-Álvarez; Francisco Javier De la Torre-Laviana; Patricia Bonachela; Francisco José Fernández; Aurelio Cayuela-Domínguez; Sandra Leal
Journal:  Interact J Med Res       Date:  2012-11-15

10.  Process Mining Methodology for Health Process Tracking Using Real-Time Indoor Location Systems.

Authors:  Carlos Fernandez-Llatas; Aroa Lizondo; Eduardo Monton; Jose-Miguel Benedi; Vicente Traver
Journal:  Sensors (Basel)       Date:  2015-11-30       Impact factor: 3.576

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