Process Mining in Healthcare: Evaluating and Exploiting Operational Healthcare Processes: SpringerBriefs in Business Process Management
Autor Ronny S. Mans, Wil M. P. van der Aalst, Rob J. B. Vanwerschen Limba Engleză Paperback – 26 mar 2015
They focus on organizational healthcare processes rather than medical treatment processes. The combination of event data and process mining techniques allows them to analyze the operational processes within a hospital based on facts, thus providing a solid basis for managing and improving processes within hospitals. To this end, they also explicitly elaborate on data quality issues that are relevant for the data aspects of the healthcare reference model.
This book mainly targets advanced professionals involved in areas related to business process management, business intelligence, data mining, and business process redesign for healthcare systems as well as graduate students specializing in healthcare information systems and process analysis.
Preț: 392.99 lei
Preț vechi: 491.24 lei
-20% Nou
Puncte Express: 589
Preț estimativ în valută:
75.21€ • 79.34$ • 62.86£
75.21€ • 79.34$ • 62.86£
Carte tipărită la comandă
Livrare economică 01-15 ianuarie 25
Preluare comenzi: 021 569.72.76
Specificații
ISBN-13: 9783319160702
ISBN-10: 3319160702
Pagini: 91
Ilustrații: X, 91 p. 43 illus., 6 illus. in color.
Dimensiuni: 155 x 235 x 10 mm
Greutate: 0.16 kg
Ediția:2015
Editura: Springer International Publishing
Colecția Springer
Seria SpringerBriefs in Business Process Management
Locul publicării:Cham, Switzerland
ISBN-10: 3319160702
Pagini: 91
Ilustrații: X, 91 p. 43 illus., 6 illus. in color.
Dimensiuni: 155 x 235 x 10 mm
Greutate: 0.16 kg
Ediția:2015
Editura: Springer International Publishing
Colecția Springer
Seria SpringerBriefs in Business Process Management
Locul publicării:Cham, Switzerland
Public țintă
ResearchCuprins
1 Introduction.- 2 Healthcare Processes.- 3 Process Mining.- 4 Healthcare Reference Model.- 5 Applications of Process Mining.- 6 Data Quality Issues.- 7 Epilogue.
Notă biografică
Ronny Mans is a postdoctoral researcher at the Eindhoven University of Technology (TU/e). He is working in the Technology Foundation STW project “Developing Tools for Understanding Healthcare Processes” in which he focuses on the development of (process mining) techniques. He has published 10 journal papers, 30 refereed conference/workshop publications, and 8 book chapters. Ronny is a member of the editorial board of the KR4HC/ProHealth workshop and of the editorial board of the International Journal of Privacy and Health Information Management.
Wil van der Aalst is a full professor of Information Systems at TU/e. He is also the Academic Supervisor of the International Laboratory of Process-Aware Information Systems of the National Research University, Higher School of Economics in Moscow. Moreover, since 2003 he has a part-time appointment at Queensland University of Technology (QUT). His research interests include workflow management, process mining, Petri nets, business process management, process modeling, and process analysis. Wil has published more than 160 journal papers, 17 books (as author or editor), 300 refereed conference/workshop publications, and 50 book chapters. Many of his papers are highly cited (he has an H-index of 113 according to Google Scholar) and his ideas have influenced researchers, software developers, and standardization committees working on process support. He is also a member of the Royal Netherlands Academy of Arts and Sciences (KNAW), the Royal Holland Society of Sciences and Humanities (Koninklijke Hollandsche Maatschappij der Wetenschappen), and the Academy of Europe (Academia Europaea).
Rob Vanwersch is a program manager at Maastricht University Medical Center. In addition, he is a doctoral candidate and guest-lecturer within the Information Systems Group of the Department of Industrial Engineering and Innovation Sciences at TU/e. His research focuses on developing methodological support for redesigning business processes in healthcare. Rob Vanwersch has published several peer-reviewed journal and conference papers, and he also is a member of the user committee of the Technology Foundation STW project ”Developing tools for understanding healthcare processes”.
Wil van der Aalst is a full professor of Information Systems at TU/e. He is also the Academic Supervisor of the International Laboratory of Process-Aware Information Systems of the National Research University, Higher School of Economics in Moscow. Moreover, since 2003 he has a part-time appointment at Queensland University of Technology (QUT). His research interests include workflow management, process mining, Petri nets, business process management, process modeling, and process analysis. Wil has published more than 160 journal papers, 17 books (as author or editor), 300 refereed conference/workshop publications, and 50 book chapters. Many of his papers are highly cited (he has an H-index of 113 according to Google Scholar) and his ideas have influenced researchers, software developers, and standardization committees working on process support. He is also a member of the Royal Netherlands Academy of Arts and Sciences (KNAW), the Royal Holland Society of Sciences and Humanities (Koninklijke Hollandsche Maatschappij der Wetenschappen), and the Academy of Europe (Academia Europaea).
Rob Vanwersch is a program manager at Maastricht University Medical Center. In addition, he is a doctoral candidate and guest-lecturer within the Information Systems Group of the Department of Industrial Engineering and Innovation Sciences at TU/e. His research focuses on developing methodological support for redesigning business processes in healthcare. Rob Vanwersch has published several peer-reviewed journal and conference papers, and he also is a member of the user committee of the Technology Foundation STW project ”Developing tools for understanding healthcare processes”.
Caracteristici
Analyzes organizational healthcare processes based on event data Provides a solid basis for BPM professionals and researchers to improve hospital processes Introduces a healthcare reference model encompassing various relevant classes of data Includes supplementary material: sn.pub/extras