What are the possibilities for process mining in hospitals? In this book the authors provide an answer to this question by presenting a healthcare reference model that outlines all the different classes of data that are potentially available for process mining in healthcare and the relationships between them. Subsequently, based on this reference model, they explain the application opportunities for process mining in this domain and discuss the various kinds of analyses that can be performed.
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.
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1 | (10) |
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1.1 Challenges in Healthcare |
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2 | (1) |
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1.2 Process Mining: Data Science in Action |
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3 | (2) |
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1.3 Applying Process Mining to Healthcare Processes |
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5 | (3) |
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8 | (3) |
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10 | (1) |
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11 | (6) |
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2.1 Different Levels of Care |
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11 | (1) |
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2.2 Classification of Healthcare Processes |
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12 | (2) |
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2.3 Four Types of Questions |
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14 | (3) |
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15 | (2) |
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17 | (10) |
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3.1 Event Data and Process Models |
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18 | (3) |
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3.2 Three Types of Process Mining |
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21 | (2) |
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3.3 The Process Mining Spectrum |
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23 | (1) |
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24 | (3) |
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26 | (1) |
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4 Healthcare Reference Model |
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27 | (26) |
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28 | (1) |
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29 | (20) |
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4.2.1 General Patient and Case Data |
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30 | (1) |
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31 | (5) |
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36 | (1) |
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37 | (1) |
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38 | (3) |
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41 | (4) |
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4.2.7 Organization and Buildings |
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45 | (2) |
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47 | (1) |
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48 | (1) |
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49 | (4) |
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51 | (2) |
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5 Applications of Process Mining |
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53 | (26) |
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5.1 Data Set from the Maastricht University Medical Center |
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54 | (3) |
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5.2 Data Set from the Academic Medical Center |
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57 | (1) |
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5.3 Process Mining Use Cases |
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57 | (22) |
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5.3.1 Use Case 1: Exploring Selections of Events |
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58 | (7) |
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5.3.2 Use Case 2: Identifying and Quantifying Deviations |
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65 | (2) |
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5.3.3 Use Case 3: Identifying and Quantifying Bottlenecks |
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67 | (3) |
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5.3.4 Use Case 4: Drilling Down |
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70 | (2) |
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5.3.5 Use Case 5: Healthcare Process Comparison |
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72 | (3) |
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5.3.6 Use Case 6: Context-Aware Process Mining |
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75 | (2) |
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77 | (1) |
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78 | (1) |
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79 | (10) |
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6.1 Classification of Event Log Quality Issues |
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80 | (3) |
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6.2 Evaluation of Data Quality Issues |
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83 | (3) |
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6.3 Improving Data Quality: Guidelines of Logging |
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86 | (2) |
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6.4 Garbage-In Garbage-Out |
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88 | (1) |
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88 | (1) |
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89 | |
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.
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