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Martínez-Salvador B, Marcos M, Palau P, Domínguez Mafé E. A model-driven transformation approach for the modelling of processes in clinical practice guidelines. Artif Intell Med 2023; 137:102495. [PMID: 36868689 DOI: 10.1016/j.artmed.2023.102495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 12/13/2022] [Accepted: 01/18/2023] [Indexed: 01/24/2023]
Abstract
Clinical Practice Guidelines (CPGs) include recommendations aimed at optimising patient care, informed by a review of the available clinical evidence. To achieve their potential benefits, CPG should be readily available at the point of care. This can be done by translating CPG recommendations into one of the languages for Computer-Interpretable Guidelines (CIGs). This is a difficult task for which the collaboration of clinical and technical staff is crucial. However, in general CIG languages are not accessible to non-technical staff. We propose to support the modelling of CPG processes (and hence the authoring of CIGs) based on a transformation, from a preliminary specification in a more accessible language into an implementation in a CIG language. In this paper, we approach this transformation following the Model-Driven Development (MDD) paradigm, in which models and transformations are key elements for software development. To demonstrate the approach, we implemented and tested an algorithm for the transformation from the BPMN language for business processes to the PROforma CIG language. This implementation uses transformations defined in the ATLAS Transformation Language. Additionally, we conducted a small experiment to assess the hypothesis that a language such as BPMN can facilitate the modelling of CPG processes by clinical and technical staff.
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Affiliation(s)
| | - Mar Marcos
- Department of Computer Engineering and Science, Univ. Jaume I, Spain
| | - Patricia Palau
- Cardiology Department, Hospital Clínico Universitario de Valencia, Univ. de València, Spain; INCLIVA Instituto de Investigación Sanitaria, Univ. de València, Spain
| | - Eloy Domínguez Mafé
- Cardiology Department, Hospital Clínico Universitario de Valencia, Univ. de València, Spain; Predepartmental Unit of Medicine, Univ. Jaume I, Spain
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ProDeM: A Process-Oriented Delphi Method for systematic asynchronous and consensual surgical process modelling. Artif Intell Med 2023; 135:102426. [PMID: 36628778 DOI: 10.1016/j.artmed.2022.102426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Revised: 08/10/2022] [Accepted: 10/11/2022] [Indexed: 11/22/2022]
Abstract
Surgical process models support improving healthcare provision by facilitating communication and reasoning about processes in the medical domain. Modelling surgical processes is challenging as it requires integrating information that might be fragmented, scattered, and not process-oriented. These challenges can be faced by involving healthcare domain experts during process modelling. This paper presents ProDeM: a novel Process-Oriented Delphi Method for the systematic, asynchronous, and consensual modelling of surgical processes. ProDeM is an adaptable and flexible method that acknowledges that: (i) domain experts have busy calendars and might be geographically dispersed, and (ii) various elements of the process model need to be assessed to ensure model quality. The contribution of the paper is twofold as it outlines ProDeM, but also demonstrates its operationalisation in the context of a well-known surgical process. Besides showing the method's feasibility in practice, we also present an evaluation of the method by the experts involved in the demonstration.
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Abstract
Process analysis and process modeling are a current topic that extends to many areas. This trend of using optimization and modeling techniques in various specific areas has led to the question of how widespread these approaches are overall in medical specializations. We compiled a list of 272 medical disciplines that we used as a search string with the Business Process Model and Notation (BPMN) for a Web of Science database search. Thus, we found a total of 485 documents that we subjected to the exclusion criteria. We analyzed the remaining 108 articles using bibliometric and content analyses to find answers to three research questions. This systematic review was carried out using the procedure proposed by Kitchenham and following the Preferred Items of the Systematic Review and Meta-Analysis Report (PRISMA). Due to the broad scope of the medical field, it was no surprise that for almost 85% of the sought-after medical specializations, we could not identify any publications in the given database when applying the BPMN. We analyzed the impact of upgrades to the BPMN on publishing. The keyword analysis showed a diametrical difference between the authors’ keywords and the so-called “Keywords Plus”, and we categorized the publications according to the purpose of applying the BPMN. However, the growing interest in combining BPMN with other approaches brings new challenges in practice.
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Gatta R, Vallati M, Fernandez-Llatas C, Martinez-Millana A, Orini S, Sacchi L, Lenkowicz J, Marcos M, Munoz-Gama J, Cuendet MA, de Bari B, Marco-Ruiz L, Stefanini A, Valero-Ramon Z, Michielin O, Lapinskas T, Montvila A, Martin N, Tavazzi E, Castellano M. What Role Can Process Mining Play in Recurrent Clinical Guidelines Issues? A Position Paper. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:E6616. [PMID: 32932877 PMCID: PMC7557817 DOI: 10.3390/ijerph17186616] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/08/2020] [Revised: 09/06/2020] [Accepted: 09/08/2020] [Indexed: 01/28/2023]
Abstract
In the age of Evidence-Based Medicine, Clinical Guidelines (CGs) are recognized to be an indispensable tool to support physicians in their daily clinical practice. Medical Informatics is expected to play a relevant role in facilitating diffusion and adoption of CGs. However, the past pioneering approaches, often fragmented in many disciplines, did not lead to solutions that are actually exploited in hospitals. Process Mining for Healthcare (PM4HC) is an emerging discipline gaining the interest of healthcare experts, and seems able to deal with many important issues in representing CGs. In this position paper, we briefly describe the story and the state-of-the-art of CGs, and the efforts and results of the past approaches of medical informatics. Then, we describe PM4HC, and we answer questions like how can PM4HC cope with this challenge? Which role does PM4HC play and which rules should be employed for the PM4HC scientific community?
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Affiliation(s)
- Roberto Gatta
- Dipartimento di Scienze Cliniche e Sperimentali dell’Università degli Studi di Brescia, 25128 Brescia, Italy;
| | - Mauro Vallati
- School of Computing and Engineering, University of Huddersfield, Huddersfield HD13DH, UK;
| | - Carlos Fernandez-Llatas
- PM4Health-SABIEN-ITACA, Universitat Politècnica de València, 46022 València, Spain; (C.F.-L.); (A.M.-M.); (Z.V.-R.)
- Department of Clinical Sciences, Intervention and Technology (CLINTEC), Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Antonio Martinez-Millana
- PM4Health-SABIEN-ITACA, Universitat Politècnica de València, 46022 València, Spain; (C.F.-L.); (A.M.-M.); (Z.V.-R.)
| | - Stefania Orini
- Alzheimer Operative Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, 25128 Brescia, Italy;
| | - Lucia Sacchi
- Department of Electrical, Computer and Biomedical Engineering, Università di Pavia, 27100 Pavia, Italy;
| | - Jacopo Lenkowicz
- Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168 Roma, Italy;
| | - Mar Marcos
- Department of Computer Engineering and Science, Universitat Jaume I, 12071 Castelló de la Plana, Spain;
| | - Jorge Munoz-Gama
- Human & Process Research Lab (HAPLAB), Department of Computer Science, School of Engineering, Pontificia Universidad Católica de Chile, 3580000 Santiago, Chile;
| | - Michel A. Cuendet
- Department of Oncology, University Hospital of Lausanne, 1011 Lausanne, Switzerland; (M.C.); (O.M.); (E.T.)
- Swiss Institute of Bioinformatics, UNIL Sorge, 1015 Lausanne, Switzerland
| | - Berardino de Bari
- Radiation Oncology, Réseau Hospitalier Neuchâtelois, 2000 La Chaux-de-Fonds, Switzerland;
- Department of Oncology, Lausanne University Hospital, University of Lausanne, 1015 Lausanne, Switzerland
| | - Luis Marco-Ruiz
- Norwegian Centre for E-health Research, University Hospital of North Norway, 7439 Tromsø, Norway;
| | - Alessandro Stefanini
- Dipartimento di Ingegneria dell’energia dei sistemi del territorio e delle costruzioni, Università degli Studi di Pisa, 56126 Pisa, Italy;
| | - Zoe Valero-Ramon
- PM4Health-SABIEN-ITACA, Universitat Politècnica de València, 46022 València, Spain; (C.F.-L.); (A.M.-M.); (Z.V.-R.)
| | - Olivier Michielin
- Department of Oncology, University Hospital of Lausanne, 1011 Lausanne, Switzerland; (M.C.); (O.M.); (E.T.)
- Swiss Institute of Bioinformatics, UNIL Sorge, 1015 Lausanne, Switzerland
| | - Tomas Lapinskas
- Department of Cardiology, Medical Academy, Lithuanian University of Health Sciences, 44307 Kaunas, Lithuania;
| | - Antanas Montvila
- Department of Radiology, Medical Academy, Lithuanian University of Health Sciences, 44307 Kaunas, Lithuania;
| | - Niels Martin
- Data Analytics Laboratory, Vrije Universiteit Brussel, 1050 Ixelles, Belgium;
- Research Foundation Flanders (FWO), 1000 Brussel, Belgium
- Hasselt University, 3500 Hasselt, Belgium
| | - Erica Tavazzi
- Department of Oncology, University Hospital of Lausanne, 1011 Lausanne, Switzerland; (M.C.); (O.M.); (E.T.)
- Department of Information Engineering, Università degli Studi di Padova, 35122 Padova, Italy
| | - Maurizio Castellano
- Dipartimento di Scienze Cliniche e Sperimentali dell’Università degli Studi di Brescia, 25128 Brescia, Italy;
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