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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:ijerph17186616. [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;
- Correspondence:
| | - 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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Pereira Detro S, Santos EAP, Panetto H, Loures ED, Lezoche M, Cabral Moro Barra C. Applying process mining and semantic reasoning for process model customisation in healthcare. ENTERP INF SYST-UK 2019. [DOI: 10.1080/17517575.2019.1632382] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
- Silvana Pereira Detro
- Graduate Program in Production Engineering and Systems (PPGEPS), Pontifícia Universidade Católica do Paraná (PUCPR), Curitiba, Brazil
- CNRS, CRAN, Université de Lorraine, Nancy, France
| | - Eduardo Alves Portela Santos
- Graduate Program in Production Engineering and Systems (PPGEPS), Pontifícia Universidade Católica do Paraná (PUCPR), Curitiba, Brazil
| | | | - Eduardo De Loures
- Graduate Program in Production Engineering and Systems (PPGEPS), Pontifícia Universidade Católica do Paraná (PUCPR), Curitiba, Brazil
| | | | - Claudia Cabral Moro Barra
- Graduate Program in Health Technology (PPGTS), Pontifícia Universidade Católica do Paraná (PUCPR), Curitiba, Brazil
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Adlassnig KP, Haug P, Jenders RA. Arden Syntax: Then, now, and in the future. Artif Intell Med 2018; 92:1-6. [PMID: 30528060 DOI: 10.1016/j.artmed.2018.09.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2018] [Accepted: 09/10/2018] [Indexed: 11/27/2022]
Affiliation(s)
- Klaus-Peter Adlassnig
- Section for Artificial Intelligence and Decision Support, Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Spitalgasse 23, A-1090 Vienna, Austria; Medexter Healthcare GmbH, Borschkegasse 7/5, A-1090 Vienna, Austria.
| | - Peter Haug
- Homer Warner Research Center, Intermountain Healthcare, 5171 South Cottonwood Street, Murray, UT 84107, USA; Department of Biomedical Informatics, University of Utah, 421 Wakara Way, Salt Lake City, UT 84108, USA
| | - Robert A Jenders
- Department of Medicine & Clinical and Translational Science Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA; Center for Biomedical Informatics, Charles Drew University, 1748 E 118th Street, LSRNE N238, Los Angeles, CA 90059, USA
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Bilici E, Despotou G, Arvanitis TN. The use of computer-interpretable clinical guidelines to manage care complexities of patients with multimorbid conditions: A review. Digit Health 2018; 4:2055207618804927. [PMID: 30302270 PMCID: PMC6172935 DOI: 10.1177/2055207618804927] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2017] [Accepted: 09/05/2018] [Indexed: 01/25/2023] Open
Abstract
Clinical practice guidelines (CPGs) document evidence-based information and recommendations on treatment and management of conditions. CPGs usually focus on management of a single condition; however, in many cases a patient will be at the centre of multiple health conditions (multimorbidity). Multiple CPGs need to be followed in parallel, each managing a separate condition, which often results in instructions that may interact with each other, such as conflicts in medication. Furthermore, the impetus to deliver customised care based on patient-specific information, results in the need to be able to offer guidelines in an integrated manner, identifying and managing their interactions. In recent years, CPGs have been formatted as computer-interpretable guidelines (CIGs). This enables developing CIG-driven clinical decision support systems (CDSSs), which allow the development of IT applications that contribute to the systematic and reliable management of multiple guidelines. This study focuses on understanding the use of CIG-based CDSSs, in order to manage care complexities of patients with multimorbidity. The literature between 2011 and 2017 is reviewed, which covers: (a) the challenges and barriers in the care of multimorbid patients, (b) the role of CIGs in CDSS augmented delivery of care, and (c) the approaches to alleviating care complexities of multimorbid patients. Generating integrated care plans, detecting and resolving adverse interactions between treatments and medications, dealing with temporal constraints in care steps, supporting patient-caregiver shared decision making and maintaining the continuity of care are some of the approaches that are enabled using a CIG-based CDSS.
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Affiliation(s)
- Eda Bilici
- Institute of Digital Healthcare, WMG, University of Warwick, UK
| | - George Despotou
- Institute of Digital Healthcare, WMG, University of Warwick, UK
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