A Design Methodology for Medical Processes

Simona Ferrante; Stefano Bonacina; Giuseppe Pozzi; Francesco Pinciroli; Sara Marceglia

doi:10.4338/ACI-2015-08-RA-0111

Applied Clinical Informatics, Table of Contents

Appl Clin Inform 2016; 07(01): 191-210
DOI: 10.4338/ACI-2015-08-RA-0111

Research Article

Schattauer GmbH

A Design Methodology for Medical Processes

Simona Ferrante

¹Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy

,

Stefano Bonacina

²Health Informatics Centre, Department of Learning, Informatics, Management and Ethics, Karolinska Institutet, Stockholm, Sweden

,

Giuseppe Pozzi

¹Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy

,

Francesco Pinciroli

¹Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy

³Engineering in Health and Wellbeing Research Group at the National Research Council of Italy IEIIT – Istituto di Elettronica e di Ingegneria dell’Informazione e delle Telecomunicazioni

,

Sara Marceglia

⁴Dipartimento di Ingegneria e Architettura, Università degli Studi di Trieste, Trieste, Italy

⁵Clinical Center for Neurostimulation, Neurotechnology, and Movement Disorders Fondazione IRCCS Ca’Granda Ospedale Maggiore Policlinico, Milano, Italy

› Author Affiliations

Abstract

Summary

Background

Healthcare processes, especially those belonging to the clinical domain, are acknowledged as complex and characterized by the dynamic nature of the diagnosis, the variability of the decisions made by experts driven by their experiences, the local constraints, the patient’s needs, the uncertainty of the patient’s response, and the indeterminacy of patient’s compliance to treatment. Also, the multiple actors involved in patient’s care need clear and transparent communication to ensure care coordination.

Objectives

In this paper, we propose a methodology to model healthcare processes in order to break out complexity and provide transparency.

Methods

The model is grounded on a set of requirements that make the healthcare domain unique with respect to other knowledge domains. The modeling methodology is based on three main phases: the study of the environmental context, the conceptual modeling, and the logical modeling.

Results

The proposed methodology was validated by applying it to the case study of the rehabilitation process of stroke patients in the specific setting of a specialized rehabilitation center. The resulting model was used to define the specifications of a software artifact for the digital administration and collection of assessment tests that was also implemented.

Conclusions

Despite being only an example, our case study showed the ability of process modeling to answer the actual needs in healthcare practices. Independently from the medical domain in which the modeling effort is done, the proposed methodology is useful to create high-quality models, and to detect and take into account relevant and tricky situations that can occur during process execution.

Keywords

Healthcare process modeling and design - computing methodologies - patient-centered care - patient care management - critical pathways

Full Text

References

References
1 Ruiz F, García F, Calahorra L, Llorente C, Gonçalves L, Daniel C, Blobel B. Business Process Modeling in Healthcare. Stud Health Technol Inform 2012; 179: 75-87.
2 Garde S, Knaup P. Requirements engineering in health care: the example of chemotherapy planning in paediatric oncology. Requirements eng 2006; 11 (04) 265-278.
3 Baacke L, Mettler T, Rohner P. Component-based process modelling in health care. Proc in the 17th European Conference on Information Systems ECIS Verona; Italy: 2009: 430-441.
4 Workflow Management Coalition Specification, Workflow Management Coalition, Terminology & Glossary (Document No. WFMC-TC-1011). Workflow Management Coalition Specification. 1999
5 Chiao CM, Künzle V, Reichert M. Integrated modeling of process- and data-centric software systems with PHILharmonic Flows. in CPSM@ICSM 2013; 1-10.
6 Horsky J, Gutnik L, Patel VL. Technology for emergency care: cognitive and workflow considerations. AMIA Annu Symp Proc 2006; 344-348.
7 Risser DT, Rice MM, Salisbury ML, Simon R, Jay GD, Berns SD. The potential for improved teamwork to reduce medical errors in the emergency department. The MedTeams Research Consortium. Ann Emerg Med 1999; 34 (03) 373-383.
8 Ozkaynak M, Brennan P. An observation tool for studying patient-oriented workflow in hospital emergency departments. Methods Inf Med 2013; 52 (06) 503-513.
9 American Medical Association [Internet], Chicago: The Association; c1995-2015 [updated 2014 Sep 16; cited 2015 Nov 5]. 8 top challenges and solutions for making EHRs usable; [about 2 screens]. Available from: http://www.ama-assn.org/ama/pub/ama-wire/ama-wire/post/8-top-challenges-solutions-making-ehrs-usable
10 Barbarito F, Pinciroli F, Mason J, Marceglia S, Mazzola L, Bonacina S. Implementing standards for the interoperability among healthcare providers in the public regionalized Healthcare Information System of the Lombardy Region. J Biomed Inform 2012; 45 (04) 736-745.
11 Malhotra S, Jordan DA, Shortliffe EH, Patel VL. Workflow modeling in critical care: Piecing together your own puzzle. J Biomed Inform 2007; 40 (02) 81-92.
12 Schweitzer M, Lasierra N, Oberbichler S, Toma I, Fensel A, Hoerbst A. Structuring clinical workflows for diabetes care: an overview of the OntoHealth approach. Appl Clin Inform 2014; 05 (02) 512-526.
13 Kumarapeli P, De Lusignan S, Ellis T, Jones B. Using Unified Modelling Language (UML) as a process-modelling technique for clinical-research process improvement. Med Inform Internet Med 2007; 32 (01) 51-64.
14 de Lusignan S, Krause P, Michalakidis G, Vicente MT, Thompson S, McGilchrist M, Sullivan F, van Royen P, Agreus L, Desombre T, Taweel A, Delaney B. Business Process Modelling is an Essential Part of a Requirements Analysis. Contribution of EFMI Primary Care Working Group. Yearb Med Inform 2012; 07 (01) 34-43.
15 Vawdrey DK, Wilcox LG, Collins S, Feiner S, Mamykina O, Stein DM, Bakken S, Fred MR, Stetson PD. Awareness of the Care Team in Electronic Health Records. Appl Clin Inform 2011; 02 (04) 395-405.
16 Lenz R, Reichert M. IT support for healthcare processes – premises, challenges, perspectives. Data Knowl. Eng 2007; 61 (01) 39-58.
17 Marceglia S, Mazzola L, Bonacina S, Tarquini P, Donzelli P, Pinciroli F. A Comprehensive e-prescribing model to allow representing, comparing, and analyzing available systems. Methods Inf Med 2013; 52 (03) 199-219.
18 Howard RMT, Barrows S. Problem-Based Learning: An Approach to Medical Education (Springer Series on Medical Education). Springer Publishing Company.;
19 Oshima ELee, Emanuel EJ. Shared decision making to improve care and reduce costs. N Engl J Med 2013; 368 (01) 6-8.
20 Panzarasa S, Maddè S, Quaglini S, Pistarini C, Stefanelli M. Evidence-based careflow management systems: the case of post-stroke rehabilitation. J Biomed Inform 2002; 35 (02) 123-139.
21 Huang B, Zhu P, Wu C. Customer-centered careflow modeling based on guidelines. J Med Syst 2012; 36 (05) 3307-3319.
22 Reichert M. What BPM Technology Can Do for Healthcare Process Support. in AIME 2011; 2-13.
23 Baresi L, Casati F, Castano L, Fugini M, Grefen P, Mirbel I, Pernici B, Pozzi G. Workflow Design Methodology. In Database Support for Workflow Management The WIDE Project. 491. Paul Grefen, Barbara Pernici, Gabriel Sánchez, Jochem Vonk, Erik Boertjes. 1999
24 Unertl KM, Weinger MB, Johnson KB, Lorenzi NM. Describing and Modeling Workflow and Information Flow in Chronic Disease Care. J Am Med Inform Assoc 2009; 16 (06) 826-883.
25 Barbarito F, Pinciroli F, Barone A, Pizzo F, Ranza R, Mason J, Mazzola L, Bonacina S, Marceglia S. Implementing the lifelong personal health record in a regionalised health information system: The case of Lombardy, Italy. Comput Biol Med 2015; 59: 164-174.
26 Peleg M, Somekh J, Dori D. A methodology for eliciting and modeling exceptions. J Biomed Inform 2009; 42 (04) 736-747.
27 Rebuge Á, Ferreira DR. Business process analysis in healthcare environments: A methodology based on process mining. Inf Syst 2012; 37 (02) 99-116.
28 Huang Z, Lu X, Duan H. On mining clinical pathway patterns from medical behaviors. Artificial Intelligence in Medicine 2012; 56 (01) 35-50.
29 Bonacina S, Marceglia S, Pinciroli F. Barriers Against Adoption of Electronic Health Record in Italy. J Healthc Eng 2011; 02 (04) 509-526.
30 Kotronoulas G, Kearney N, Maguire R, Harrow A, Di Domenico D, Croy S, MacGillivray S. What is the value of the routine use of patient-reported outcome measures toward improvement of patient outcomes, processes of care, and health service outcomes in cancer care? A systematic review of controlled trials. J Clin Oncol 2014; 32 (14) 1480-1501.
31 Koh HK, Brach C, Harris LM, Parchman ML. A proposed ‘Health Literate Care Model’ would constitute a systems approach to improving patients’ engagement in care. Health Affairs 2013; 32 (02) 357-367.
32 Anzböck R, Dustdar S. Modeling and implementing medical Web services. Data Knowl Eng 2005; 55 (02) 203-236.
33 Leonardi G, Panzarasa S, Quaglini S, Stefanelli M, van der Aalst WMP. Interacting agents through a web-based health serviceflow management system. Journal of Biomedical Informatics 2007; 40 (05) 486-499.
34 Reichert M, Weber B. Enabling Flexibility in Process-Aware Information Systems. Springer; 2012
35 Peleg M, Tu SW. Design patterns for clinical guidelines. Artificial Intelligence in Medicine 2009; 47 (01) 1-24.
36 González-Ferrer A, ten Teije A, Fdez-Olivares J, Milian K. Automated generation of patient-tailored electronic care pathways by translating computer-interpretable guidelines into hierarchical task networks. Artif Intell Med 2013; 57 (02) 91-109.
37 Musen MA, Tu SW, Das AK, Shahar Y. EON: a component-based approach to automation of protocol-directed therapy. J Am Med Inform Assoc 1996; 03 (06) 367-388.
38 De Clercq PA, Blom JA, Hasman A, Korsten HH. GASTON: an architecture for the acquisition and execution of clinical guideline-application tasks. Med Inform Internet Med 2000; 25 (04) 247-263.
39 Terenziani P, Molino G, Torchio M. A modular approach for representing and executing clinical guidelines. Artif Intell Med 2001; 23 (03) 249-276.
40 Peleg M, Boxwala AA, Bernstam E, Tu S, Greenes RA, Shortliffe EH. Sharable representation of clinical guidelines in GLIF: relationship to the Arden Syntax. J Biomed Inform 2001; 34 (03) 170-181.
41 Quaglini S, Stefanelli M, Lanzola G, Caporusso V, Panzarasa S. Flexible guideline-based patient careflow systems. Artif Intell Med 2001; 22 (01) 65-80.
42 Klein M, Dellarocas C. A Knowledge-based Approach to Handling Exceptions in Workflow Systems. Computer Supported Cooperative Work 2000; 09 3/4 399-412.
43 de Carvalho ECA, Jayanti MK, Batilana AP, Kozan AMO, Rodrigues MJ, Shah J, Loures MR, Patil S, Payne P, Pietrobon R. Standardizing clinical trials workflow representation in UML for international site comparison. PLoS ONE 2010; 05 (11) e13893.
44 Assimakopoulos NA. Workflow management with systems approach: anticipated and ad-hoc workflow for scientific applications ISA Trans. 2000; 39 (02) 153-167.
45 Ferrante S, Bonacina S, Pinciroli F. Modeling stroke rehabilitation processes using the Unified Modeling Language (UML). Comp in Bio and Med 2013; 43 (10) 1390-1401.
46 Garde S, Baumgarten B, Basu O, Graf N, Haux R, Herold R, Kutscha U, Schilling F, Selle B, Spiess C, Wetter T, Knaup P. A meta-model of chemotherapy planning in the multi-hospital/multi-trial-center-environment of pediatric oncology. Methods Inf Med 2004; 43 (02) 171-183.
47 Shiki N, Ohno Y, Fujii A, Murata T, Matsumura Y. Time process study with UML. Methods Inf Med 2009; 48 (06) 582-588.
48 van der Aalst W, ter Hofstedeb A. YAWL – Yet Another Workflow Language. Information Systems. Information Systems 2005; 30: 245-275.
49 Reichert M, Rinderle S, Almagro PL. ADEPT flex – Supporting Dynamic Changes of Workflows Without Loosing Control. Journal of Intelligent Information Systems 1998; 10 (02) 93-129.
50 Reichert M, Rinderle S, Dadam P. ADEPT Workflow Management System: Flexible Support for Enterprise-Wide Business Processes. in Proceedings of the international conference on Business process management 2003; 370-379.
51 Fasola G, Rizzato S, Merlo V, Aita M, Ceschia T, Giacomuzzi F, Lugatti E, Meduri S, Morelli A, Rocco M, Tozzi V. Adopting integrated care pathways in non-small-cell lung cancer: from theory to practice. J Thorac Oncol 2012; 07 (08) 1283-1290.
52 Fasola G, Aprile G, Aita M. A model to estimate human resource needs for the treatment of outpatients with cancer. J Oncol Pract 2012; 08 (01) 13-17.
53 Shahar Y, Miksch S, Johnson P. The Asgaard project: a task-specific framework for the application and critiquing of time-oriented clinical guidelines. Artif Intell Med 1998; 14 1–2 29-51.
54 Mendling J. Metrics for Process Models: Empirical Foundations of Verification, Error Prediction, and Guidelines for Correctness. 2008. 06 Springer.;
55 Bertino E, Ferrari E, Atluri V. The Specification and Enforcement of Authorization Constraints in Workflow Management Systems. ACM Trans Inf Syst Secur 1999; 02 (01) 65-104.
56 Combi C, Degani S. Seamless (and Temporal) Conceptual Modeling of Business Process Information. in ADBIS 2011; 02: 23-32.
57 Tu SW, Campbell JR, Glasgow J, Nyman MA, McClure R, McClay J, Parker C, Hrabak KM, Berg D, Weida T, Mansfield JG, Musen MA, Abarbanel RM. The SAGE Guideline Model: achievements and overview. J Am Med Inform Assoc 2007; 14 (05) 589-598.
58 Swartz J. Airport 95: Automated Baggage System?. Software Engineering Notes 1996; 21 (02) 79-83.
59 Leape LL, Lawthers AG, Brennan TA, Johnson WG. Preventing medical injury. QRB Qual Rev Bull 1993; 19 (05) 144-149.
60 Liaw ST, Deveny E, Morrison I, Lewis B. Clinical, information and business process modeling to promote development of safe and flexible software. Health Informatics J 2006; 12 (03) 199-211.
61 Business Process Modeling Language. Business Process Management Institute; 2003
62 Askari M, Westerhof R, Eslami S, Medlock S, de Rooij SE, Abu-Hanna A. A combined disease management and process modeling approach for assessing and improving care processes: A fall management case-study. I J Medical Informatics 2013; 82 (10) 1022-1033.
63 Jun GT, Ward J, Morris Z, Clarkson J. Health care process modelling: which method when?. International Journal for Quality in Health Care 2009; 21 (03) 214-224.
64 Geambasu CV. BPMN vs. UML Activity Diagram for Business Process Modeling. Journal of Accounting and Management Information Systems 2012; 11 (04) 637-651.
65 Rumbaugh JE, Jacobson I, Booch G. The unified modeling language reference manual. Addison-Wesley-Longman; 1999
66 OMG-UML-SUP. 2005 Unified modeling language: Superstructure. OMG document formal/05–07–04.
67 Shiki N, Ohno Y, Fujii A, Murata T, Matsumura Y. Unified Modeling Language (UML) for hospital-based cancer registration processes. Asian Pac J Cancer Prev 2008; 09 (04) 789-796.
68 National Guidelines Clearinghouse [Internet]. Rockville, MD: Agency for Healthcare and Quality. c2000–01 [updated 2015 June 18; cited 2015 Nov 5]. Available from: http://www.guideline.gov/
69 National Stroke Foundation, Australia. Clinical Guidelines for Stroke Management 2010 – Recommendations. 2010
70 Bates B, Choi JY, Duncan PW, Glasberg JJ, Graham GD, Katz RC, Lamberty K, Reker D, Zorowitz R. US Department of Defense; Department of Veterans Affairs. Veterans Affairs/Department of Defense Clinical Practice Guideline for the Management of Adult Stroke Rehabilitation Care: Executive summary. Stroke 2005; 36 (09) 2049-2056.
71 Scottish Intercollegiate Guidelines Network. Management of Patients with Stroke or TIA: Assessment, Investigation, Immediate Management and Secondary Prevention. A national clinical guideline. 2008
72 Lindsay P, Bayley M, McDonald A, Graham ID, Warner G, Phillips S. Toward a more effective approach to stroke: Canadian Best Practice Recommendations for Stroke Care. Canadian Medical Association Journal 2008; 178 (11) 1418-1425.
73 Kirkpatrick DL, Kirkpatrick JD. Evaluating training programs: the four levels. 2006. 3rd ed. Berkeley: Berrett-Koehler Publishers, Inc.;