Leveraging Workflow Control Patterns in the Domain of Clinical Practice Guidelines

Overview

Journal BMC Med Inform Decis Mak

Publisher Biomed Central

Specialty Medical Informatics

Date 2016 Feb 12

PMID 26863868

Citations 3

Authors

Katharina Kaiser

Mar Marcos

Affiliations

Soon will be listed here.

Abstract

Background: Clinical practice guidelines (CPGs) include recommendations describing appropriate care for the management of patients with a specific clinical condition. A number of representation languages have been developed to support executable CPGs, with associated authoring/editing tools. Even with tool assistance, authoring of CPG models is a labor-intensive task. We aim at facilitating the early stages of CPG modeling task. In this context, we propose to support the authoring of CPG models based on a set of suitable procedural patterns described in an implementation-independent notation that can be then semi-automatically transformed into one of the alternative executable CPG languages.

Methods: We have started with the workflow control patterns which have been identified in the fields of workflow systems and business process management. We have analyzed the suitability of these patterns by means of a qualitative analysis of CPG texts. Following our analysis we have implemented a selection of workflow patterns in the Asbru and PROforma CPG languages. As implementation-independent notation for the description of patterns we have chosen BPMN 2.0. Finally, we have developed XSLT transformations to convert the BPMN 2.0 version of the patterns into the Asbru and PROforma languages.

Results: We showed that although a significant number of workflow control patterns are suitable to describe CPG procedural knowledge, not all of them are applicable in the context of CPGs due to their focus on single-patient care. Moreover, CPGs may require additional patterns not included in the set of workflow control patterns. We also showed that nearly all the CPG-suitable patterns can be conveniently implemented in the Asbru and PROforma languages. Finally, we demonstrated that individual patterns can be semi-automatically transformed from a process specification in BPMN 2.0 to executable implementations in these languages.

Conclusions: We propose a pattern and transformation-based approach for the development of CPG models. Such an approach can form the basis of a valid framework for the authoring of CPG models. The identification of adequate patterns and the implementation of transformations to convert patterns from a process specification into different executable implementations are the first necessary steps for our approach.

Citing Articles

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System for Context-Specific Visualization of Clinical Practice Guidelines (GuLiNav): Concept and Software Implementation.

Fortmann J, Lutz M, Spreckelsen C JMIR Form Res. 2022; 6(6):e28013.

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What Role Can Process Mining Play in Recurrent Clinical Guidelines Issues? A Position Paper.

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References

Mulyar N, van der Aalst W, Peleg M . A pattern-based analysis of clinical computer-interpretable guideline modeling languages. J Am Med Inform Assoc. 2007; 14(6):781-7. PMC: 2213484. DOI: 10.1197/jamia.M2389. View

Kaiser K, Akkaya C, Miksch S . How can information extraction ease formalizing treatment processes in clinical practice guidelines? A method and its evaluation. Artif Intell Med. 2006; 39(2):151-63. PMC: 2858817. DOI: 10.1016/j.artmed.2006.07.011. View

Inzitari D . The Italian Guidelines for stroke prevention. The Stroke Prevention and Educational Awareness Diffusion (SPREAD) Collaboration. Neurol Sci. 2000; 21(1):5-12. DOI: 10.1007/s100720070112. View

Scheuerlein H, Rauchfuss F, Dittmar Y, Molle R, Lehmann T, Pienkos N . New methods for clinical pathways-Business Process Modeling Notation (BPMN) and Tangible Business Process Modeling (t.BPM). Langenbecks Arch Surg. 2012; 397(5):755-61. DOI: 10.1007/s00423-012-0914-z. View

Swedberg K, Cleland J, Dargie H, Drexler H, Follath F, Komajda M . Guidelines for the diagnosis and treatment of chronic heart failure: executive summary (update 2005): The Task Force for the Diagnosis and Treatment of Chronic Heart Failure of the European Society of Cardiology. Eur Heart J. 2005; 26(11):1115-40. DOI: 10.1093/eurheartj/ehi204. View

Patel V, Arocha J, Diermeier M, Greenes R, Shortliffe E . Methods of cognitive analysis to support the design and evaluation of biomedical systems: the case of clinical practice guidelines. J Biomed Inform. 2001; 34(1):52-66. DOI: 10.1006/jbin.2001.1002. View

. Management of hyperbilirubinemia in the newborn infant 35 or more weeks of gestation. Pediatrics. 2004; 114(1):297-316. DOI: 10.1542/peds.114.1.297. View

Peleg M, Tu S, Bury J, Ciccarese P, Fox J, Greenes R . Comparing computer-interpretable guideline models: a case-study approach. J Am Med Inform Assoc. 2003; 10(1):52-68. PMC: 150359. DOI: 10.1197/jamia.m1135. View

Peleg M . Computer-interpretable clinical guidelines: a methodological review. J Biomed Inform. 2013; 46(4):744-63. DOI: 10.1016/j.jbi.2013.06.009. View

10.

Serban R, ten Teije A . Exploiting thesauri knowledge in medical guideline formalization. Methods Inf Med. 2009; 48(5):468-74. DOI: 10.3414/ME0629. View

11.

Gooch P, Roudsari A . Computerization of workflows, guidelines, and care pathways: a review of implementation challenges for process-oriented health information systems. J Am Med Inform Assoc. 2011; 18(6):738-48. PMC: 3197986. DOI: 10.1136/amiajnl-2010-000033. View

12.

Perez B, Porres I . Authoring and verification of clinical guidelines: a model driven approach. J Biomed Inform. 2010; 43(4):520-36. DOI: 10.1016/j.jbi.2010.02.009. View

13.

Grando M, Glasspool D, Fox J . A formal approach to the analysis of clinical computer-interpretable guideline modeling languages. Artif Intell Med. 2011; 54(1):1-13. DOI: 10.1016/j.artmed.2011.07.001. View

14.

Dominguez E, Perez B, Zapata M . Towards a traceable clinical guidelines application. A model-driven approach. Methods Inf Med. 2009; 49(6):571-80. DOI: 10.3414/ME09-01-0038. View

15.

Ohno-Machado L, Gennari J, Murphy S, Jain N, Tu S, OLIVER D . The guideline interchange format: a model for representing guidelines. J Am Med Inform Assoc. 1998; 5(4):357-72. PMC: 61313. DOI: 10.1136/jamia.1998.0050357. View

16.

Seyfang A, Kaiser K, Miksch S . Modelling clinical guidelines and protocols for the prevention of risks against patient safety. Stud Health Technol Inform. 2009; 150:633-7. PMC: 2854800. View

17.

de Clercq P, Blom J, Korsten H, Hasman A . Approaches for creating computer-interpretable guidelines that facilitate decision support. Artif Intell Med. 2004; 31(1):1-27. DOI: 10.1016/j.artmed.2004.02.003. View

18.

Peleg M, Tu S . Design patterns for clinical guidelines. Artif Intell Med. 2009; 47(1):1-24. DOI: 10.1016/j.artmed.2009.05.004. View

19.

Patel V, Allen V, Arocha J, Shortliffe E . Representing clinical guidelines in GLIF: individual and collaborative expertise. J Am Med Inform Assoc. 1998; 5(5):467-83. PMC: 61328. DOI: 10.1136/jamia.1998.0050467. View

20.

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. DOI: 10.1016/s0933-3657(98)00015-3. View