Interplay between Clinical Guidelines and Organizational Workflow Systems^[*]

Summary

Background: Implementing a decision-support system within a healthcare organization requires integration of clinical domain knowledge with resource constraints. Computer-interpretable guidelines (CIG) are excellent instruments for addressing clinical aspects while business process management (BPM) languages and Workflow (Wf) engines manage the logistic organizational constraints.

Objectives: Our objective is the orchestra -tion of all the relevant factors needed for a successful execution of patient’s care pathways, especially when spanning the contin -uum of care, from acute to community or home care.

Methods: We considered three strategies for integrating CIGs with organizational work-flows: extending the CIG or BPM languages and their engines, or creating an interplay between them. We used the interplay approach to implement a set of use cases arising from a CIG implementation in the domain of Atrial Fibrillation. To provide a more scalable and standards-based solution, we explored the use of Cross-Enterprise Document Workflow Integration Profile.

Results: We describe our proof-of-concept implementation of five use cases. We utilized the Personal Health Record of the MobiGuide project to implement a loosely-coupled approach between the Activiti BPM engine and the Picard CIG engine. Changes in the PHR were detected by polling. IHE profiles were used to develop workflow documents that orchestrate cross-enterprise execution of cardioversion.

Conclusions: Interplay between CIG and BPM engines can support orchestration of care flows within organizational settings.

Keywords

Clinical guidelines - computer-interpretable guidelines - workflow management systems - business processes - interoperability standards

^* Supplementary material published on our website http://dx.doi.org/10.3414/ME16-01-0006

• References

• 1 Institute of Medicine.. Clinical practice guidelines we can trust. Consensus Report. 2013
• 2 Peleg M. Computer-interpretable Clinical Guidelines: a Methodological Review. J Biomed Inf 2013; 46 (Suppl. 04) 744-763.
• 3 Peleg M, Gonzalez-Ferrer A. Chapter 16: Guidelines and Workflow Models. In: Greenes RA. editor. Clinical Decision Support: The Road to Broad Adoption. 2nd Edition. Academic Press; 2014. p. 435-464.
• 4 Bates DW, Kuperman GJ, Wang S, Gandhi T, Kittler A, Volk L. et al. Ten Commandments for Effective Clinical Decision Support: Making the Practice of Evidence-based Medicine a Reality. J Am Med Inform Assoc 2003; p. 523-530.
• 5 Shvo AS, Peleg M. Integrating Organizational Workflows into MobiGuide Clinical Guidelines (Position paper). Prohealth Workshop. 2014
• 6 Burke D, Yu F, Au D, Menachemi N. Best of breed strategies – hospital characteristics associated with organizational HIT strategy. J Healthc Inf Manag 2008; 23 (Suppl. 02) 46-51.
• 7 Huff S. Letter from the Chair of Health Level 7 International Board of Directors. 2015
• 8 Raunak MS, Osterweil LJ. Resource Management for Complex, Dynamic Environments. IEEE Trans Softw Eng 2013; 39: 384-402.
• 9 HealthIT.. Meaningful Use of HIT in the USA. 2015 Available from: http://www.healthit.gov/providers-professionals/meaningful-use-definition-objectives
• 10 Peleg M, Shahar Y, Quaglini S. Making healthcare more accessible, better, faster, and cheaper: the MobiGuide Project. Eur J ePractice 2015; 20: 5-20.
• 11 IHE.. XDW – Cross-Enterprise Document Workflow. An IHE Integration Profile in IHE technical implementation profiles document. 2015 Available from: http://www.ihe.net/uploadedFiles/Documents/ITI/IHE_ITI_TF_Vol1.pdf
• 12 Tu SW, Campbell JR, Glasgow J, Nyman MA, McClure R. The sage guideline model: achievements and overview. J Am Med Informatics Assoc 2007; 14 (Suppl. 05) 589-598.
• 13 Ciccarese P, Caffi E, Quaglini S, Stefanelli M. Architectures and tools for innovative Health Information Systems: the Guide Project. Int J Med Inform 2005; 74 7–8 553-562.
• 14 Mulyar N, Aalst WMP van der, Peleg M. A Pattern-based Analysis of Clinical Computer-Interpretable Guideline Modeling Languages. J Am Med Inform Assoc 2007; p. 781-787.
• 15 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.
• 16 Shalom E, Shahar Y, Parmet Y, Lunenfeld E. A multiple-scenario assessment of the effect of a continuous-care, guideline-based decision support system on clinicians’ compliance to clinical guidelines. Int J Med Inf 2015; 84 (Suppl. 04) 248-262.
• 17 Shahar Y, Young O, Shalom E, Mayaffit A, Hessing RM, Galperin M. DeGeL: A Hybrid, Multiple-Ontology Framework for Specification and Retrieval of Clinical Guidelines. Proc Conference on Artificial Intelligence in Medicine Europe (AIME) 2003 p. 122-131.
• 18 Marcos Carlos, González-Ferrer A, Peleg M, Cave-ro C. Solving the interoperability challenge of a distributed complex patient guidance system: A data integrator based on HL7’s Virtual Medical Record standard. J Am Med Informatics Assoc 2015; 22 (Suppl. 03) 587-599.
• 19 Health Level Seven.. HL7 Version 3 Standard: Clinical Decision Support; Virtual Medical Record (vMR) Logical Model. Release 2. 2014 Available from: http://www.hl7.org/implement/standards/product_brief.cfm?product_id=338
• 20 Group OM. BPMN – Business Process Modeling Notation. 2014 Available from: http://www.omg.org/bpmn/
• 21 OASIS.. BPEL – Business Process Execution language. 2007 Available from: http://docs.oasis-open.org/wsbpel/2.0/wsbpel-v2.0.html
• 22 JBoss Community.. jBPM – Business Process Management (BPM) Suite. 2015 Available from: http://www.jbpm.org
• 23 Activity.. Activiti – a light-weight workflow and Business Process Management (BPM) Platform. 2015 Available from: http://activiti.org
• 24 Mans RS, Aalst WMP van der, Russell NC, Bakker PJM, Moleman AJ. Process-Aware Information System Development for the Healthcare Domain – Consistency, Reliability, and Effectiveness. Business Process Management Workshops, LNBIP 43. Springer; 2009. p. 635-646.
• 25 Becker J, Fischer R, Janiesch C, Becker J. Optimizing US Health Care Processes – A Case Study in Business Process Management. Proc Thirteen Am Conf Inf Syst. 2007 paper 504.
• 26 Dumas M, Ter-Hofstede AHM, Aalst WMP van der. Process aware information systems. New York: John Wiley & Sons; 2005
• 27 Lenz R, Peleg M, Reichert M. Healthcare Process Support: Achievements, Challenges, Current Research. Spec issue Int J Knowledge-Based Organ Process Support Healthc. 2012 2. 03
• 28 XDS – Cross-Enterprise Document Sharing.. An IHE Integration Profile in IHE technical implementation profiles document. 2015 Available from: http://www.ihe.net/uploadedFiles/Documents/ITI/IHE_ITI_TF_Vol1.pdf
• 29 January CT, Wann LS, Alpert JS, Calkins H, Cigar-roa JE, Conti JB. et al. 2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and the Heart Rhythm Society. J Am Coll Cardiol 2014; 64 (Suppl. 21) e1-76.
• 30 JBoss Community.. Drools – a Business Rules Management System (BRMS) solution. 2015 Available from: http://www.drools.org
• 31 Isern D, Sánchez D, Moreno A. HeCaSe2: a multi-agent ontology-driven guideline enactment engine. Multi-Agent Systems and Applications V.. LNCS 4696. 2007 p. 322-324.
• 32 Vermeulen I, Bohte S, Somefun K, Poutré H La. Multi-agent Pareto appointment exchanging in hospital patient scheduling. Serv Oriented Comput Appl 2007; 1 (Suppl. 03) 185-196.
• 33 Wilk S, Michalowski W, O’Sullivan D, Farion K, Sayyad-Shirabad J, Kuziemsky C. et al. A task-based support architecture for developing point-of-care clinical decision support systems for the emergency department. Methods Inf Med 2013; 52 (Suppl. 01) 18-32.