Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress 2023 EHA Congress 2023 ASCO Annual Meeting
Clinical Collections
Advances in Alzheimer’s

At a glance: The ONWARDS insulin icodec trials

A round-up of the ONWARDS phase 3 clinical trials evaluating the novel weekly insulin icodec in people with diabetes.
ADVANCED SEARCH
Log in
Top
BMC Medical Research Methodology
Published in: BMC Medical Research Methodology 1/2011

Open Access 01-12-2011 | Software

Implementation of workflow engine technology to deliver basic clinical decision support functionality

Authors: Vojtech Huser, Luke V Rasmussen, Ryan Oberg, Justin B Starren

Published in: BMC Medical Research Methodology | Issue 1/2011

Login to get access

Abstract

Background

Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic.

Results

We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture.

Conclusions

We describe an implementation of a free workflow technology software suite (available at http://​code.​google.​com/​p/​healthflow) and its application in the domain of clinical decision support. Our implementation seamlessly supports clinical logic testing on retrospective data and offers a user-friendly knowledge representation paradigm. With the presented software implementation, we demonstrate that workflow engine technology can provide a decision support platform which evaluates well against an established clinical decision support architecture evaluation framework. Due to cross-industry usage of workflow engine technology, we can expect significant future functionality enhancements that will further improve the technology's capacity to serve as a clinical decision support platform.
Appendix
Available only for authorised users
Literature
1.
De Clercq P, Kaiser K, Hasman A: Computer-Interpretable Guideline formalisms. Stud Health Technol Inform. 2008, 139: 22-43.PubMed
2.
Greenes RA: Clinical decision support: the road ahead. 2007, Amsterdam; Boston; London: Elsevier Academic Press
3.
Boxwala AA, Peleg M, Tu S, Ogunyemi O, Zeng QT, Wang D, Patel VL, Greenes RA, Shortliffe EH: GLIF3: a representation format for sharable computer-interpretable clinical practice guidelines. J Biomed Inform. 2004, 37 (3): 147-161. 10.1016/j.jbi.2004.04.002.CrossRefPubMed
4.
van der Aalst WMP, van Hee K: Workflow management: models, methods, and systems. 2002, Cambridge, Mass: MIT Press
5.
Embi PJ, Jain A, Clark J, Harris CM: Development of an electronic health record-based Clinical Trial Alert system to enhance recruitment at the point of care. AMIA Annu Symp Proc. 2005, 231-235.
6.
Huser V, Narus SP, Rocha RA: Evaluation of a flowchart-based EHR query system: a case study of RetroGuide. J Biomed Inform. 2010, 43 (1): 41-50. 10.1016/j.jbi.2009.06.001.CrossRefPubMed
7.
Huser V, Rocha RA, James B: Use of Workflow Technology Tools to Analyze Medical Data. 19th IEEE CBMS Symposium Proceedings; Salt Lake City. 2006, 455-460.
8.
Emanuele J, Koetter L: Workflow Opportunities and Challenges in Healthcare. 2007 BPM & Workflow Handbook. Edited by: Fischer L. 2007, Lighthouse Point, Florida: Future Strategies Inc, 1
9.
Quaglini S, Stefanelli M, Lanzola G, Caporusso V, Panzarasa S: Flexible guideline-based patient careflow systems. Artificial Intelligence in Medicine. 2001, 22 (1): 65-80. 10.1016/S0933-3657(00)00100-7.CrossRefPubMed
10.
Peleg M: Chapter 13: Guidelines and Workflow Models. Clinical Decision Support: The Road Ahead. Edited by: Greenes RA. 2007, London; Oxford; Boston; New York; San Diego: Academic Press, 581-1
11.
Mulyar N, Pesic M, Aalst WMPvd, Peleg M: Declarative and Procedural Approaches for Modelling Clinical Guidelines:Addressing Flexibility Issues. Proceedings of ProHealth Workshop. 2007, Brisbane, Australia
12.
Mulyar N, van der Aalst WM, Peleg M: A pattern-based analysis of clinical computer-interpretable guideline modeling languages. J Am Med Inform Assoc. 2007, 14 (6): 781-787. 10.1197/jamia.M2389.CrossRefPubMedPubMedCentral
13.
Aalst WMPvd AHM, ter Hofstede BK, Barros AP: Workflow Patterns. Distributed and Parallel Databases. 2003, 14 (3): 5-51.CrossRef
14.
Haux R, Seggewies C, Baldauf-Sobez W, Kullmann P, Reichert H, Luedecke L, Seibold H: Soarian - workflow management applied for health care. Methods Inf Med. 2003, 42 (1): 25-36.PubMed
15.
Wright A, Sittig DF: A framework and model for evaluating clinical decision support architectures. J Biomed Inform. 2008, 41 (6): 982-990. 10.1016/j.jbi.2008.03.009.CrossRefPubMedPubMedCentral
16.
17.
18.
19.
Ko RKL: A computer scientist's introductory guide to business process management (BPM). Crossroads. 2009, 15 (4): 11-18. 10.1145/1558897.1558901.CrossRef
20.
Seebregts CJ, Mamlin BW, Biondich PG, Fraser HS, Wolfe BA, Jazayeri D, Allen C, Miranda J, Baker E, Musinguzi N, et al: The OpenMRS Implementers Network. Int J Med Inform. 2009, 78 (11): 711-720. 10.1016/j.ijmedinf.2008.09.005.CrossRefPubMed
21.
22.
Huff SM, Rocha RA, Bray BE, Warner HR, Haug PJ: An event model of medical information representation. J Am Med Inform Assoc. 1995, 2 (2): 116-134. 10.1136/jamia.1995.95261905.CrossRefPubMedPubMedCentral
23.
Murphy SN, Weber G, Mendis M, Gainer V, Chueh HC, Churchill S, Kohane I: Serving the enterprise and beyond with informatics for integrating biology and the bedside (i2b2). J Am Med Inform Assoc. 2010, 17 (2): 124-130. 10.1136/jamia.2009.000893.CrossRefPubMedPubMedCentral
24.
Deshmukh VG, Meystre SM, Mitchell JA: Evaluating the informatics for integrating biology and the bedside system for clinical research. BMC Med Res Methodol. 2009, 9: 70-10.1186/1471-2288-9-70.CrossRefPubMedPubMedCentral
25.
Kim S, Haug PJ, Rocha RA, Choi I: Modeling the Arden Syntax for medical decisions in XML. Int J Med Inform. 2008, 77 (10): 650-656. 10.1016/j.ijmedinf.2008.01.001.CrossRefPubMed
26.
Tu SW, Musen MA: The EON model of intervention protocols and guidelines. Proc AMIA Annu Fall Symp. 1996, 587-591.
27.
Fox J, Patkar V, Thomson R: Decision support for health care: the PROforma evidence base. Inform Prim Care. 2006, 14 (1): 49-54.PubMed
28.
Pryor TA, Hripcsak G: Sharing MLM's: an experiment between Columbia-Presbyterian and LDS Hospital. Proc Annu Symp Comput Appl Med Care. 1993, 399-403.
29.
Huser V, Starren JB: EHR Data Pre-processing Facilitating Process Mining: an Application to Chronic Kidney Disease. AMIA Annu Symp Proc. 2009
30.
Huser V, Rocha RA, Huser M: Conducting Time Series Analyses on Large Data Sets: a Case Study With Lymphoma. Medinfo. 2007
31.
Huser V: Running Decision Support Logic Retrospectively to Determine Guideline Adherence: a Case Study With Diabetes. Spring AMIA2007 symposium. 2007
32.
Huser V, Rocha RA: Retrospective Analysis of the Electronic Health Record of Patients Enrolled in a Computerized Glucose Management Protocol. CBMS 2007. 2007
33.
Huser V, Rocha RA: Analyzing medical data from multi-hospital healthcare information system using graphical flowchart models. Biomedical Informatics and Cybernetics Symposium; Orlando. 2007
34.
Huser V, Rocha RA: Graphical Modeling of HEDIS Quality Measures and Prototyping of Related Decision Support Rules to Accelerate Improvement. Proc AMIA Annu Fall Symp. 2007
35.
Wright A, Goldberg H, Hongsermeier T, Middleton B: A description and functional taxonomy of rule-based decision support content at a large integrated delivery network. J Am Med Inform Assoc. 2007, 14 (4): 489-496. 10.1197/jamia.M2364.CrossRefPubMedPubMedCentral
36.
Wright A, Sittig DF, Ash JS, Sharma S, Pang JE, Middleton B: Clinical decision support capabilities of commercially-available clinical information systems. J Am Med Inform Assoc. 2009, 16 (5): 637-644. 10.1197/jamia.M3111.CrossRefPubMedPubMedCentral
37.
Huser V: Analyzing biomedical datasets using executable graphical models: RetroGuide system. 2009, VDM Verlag
38.
Venkatesh V, Morris MG, Davis GB, Davis FD: User acceptance of information technology: Toward a unified view. MIS Quarterly. 2003, 27 (3): 425-478.
39.
Tu S: SAGE:Guideline Modeling: Motivation and Methodology. Proceedings of CPG 2004 Prague. 2004
40.
Kawamoto K, Lobach DF: Design, implementation, use, and preliminary evaluation of SEBASTIAN, a standards-based Web service for clinical decision support. AMIA Annu Symp Proc. 2005, 380-384.
41.
Wright A, Sittig DF: SANDS: a service-oriented architecture for clinical decision support in a National Health Information Network. J Biomed Inform. 2008, 41 (6): 962-981. 10.1016/j.jbi.2008.03.001.CrossRefPubMedPubMedCentral
42.
Hess R: The Chester County Hospital: Case Study. 2007 BPM and Workflow Handbook. Edited by: Fischer L. 2007, Lighthouse Point, Florida: Future Strategies Inc, 1
43.
Fox J, Johns N, Lyons C, Rahmanzadeh A, Thomson R, Wilson P: PROforma: a general technology for clinical decision support systems. Comput Methods Programs Biomed. 1997, 54 (1-2): 59-67. 10.1016/S0169-2607(97)00034-5.CrossRefPubMed
44.
Huser V, Rasmussen L, Starren JB: Representing clinical processes in XML process definition language (XPDL). AMIA Spring Symposium. 2009, Orlando, Florida
45.
Murphy SN, Mendis M, Hackett K, Kuttan R, Pan W, Phillips LC, Gainer V, Berkowicz D, Glaser JP, Kohane I, Chueh HC: Architecture of the open-source clinical research chart from Informatics for Integrating Biology and the Bedside. AMIA Annu Symp Proc. 2007, 548-552.
46.
47.
48.
Peleg M, Tu SW: Design patterns for clinical guidelines. Artif Intell Med. 2009, 47 (1): 1-24. 10.1016/j.artmed.2009.05.004.CrossRefPubMed
49.
de Clercq PA, Blom JA, Korsten HH, Hasman A: Approaches for creating computer-interpretable guidelines that facilitate decision support. Artif Intell Med. 2004, 31 (1): 1-27. 10.1016/j.artmed.2004.02.003.CrossRefPubMed
50.
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. 10.1016/S0933-3657(98)00015-3.CrossRefPubMed
51.
Johnson PD, Tu S, Booth N, Sugden B, Purves IN: Using scenarios in chronic disease management guidelines for primary care. Proc AMIA Symp. 2000, 389-393.
52.
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. 10.1016/j.ijmedinf.2005.02.001.CrossRefPubMed
53.
Fox J, Johns N, Rahmanzadeh A: Disseminating medical knowledge: the PROforma approach. Artif Intell Med. 1998, 14 (1-2): 157-181. 10.1016/S0933-3657(98)00021-9.CrossRefPubMed
54.
Terenziani P, Montani S, Bottrighi A, Torchio M, Molino G, Correndo G: The GLARE approach to clinical guidelines: main features. Stud Health Technol Inform. 2004, 101: 162-166.PubMed
55.
Quaglini S, Stefanelli M, Lanzola G, Caporusso V, Panzarasa S: Flexible guideline-based patient careflow systems. Artif Intell Med. 2001, 22 (1): 65-80. 10.1016/S0933-3657(00)00100-7.CrossRefPubMed
56.
Sutton DR, Fox J: The syntax and semantics of the PROforma guideline modeling language. J Am Med Inform Assoc. 2003, 10 (5): 433-443. 10.1197/jamia.M1264.CrossRefPubMedPubMedCentral
57.
Metadata
Title
Implementation of workflow engine technology to deliver basic clinical decision support functionality
Authors
Vojtech Huser
Luke V Rasmussen
Ryan Oberg
Justin B Starren
Publication date
01-12-2011
Publisher
BioMed Central
Published in
BMC Medical Research Methodology / Issue 1/2011
Electronic ISSN: 1471-2288
DOI
https://doi.org/10.1186/1471-2288-11-43

Other articles of this Issue 1/2011

BMC Medical Research Methodology 1/2011 Go to the issue

Research article

Alternative statistical methods for estimating efficacy of interferon beta-1b for multiple sclerosis clinical trials

Research article

Validation of the Comprehensive Feeding Practices Questionnaire with parents of 10-to-12-year-olds

Research article

Population versus hospital controls for case-control studies on cancers in Chinese hospitals

Research article

Multiple dimensions of health locus of control in a representative population sample: ordinal factor analysis and cross-validation of an existing three and a new four factor model

Research article

Estimating uncertainty of alcohol-attributable fractions for infectious and chronic diseases

Research article

Effort, reward and self-reported mental health: a simulation study on negative affectivity bias