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Healthcare use of workflow engine technology with emphasis on data  analysis and decision support
 

Healthcare use of workflow engine technology with emphasis on data analysis and decision support

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Healthcare use of workflow engine technology with emphasis on data analysis and decision support...

Healthcare use of workflow engine technology with emphasis on data analysis and decision support



1. Describe the abstract notion of a workflow engine and workflow technology in general
2. Understand the relationship of flowcharts (common in medical guidelines) to executable models of processes used by workflow engines
3. Understand current use of workflow engines in healthcare in production environment and in research context (phenotype modeling, data analysis, clinical decision support, process mining and discovery)
Includes description of some of my research projects
4. List the evidence for benefits and challenges of using workflow engines in healthcare

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  • Vojtech Huser, MD, PhD Morgridge: Project proposal     -----Original Message----- From: Harold Lehmann [mailto:lehmann@jhmi.edu] Sent: Tuesday, January 10, 2012 12:02 AM To: Huser, Vojtech (NIH/CC/OD) [E] Subject: Re: title - RE: Hopkins Grand Rounds   Many thanks!   Harold     > From: Vojtech Huser < [email_address] > > Date: Mon, 9 Jan 2012 10:32:42 -0500 > To: Harold Lehmann < [email_address] > > Cc: LaShawn Johnson < [email_address] > > Subject: RE: title - RE: Hopkins Grand Rounds > > Harold, > > Here are the edits: > > > > 1. Describe the abstract notion of a workflow engine and workflow > technology in general 2. Understand the relationship of flowcharts > (common in medical guidelines) to executable models of processes used > by workflow engines 3. Understand current use of workflow engines in > healthcare in production environment and in research context > (phenotype modeling, data analysis, clinical decision support, process > mining and discovery) 4. List the evidence for benefits and challenges > in using workflow engines in healthcare > > > Vojtech > > > > -----Original Message----- > From: Harold Lehmann [mailto:lehmann@jhmi.edu] > Sent: Thursday, January 05, 2012 2:32 PM > To: Huser, Vojtech (NIH/CC/OD) [E] > Cc: LaShawn Johnson-Thomas > Subject: Re: title - RE: Hopkins Grand Rounds > > Fantastic. > > We have to turn "topics" into "learning objectives," so let me > suggest the > following: > > 1. Describe the abstract notion of a workflow engine 2. Articulate > rules for turning workflow knowledge into flowcharts 3. Comparing the > uses of workflow engines in research (phenotype modeling and data > analysis), in clinical care (decision support), and in clinical > management (discovering healthcare processes) 4. List the evidence for > benefits and challenges in using workflow engines > > Please edit! > > Harold > > >> From: Vojtech Huser < [email_address] > >> Date: Thu, 5 Jan 2012 09:53:08 -0500 >> To: Harold Lehmann < [email_address] > >> Cc: LaShawn Johnson < [email_address] > >> Subject: title - RE: Hopkins Grand Rounds >> >> Feb 3 it is, then. >> >> >> >> >> I would propose this title >> >> >> >> Title: >> Healthcare use of workflow engine technology (with emphasis on data >> analysis and decision support) >> >> Topics covered: (abstract outline) >> -What is a workflow engine >> -Modeling knowledge as flowcharts >> -Use in phenotype modeling and data analysis -Use in clinical >> decision support -Mining healthcare data (discovering healthcare >> processes) >> >> >> >> >> V >> >> >> -----Original Message----- >> From: Harold Lehmann [mailto:lehmann@jhmi.edu] >> Sent: Thursday, January 05, 2012 9:35 AM >> To: Huser, Vojtech (NIH/CC/OD) [E] >> Cc: LaShawn Johnson-Thomas >> Subject: Re: Hopkins Grand Rounds >> >> Yes, I meant Feb 3. >> >> Terrific! >> >> So do send me a title if you can this week. We can work out objectives then. >> >> Harold >> >> >> >>> From: Vojtech Huser < [email_address] > >>> Date: Thu, 5 Jan 2012 09:28:32 -0500 >>> To: Harold Lehmann < [email_address] > >>> Cc: LaShawn Johnson < [email_address] > >>> Subject: RE: Hopkins Grand Rounds >>> >>> Harold, >>> >>> Feb 1 is not a Friday and I have one scheduled event. >>> If it were Friday Feb 3th, then yes. >>> >>> Otherwise I would stick to the Feb 24th >>> >>> >>> Vojtech >>> >>> -----Original Message----- >>> From: Harold Lehmann [mailto:lehmann@jhmi.edu] >>> Sent: Thursday, January 05, 2012 1:21 AM >>> To: Huser, Vojtech (NIH/CC/OD) [E] >>> Cc: LaShawn Johnson-Thomas >>> Subject: Re: Hopkins Grand Rounds >>> >>> Vojtech -- >>> >>> Great, I'm pencilling you in for Feb 24. Is there a possibility you >>> could do Feb 1? >>> >>> You will be reimbursed for a receipt or for mileage; your choice! We >>> pay for lunch :) >>> >>> La Shawn Johnson-Thomas, our staff member in charge of these Rounds, >>> will get back to you with logistical and paperwork details, >>> especially those related to CME and to Webcasting/videotaping. >>> >>> Re EHRs---we will have rolling go lives. Community >>> hospitals-->JHH-->JHCP (outpatient clinics) is the order, I think. The first go-live is Apr 2013. >>> The hospital will be two years later, if I'm not mistaken. We will >>> be supporting Eclipsys until the transition is complete. >>> >>> I have no idea about the long term prospect for any of the vendors! >>> >>> Harold >>> >>> >>> >>>> From: Vojtech Huser < [email_address] > >>>> Date: Wed, 4 Jan 2012 09:52:03 -0500 >>>> To: Harold Lehmann < [email_address] > >>>> Cc: LaShawn Johnson < [email_address] > >>>> Subject: RE: Hopkins Grand Rounds >>>> >>>> Harold, >>>> >>>> I would be glad to come! >>>> Feb 24th is slightly better than the March date. >>>> >>>> The workflow work is probably a better topic and this topic can (at >>>> the >>>> end) >>>> include some of the process mining work which is one of the >>>> projects I am doing currently. >>>> >>>> What are some technicalities I should know about being a seminar speaker. >>>> (e.g., receipt strategy when taking a train vs. driving my own car) >>>> >>>> Vojtech >>>> >>>> >>>> >>>> P.S. >>>> The Epic move is interesting. Has the go-live date been scheduled? >>>> >>>> I think you were on Eclipsys as well (like NIH was and is). >>>> We stick to Eclipsys for now. >>>> I wonder what will AllScripts, in the long run, do to the future of >>>> Eclipsys (acquired product for them). >>>> >>>> >>>> -----Original Message----- >>>> From: Harold Lehmann [mailto:lehmann@jhmi.edu] >>>> Sent: Tuesday, January 03, 2012 9:40 PM >>>> To: Huser, Vojtech (NIH/CC/OD) [E] >>>> Cc: LaShawn Johnson-Thomas >>>> Subject: Hopkins Grand Rounds >>>> >>>> Vojtech -- >>>> >>>> I wanted to followup on my verbal invitation for a Grand Rounds >>>> presentation here at Hopkins (see http://dhsi.med.jhmi.edu/node/25 >>>> and the link to prior Rounds). They are presented on Fridays at >>>> 12:15. I would love for you to speak either about the workflow work >>>> you did in the past or the research informatics work you are doing >>>> now. We are taking on Epic and its new research environment and >>>> need very much to learn from others. >>>> >>>> Date wise, Feb 24 or Mar 9 would be ideal; we have dates 4/27, 5/4, >>>> 5/11 >>>> 6/1 >>>> and 6/8 open as well. >>>> >>>> Harold >>>> >>> >> >  
  • Vojtech Huser, MD, PhD Morgridge: Project proposal January 26, 2012   Dear Vojtech,   We are looking forward to your presentation at our February 3, 2012 Informatics Grand Rounds at 12:15 p.m. Please allow an hour for your talk and a brief question period. As I am sure you know, there are a number of important administrative things that we need to do in order to comply with CME's very strict regulations. Please be certain to make a verbal disclosure at the start of your presentation as well as including the Disclosure slide at the start of the talk. I would be most grateful if you could return the information and various forms listed below to me by email on or before February 1, 2012. We are now publicizing your talk around the campus.   1.  Title of Talk, abstract (have already) 2.  Learning Objectives (have already) 3.  Your CV or Bio   4.  Signed Disclosure Form (attached) 5.  Signed Webcast Permission Form (attached) 6.  Copies of your disclosure & objectives slides (see attached, please edit as you wish) 7.  Speaker Information Sheet (attached)   -JHU's CME office requires that a disclosure and objectives slide be part of your presentation. Please visit: http://www.hopkinscme.net/Resources/RSCSupport.aspx , for examples.   If you have any questions or concerns about this Webcasting/archiving, please let us know. Previous recordings are posted at http://dhsi.med.jhmi.edu/content/past_seminars.cfm   For more information regarding requirements visit: http://dhsi.med.jhmi.edu/content/speakers.html   You may send these documents via email.   For driving directions visit: http://dhsi.med.jhmi.edu/content/visitors.html   I know that Harold has already sent you the objectives of the DHSI Seminar Series, but have listed them again below for you to reference while filling out these forms.   OBJECTIVES FOR THE SERIES: 1. Evaluate the ongoing development of the National Health Information Network 2. Identify key components of health information technology in a variety of health care and public health settings 3. Critique the success of health information technology through evaluation studies 4. Assess fit between information architecture in complex health settings and health needs 5. Characterize success of information technologies in technology-poor settings 6. Evaluate decision support in a variety of health-care related settings   Thank you very much for participating in our seminar, and especially for doing the extra paper work required by CME.   Best wishes,     La Shawn L. Johnson-Thomas Administrative Coordinator Division of Health Sciences Informatics 2024 E. Monument Street, Ste 1-200 Baltimore, MD. 21205 443-287-6083 (P) 410-614-2064 (F) [email_address]  
  • 2007 Garnter report Oracle workflow, SAP, Microsoft, Fujitsi Workflow-only companies: Tibco (Staffware), Global 360 He Vojtech Huser, MD, PhD Morgridge: Project proposal
  • Vojtech Huser, MD, PhD Morgridge: Project proposal
  • Vojtech Huser, MD, PhD Morgridge: Project proposal NOTICE: we can also defin a process where only IT tools play a role. (no humans) bad news: now we became a wheel in an big machine (workers) good news: now we won’t have to remember the order and maintain the record of in which order we run what applications. Executable visio. (managers)
  • Vojtech Huser, MD, PhD Morgridge: Project proposal
  • Vojtech Huser, MD, PhD Morgridge: Project proposal system only participants mode retrospective mode real time mode (waiting application for next event) (instead of read next event)
  • Vojtech Huser, MD, PhD Morgridge: Project proposal Global 360 – wf editor (Process Designer)
  • Vojtech Huser, MD, PhD Morgridge: Project proposal
  • Vojtech Huser, MD, PhD Morgridge: Project proposal
  • Processes can be hierarchical – sub flow
  • One in 2010 Another in 2011
  • Vojtech Huser, MD, PhD Morgridge: Project proposal
  • Vojtech Huser, MD, PhD Morgridge: Project proposal e.g., enrolling every woman with endometriosis who was treated with drug X and it did not work There is adverse event using treatment C – additional info must be collected – (triggered by treatment or something else – other ilness (infection))
  • Vojtech Huser, MD, PhD Morgridge: Project proposal
  • Vojtech Huser, MD, PhD Morgridge: Project proposal
  • Vojtech Huser, MD, PhD Morgridge: Project proposal
  • Vojtech Huser, MD, PhD Morgridge: Project proposal 1: define scenario
  • Vojtech Huser, MD, PhD Morgridge: Project proposal 1 query which runs one of whole population vs. algorithm executed (and traced) on each patient
  • Vojtech Huser, MD, PhD Morgridge: Project proposal
  • Vojtech Huser, MD, PhD Morgridge: Project proposal
  • Vojtech Huser, MD, PhD Morgridge: Project proposal
  • Vojtech Huser, MD, PhD Morgridge: Project proposal
  • Vojtech Huser, MD, PhD Morgridge: Project proposal
  • Vojtech Huser, MD, PhD Morgridge: Project proposal
  • Vojtech Huser, MD, PhD Morgridge: Project proposal
  • Vojtech Huser, MD, PhD Morgridge: Project proposal Linear regression (LR) was used to determine whether score difference could be predicted by any of the participant characteristics such as gender, age, SQL experience, or SQL experience source. No LR model could predict the score difference (adjusted R-squared < 0.1) and none of the factors were statistically significant. A two-sample t-test showed no statistical difference in test score differences between the group which started with SQL approach versus the group which started with RG approach. TRANSITION: In a way the quantitative part served as a preparation for the later qualitative questionnaire part Giving the users an active experience with both compared technology – do you want to be facing flowcharts or SQL code There was a suggestion to conduct just the qualitative part, Since there are some design limitations of the task-based quantitative study – which, in fact, do not play such role in the qualitative study. So in a way I consider the qualitative study of higher importance
  • Vojtech Huser, MD, PhD Morgridge: Project proposal Content – qualitative analysis categorization, summarization of the available textual data Transition: The remaining part of the qualitative study contained
  • Vojtech Huser, MD, PhD Morgridge: Project proposal Other studies Hu (1999) telemedicine Chismar (2002), Wilson (2004) e-health internet applications Hooff (2003) knowledge sharing Based on many previous underlying theories - Including the Fishbein’s theory of reasoned action TRANSITION: So in summary the very Hu PJ, et al. Examining the Technology Acceptance Model Using Physician Acceptance of Telemedicine Technology. Journal of Management of Information Systems 1999; 16 (2): 91-112. Chismar WG, Wiley-Patton S. Test of the technology acceptance model for the internet in pediatrics. Proc AMIA Symp 2002. pp 155-9. Wilson EV, Lankton NK. Modeling patients’ acceptance of provider-delivered e-health. J Am Med Inform Assoc 2004; 11 (4): 241-8. Hooff B v d, et al. Knowledge Sharing in Knowledge Communities in Communities and Technologies. M. Huysman (ed.). The Netherlands: Kluwer Academic Publishers; 2003. pp 119-41.

Healthcare use of workflow engine technology with emphasis on data  analysis and decision support Healthcare use of workflow engine technology with emphasis on data analysis and decision support Presentation Transcript

  • Healthcare use of workflow engine technology with emphasis on data analysis and decision support Vojtech Huser MD PhD Laboratory for Informatics Development National Institutes of Health, Clinical Center Bethesda, MD, USA
  • Objectives
    • 1. Describe the abstract notion of a workflow engine and workflow technology in general
    • 2. Understand the relationship of flowcharts (common in medical guidelines) to executable models of processes used by workflow engines
    • 3. Understand current use of workflow engines in healthcare in production environment and in research context (phenotype modeling, data analysis, clinical decision support, process mining and discovery)
        • Includes description of some of my research projects
    • 4. List the evidence for benefits and challenges of using workflow engines in healthcare
    Vojtech Huser, MD, PhD
  • Introduction
    • Workflow technology: focus on my research for the last 8.5 years
    • This talks is a mixture of
      • Workflow technology tutorial
      • Larger context of WT
      • My prior and current work
    Vojtech Huser, MD, PhD HealthcareWorkflow.wordpress.com
  • Workflow Technology (WT) Vojtech Huser, MD, PhD
  • Workflow Technology (WT)
    • Business process management system (BPMS)
    • Workflow = The automation of a business process, in whole or part, during which documents, information or tasks are passed from one participant to another for action, according to a set of procedural rules.
    • Workflow Process = A set of one or more linked procedures or activities which collectively realize a business objective or policy goal, normally within the context of an organizational structure defining functional roles and relationships (definition vs. instance)
    • Worklist Handler = A software component that manages the interaction between the user and the worklist maintained by a workflow engine (task display, completion, acceptance, referral)
    Vojtech Huser, MD, PhD WfMC: Terminology & Glossary, Document Number WFMC-TC-1011, Feb 99 http://www.wfmc.org/index.php?option=com_docman&task=doc_download&gid=93&Itemid=74 HealthcareWorkflow.wordpress.com
  • WT history
    • History
      • 1960 Carl Adam Petri
      • 1999 SDO, standard terminology
      • 2000s
        • 2002: XPDL 1.0, 2008 XPDL 2.1
    • Since 2000s
      • offered by large IT companies (MS, Oracle, SAP, IBM, Fujitsu)
    • Healthcare
      • 2008 Gartner report
    Vojtech Huser, MD, PhD
  • Vojtech Huser, MD, PhD HealthcareWorkflow.wordpress.com
  • Vojtech Huser, MD, PhD
  • Humans & machines working together Vojtech Huser, MD, PhD
  • Executable flowchart Vojtech Huser, MD, PhD
  • Vojtech Huser, MD, PhD HealthcareWorkflow.wordpress.com
  • Minimum components Vojtech Huser, MD, PhD language editor execution engine
  • Vojtech Huser, MD, PhD
  • Vojtech Huser, MD, PhD HealthcareWorkflow.wordpress.com
  • Vojtech Huser, MD, PhD
  • Vojtech Huser, MD, PhD
  • Workflow engine Vojtech Huser, MD, PhD
  • Engine Vojtech Huser, MD, PhD
  • Use of WT
    • Pioneer domains
      • Banking
      • Manufacturing
      • Shipping
      • Government authorities
      • Pharmaceutical
    • Healthcare
      • Gartner 2008 report: <5% use
          • More in the third section
    Vojtech Huser, MD, PhD
  • Flowcharts Vojtech Huser, MD, PhD
  • Flowcharts
    • Present in clinical guidelines
    • Can summarize several pages of text
    • Take-home message
    • Algorithmic nature (step by step)
    • Usually very well defined terms, thresholds and treatment options
    • Used even more often in local guidelines
    Vojtech Huser, MD, PhD
  • Clinical Guidelines Quality Improvement measures Process definition (workflow editor)
  • Examples of WT use in healthcare Vojtech Huser, MD, PhD Bed management Infections control (MRSA) J. Emanuele and L. Koetter, &quot;Workflow Opportunities and Challenges in Healthcare,&quot; in 2007 BPM & Workflow Handbook, 2007. L. Koetter, &quot;MRSA infection control with workflow technology,&quot; Spring AMIA Conference, Orlando, FL, 2007. R. Hess, &quot;The Chester County Hospital: Case Study,&quot; in 2007 Excellence in Practice: Moving the Goalposts., 2007.
  • Stroke guideline (WfMS) Vojtech Huser, MD, PhD
  • Soarian Vojtech Huser, MD, PhD
  • Vojtech Huser, MD, PhD
  • Current Soarian Example Vojtech Huser, MD, PhD Main Line Health (Harm Sherpbier) Soarian: Workflow engine (Tibco), MLM (Arden Syntax)
  • Rheumatology decision support Vojtech Huser, MD, PhD HealthcareWorkflow.wordpress.com
  • My research in workflow technology
  • Vojtech Huser, MD, PhD 1. 2. HealthcareWorkflow.wordpress.com
  • Vojtech Huser, MD, PhD
  • Vojtech Huser, MD, PhD
  • Vojtech Huser, MD, PhD Medinfo 2007
  • Implemented processes
    • RetroGuide (v2) (2004-2008) (published)
      • Quality improvement
        • Osteoporosis
        • Cholesterol management
        • Blood pressure control in diabetics
      • Decision support
        • Computerized glucose management protocol
        • Adverse Drug Events (naloxon, sleep apnea)
      • Research
        • Hodgkin's lymphoma and pregnancy
        • Hepatitis C
    • + several other experimental
    • RetroGuide (v3)
      • 20+ scenarios
        • US Prev. Services TF
        • Health plan rules
        • hsCRP
        • Genetic counseling
        • Thyroid disease, ACEi monitoring
        • Osteoporosis
    • FlowGuide
        • Surgical patient discharge (feasibility)
        • Cholesterol management
        • Rheumatoid arthritis
    Vojtech Huser, MD, PhD HealthcareWorkflow.wordpress.com Huser (2010) J Biomed Inform
  • Problems which HealthFlow tries to address?
    • EHR systems need user-friendly customization
    • Representation must be able to represent complex logic and understandable
    • Execution must be integrated into an routine-care EHR system (standalone engine vs. integrated)
    • Same representation/execution must be deployed at multiple institutions
    • Switchable representation (retrospective experiment, prospective observation)
    • Re-uses existing cross-industry technology
    Vojtech Huser, MD, PhD HealthcareWorkflow.wordpress.com
  • HealthFlow System Vojtech Huser, MD, PhD code.google.com/p/HealthFlow
  • HealthFlow: RetroGuide, FlowGuide Vojtech Huser, MD, PhD code.google.com/p/HealthFlow
  • HealthFlow: RetroGuide + FlowGuide Vojtech Huser, MD, PhD HealthcareWorkflow.wordpress.com
  • HealthFlow : key concepts
    • Flowchart layer + code layer (applications)
    • Set of HF external applications (EAs)
    • Single patient execution model (DSS)
    • Works with time ordered chart
    • Resembles manual chart review
    • Concept of current position in EHR
    • Use of variables
    • No AI component
      • No autonomous DM algorithm, advanced ML methods
      • Simple execution of human-specified steps (prior knowledge), no machine input
        • Data querying, answering questions, data exploration
    Vojtech Huser, MD, PhD
  • Vojtech Huser, MD, PhD self service tools (i2b2)
  • HealthFlow: RetroGuide, FlowGuide Vojtech Huser, MD, PhD HealthcareWorkflow.wordpress.com
  • Vojtech Huser, MD, PhD HealthcareWorkflow.wordpress.com
  • Vojtech Huser, MD, PhD HealthcareWorkflow.wordpress.com
  • Code Layer (node; right click properties) Vojtech Huser, MD, PhD HealthcareWorkflow.wordpress.com
  • HealthFlow: RetroGuide, FlowGuide Vojtech Huser, MD, PhD HealthcareWorkflow.wordpress.com
  • Together Workflow Engine (Community edition) Vojtech Huser, MD, PhD HealthcareWorkflow.wordpress.com
  • HealthFlow: RetroGuide, FlowGuide Vojtech Huser, MD, PhD HealthcareWorkflow.wordpress.com
  • Example of retrospective execution Vojtech Huser, MD, PhD 0.9% of patients with high risk patients with subsequent MI
  • Example of execution Vojtech Huser, MD, PhD
  • Process mining
    • Arrive at process definition by examining retrospective data
    • Compare processes from different settings
    • Even younger field then workflow technology
    • Examples
      • Prior work on Chronic Kidney Disease
      • Current work on Clinical Research Protocols
    • www.processmining.org
  • Chronic kidney disease (mining)
  •  
  •  
  • Benefits and challenges of using workflow engines in healthcare Vojtech Huser, MD, PhD
  • Decision support (wish list)
    • Understandable format
        • Graphical - task network paradigm – SAGE,GLIF, ProForma
            • Textual (Arden Syntax), GELLO
    • Several implementations (compare to databases, BI, prog. IDE)
        • Choice of editor
        • Choice of execution engine
    • Handles well logic and context
      • Logic
          • >66yo, history of fracture -> recommend bone mineral density scan
      • Context
          • Display when and to whom,
          • Resource modeling (nurse role, current nurse, hospitalist; in-house machine vs. referral)
          • Modeling the opportunities for decision support (SAGE)
    • Explanation function
        • Authoring, Reviewing
          • Not-developed-here syndrome, owner of logic vs. happy user vs. victim
    • Knowledge exchange (business model)
  • Benefits of WT
    • Ability to customize processes within an EHR
    • Graphical representation
        • author from scratch, modify slightly the logic, modify to fit local context
      • Programmer vs. analyst (hard coded processes)
      • Understandability (clinician, explanation function) (flowcharts)
    • Auditing / change management
      • EHR with APIs/links (add task, track tasks, see roles, provide event triggers)
      • Observation mode/ Intervention mode
    • Ability to share workflows
      • Sharing on a graphical level only (no “code”)
    • Cross industry technology
  • Challenges of WT
    • Process administration
        • Owner of a process
            • Medical home, infections control nurse, consumer (PHR)
        • Physician autonomy
            • Cook book medicine
    • Workflow technology enabled EHR systems
          • Add-on integration (TheraDoc, iList)
          • Direct integration (Siemens Soarian, % of hardcoded steps)
    • Graphical modeling
          • Several standards (BPMN, YAWL)
          • Workflow patterns
          • Handling exceptions (model in a flowchart), swim-lanes (roles)
          • Very complex processes (code + HTML docs, just flowchart, simplified flowchart)
  • Conclusion
    • 4 objectives
      • Workflow engine, flowcharts (guidelines), current use in healthcare, benefits and challenges
    • WT is an emerging technology
        • Compared with databases, started in 1999
        • Not everyone means executable process definitions (within a workflow engine) when they say “workflow”
    • Cross industry standard to watch/use
        • vs. healthcare specific guidelines engines
    • Thank you for attention.
        • [email_address]
        • http://healthcareworkflow.wordpress.com
  •  
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  • Extra slides
  • Vojtech Huser, MD, PhD
  •  
  • Evaluation
    • 18 users, 2 parts, qualitative
    • 9 task questions (T1-T9)
          • T5: Find all patients who had at least 2 creatinine lab results flagged too high (but they must be at least 180 days apart).
    • 5 choice questions (C1-C5)
          • Solved problem 1 -> extended problem 2 + choices A), B), C)
    • Results
      • Statistically significant difference in scores (paired t-test, 2-sided)
        • RG: 11.1 ± 1.8 vs. SQL: 6.3 ± 2.1 (p<<0.0001)
    Vojtech Huser, MD, PhD
  • Evaluation (SQL and RG)
    • Which technology do you prefer (SQL or RG)?
          • 94% of participants preferred RG
      • and why do you prefer it?
          • 1. easy to learn/use/understand
          • 2. temporal modeling capabilities
          • 3. more intuitive/natural/logical
    • Disadvantages of SQL?
          • 1. must know exact syntax/be expert
          • 2. difficult to use
          • 3. insufficient support for temporal criteria
    • Disadvantages of RG?
          • 1. need to know function of various apps and new terminology
          • 2. none
          • 3. hard to understand what data user gets back
          • 4. can be slow for queries involving a larger population
    Vojtech Huser, MD, PhD Hancock (2004), Lacey (2004)
  • Evaluation
    • General important features: (general question)
      • Highest ranking features
        • Intuitive modeling paradigm
        • Short training time
    • Technology acceptance: (RG only)
      • Unified Theory of Acceptance and Use of Technology (UTAUT)
      • Performance expectancy, Effort Expectancy, Behavioral intention
      • Favorable scores predicting high actual use
    • CDS architecture evaluation (Wright, 2009)
    Vojtech Huser, MD, PhD Venkatesh (2003), Hulse (2006), Hu (1999), Chismar (2002), Wilson (2004), Hoof (2003)