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
Vojtech Huser MD PhDLaboratory for Informatics Development
National Institutes of Health, Clinical CenterBethesda, MD, USA
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD2
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
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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, PhDVojtech Huser, MD, PhD3
HealthcareWorkflow.wordpress.com
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Workflow Technology (WT)
Vojtech Huser, MD, PhD 4
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD5
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)
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
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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, PhDVojtech Huser, MD, PhD6
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD7
HealthcareWorkflow.wordpress.com
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD8
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD9
Humans & machines working together
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD10
Executable flowchart
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD11
HealthcareWorkflow.wordpress.com
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD12
Minimum componentslanguage editor
execution engine
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD13
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD14
HealthcareWorkflow.wordpress.com
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD15
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD16
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD17
Workflow engine
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD18
Engine
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD19
Use of WT Pioneer domains
Banking Manufacturing Shipping Government authorities Pharmaceutical
Healthcare Gartner 2008 report: <5% use
More in the third section
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Flowcharts
Vojtech Huser, MD, PhD 20
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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, PhDVojtech Huser, MD, PhD21
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Clinical Guidelines Quality Improvement measures
Process definition (workflow editor)
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD23
Examples of WT use in healthcareBed management
Infections control (MRSA)
J. Emanuele and L. Koetter, "Workflow Opportunities and Challenges in Healthcare," in 2007 BPM & Workflow Handbook, 2007.L. Koetter, "MRSA infection control with workflow technology," Spring AMIA Conference, Orlando, FL, 2007.R. Hess, "The Chester County Hospital: Case Study," in 2007 Excellence in Practice: Moving the Goalposts., 2007.
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD24
Stroke guideline (WfMS)
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD25
Soarian
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD26
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD27
Current Soarian Example
Main Line Health (Harm Sherpbier)Soarian: Workflow engine (Tibco), MLM (Arden Syntax)
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD28
Rheumatology decision support
HealthcareWorkflow.wordpress.com
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My research in workflow technology
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD30
1.
2.
HealthcareWorkflow.wordpress.com
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD31
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD32
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD33
Medinfo 2007
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD34
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
HealthcareWorkflow.wordpress.com
Huser (2010) J Biomed Inform
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD35
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
HealthcareWorkflow.wordpress.com
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD36
HealthFlow System
Actions
Knowledge Base(workflow process
definitions)
Data Inquiry
Workflow Execution
Engine(Shark)
EHR System layer:
Workflow editor(JaWE)
Data Visualization
Additional Components:
Event Data Model
code.google.com/p/HealthFlow
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD37
HealthFlow: RetroGuide, FlowGuide
EHR systemEvent
Listener
Notifications
Actions
Knowledge Base(workflow process
definitions)
Data Inquiry
Workflow Execution
Engine(Shark)
EHR System layer:
Prospective mode (FlowGuide):
Retrospective mode(RetroGuide):
Reports
Data Warehouse
Workflow editor(JaWE)
Data Visualization
Additional Components:
Event Data Model
Additional External Services(Terminology services, NLP services,
Statistical Analysis)
code.google.com/p/HealthFlow
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD38
HealthFlow: RetroGuide + FlowGuide
HealthcareWorkflow.wordpress.com
EHR systemEvent
Listener
Notifications
Actions
Knowledge Base(workflow process
definitions)
Data Inquiry
Workflow Execution
Engine(Shark)
EHR System layer:
Prospective mode (FlowGuide):
Retrospective mode(RetroGuide):
Reports
Data Warehouse
Workflow mining(ProM)
Workflow editor(JaWE)
Data Visualization
Additional Components:
Event Data Model
Ontology Model
Host EHR Passive Interaction Model
Host EHR Active Interaction Model
Additional External Services(Terminology services, NLP services,
Statistical Analysis)
Workflow log analysis
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD39
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
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD40self service tools (i2b2)
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD41
HealthFlow: RetroGuide, FlowGuide
HealthcareWorkflow.wordpress.com
EHR systemEvent
Listener
Notifications
Actions
Knowledge Base(workflow process
definitions)
Data Inquiry
Workflow Execution
Engine(Shark)
EHR System layer:
Prospective mode (FlowGuide):
Retrospective mode(RetroGuide):
Reports
Data Warehouse
Workflow mining(ProM)
Workflow editor(JaWE)
Data Visualization
Additional Components:
Event Data Model
Ontology Model
Host EHR Passive Interaction Model
Host EHR Active Interaction Model
Additional External Services(Terminology services, NLP services,
Statistical Analysis)
Workflow log analysis
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD42
HealthcareWorkflow.wordpress.com
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD43
HealthcareWorkflow.wordpress.com
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD44
Code Layer (node; right click properties)
HealthcareWorkflow.wordpress.com
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD45
HealthFlow: RetroGuide, FlowGuide
HealthcareWorkflow.wordpress.com
EHR systemEvent
Listener
Notifications
Actions
Knowledge Base(workflow process
definitions)
Data Inquiry
Workflow Execution
Engine(Shark)
EHR System layer:
Prospective mode (FlowGuide):
Retrospective mode(RetroGuide):
Reports
Data Warehouse
Workflow mining(ProM)
Workflow editor(JaWE)
Data Visualization
Additional Components:
Event Data Model
Ontology Model
Host EHR Passive Interaction Model
Host EHR Active Interaction Model
Additional External Services(Terminology services, NLP services,
Statistical Analysis)
Workflow log analysis
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD46
Together Workflow Engine (Community edition)
HealthcareWorkflow.wordpress.com
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD47
HealthFlow: RetroGuide, FlowGuide
HealthcareWorkflow.wordpress.com
EHR systemEvent
Listener
Notifications
Actions
Knowledge Base(workflow process
definitions)
Data Inquiry
Workflow Execution
Engine(Shark)
EHR System layer:
Prospective mode (FlowGuide):
Retrospective mode(RetroGuide):
Reports
Data Warehouse
Workflow mining(ProM)
Workflow editor(JaWE)
Data Visualization
Additional Components:
Event Data Model
Ontology Model
Host EHR Passive Interaction Model
Host EHR Active Interaction Model
Additional External Services(Terminology services, NLP services,
Statistical Analysis)
Workflow log analysis
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD48
Example of retrospective execution
0.9% of patients with high
risk patients with
subsequent MI
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD49
Example of execution
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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
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Chronic kidney disease (mining)
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Benefits and challenges of using workflow engines in healthcare
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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)
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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
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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)
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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 protected]
http://healthcareworkflow.wordpress.com
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Extra slides
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD64
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD66
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)
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD67
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
Hancock (2004), Lacey (2004)
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Vojtech Huser, MD, PhDVojtech Huser, MD, PhD68
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)
Venkatesh (2003), Hulse (2006), Hu (1999), Chismar (2002), Wilson (2004), Hoof (2003)