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Semantic Data Capture Initiative. Hemant Shah M.D., M.Surg. Sr. Research Informatician Henry Ford Health System [email protected]. What is Semantic Data Capture Initiative (SDCI)?. - PowerPoint PPT Presentation
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Semantic Data Capture Initiative
Hemant Shah M.D., M.Surg.
Sr. Research InformaticianHenry Ford Health System
What is Semantic Data Capture Initiative (SDCI)?
A project to develop decision support capabilities combined with structured data capture for CarePlus NG, and its evaluation
Under a TATRC (DoD) supervised grant All code is available as Open Source (EPL) Period of Performance
From April 2008 to October 2010
The Team Investigators:
R. David Allard, MD (PI) Hemant Shah, MD (Co-PI) Patricia Williams Ganesh Krishnan (Lead Developer)
Support from: CPNG development team Rich Vollmerhausen CSRI Research Staff CSRI Training Staff Gloria Whitten Marie McLenaghan
External Adviser: Prakash Nadkarni MD
Goal
Provide Data Capture in CarePlus EMR, which is:StructuredStandard BasedSemantic
Encourage point-of-care data entry with Decision Support as an incentive for the clinician
Hypothesis
Clinical documentation templates that leverage metadata with controlled medical
vocabularies and interoperate with clinical decision support can be integrated into key
ambulatory care processes in a manner acceptable to clinicians and support staff
Components of SDCI
Research Component Software Development Component Knowledge Development ComponentEvaluation Component
Research Component
Structured Data Entry Literature Review Guideline Systems Comparative Analysis Controlled Medical Vocabulary Analysis
Criteria specification for Vocabularies for CPNG and Decision Support
Examine Vocabularies SNOMED-CT LOINC ICD-9 CPT NCI Thesaurus UMLS Metathesaurus MEDCIN 3.0
Application of Criteria Industry Scan of existing systems
Development ComponentProtean – Guideline Authoring Tool
Proteus Guideline Engine
Greed – Rule Authoring tool
Semantic Annotation Tool
Interactions with CPNGMetadata RepositoryPatient Record
Editable Clinical Process
Editable Clinical Process
Internet
Knowledge Component Repository
Editable Clinical Process
CardiovascularSystemExpert
Diabetes
Expert
Proteus may be used for…
Creating executable clinical guidelines to provide decision-support to clinicians about individual patients
Creating process-oriented EMRs with integrated clinical decision-support
Proteus Model Contains…
A specification of an architecture for:KCsExecutable Workflows (Guidelines) built with KCsTools and Systems to handle them
A graphical language for Workflows Human & machine readable Proteus Graphical Language - PGL
Knowledge Component (KC)
A modular building block for Clinical Processes
Each KC Represents either a Clinical Action, a Clinical Event or a Clinical Process
Contains knowledge about a clinical activity: Actions to be performed Events to look for Data to be collected from the actions and events Interpretation and implications of that data Supplementary information about the activities (e.g.
links to websites)
Knowledge Component Basics
KC Represents: Clinical Process (e.g. diagnosis
of acute abdomen pain)
Clinical Atomic Activity, which may be: Clinical Action (e.g. palpation of
liver)
Clinical Event (e.g. vomiting)
Knowledge Component (KC)
KC may contain data-fields describing the underlying clinical entity
Lump
Tenderness
Vomiting
Temperature
AbstractionAbstraction
Value of KC
Knowledge Component Features
KCs can be NestedTo represent composite processesTo reduce complexity
KCs can be linked by Activity-links To represent processes To define guidelines
LumpTendernessVomitingTemperature
Instantiated (executed) KCs become medical record
Abstraction
yessevereyes
102 F
Inference Tools as Components (SOA)
Only a reference to an Interface
Swappable
Location neutral
Inferencing technology neutral
Technologies•Hard Coded Algorithm•Production Rules •Decision Tables•Decision Theory•Neural Networks •Fuzzy Logic •Any other …
•Patient assisted decisions•Human expert (even user)•Combination of these
Technologies•Hard Coded Algorithm•Production Rules •Decision Tables•Decision Theory•Neural Networks •Fuzzy Logic •Any other …
•Patient assisted decisions•Human expert (even user)•Combination of these
Inference Tools as Components
Two Types of Inference Tools
Inference tool for Abstraction
Inference tool for Action
Inference Tool for Abstraction
Decides Abstraction – The
value of the KC
Lump
Tenderness
Vomiting
Temperature
Abstraction
Inference Tool for Action
Decides If an Action has to be
triggered based upon some intelligence
Test ATest A
Test BTest B
Test CTest C
Action AAction A
Action BAction B
Protean – An Integrated Process Authoring Tool
A Demo
Data
ElementsPatient Data
Vocab Vocab ServerServer
Vocab Vocab ServerServer
Patient Data
Patient DataSemantic Data Elements
Semantic Data Elements
TemplateTemplate
ProteanProteanProteanProtean
CarePlus NGCarePlus NG
ViewViewViewViewEHR Adaptor EHR Adaptor (vMR)(vMR)
EHR Adaptor EHR Adaptor (vMR)(vMR)
Proteus Proteus Guideline Guideline
EngineEngine
Proteus Proteus Guideline Guideline
EngineEngine
GreEd GreEd GreEd GreEd
Rule Rule EngineEngine
Rule Rule EngineEngine
Guideline Guideline RepositoryRepository
Guideline Guideline RepositoryRepository
Semantic Semantic Annotation Annotation
ToolTool
Semantic Semantic Annotation Annotation
ToolTool
Semantic Data Capture Initiative – Architecture
SNOMED-CT
What is Greed? A tool to author and edit rules
Easy to use graphical representation of rules Drag and drop is all you need Internal rule syntax inspired by LISP Ability to create rules in multiple languages, e.g.,
Arden Syntax, Java, RuleML, Jess, JBoss Rules etc. Semantic and Completeness checks on rules Allows testing of rules from within the environment Currently in use by Protean Future Plans:
Use ISO/IEC 11179 data elements for conditions and inferences
Extensibility – New logical or math operations can be added Rule repository related features To be made available as an independent Rules system
Semantic Annotation Tool Allows authoring of standard based data elements that
are linked (annotated) with concepts in SNOMED-CT Connects to CPNG metadata repository and gets ‘raw’
data elements Allows authors to select appropriate concepts for them
and annotate the data elements with them Stores the annotated data elements which are now
called Semantic Data Elements Semantic Data Elements provide interoperability Semantic Data Elements are used by:
Processes authored in the Process authoring environment (Protean)
Proteus engine Greed and the Rules Engine to understand what
Proteus Engine is expecting inferences for
Knowledge Development Processes Selected
Follow-up visit for Hypertension Patients Uncomplicated Upper Respiratory Tract Infection
Selected Processes were analyzed
Improvement Opportunities were identified in the Processes
Proteus Process (knowledge) Authoring
Ongoing Iterative refinement
Deployment of Proteus processes
Interaction between CPNG and SDCI Apps – Metadata API
To be used only at author time
Method suggestions searchDataElements() getDataElementByValue() getDataElementsByFormName() getDataElementsByFormID() getDataElementsByModuleName() getDataElementsByModuleID()
CPNG Web App
SDCI Web App
CPNG Web Service
hyperlink with the encrypted authentication
info
Method call using encrypted
authentication info
Interaction between CPNG and SDCI Apps – Patient Data API
For accessing existing patient data, during run-time Aim is to prevent re-entry of data already available in
CPNG Save data collected during execution of a Proteus
process to be available for future use by CPNG or SDCI App users
Interaction between CPNG and SDCI Apps – Patient Data API
Suggested Methods getAllPatientByDataValues() for the time range getPatientDataValue() for the data element specified by
data element id savePatientData() for the specified patient and given
data element id
thank you
Greed(Rules Authoring Tool)
Protean(Process Authoring Tool)
CPNG (EMR)
MetadataPatient
Data
vMRvMR
Patient Data
TemplateTemplate
Henry Ford KR
KC
Proteus Engine(Process/Guideline Engine)
A B
D
C
E
C1
Rules Engine
Morningside KR
KC
The Big Picture
Deployable Guideline
A B
D
C
E
C1
Value of Editability – Effort and Time Reduction
DevelopersDevelopersDomain ExpertsDomain Experts
Consensus Building Initial Development
Testing
Modification
Without Authoring Tool
Deployable Guideline
A B
D
C
E
C1
Value of Editability – Effort and Time Reduction
Domain ExpertsDomain Experts
Consensus Building
Testing
Authoring
With Authoring Tool
Value of Editability – Applicability to different Locales
DiseaseDisease PopulationPopulation Medical Setup/Skills
Medical Setup/Skills
Level A
Level A Guideline
Level A Guideline
Top Level
Top - Level Guideline
Top - Level Guideline
Level B
Level B Guideline
Level B Guideline
Evaluation