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Semantic Data Capture Initiative

Semantic Data Capture Initiative. Hemant Shah M.D., M.Surg. Sr. Research Informatician Henry Ford Health System hshah2@hfhs.org. What is Semantic Data Capture Initiative (SDCI)?.

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Semantic Data Capture Initiative

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  1. Semantic Data Capture Initiative Hemant Shah M.D., M.Surg. Sr. Research Informatician Henry Ford Health System hshah2@hfhs.org

  2. 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

  3. 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

  4. Goal • Provide Data Capture in CarePlus EMR, which is: • Structured • Standard Based • Semantic • Encourage point-of-care data entry with Decision Support as an incentive for the clinician

  5. 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

  6. Components of SDCI • Research Component • Software Development Component • Knowledge Development Component • Evaluation Component

  7. 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

  8. Development Component • Protean – Guideline Authoring Tool • Proteus Guideline Engine • Greed – Rule Authoring tool • Semantic Annotation Tool • Interactions with CPNG • Metadata Repository • Patient Record

  9. Editable Clinical Process Diabetes Cardiovascular Evaluation General Evaluation

  10. Editable Clinical Process Renal Evaluation Diabetes Cardiovascular Evaluation General Evaluation

  11. Editable Clinical Process Cardiovascular System Expert Internet Diabetes Expert Knowledge Component Repository General Evaluation Diabetes Cardiovascular Evaluation

  12. 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

  13. Proteus Model Contains… • A specification of an architecture for: • KCs • Executable Workflows (Guidelines) built with KCs • Tools and Systems to handle them • A graphical language for Workflows • Human & machine readable • Proteus Graphical Language - PGL

  14. 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)

  15. Knowledge Component Basics Knowledge Component (KC) Value of KC Abstraction Lump Tenderness Vomiting Temperature KC may contain data-fields describing the underlying clinical entity • 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)

  16. Knowledge Component Features Abstraction Lump yes Tenderness severe yes Vomiting 102 F Temperature • KCs can be Nested • To represent composite processes • To reduce complexity • KCs can be linked by Activity-links • To represent processes • To define guidelines Instantiated (executed) KCs become medical record

  17. 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

  18. Inference Tools as Components • Two Types of Inference Tools • Inference tool for Abstraction • Inference tool for Action

  19. Inference Tool for Abstraction • Decides • Abstraction – The value of the KC Abstraction Lump Tenderness Vomiting Temperature

  20. Inference Tool for Action Test A • Decides • If an Action has to be triggered based upon some intelligence Action A Test B Action B Test C

  21. Protean – An Integrated Process Authoring Tool A Demo

  22. Semantic Data Capture Initiative – Architecture Patient Data Semantic Data Elements Template Data Elements Protean GreEd Vocab Server Semantic Annotation Tool Proteus Guideline Engine Guideline Repository Rule Engine SNOMED-CT EHR Adaptor (vMR) View CarePlus NG Patient Data Patient Data

  23. 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

  24. 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

  25. 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

  26. Interaction between CPNG and SDCI Apps – Metadata API • To be used only at author time • Method suggestions • searchDataElements() • getDataElementByValue() • getDataElementsByFormName() • getDataElementsByFormID() • getDataElementsByModuleName() • getDataElementsByModuleID()

  27. 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 SDCI Web App hyperlink with the encrypted authentication info Method call using encrypted authentication info CPNG Web App CPNG Web Service

  28. 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

  29. thank you

  30. The Big Picture Morningside KR Greed (Rules Authoring Tool) Protean (Process Authoring Tool) Henry Ford KR B KC D KC E A C Proteus Engine (Process/Guideline Engine) Rules Engine C1 CPNG (EMR) vMR Metadata Template Patient Data Patient Data

  31. Value of Editability – Effort and Time Reduction A B D C E Deployable Guideline C1 Without Authoring Tool Domain Experts Developers Consensus Building Initial Development Testing Modification

  32. Value of Editability – Effort and Time Reduction A B D C E Deployable Guideline C1 Domain Experts With Authoring Tool Consensus Building Authoring Testing

  33. Value of Editability – Applicability to different Locales Top Level Top - Level Guideline Level A Level A Guideline Level B Level B Guideline Medical Setup/Skills Disease Population

  34. Evaluation

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