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Initial Prototype for Clinical Data Normalization and High Throughput Phenotyping

Initial Prototype for Clinical Data Normalization and High Throughput Phenotyping. SHARPn F2F June 30,2011. Purpose. Demonstrate a proof of concept solution, based on new tools, technology, models and methods. The prototype demonstrates:

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Initial Prototype for Clinical Data Normalization and High Throughput Phenotyping

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  1. Initial Prototype for Clinical Data Normalization and High Throughput Phenotyping SHARPn F2F June 30,2011

  2. Purpose • Demonstrate a proof of concept solution, based on new tools, technology, models and methods. • The prototype demonstrates: • The ability to push unsolicited data using NwHIN exchange protocols • Conversion and normalization of HL7 2.x lab messages to XML clinical element model (CEM) instances • Conversion and normalization of HL7 2.x medication orders to CEMs. • Extraction of medication CEM instances from narrative clinical documents using NLP processing • Persistence of CEM instances in a light weight SQL database • Phenotype processing across the CEM database utilizing the Drools rules engine

  3. High Level Architecture Diagram Mayo EDT System 6a 5 1 7 IHC IHC SHARP Mirth Mirth UIMA (Backend CDR NwHIN NwHIN Connect Connect Pipeline 2 4 Systems) 6 Aurion Aurion 8 Gateway Gateway 3 9 10 SHARP Processing Sequence CEM Instance 1. Use Data from IHC (De-Identified) HL7 2.x messages 2. Send data into Mirth Connect on the IHC side 3. Create NwHIN Document Submission (XDR) message using HL7 2.x message as payload 4. Send Document Submission (XDR) message from Mirth to IHC NwHINAurion Gateway 5. Send XDR message from IHC Aurion Gateway to SHARP NwHINAurion Gateway 6. Send XDR message from SHARP NwHINAurion to Mirth Connect 6a. Send Mayo HL7 2.x Lab Messages & Clinical Documents to Mirth Connect 7. Process HL7 2.x messages and/or clinical documents in the UIMA Pipelines, to normalize and transform into Clinical Element Model (CEM) instances 8. Send the resulting XML instance of Clinical Element Model (CEM) to Mirth Connect 9. Persist Clinical Element Model (CEM) instances to MySql database. 10. Perform phenotype processing on the CEM instance database. Database

  4. Mirth Connect • Enables information flow and transformation • Mirth channel receives message from some source, transforms it, and routes it to one or more destinations • Product is open source • NwHIN with Aurion/CONNECT can be source or destination of a channel • Used to store CEM Instances to the database • Can be used to route data to other locations or databases

  5. High level flow - Mayo CDA for Meds SharpDb cTAKES cTAKES cTAKES cTAKES (NLP) Mayo EDT CEM Mirth Custom UIMA pipeline HL7 for labs Custom UIMA pipeline Configurable UIMA pipeline CEM Mayo EDT AdminDiagnosis processor Tabular data CEM

  6. Medication to CEM - Mayo data cTAKESUIMA Annotators (NLP) SharpDb CDA-Initializer POS Tagger Chunker CDA Mirth Sentence Annotator Context Dependent Tokenizer Dictionary Lookup Annotator Tokenizer Annotator LVG Drug CEM CAS Consumer Drug Mention Annotator Patient count – 10000CDA document count - 360452CEM count for medication – 3442000

  7. IHC-Medication, Mayo, IHC LAB to CEM IHC RXNORM resource New UIMA Process Nodes SharpDb HL7 Initializer Drug CEM CAS Consumer IHC-GCN TO-RXNORM Annotator HL7 Meds HL7 Initializer LAB CEM CAS Consumer Generic-LAB- Annotator Mirth HL7 Labs Mayo LOINC resource IHC LOINC resource

  8. SharpDB a CEM Instance Database

  9. Phenotyping (Drools) Clinical Element Database Data Access Layer Business Logic Transformation Layer Inference/ workflow Engine (Drools) List of Diabetic Patients Service for Creating Output (File, Database, etc) Transform physical representation  Normalized logical representation (Fact Model)

  10. Completed Work • Installation of informatics “SHARP” Cloud system at Mayo • Installation and configuration of tools on IHC side and SHARP Cloud • “Tracer Message” processing • Used to test communication throughout system • Successful transfer using NwHIN/Aurion of test message between IHC & Mayo • 30 de-id IHC patients through pipeline/Drools end-to-end • 134 Thousand CEMS generated • Extraction and message generation for 10,000 patients • Processing of 10,000 patients Meds, Labs, Billing data • 15 Million CEMS generated • Conversion to selected CEM models via UIMA framework • Persisted from CEM to MySQL

  11. Completed Work (Cont.) • Produced New XML Schemas for CEM Models • Standard lab panel • Ambulatory medication order • Administrative diagnosis Excerpt of Lab CEM instance These three models were used for the prototype experiment. CEM Search Tool: http://intermountainhealthcare.org/cem

  12. Completed Work (Cont.) • Mirth Enhancements • Implemented NwHIN XDR connector capability • Implemented UIMA connector capability • Created NwHIN Aurion XDR adapter • Channels Created

  13. Dual Security Certificate Exchange Intermountain Healthcare Mirth Aurion Gateway IHC Proxy Internet SHARP/Mayo Cloud SHARP Proxy SHARP Aurion Gateway Mirth

  14. Thank You! Calvin Beebe Christopher Chute Craig ParkerCui TaoCyndalynn Tilley David MeadDingcheng LiDonna IhrkeGerald BortisGuerganaSavova • James MasanzJeff Ferraro • John HolmanJon TeichrowKevin Bruce • Kyle Marchant • Les WestbergMargarita Sordo • Mat BockolMichael Turk Mitch DempseyNathan Davis Pei ChenSean MurphySridhar DwarkanathStan Huff Susan WelchTim PetersTom OnikiVinodKaggal

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