initial prototype for clinical data normalization and high throughput phenotyping l.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
Initial Prototype for Clinical Data Normalization and High Throughput Phenotyping PowerPoint Presentation
Download Presentation
Initial Prototype for Clinical Data Normalization and High Throughput Phenotyping

Loading in 2 Seconds...

play fullscreen
1 / 14

Initial Prototype for Clinical Data Normalization and High Throughput Phenotyping - PowerPoint PPT Presentation


  • 173 Views
  • Uploaded on

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:

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Initial Prototype for Clinical Data Normalization and High Throughput Phenotyping' - roxy


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
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
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
high level architecture diagram
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

mirth connect
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
high level flow mayo
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

medication to cem mayo data
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

ihc medication mayo ihc lab to cem
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

phenotyping drools
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)

completed work
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
completed work cont
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

completed work cont12
Completed Work (Cont.)
  • Mirth Enhancements
    • Implemented NwHIN XDR connector capability
    • Implemented UIMA connector capability
    • Created NwHIN Aurion XDR adapter
  • Channels Created
dual security certificate exchange
Dual Security Certificate Exchange

Intermountain Healthcare

Mirth

Aurion Gateway

IHC Proxy

Internet

SHARP/Mayo Cloud

SHARP Proxy

SHARP Aurion Gateway

Mirth

thank you
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