David Blevins 28 July, 2014 Ontologies in Medical Care Data Integration and Reuse Challenges...
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Transcript of David Blevins 28 July, 2014 Ontologies in Medical Care Data Integration and Reuse Challenges...
David Blevins28 July, 2014
Ontologies in Medical CareData Integration and Reuse Challenges
Ontologies in Medical Care: Data Integration and Reuse Challenges
2Ontologies in Medical Care: Data Integration and Reuse Challenges
Quick Introductions
Ontologies in medicine
Practical uses
Uses in big data
3Ontologies in Medical Care: Data Integration and Reuse Challenges
Ontologies in Medical Care
Background– Standards
Implementation– Standards Compliance– Regulatory Compliance– Feasibility– Case studies
Remarks
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Messaging Standards
HL7– HL7 v2.3 and v2.5 required under Meaningful Use (started in 1989)– HL7 v3 (started 1995, uses ISO Reference Information model)
Purpose: electronically transmit medical requests and information between distributed systems
Ontologies in Medical Care: Data Integration and Reuse Challenges
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HL7 Samples Lab result
Procedure result (note)
Lab Result Corrections
Ontologies in Medical Care: Data Integration and Reuse Challenges
© Copyright 2008 by Health Level Seven
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Continuity of Care Documents
Two standards: – Continuity of Care Record (CCR)– Clinical Document Architecture (CDA)
Purpose: Provide a vendor-neutral copy of a structured and well formatted patient health record that can be electronically transmitted and understood by medical record systems
Ontologies in Medical Care: Data Integration and Reuse Challenges
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Sample CDA excerpt
Ontologies in Medical Care: Data Integration and Reuse Challenges
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Sample CCR Spec
Ontologies in Medical Care: Data Integration and Reuse Challenges
Copyright © ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959, United States
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Other Standards
SNOMED
LOINC
CPT
ICD– ICD-9– ICD-10
Purpose: Provide standard vocabularies for documenting patient procedures, diagnoses, lab results, and various other medical details
Ontologies in Medical Care: Data Integration and Reuse Challenges
10Ontologies in Medical Care: Data Integration and Reuse Challenges
Ontologies in Medical Care
Background– Standards
Implementation– Standards Compliance– Regulatory Compliance– Feasibility– Case studies
Remarks
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A Quick Note Before We Proceed
Medical data is ideal for big data analysis: high volume, high variety data with high contextual meaning
Massive challenges in spite of mature standards– Data Silos (no cooperation between vendors)– Failure to comply with standards
Ontologies in Medical Care: Data Integration and Reuse Challenges
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HL7 is a series of tubes, treated like a truck Making the standard perform activities it was never meant to handle
Example: Device interfaces
Ontologies in Medical Care: Data Integration and Reuse Challenges
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Burn your dictionaries Users can enter custom vocabularies, rendering the LOINC/CPT/ICD dictionaries useless
Labs use different service compendiums
Ontologies in Medical Care: Data Integration and Reuse Challenges
14Ontologies in Medical Care: Data Integration and Reuse Challenges
Standards and “Standards”
HL7 variety
Testing Variety
Inconsistent implementation
15Ontologies in Medical Care: Data Integration and Reuse Challenges
Ontologies in Medical Care
Background– Standards
Implementation– Standards Compliance– Regulatory Compliance– Feasibility– Case studies
Remarks
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Meaningful Use
MU 1– 13 required core objectives– Selection of 5 objectives from a list of 9 optional objectives– Clinical Quality Measures
MU 2– 17 required core objectives– Selection of 3 objectives from a list of 6 optional objectives– Comprehensive CCD
MU 3– Ongoing development. Planned finalization in 2016
Ontologies in Medical Care: Data Integration and Reuse Challenges
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Meaningful Use certification
Certified third parties– Non-governmental (Industry) groups permitted to certify compliance– The private sector handles certification of functionality
What happens when something breaks?– What about compliance-critical components, like clinical quality measures?
Ontologies in Medical Care: Data Integration and Reuse Challenges
18Ontologies in Medical Care: Data Integration and Reuse Challenges
Ontologies in Medical Care
Background– Standards
Implementation– Standards Compliance– Regulatory Compliance– Feasibility– Case studies
Remarks
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Feasibility
Acquisitions– Are the new owners maintaining documentation?– Are the new owners concerned about quality, or merely being compliant?
Resources (monetary, human)– Is there enough money to implement changes?– Are there enough competent staff to implement changes?
Outsourcing (Stakeholder engagement, quality, support)– Does the contractor care about quality?– Is the contractor competent?– Does the contractor support their work? If they do, in what ways?
Ontologies in Medical Care: Data Integration and Reuse Challenges
20Ontologies in Medical Care: Data Integration and Reuse Challenges
Ontologies in Medical Care
Background– Standards
Implementation– Standards Compliance– Regulatory Compliance– Feasibility– Case studies
Remarks
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Immunization Registries
Background– Timeline: 1 year– Impetus: regulatory compliance– Result: “Probably ongoing”– Problem: Vendor support
Ontologies in Medical Care: Data Integration and Reuse Challenges
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Practice Management Systems Background
– Products: may be vendor supplied, or third party. May or may not be intended to work with a specific system
– Messages: ADTs (Admit Discharge Transfer) and DFTs (Detailed Financial Transactions)
Ontologies in Medical Care: Data Integration and Reuse Challenges
Medscape EHR Report 2014Copyright Medscape 2014
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Data Migrations
Background– Legislation: right to your data– Vendor approach: have your data (be careful what you wish for)
Ontologies in Medical Care: Data Integration and Reuse Challenges
Medscape EHR Report 2014Copyright Medscape 2014
24Ontologies in Medical Care: Data Integration and Reuse Challenges
Ontologies in Medical Care
Background– Standards
Implementation– Standards Compliance– Regulatory Compliance– Feasibility– Case studies
Remarks