nlp as a data integration tool for your cio james m. maisel, md chairman, zydoc [email protected]
TRANSCRIPT
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Overview
• Business Needs• Billing• EHR Meaningful Use • Reporting & Analytics• Interoperability
• The NLP Solution• Important NLP Technical Attributes
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Paradigm Shift toward Data-Centric Health CareOld Paradigm New Paradigm
Little coded data required Large amount of coded data required
Little detail required in documentation
Increasingly granular documentation required
Coding personnel responsible for billing only
Coding personnel responsible for billing, documentation quality, and data for secondary use
Minimal structured data entered manually into EHR by physician
Rich structured data captured using dictation with natural language processing and edited by coders
Manual coding with “lookup” software
EHR, CAC or Natural language processing and automated coding necessary
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NLP Can Generate:For Billing• CPT-4® – Procedures• ICD-9-CM – Diagnoses• ICD-10-CM/PCS – Diagnoses/Procedures• RxNorm - Medications
Beyond Billing• SNOMED-CT® – Clinical Codes & Section
Headers• LOINC® – Laboratory Results• RxNorm – Medications
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How is NLP the Solution?
• Billing
• EHR Meaningful Use
• Interoperability
• Reporting & Analytics
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Natural Language ProcessingGenerates structured datafrom unstructured text
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How Natural Language Processing Works
• Automatic generation of codes from unstructured text, semi-structured EHR data, or structured EHR data.
• Can generate very specific codes = Accuracy
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June 14, 2012 Presented by James Maisel, MD2012 NJHIMA Annual Meeting 88
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NLP Producing SNOMED-CT
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NLP Producing ICD-10-CM
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NLP as a part of a Billing Solution
• Faster, more accurate, more reliable, more thorough than manual coding alone
• Works for both in-patient and ambulatory records
• ICD-10 capability
• Effective educational platform
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NLP as part of a Billing Solution (cont.)(Reducing RAC Audit Risk)
• Traceable coding
• Reproducible coding
• Thorough coding supports more appropriate billing
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Billing Needs(ICD-9, CPT-4, RxNorm and ICD-10 Codes)
• Coder productivity
• ICD-10
• Coder education
• Appropriate coding for correct reimbursement
• RAC Audit Risk reduction
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The ICD-10 Challenge
S82.51Displaced fracture of medial malleolus of right tibiaS82.51XA…… initial encounter for closed fractureS82.51XB…… initial encounter for open fracture type I or IIS82.51XC…… initial encounter for open fracture type IIIA, IIIB, or IIICS82.51XD…… subsequent encounter for closed fracture with routine healingS82.51XE…… subsequent encounter for open fracture type I or II with routine healingS82.51XF…… subsequent encounter for open fracture type IIIA, IIIB, or IIIC with routine healingS82.51XG…… subsequent encounter for closed fracture with delayed healingS82.51XH…… subsequent encounter for open fracture type I or II with delayed healingS82.51XJ…… subsequent encounter for open fracture type IIIA, IIIB, or IIIC with delayed healingS82.51XK…… subsequent encounter for closed fracture with nonunionS82.51XM…… subsequent encounter for open fracture type I or II with nonunionS82.51XN…… subsequent encounter for open fracture type IIIA, IIIB, or IIIC with nonunionS82.51XP…… subsequent encounter for closed fracture with malunionS82.51XQ…… subsequent encounter for open fracture type I or II with malunionS82.51XR…… subsequent encounter for open fracture type IIIA, IIIB, or IIIC with malunionS82.51XS…… sequela
How to select the correct fracture from a drop-down menu?
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EHR ParadigmDictation Transcription Auto Coding Import to EHR
Current ParadigmPhysician Enters Data in EHR
10 minute
s
2 minute
s
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EHR Meaningful Use (SNOMED-CT, ICD-9, LOINC, and RxNORM Codes)
• Data capture using dictation & transcription with NLP
• Faster EHR adoption
• Increased EHR usability
• Less training and customization
• More efficient data entry
• More thorough coding
• Easier to read Health Story + codes
• Manual coding infeasible for SNOMED-CT
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NLP as part of an EHRMeaningful Use Solution
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Business Needs
http://www.cio-chime.org/chime/press/surveys/pdf/CHIME_MU2_Survey_Report.pdf
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NLP as a Reporting Solution
Standardized codes can be used for numerous secondary uses
• ORYX, SOI, POA, PQRI
• Quality measures
• Health care analytics
• Data can be stored in a clinical data repository and is accessible even if the EHR cannot do reporting
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Example of NLP as a Reporting Solution:
Clinical Core Measures for Diabetes1. Hemoglobin A1C poor control
2. Hemoglobin A1C (<8.0%)
3. LDL Management and Control
4. BP Management
5. Eye Exam
6. Diabetic Retinopathy: Severity of Retinopathy
7. Diabetic Retinopathy: Communication
8. Urine screening
9. Foot Exam20
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Benefits of Improved Coordination of Care
• Avoid unnecessary tests and/or adverse drug reactions• Reduce preventable hospital admissions or readmissions• Enable informed treatment plans for better health
outcomes• Enable reporting and tracking for quality measurement and
audit functionality• Increased efficiency in gathering correct documentation
more time for patient care and education
• Especially for patients with multiple physicians • i.e. patients with chronic conditions or multi-systemic
diseases
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NLP Enables Coordination of Care
Data currently in silosin various formats
NLP systems create aconsolidated record
Providers access the record through an HIEand address issues holistically & efficiently
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NLP Systems Perform 3 Functions
Capturing Data
Structuring Data
Facilitating Exchange of Data
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NLP Systems Can Accept• Dictated, transcribed, voice-recognized, or scanned
patient encounter notes regardless of source
• Semi-structured patient data from any ONC-certified EHR
NLP Systems Can Output
• Fully coded structured data that can be shared cross-platform • e.g. in HL7 Level 3 CDA R2 documents
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Interoperability
• Metcalfe’s Law
• HIE, RHIO, data exchanges
• CDA-standards for interoperability
• Security and Privacy
• Audit trails
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NLP Facilitates InteroperabilityMetcalfe’s Law
• EHRs require ICD-9 or SNOMED codes for diagnoses and allergies and RxNorm for medications for interoperability certification and Meaningful Use
• All EHRs must receive data from external systems that can contain standardized data (i.e., CCDs and CCRs - IHE Interoperability at HIMSS)
• EHR acceptance of data from multiple unstructured sources, including transcribed dictation, legacy text, scanned documents (CDA4CDT)
• All EHRs must generate CCD and CCR documents that contain semi-structured data that can be further coded
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NLP as an EHR Meaningful Use & Interoperability Solution
(for data transmission)
• Meet interoperability standards by generating the right codes
• Interface with external systems due to standardization of data and delivery format(i.e., CDA)
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Important NLP Technical Attributes
• Security, Confidentiality, Privacy
• Cloud-Based SaaS Systems
• Browser-Independence
• Flexibility
• Data Accessibility
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Cloud-Based SaaS Systems
Benefits• Low Implementation
Costs
• Low Ongoing Costs
• Professionally managed
• Off-site Internet access
• Upgrades for all users
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Browser-Independence
Benefits
• User-Friendliness
• Low Implementation Costs
• Low Ongoing Costs
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Security, Confidentiality, Privacy
• Security in transit
• Security in storage
• Automatic log-off
• Off-site long term storage
• Tracking and Monitoring– Audit trail
– Time tracking for productivity
– Accuracy monitoring
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Flexibility
Should the software fit the provider or the provider fit the software?
• Adjustability to fit various work flow models
• Customizability
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Thank YouJames M. Maisel, MD
Founder and Chairman
MediSapien Natural Language Processing
Medical Transcription
Clinical Data
ZyDoc
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