NLP as a Data Integration Tool for Your CIO

James M. Maisel, MD

Chairman, ZyDoc

jmaisel@zydoc.com

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

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

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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