1. Data Quality: Practices, Technologies and Implications
Symposium on Data Science for Healthcare (DaSH)
October 19 & 20, 2017
John Novak, Sr. Director of Architecture and Government Technologies

2. New Jersey Innovation Institute (NJII)

3. NJII Healthcare iLab
2010 – 2015: $23 Million - Regional Extension Center, formerly NJ-HITEC (9,000+ Physician and Specialist Network) #1 recognized in the country
2010 – Present: Health Information Exchange, Highlander Health Data Network (5-hospital healthcare data exchange network)
2011 – Present: CMS Certified Data Registry (300+ Measures covering over 40 specialties for over 4,500 providers)
2012 – Present: Population Health Service Provider (Serving 17 DSRIP Hospitals, 5 ACOs, and 500,000 lives)
2015 – 2017: $5 Million – ONC HIE Interoperability Grant as State-Designated Entity NJ Master Person Index (MPI), Healthcare Provider Directory (HPD), Common Key Service (CKS), State Registry Gateway for Immunizations History and Statewide ADT Notification Service and Transitions of Care Use Cases
2015 – 2019: $50 Million - CMS Practice Transformation Network Awardee (Transform 11,500 providers to achieve performance targets and MIPS / APM scoring and preparedness
2016 – 2018: $1.5 Million- Medicaid IAPD Onboard and implement ToC for Medicaid Providers onto existing HIEs for the achievement of Meaningful Use

4. What we Found Incomplete demographics Lack of mapping/normalization
Public Health Registries (not all elements are covered)
HIO/IDNs inconsistent or not captured
Lack of mapping/normalization
Set up and never monitored for quality
Stale information
Purpose of connections
Meaningful Use, was a connection not much about what/how/why

5. What are the Data Quality Issues in Healthcare?
Standards
Lack of standard requirements
The one standard is there is no standard
Consistency
What and is collected
How is it collected
Data exists in a variety of different places
Across the continuum of care
Data exists in many different formats
Structured/Unstructured
What are the data quality issues in healthcare?

6. Standards Lack of standards Conformance
Patient identifiers not a set of defined, there are recommendations
Public Health
Willingness to collect data
Conformance
Variety of standards
HL7 v2.x, v3.0, DICOM, CCDA & FHIR
Even with in these standards conformance is a challenge
RxNorm, SNOMED, ICD-9 & ICD-10
Mapping across vocabularies

7. Lack of Consistency Terminology Workflows Technology
Hemoglobin A1C (lab test)
Hemoglobin A1C
Hgb A1C, Hb
A1c
Glycohemoglobin
H and H (Hemoglobin and Hematocrit)
Common fields
Workflows
Technology
Platforms
Maturity of Organizations

8. Format/Interoperability
Data exists in many different formats
Discreet data
Transcribed data
Structured/Unstructured data
Formats
PDFS, images, video, audio recordings
Discrepancies
Based on the source systems
For Interoperability
Standards
Consistency
Format

9. Moving Data Even a basic transaction can have its challenges,
when scaled it be comes significantly more complex.

10. Notification Example

11. Where is the Data?

12. Sample Scorecard

13. Moving the Needle Standards Validation Regulatory levers
Organizational compliance
Regionalization
Validation
Human validation and intervention
Technical validators