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1 Dealing with Uncertainties: HIT Standardization Public Health Data Standards Consortium Hyattsville, MD Dina Dickerson, MPH [email protected] Oregon Health Authority Center for Prevention and Health Promotion 11.21.2013

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Dealing with Uncertainties: HIT Standardization Public Health Data Standards Consortium Hyattsville, MD Dina Dickerson, MPH [email protected] Oregon Health Authority Center for Prevention and Health Promotion 11.21.2013 . HIE pulse in Oregon. Meaningful Use: - PowerPoint PPT Presentation

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Page 1: Dealing with Uncertainties:  HIT Standardization Public Health Data Standards Consortium Hyattsville, MD Dina Dickerson,  MPH Dina.Dickerson@state.or.us

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Dealing with Uncertainties: HIT Standardization

Public Health Data Standards ConsortiumHyattsville, MD

Dina Dickerson, [email protected]

Oregon Health AuthorityCenter for Prevention and Health Promotion

11.21.2013

Page 2: Dealing with Uncertainties:  HIT Standardization Public Health Data Standards Consortium Hyattsville, MD Dina Dickerson,  MPH Dina.Dickerson@state.or.us

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HIE pulse in Oregon

Meaningful Use:• Stage 1: HIE is live for Immunizations and ELR; syndromic

surveillance is piloting in 3 local sites• Stage 2: Phase 1 testing of HIE between partner EHR and state

newborn hearing screening registry is complete and Phase 2 planning is underway

• Stage 3: Work is underway to align with PHRI common data elements and to get experience with the HIT tools so that state programs are ready to receive the data from EHRs when available

Other:• Lots of nonstandard program-to-program data sharing, such as

Immunizations to WIC and ELR to CD reporting, but each dedicated interface adds another silo to maintain

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Other standards-based data sharing initiatives in Oregon

Maternal and Child Health and Related Services• Race to the Top: integrate and coordinate early childhood data

and services across agencies including health, public health, education and mental health

• Maternal, Infant, Early Childhood Home Visiting: integrate and coordinate home visiting data and services across agencies including health, public health, education and mental health

• HRSA MCHB Minimum Data Set: align performance measures across programs, identify supporting data elements, harmonize across data elements and value sets, and designate a standard for use by all HRSA MCHB-funded programs

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Oregon EHDI* CDA Phase 1 Pilot - Lessons Learned

Step-1 Setting: Birthing Facility IT Product: Epic 2012 EHR (Test Harness) Report Content: Patient demographic information, NHS resultsStandards: HL7 CCD, IHE RFDActor: Content Creator Form Filler

Step-2 Setting: HIE IT Product: OZ Form Manager

Report Content: NHS Outcome Report Standards: HL7 CDA, IHE EHCP, IHE RFD, IHE XDR Actor: Form ManagerForm ReceiverContent CreatorDocument Source

Step-3 Setting: Oregon EHDIIT Product: Orion Rhapsody, Filemaker DBReport Content: NHS Outcome ReportStandards: HL7 CDA, IHE EHCP, IHE XDR Actor: Content ConsumerDocument Recipient

Interoperability Standards**

* Early Hearing Detection and Intervention (EHDI) program. Newborn hearing screening (NHS) is a Stage 2 Meaningful Use objective.

** Public Health Data Standards Consortium EHDI CDA Final Report

Page 5: Dealing with Uncertainties:  HIT Standardization Public Health Data Standards Consortium Hyattsville, MD Dina Dickerson,  MPH Dina.Dickerson@state.or.us

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Oregon EHDI Manual NHS Report Form*

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EHDI CDA SDC RFD Template*

* Public Health Data Standards Consortium EHDI CDA Final Report

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EHDI CDA Phase 1 Pilot – Lessons Learned

Data Exchange Architecture*

* Public Health Data Standards Consortium EHDI CDA Final Report

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EHDI CDA Phase 2 Proposal: Real Data & Systems

EHDI User Story – Report Form for Data Capture (RFD)

Page 9: Dealing with Uncertainties:  HIT Standardization Public Health Data Standards Consortium Hyattsville, MD Dina Dickerson,  MPH Dina.Dickerson@state.or.us

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EHDI CDA Phase 2: SDC Template

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HIE: even more silos?• Hospital IT staff fear a proliferation of one-off requests for EHR data

• Each request requires resources to set up and maintain• Can they do this once and address all reporting needs for Public

Health?

• Need to acknowledge and address those fears• minimize impact on stakeholders and partners• let them know up front what data Public Health requires and in

what format

• Transition to a shared data and workflow model• harmonize and standardize data and processes• receive standards-based data into shared data model• populate silos with shared data until they can be retired• use metadata to simplify the structure and process

Page 11: Dealing with Uncertainties:  HIT Standardization Public Health Data Standards Consortium Hyattsville, MD Dina Dickerson,  MPH Dina.Dickerson@state.or.us

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Priority areas to move toward HIT standardization• Awareness

• Flea Pushing a Boulder, 2009• Standards overload can be overwhelming

• Coordination• CCO’s and other clinical providers• Local health departments• Statewide programs

• Infrastructure• Shared data model• Shared workflow tools• Funding

• Workforce• No Public Health-wide Informatics in Oregon• Need trained Chief Informatics Officer, not Technology Officer• Need training in harmonization and standardization

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Awareness

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Awareness: standards overload

Data standards• CPT• DSM• ICD9, ICD10• LOINC• NIC-NOC-

NANDA• SNOMED• NFP• and so on

Interoperability standards• HL7 CCD• HL7 CDA• IHE RFD• IHE EHCP• IHE XDR• and so on

Data models• FHIM• HL7 • European RIM• and so on

Forms• SDC Template• RFD• and so on

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Coordination: CCO’s, LHDs, Nonprofits, State• Periodically receive a file from partner EHRs that contains all instances

of data needed by Public Health for prescribed time frame

• Parse the data on Public Health side and use it to update shared standards-based data model

• Public Health silos draw on shared data model for updates and actions• Harmonize and standardize the actions occurring in silos• Build shared functionality to address needed actions and notifications• Provide one stop shopping for providers to access and act on

notifications about their patients

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Infrastructure: standards deployment via a shared data model

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Infrastructure: standards development using a knowledge builder

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Workforce

IT is still in control today • Lack domain knowledge• Focus is on project management to acquire/implement a system• Little awareness of data and workflow standards

Decision-makers are skeptical• Burned by repeated IT failures• No background in informatics • Inroads in MCH, ELR and CD reporting but not integrated

Train program side people in harmonization and standardization• Data• Functionality

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Standards development and deployment: methodology to move from siloed to shared data

Inventory Consolidate Harmonize Standardize Classify Use Monitor

Create knowledge base of all forms, data elements and value sets

Organize data elements around shared themes

Align definitions and value sets for a theme

Identify standard representation and permissions

Assign metadata tags and user permissions to share data

Capture, act on and report the data

Track access and evaluate quality

Data Level

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Standards development and deployment: methodology to move from siloed to shared workflow

Inventory Consolidate Modularize Standardize Pilot Implement Monitor

Collect and deconstruct user stories according to workflow requirements

Create master user story that includes all workflow requirements

Align, simplify and reconstruct workflow requirements

Adopt one methodology to address workflow requirements

Test and fine tune modular solution and training tools in limited settings

Roll out solution

Track access and evaluate quality

Functionality Level

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Harmonization of core common data elements*

* Public Health Reporting Initiative Data Harmonization Profile

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Acknowledgements• Claudia Bingham• John Eichwald• Jay Eisenberg• Ellen Larsen• Nikolai Lipskiy• Riki Merrick• Steve Modesitt• Heather Morrow-Almeida• Trong Nguyen• Sue Omel• Anna Orlova• Lari Peterson• Matt Pitney• Walter Suarez• Meuy Swafford• Cate Wilcox• Patricia Yao• Chia-Hua Yu• Laura Zukowski