Data Standards and the United States Health Information Knowledgebase AHRQ Annual Research Conference 2011 September 20, 2011.

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Presentation transcript:

Data Standards and the United States Health Information Knowledgebase AHRQ Annual Research Conference 2011 September 20, 2011

Agency for Healthcare Research and Quality (AHRQ) Mission Improve the quality, safety, efficiency and effectiveness of health care for all Americans 2

Presentation Moderator: J. Michael Fitzmaurice PhD, AHRQ Moderator: J. Michael Fitzmaurice PhD, AHRQ Speakers: Speakers: – John Donnelly, IntePro Solutions – Robin Barnes, Data Consulting Group 3

Learning Objectives What is the U. S. Health Information Knowledgebase ? What is the U. S. Health Information Knowledgebase ? – A metadata registry – Supporting the HHS Secretary’s Initiatives Why is USHIK important? Why is USHIK important? – To AHRQ – For Quality Measures – For Patient Safety Common Formats What can you do with USHIK.ahrq.gov? What can you do with USHIK.ahrq.gov? – Application Projects implemented as USHIK Portals 4

5 Card Games Metadata Registry Each game master is the authority for its game’s cards Each game master is the authority for its game’s cards The same card can be used in different games The same card can be used in different games The same metadata about a card can be reused many times, in a metadata registry The same metadata about a card can be reused many times, in a metadata registry Bridge: all 52 cards Bridge: all 52 cards Euchre: 24 cards, all higher than an 8 Euchre: 24 cards, all higher than an 8 Pinochle: 48 cards, all higher than an 8, duplicated Pinochle: 48 cards, all higher than an 8, duplicated Poker: all 52 cards Poker: all 52 cards In total, it would take 176 cards for each of you to display the cards for your games with separate decks In total, it would take 176 cards for each of you to display the cards for your games with separate decks

6 What cards are needed to play? Bridge PinochleEuchrePoker Deck of 52 CARDS Not 176

7 Which games use the 4 of spades? Bridge PinochleEuchrePoker Deck of 52 CARDS 4 of Spades

8 Bridge: Normal Deck of 52 Cards Data element name(1 of 52): 4 of spades Data element name(1 of 52): 4 of spades Attributes: Attributes: – Definitionplaying card – Number4 – Suitspades – Odd/eveneven – Picture cardNo – AuthorityYou, or Hoyle – Version or date effective – Bridge deck memberYes – Pinochle deck memberNo – Euchre deck memberNo – Poker deck memberYes

9 Example: AHRQ-USHIK Data Element Data Element Name : Gender code Data Element Name : Gender code Attributes (Metadata): Attributes (Metadata): – DefinitionFor eligibility, id gender of the individual member – ContextNCPDP Data Dictionary – Registered AuthorityNCPDP – Effective date – Data typeAlphabetic extended – Representation LayoutX(1) – Value DomainGender, coded_VD – CodesM (male), F (female), blank (unknown)

10 How does each authority express gender? X12 NCPDPHL7HITSP USHIK Gender

11 Comparison Matrix Aids in Harmonizing Data Elements

12 Do the data elements in my EHR fit Meaningful Use specifications? X12N NCPDPHL7HITSP USHIK Are my EHR’s data defined the same as for Meaningful Use reqs? Meaningful Use

What Portals are in USHIK? 1. USHIK 1. USHIK: HHS Secretary’s adopted, endorsed, recognized data elements: HIPAA, CHI, HITSP, and all other data elements 2. HITSP 2. HITSP: HITSP data elements linked to all 13 HITSP use cases, interoperability specifications, and other documents Patient Safety Common Formats: Specifications for electronically reporting patient safety events in hospitals among Patient Safety Organizations 4. Meaningful Use 4. Meaningful Use (pilot): Example: quality measures and the data elements associated with their numerators, denominators, inclusions, and exclusions 5. State All-Payer Claims Data 5. State All-Payer Claims Data (pilot): Data element specifications from all-payer data bases of 7 states 6. Standards and Interoperability Framework 6. Standards and Interoperability Framework (New) Data element Specs from Transitions of Care, Lab Results Interface, and CDA Harmonization initiatives.

Application Projects Highlighted HITSP: ONC, AHIC Use Case’s resolved into Interoperabilty Specs and other constructs HITSP: ONC, AHIC Use Case’s resolved into Interoperabilty Specs and other constructs S&I Framework: ONC, Use Case’s resolved into Requirements, Standards Analysis and Reference Implementation artifacts S&I Framework: ONC, Use Case’s resolved into Requirements, Standards Analysis and Reference Implementation artifacts Meaningful Use: CMS, Quality Measure numerators & denominators, exclusions etc Meaningful Use: CMS, Quality Measure numerators & denominators, exclusions etc 14

HITSP Project Background Approach: Approach: – Use Case’s – AHIC – Standards Analysis – HITSP – Pilot Implementations – NwHIN Artifacts: Interoperability Specs; Transactions/Transaction Packages; Components Artifacts: Interoperability Specs; Transactions/Transaction Packages; Components Data: Transaction Metadata; Clinical Data Data: Transaction Metadata; Clinical Data 15

HITSP Project Organization 16 Care Management and Health Records Technical Committee Infrastructure, Security and Privacy Technical Committee Administrative and Financial Technical Committee Modeling Messaging and Datatypes Terminology And Knowledge Representation Workflow and Process Use Case Consumer Perspective TC Provider Perspective TC Population Perspective TC Security & Privacy Domain TCs Foundations Committee Perspective Technical Committees

HITSP Deliverables Use Case Artifacts Use Case Artifacts – 15+ Interoperability Specs – 30+ Transaction Packages / Transactions – 40+ Components Technical Notes (7) Technical Notes (7) Acronym and Data Element Glossaries Acronym and Data Element Glossaries

USHIK Focus and Deliverables HITSP Data Component Artifacts HITSP Data Component Artifacts – Constrain existing data standards from SDO’s – HL7 CDA, HL7 2.x, ASTM CCR, ANSI X12, etc – Re-purposing structure for CDA data elements C154  C83  C32, C37, C48, C78 C154  C83  C32, C37, C48, C78 Clinical Data Portal: Clinical Data Portal: – Clinical Data “Concepts” – “Model” Primarily Use Case specific – Leverage HITSP Glossaries 18

USHIK Demonstration HITSP Portal 19

S&I Framework Project Background Approach: Approach: – Use Case’s, Standards Analysis, Reference and Pilot Implementations –> Single Contiguous Program – Cross-Use Case Harmonization; Use Case Simplification WG for re-purposing Artifacts: Use Case Requirements, Clinical Information Model (CIM). Standards Analysis Worksheet, Reference Impl Guide, Pilots Results Artifacts: Use Case Requirements, Clinical Information Model (CIM). Standards Analysis Worksheet, Reference Impl Guide, Pilots Results 20

S&I Framework Project Organization 21

S&I Framework Deliverables Use Case and Implementation Artifacts Use Case and Implementation Artifacts – 2 Clinical Operations Initiatives Transitions of Care (ToC), Lab Results Interface (LRI) Transitions of Care (ToC), Lab Results Interface (LRI) – 2 IT Infrastructure Initiatives Provider Directories, Certificate Interoperability Provider Directories, Certificate Interoperability – 1 Population Health Initiative (new) Query Health Query Health Cross-Initiative Workgroups and Functions Cross-Initiative Workgroups and Functions

USHIK Focus and Deliverables S&I Cross-Initiative Artifacts S&I Cross-Initiative Artifacts – Use Case Simplification Matrix Actors, Actions, Data Element Sets (DES) Actors, Actions, Data Element Sets (DES) Clinical Information Model (CIM) Clinical Information Model (CIM) Transitions of Care (ToC), Lab Results Interface (LRI) Transitions of Care (ToC), Lab Results Interface (LRI) Standards Analysis Results Standards Analysis Results – CDA Consolidation Ballot templates – DES correlation to SDO standards Currently CDA, HL7 v2.x Currently CDA, HL7 v2.x 23

USHIK Demonstration S&I Framework Portal 24

Meaningful Use Project Background Approach: Approach: – Product Certification as per HITSP interoperability requirements (ONC/NIST) – Administrative/Operational process changes – Quality Measures in harmonization with existing AHRQ authored measures (CMS/AHRQ/NQF) Artifacts: Quality measures expressed as “eMeasures” leveraging HITSP and S&I Framework recognized data definitions and vocabularies Artifacts: Quality measures expressed as “eMeasures” leveraging HITSP and S&I Framework recognized data definitions and vocabularies 25

Meaningful Use Measures Meaningful Use Guidance Meaningful Use Guidance – Administrative/Operative and Clinical measures – eMeasure Numerators, Denominators, Exclusions, Inclusions Targeting EP and EH provider types Targeting EP and EH provider types – PQRI, RHQDAPU, NQF Time Period Based Registration & Attestation Requirements to Qualify Time Period Based Registration & Attestation Requirements to Qualify 512&mode=2&objID= &mode=2&objID= &mode=2&objID= &mode=2&objID=

USHIK Focus and Deliverables Quality Measure Definition Quality Measure Definition – Description, objective, numerical components Help with knowing “what measures are for what purpose” Help with knowing “what measures are for what purpose” – MU, PQI, other quality improvement/payment programs Help with knowing more about the data elements used in the measure Help with knowing more about the data elements used in the measure – Base Standards used (e.g SNOMED, LOINC) – Where else these data elements are used 27

USHIK Demonstration MUMM Portal 28

At the bottom left of each page, please find a notepad/pencil icon stating “Give your feedback”

Lessons Learned Use information models Trade off value of what USHIK supplies against the cost of supplying it Intellectual property has value—protect its value Work with users – – Anticipate their needsSave them time – – Give them accuracy Save them money – – Seek their feedback

31 Finale Data Dictionaries promote understanding Data Dictionaries promote understanding Metadata registries promote interoperability, reuse, and one-stop shopping for information Metadata registries promote interoperability, reuse, and one-stop shopping for information Research needs health data that are more uniform, accurate, and computerized Research needs health data that are more uniform, accurate, and computerized Don’t we all! Don’t we all! See the HITSP, S&I Framework, MU, USHIK Common Format and APCD Portals at See the HITSP, S&I Framework, MU, USHIK Common Format and APCD Portals at

Data Standards and the United States Health Information Knowledgebase AHRQ Annual Research Conference 2011 J. Michael Fitzmaurice, Ph.D. [AHRQ] John Donnelly [Intepro Solutions] Robin Barnes (Data Consulting Group) Thank You