ron fichtner, chief, prevention informatics office alan sim, public health informatics fellow

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Common Data Elements and Metadata: Their Roles in Integrating Public Health Surveillance and Information Systems Ron Fichtner, Chief, Prevention Informatics Office Alan Sim, Public Health Informatics Fellow (e-mail: [email protected]) National Center for HIV,STD, & TB Prevention Centers for Disease Control and Prevention (CDC)

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Common Data Elements and Metadata: Their Roles in Integrating Public Health Surveillance and Information Systems. Ron Fichtner, Chief, Prevention Informatics Office Alan Sim, Public Health Informatics Fellow - PowerPoint PPT Presentation

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Page 1: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow

Common Data Elements and Metadata: Their Roles in Integrating Public Health Surveillance and Information Systems

Ron Fichtner, Chief, Prevention Informatics Office Alan Sim, Public Health Informatics Fellow

(e-mail: [email protected])

National Center for HIV,STD, & TB PreventionCenters for Disease Control and Prevention (CDC)

Page 2: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow

Outline

• Introduction– Metadata – CDC

• Standards & Integration Initiatives

• Uses of Metadata at CDC

• Metadata Options for the Future

Page 3: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow

"Managing data, information, and knowledge will be the business driver”

- Robert S. Seiner, Data Administration Newsletter

Is Metadata Significant?

Page 4: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow

Definition of Metadata

“Metadata is information, documented in IT tools, that improves both business and

technical understanding, of data and data-related processes.”

Page 5: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow

About CDC

• 11 Centers, Institute, and Offices (CIOs)

• Collect data, convert data into knowledge, and apply knowledge to accomplish its mission– “To promote health and quality of life by

preventing and controlling disease, injury, and disability”

Page 6: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow
Page 7: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow

Problems

• Multitude of disparate CDC surveillance systems and software products

• Lack of uniform standards (e.g. multiple codes sets, user interfaces, etc.)

• Duplicative work

Page 8: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow

HISSB Processes

• Health Information and Surveillance System Board (HISSB)– Standards and Liaison Committee (S&LC)– Integration Project: NEDSS– For more information:http://www.cdc.gov/od/hissb

HISSB created

1995 200019971996 19991998

S&LC Integration Project

Page 9: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow

Standards & Liaison Committee

• History

• Purpose

• Functions– Facilitate development of CDC wide standards– Interact and communicate with other standards

development groups

• Primarily targets CIOs, state health departments, and other federal agencies

Page 10: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow

S&LC Deliverables

• 20 common data elements standardized• Common Data Elements (CDE)

Implementation Guide http://www.cdc.gov/data/index.htm

• Metadata Registry Prototype

• Formalized relationships with leading standards development organizations (e.g. HL7, X12)

Page 11: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow

S&LC Lessons Learned

• Define scope at onset

• Support multiple representations

• Participate and influence US & international standards process (i.e. standards development organizations)

• Market products

Page 12: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow

Integration Project: NEDSS

• National Electronic Disease Surveillance System (NEDSS)– Purpose– Current Situation– Proposed Integrated System

Page 13: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow

NEDSS Deliverables

• Data Model

• Common Information for Public Health Electronic Reporting (CIPHER) Standards

• Common User Interface Standards

• Framework for Component Development and Reuse

Page 14: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow

Related Activities

• Health Alert Network/Secure Data Network

• Electronic Laboratory Reporting

Page 15: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow

Metadata Use

• Potential ways CDC can use metadata:– Support ongoing standards process– Core of Integration project– Facilitate development of a standard vocabulary

(e.g. common case definitions)– Share and receive metadata from other

agencies/organizations

Page 16: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow

Metadata tool

• Standards based

• Promotes convergence

• Dissemination of concepts

• Downloadable tables

• Encourages reuse of standards

• If internet-based, registry widely accessible

Page 17: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow

Metadata Registry Prototype

• Metamodel based on ISO11179 / ANSI X3.285

• Facilitate dissemination of standards

• Tool for comparison

• Serves as a “proof of concept”

• Simple design, easy to develop and use

Page 18: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow

ISO11179 / ANSI X3.285

Metamodel Regions – Stewardship region

– Naming and identification region

– Classification region

– Data element concept administration region

– Conceptual domain and value domain administration region

– Data element administration region

Page 19: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow
Page 20: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow

Prototype (Back End)

• Database created in Microsoft Access

• Written in Visual Basic 6.0

Page 21: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow
Page 22: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow

Prototype (Front End) Features

• HTML, Javascript

• Browser independent (IE 5.0, Netscape)

• Tables downloadable in text or XML

• Available on CDC Intranet

Page 23: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow
Page 24: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow
Page 25: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow
Page 26: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow
Page 27: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow
Page 28: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow

Options for CDC

• Develop CDC registry internally– Expand on existing prototype– Start from scratch

• Adopt existing registry (EPA or HCFA/DOD)

• Contract out

Page 29: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow

Develop CDC Registry

• Advantages– Able to focus on organizational concepts– Train internal staff – “Practice by doing”

• Disadvantages– $$$$$– Time – Huge learning curve

Page 30: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow

Expand on Existing Prototype

• Maintenance/Versioning

• Searching/Grouping Features

• Enable comparison of multiple standards

• Reference other existing standards (e.g. SNOMED, ICD-CM, HL7, UMLS, etc.)

Page 31: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow

Adopt Existing Registry

• EPA (Environmental Data Registry)

• HCFA-DOD (US Knowledgebase)

• Interagency Agreement?

Page 32: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow

Adopt Existing Registry

• Advantages– Save resources to focus on other activities– Share concepts with participating agencies– Promote organizational metadata to broader

audience

• Disadvantages– More complex– (perceived) lack of centralized control?

Page 33: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow

Contract

• Advantages– Obtain services of company with metadata

implementation expertise.– Maintenance (in the short-term)

• Disadvantages– $$$$– Internal staff “left in the dark”– Still requires data modeling, consensus building,

etc.

Page 34: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow

Future of Metadata at CDC

• Short Term– Common data element standards– Standardized codes for clinical findings

• Long Term– CDC or HHS supported enterprise-wide data

registry

Page 35: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow

Final Words...

“Metadata serves as a mechanism to facilitate convergence towards the use and adoption of standards… it is this process upon which

the integration of systems is made possible.”

Page 36: Ron Fichtner, Chief, Prevention Informatics Office  Alan Sim, Public Health Informatics Fellow

Your Feedback….

– How to integrate and use other efforts (e.g. data model, standards development, etc.) in facilitating the collection and management of metadata?

– Build, Buy, or Join?– How to market and obtain buy-in from involved

parties (upper management, CIOs, systems)?– ISO11179, OIM (Metadata Coalition) --

Competing Standards????