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Building An Ontology of the NHIN: Status Report 3. Brand Niemann Co-Chair, Semantic Interoperability Community of Practice (SICoP) Best Practices Committee (BPC), CIO Council, and Enterprise Architecture Team, Office of Environmental Information U.S. Environmental Protection Agency
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Building An Ontology of the NHIN: Status Report 3 Brand Niemann Co-Chair, Semantic Interoperability Community of Practice (SICoP) Best Practices Committee (BPC), CIO Council, and Enterprise Architecture Team, Office of Environmental Information U.S. Environmental Protection Agency April 5, 2005
Overview • 1. The National Health Information Network (NHIN) Request for Information (RFI): • 1.1 Scope & Quality • 1.2 Statistics • 1.3 Analysis & Reporting Strategy • 1.4 Business Cases • 1.5 Leadership Statements • 1.6 Related Activities • 1.7 Building Ontologies • 2. Results and Next Steps • Appendices
NHIN RFI:1.1 Scope & Quality • The NHIN RFI stimulated substantial and unprecedented interest. • Cumulatively, the 512 responses yielded nearly 5,000 pages of information. • The National Coordinator established a federal government wide RFI review task force (RTF) to review, summarize and analyze the RFI responses. • The RTF consists of more than 120 Federal officials from 17 agencies.
NHIN RFI:1.1 Scope & Quality • The responses to these initial questions yielded the richest and most descriptive collection of thoughts on interoperability and health information exchange that has likely ever been assembled in the United States. • The responses to the general questions are a treasure trove of the best thinking on the topic.
NHIN RFI:1.3 Analysis & Reporting Strategy • The NHIN RFI consisted of: • Twenty-four (24) questions, in • Six (6) basic groups • The NHIN Team divided the RFI’s into two basic groups: • Individuals (283) • Organizations (229) • The NHIN Team organized the Organization responses for review in: • Thirty (30) sets with 2-3 reviewers for each set • Templates (matrices) with 13 entities by about 4 categories of the 24 questions mapped to each of the three Work Groups (see next slide). • For example: WG1 – Standards (Questions 4b, 14-18), Technical Development/Architecture (Questions 2-4a, 23), Technical Services/Operations (Questions 9-11), and General Comments by Federal Government, Industry – Software/Hardware Vendors, etc.
NHIN RFI:1.3 Analysis & Reporting Strategy • NHIN Team divided the participants into three Work Groups: • Technical and Architecture • Organization and Business Framework • Finance, Privacy, Regulatory, and Legal • Each Work Group created Major Themes: • WG1: 3, WG2: 2, and WG3: 3 • Each Work Group reported out on Sub-teams: • WG1: 5, WG2: 5, and WG3: 4 • NHIN Team mapped the Work Group results to new structures for two reports: • Report 1 - Sections: 7, Sub-sections: 17, and Sub-Sub-sections: 18 • Report 2 - Sections: 4, Sub-sections: 16, and Sub-Sub-sections: 86
NHIN RFI:1.3 Analysis & Reporting Strategy • There is and will be criticism: • “It is important to note, in the front when talking about the process, that approximately 270 RFIs were not reviewed by the interagency process. The process that ONCCHIT used to select and review these responses should be made clear.” (name withheld) • There will be responses to criticism: • Statistical Summary Analysis of Responses from Individuals: • 85% of the responses had strong concerns about the potential loss of privacy along with 53% of health officials who had the same concern. • 17% of health officials shared their experiences with implementations of EHR systems. • Only about 4% expressed enthusiasm for the creation of a system that would facilitate interoperability.
NHIN RFI:1.4 Business Cases • Veterans Can Personalize Medical Records on VA Web Site, GCN, November 9, 2004: • My HealtheVet (also copy parts of VistA) • Could allow the VA to share patient data with other providers. • Patients can request changes to their medical records and allow their loved ones or their physicians to access portions of their records. • iHealthBeat, November 13, 2004.
NHIN RFI:1.4 Business Cases • Canadian Health Infoway*: • An EHR solution is a combination of people, organizational entities, business processes, systems, technology and standards that interact and exchange clinical data. A network of interoperable EHR solutions—one that links clinics, hospitals, pharmacies, and other points of care—will help enhance quality of care and patient safety, improve Canadian's access to health services, and make the health care system more efficient. • Interoperability for electronic health records is the capability of computer and software systems to seamlessly communicate with each other. It is central to Infoway's mission, making clinical data available across the continuum of care and across health delivery organizations and regions, promoting reusable and replicable solutions that can be aligned with jurisdictional priorities and deployed across the country more cost-efficiently. Without a common framework and sets of standards, EHR systems across Canada would be a patchwork of incompatible systems and technologies. *Accelerating the development of Electronic Health Information Systems for Canadians http://www.infoway-inforoute.ca/ehr/index.php?lang=en
NHIN RFI:1.4 Business Cases Canadian Health Infoway Standards Collaboration http://www.infoway-inforoute.ca/ehr/standards_overview.php?lang=en#
NHIN RFI:1.4 Business Cases • One recent study estimated a net savings from national implementation of fully-standardized interoperability between providers and five other types of organizations could yield $77.8 billion annually, or approximately 5 percent of the projected $1.7 trillion spent on U.S. health care in 2003 • Source: J. Walker et al., “The Value of Health Care Information Exchange and Interoperability,” Health Affairs, January 19, 2005.
NHIN RFI:1.5 Leadership Statements • HHS Administrator Leavitt’s Keynote Address at AFCEA International’s Homeland Security Conference, February 22, 2005 (See http://www.fcw.com/article88110): • The next frontier of human productivity is the Interoperability Era. • Collaboration is the premium leadership skill that’s need in this new era. • Interoperability begins by setting standards and should be organically grown through the "messy, complex, difficult process called collaboration.” • Several elements (8) will improve the chances for success (a “common pain”, a “convener of stature”, a committed leader, openness, transparency, and voluntary participation, a critical mass of stakeholders, representative of substance, a clearly defined purpose and goal, and a formally written and signed charter).
1. NHIN RFI:1.5 Leadership Statements • Dr. Brailer’s Keynote Address at HIMSS Conference, February 17, 2005: • Interoperability Themes from RFIs: • Standards (WG1 & WG2)* • Governance (WG2) • Privacy (WG3) • Regionalization (Initially none, then WG2) • Financing (WG3) • Architecture (WG1) • Regulation (WG3) *Mappings to WG’s added by author of this presentation.
NHIN RFI:1.6 Related Activities • Federal Health Architecture (FHA) Interoperability Work Group, March 17 and 24, 2005: • Goal: Technology Standards Harmonization • Strive for consensus on some of the potential technical specifications (see next slide) • Draft Health Information Interoperability Standards Profile • Present standards to OMB as Draft Standards for Trial Use (DSTU) • Follow-up with more detailed guidance on implementation • Concern: Narrow focus of Work Group is on the less crucial aspect of interoperability (technical standards)
Approach for Technology Classification HL7 V 3.0 • XML Digital Signature • XKMS • SAML • WS-Security • XACML • PKI • SSL Data V 2.x XML XSLT, XSL, etc. Other ASCII, Binary (e.g., image) Business Process BPEL BPSS Message Oriented Interchange Registry (RIM) Discovery UDDI Description WSDL CPP/A Message SOAP SOAP w/ attach., ebMS SOAP Transport HTTP HTTP HTTP, SMTP, FTP Other Web Services ebXML Security Source: FHA Health Interoperability Work Group, March 24, 2005.
NHIN RFI:1.6 Related Activities • FHA Architectural Peer Review Group (APRG) Initial Meeting, February 11, 2005: • Scope – Health Domains as identified by the FHA Health Domain WG and incorporated into the FHA BRM (see FEA’06 Revision Summary, page 4). • Semantics – Recommendations were made to consider an ontology that is being developed for this purpose by the CIO Council (actually by GSA, TopQuadrant, and SICoP). • See Slide 18 for Example.
NHIN RFI:1.6 Related Activities • Healthcare Informatics Online, January 2004 Cover Story on Emerging Technologies: • Concept introduced in 2001 Scientific American article and described using the scenario of a man who goes online, employing intelligent agents on the Semantic Web to set up a series of physician appointments and physical therapy sessions for his ailing mother. (It could be 10 years before such agent-enabled scenarios play out, but simpler semantic functions are already emerging.) • My Note: Semantic Web Applications for National Security (SWANS), April 7-8, 2005, Crystal City, Virginia.
NHIN RFI:1.6 Related Activities • Healthcare Informatics Online, January 2004 Cover Story on Emerging Technologies: • “It’s not a Web replacement, it’s an evolution based largely on eXtensible Markup Language (XML) with added technologies that allow computers to interpret and process data “ontologies”, or relationships between disparate pieces of information.” • “The Semantic Web would represent a worldwide Web of connected data, radically different from today’s Web of discrete documents, which is why it could be the affordable answer to the electronic health record.” • My Note: The Semantic Web could also deal with the privacy and security concerns expressed in the RFI Individual Responses.
NHIN RFI:1.7 Building Ontologies • The Mind Map Book: How to Use Radiant Thinking to Maximize Your Brain’s Untapped Potential (Tony Buzan): • Before the web came hypertext. And before hypertext came mind maps. • A mind map consists of a central word or concept, around the central word you draw the 5 to 10 main ideas that relate to that word. You then take each of those child words and again draw the 5 to 10 main ideas. • Mind maps allow associations and links to be recorded and reinforced. • The non-linear nature of mind maps makes it easy to link and cross-reference different elements of the map. • See next slide for examples from the “Explorer’s Guide to the Semantic Web,” Thomas Passin, Manning Publications, 2004, pages 106 and 141.
Mind Maps for Searching and Ontologies informal formal distinctions multiple trees hierarchies taxonomies vocabularies adhoc categories internet hugh changing growing inconsistent predefined ENVIRONMENT CLASSIFICATION KINDS Searching Ontologies ONTOLOGIES keywords ontologies classification metadata semantic Focusing social Analysis multiple Passes clustering combining specifying committment NAMES STRATEGIES LANGUAGES properties relationships constraints identifiers RDFS OWL DAML Description Logics Note: These are not complete.
NHIN RFI:1.7 Building Ontologies • standards • governance • privacy • regionalization • financing • architecture • regulation organizational technical semantic general organizational & business management & operational standards & policies financial, regulatory, & legal other DR. BRAILER RFI FRAMEWORKS STANDARDS ORGANIZATIONS NHIN WORK GROUPS NCVHS CCHIT Etc. technical & architecture organization & business financial, regulatory, & legal ORGANIZATIONAL STRUCTURE OTHER other STRATEGIC PLAN GOALS regional initiatives clinical practice population health health interoperability Federal Health Architecture Possible/probable interrelationships Inform Clinical Practice Interconnect Clinicians Personalize Care Improve Population Health
NHIN RFI:1.7 Building Ontologies • An ontology is the organization of things into types and categories with a well-defined structure that are “networks of concepts”. • Specific ontologies must be constructed with known vocabularies and rules of construction. • A good ontology requires: • The ability to conceptualize and articulate the underlying ideas. • Skill at modeling abstractions. • Knowledge of the syntax of the modeling language. • OWL is poised to become the major ontology language for the Web. • Use of well-developed and accepted ontologies whenever possible. • The Suggested Upper Merged Ontology (SUMO) is a best practice example. • A Community of Practice with all of these skills that can collaborate to develop the ontology. • The Ontolog Forum is a best practice example (see next slide).
NHIN RFI:1.7 Building Ontologies • A key aspect of successful large scale interoperability is shared meaning. • Shared meaning requires not only a common syntax (XML), but a common vocabulary. • That common vocabulary should be defined in terms of the broadest and most general foundation concepts and be in a formal and computable language not subject to human interpretation in English alone. • Formal ontologies, defined in logic, and a hierarchy of ontologies that build from a common semantic foundations are needed (se next slide).
Current Ontology-Driven Information System for FHA/NHIN Examples SUMO HL7 RIM FEA-RMO EON SNOMED CT LOINC Source: Netcentric Semantic Linking (Mapping): An Approach for Enterprise Semantic Interoperability, Mary Pulvermacher, et. Al. MITRE, October 2004.
NHIN RFI:1.7 Building Ontologies • Strategy for the NHIN Ontology: • Compile repository/library of NHIN public and RFI documents in their native file formats. • Repurpose the documents: • Proprietary to text formats. • Proprietary to XML documents. • Chunk large documents into sub-documents. • Compile the NHIN “Mind Maps” for defining searches and building the ontology. • Work with ontology community of practices to draw in their expertise. • Proposed new Ontology and Taxonomy Coordinating Group (ONTACG) of SICoP.
2. Results and Next Steps • 2.1 The Challenge • 2.2 A Suggested Solution • 2.3 The Content • 2.4 The Pilot • 2.5 Sample Results • 2.6 Next Steps
2.1 The Challenge • Extract and organize the semantic concepts from about 5000 pages of semi-structured content in support of a comprehensive analysis to recommend the plan for the National Health Information Network (NHIN). • For example: Dr. Brailer, ONCHIT Technical Assistance Call December 6, 2004, “NHIN refers to a specific bundle of technologies, business frameworks, financing arrangements, legal contracting or other mechanisms, policy requirements, organizational issues and related things that allow for network interoperability. So NHIN is the middleware in the grand schema of these pieces.”
2.2 A Suggested Solution • Besides manual human extraction individually and in the Work Group environment, there are machine-aided extraction, analysis, and visualization tools that could and should be brought to bear on this problem that would lead to the building on an ontology • This approach was taken with the Federal Enterprise Architecture Reference Models to produce an ontology that has been released. • http://web-services.gov/fea-rmo.html
2.3 The Content • Indexing, categorization, and relationship linking. • Indexing, keyword/concept extraction, and taxonomy. • Same as (2).
2.4 The Pilot • A Recommended Start to the NHIN Ontology: • The European Interoperability Framework: • Organisational • Technical, & • Semantic • Leavitt see interoperability: ..interoperability should be organically grown through the "messy, complex, difficult process called collaboration.” • http://www.fcw.com/article88110
2.4 The Pilot • Tools: • Selection Criteria: • Selected for participation in the SWANS Conference, April 7-8, 2005, because of support for Semantic Technologies (RDF/OWL). • Willing to provide hardware, software, and advice for proof of concept. • Two or more vendors initially – more after SWANS Conference • Selection: • NextPage FolioViews and LivePublish (recently acquired by FAST Search & Transfer) • FAST Data Search and ProPublish • http://www.fastsearch.com • Content Analyst • http://www.contentanalyst.com
2.4 The Pilot • Ontology Expertise: • Ontolog Forum: • Submitted Response to the RFI • Available on the Internet • Providing Ontology Engineering Advice • Suggests Brainstorming Session • Proposed New SICoP Ontology and Taxonomy Coordinating Work Group (ONTACG)
2.5 Sample Results http://web-services.gov, See Best Practices
2.5 Sample Results http://web-services.gov, See Best Practices
2.5 Sample Results http://web-services.gov, See Best Practices
2.5 Sample Results http://web-services.gov, See Best Practices
2.5 Sample Results Folio Views Infobase of RFI’s
2.5 Sample Results Content Analyst: Compute Taxonomy
2.5 Sample Results Content Analyst: Run Queries
2.5 Sample Results Content Analyst: Set Training Documents
2.5 Sample Results FAST ProPublish: Production Manager
2.5 Sample Results FAST ProPublish: Build Progress
2.5 Sample Results FAST Data Search: Search View
2.5 Sample Results FAST Data Search: Taxonomy Results Saved in Excel Spreadsheet
2.6 Next Steps • NHIN Suggest a Series of Queries: • Results can be provided in Excel spreadsheets for further analysis and reuse • Add content from those agencies interviewed by the FHA Interoperability Work Group recently: • VA, DoD, EPA, CDC, FDA, NIH-NCI/DHS/HIS • See future demonstrations with the initial public domain databases for semantic searching and ontology building (see next slide): • SWANS Conference, April 7-8, 2005 • SICoP Meeting at KM Conference, April 22, 2005
2.6 Next Steps Initial Public Domain Databases for Semantic Searching and Ontology Building
Appendices • A. Ontology Engineering • B. FAST Data Search and ProPublish • C. Content Analyst
Appendix A: Ontology Engineering • A.1 What Is An Ontology? • A.2 Basic Requirements For an Ontology • A.3 Ontology Examples • A.4 Formal Taxonomies for the U.S. Government • A.5 Medical Informatics Ontologies: Examples and Design Decisions • A.6 GLIF in Protégé • A.7 Why Develop an Ontology? • A.8 Ontology-Development Process • A.9 What Is “Ontology Engineering”? • A.10 Ontology-Driven Information Systems