1. Standards Influenced Research Information Systems InteroperabilitySession One: Information Modeling AbdulMalik Shakir, Information Management Strategist City of Hope, Duarte, CA
2. About Me Abdul-Malik Shakir Information Management Strategist with City of Hope Principal Consultant with Shakir Consulting HL7 Member since 1991 Co-Chair of the HL7 Education Workgroup Member of the HL7: Architectural Review Board Public Health and Emergency Response Workgroup Regulated Clinical Research Information Management Workgroup Modeling and Methodology Workgroup Member of the BRIDG Board of Directors since January 2010 Modeling Facilitator for CTR&R, SAP, STDM, and caEHR May 2010 2 Standards Influenced Research Information Systems Interoperability
3. Research Informatics Systems Engineering May 2010 3 Standards Influenced Research Information Systems Interoperability
4. Session Overview Domain Analysis Modeling The Value of Modeling What is a Domain Analysis Model (DAM) What is the Unified Modeling Language (UML) Biomedical Research Integrated Domain Group (BRIDG – Domain Analysis Model) HL7 Clinical Trail Registration & Results DAM Requirements Gathering BRIDG DAM Mapping BRIDG Subset Definition COH Semantic Interoperability Infrastructure Metadata Services Terminology Services Ontology Services Rule Services May 2010 4 Standards Influenced Research Information Systems Interoperability
5. Domain Analysis Modeling PARTY IDENTIFICATION NUMBER PARTY PARTY ACTIVITY ROLE Identification Number Begin Date Issuing Authority Name End Date Issue Begin Date Role Code Issue End Date CASE DEFINITION PARTY CASE DEFINITION ROLE Type Code Begin Date Begin Date Category Code End Date Description Role Code End Date PATIENT COVERAGE Name Provider Code PARTY CASE ROLE Begin Date End Date Role Code BILLING ACCOUNT PARTY NOTIFICATION CASE Begin Date Begin Date End Date Confirmation Method Code PARTY TO PARTY ASSOCIATION Notification Receiver Identification Number Count Notification Sender Identification Number Begin Date Count Type Code Code Detection Method Code End Date End Date Identification Number Transmission Mode Code Status Code Status Date PUBLIC HEALTH NOTIFICATION Begin Date End Date Identification Number Reason Code ORGANIZATION INDIVIDUAL Entity Alias Name Name Name Type Type Code Outbreak Begin Date DIAGNOSIS End Date PARTY CONDITION Classification Scheme Code Extent Code Disease Code Begin Date Peak Date Diagnosis Code Description Diagnosis Date End Date Source Code Name Source Text Name Status Text PERSON NON PERSON LIVING ORGANISM INFORMAL ORGANIZATION Formal Organization Status Date OUTBREAK STATISTIC Birth Date Genus Name Industry Code Death Date Species Name Amount Ethnicity Code Category Code PARTY LOCATION ROLE Race Code Type Code Begin Date Sex Code End Date Soundex Text Role Code Occupation Name Status Code Status Date PARTY SPECIMEN ROLE PERSON NAME Begin Date Degree Name End Date First Name Role Code Last Name Middle Name Prefix Name Suffix Name Type Code PARTY VEHICLE ROLE Begin Date End Date Role Code VEHICLE HEALTH RELATED ACTIVITY Description Begin Date Time Name Disposition Date Time (Implication) Status Code Disposition Description Status Date End Date Type Code Identification Number Notification Indicator Priority Code Source Type Code DISEASE ASSOCIATION Type Code LOCATION Disease Code Address Disease Imported Code Identification Number Etiologic Status Code Name Etiologic Status Date VEHICLE CONDITION Setting Code Exposure Begin Date Type Code Description Exposure End Date Description Status Code Infection (or Illness) Type Code(s) Status Date SPECIMEN LOCATION Begin Date End Date TEST REFERENCE TABLE Method Code Name Samples Required Number Samples Required Unit Code SPECIMEN Type Code Collection Date DISEASE CAUSING AGENT Description Agent Type Code TEST Identification Number HEALTH STATUS INQUIRY INTERVENTION Agent Name REFERRAL Name Amount Amount Referral Basis Code Source Code Amount Unit Code Amount Number Referral Type Name Type Code Begin Date Amount Unit Code Referral Acceptance Code Description Description Description Code Duration ADDRESS TELEPHONE Duration Duration Unit Code Begin Date Telephone Type Code Duration Unit Code Enrollment Code City Name Area Code End Date Enrollment Type Code Country Name Number Live Births Number Manufacturer Lot Number County Name Manufacturer Lot Number Manufacturer Name End Date Manufacturer Name Name Postal Code Reason Text Route Code TEST RESULT CODE Status Date Result Date Status Code Amount State Code Code Result Text Status Date Amount Unit Code Street Address Text Description Status Code Code Type Code Coding System Name Status Date Date Travel Country Name Description Type Code Description Code May 2010 5 Standards Influenced Research Information Systems Interoperability
6. Why Model To aid in understanding relevant functions and information needs of a particular domain To communicate the modeler’s understanding of the domain and allow that understanding to be assessed by others To aid in reconciling multiple perspectives of a domain by combining varying perspectives into a single specification To document a solution design (existing or planned) so that the design may be evaluated May 2010 6 Standards Influenced Research Information Systems Interoperability
7. Do you play football? Yes, I do play football. Revealing assumptions is an essential component of effective communication. Data models are an effective means of documenting our assumptions about a domain Reveal Assumptions May 2010 7 Standards Influenced Research Information Systems Interoperability
8. Reduce Ambiguity A B 0..* 1 0..* 0..* C Modeling provides a language that allows us to unambiguously express our understanding and assumptions about the actions and information of interest in a particular domain May 2010 8 Standards Influenced Research Information Systems Interoperability
9. Reconcile Conflicts X B A B 0..* 0..* 1 1 0..* 0..* 0..* 0..* C C Sharing models provides an opportunity to identify and reconcile conflicts in our understanding and to validate our assumptions. May 2010 9 Standards Influenced Research Information Systems Interoperability
10. Expand Understanding A B A B 0..* 1 0..* 0..* 0..* 1 0..* 0..* C D Sharing models also provides an opportunity to identify gaps in our understanding. No one of individual has the complete view of domain of interest. May 2010 10 Standards Influenced Research Information Systems Interoperability
11. Consolidate Ideas A B X B A B 0..* 1 0..* 0..* 0..* 1 0..* 1 0..* 0..* 0..* 0..* C D C B G E 0..* 1 0..* 1 0..* 1 D X F C A 0..* 0..1 0..* 1 Model I Model II Model III May 2010 11 Standards Influenced Research Information Systems Interoperability
12. Value of Modeling Reveal Assumptions Reduce Ambiguity Reconcile Conflicts Expand Understanding Consolidate Ideas May 2010 12 Standards Influenced Research Information Systems Interoperability
13. What is a Domain Analysis Model A Domain Analysis Model (DAM) is a conceptual model used to depict the behavioral and static semantics of a domain of interest. A DAM provides an opportunity for subject matter experts (SMEs) within a particular domain to integrate and harmonize their perspectives regarding the use cases, activities, and information needs of their shared domain. A DAM is particularly useful when used in a domain with broad interests and a diverse population of SMEs. 13 May 2010 Standards Influenced Research Information Systems Interoperability
14. Domain Analysis Model Use A domain analysis model is used as reference material in development of information system interoperability specifications as well as design specifications of information system components The DAM is a requirement specification and is the primary artifact from which information system design specifications are derived. The preferred language for expression of a domain analysis model is UML. 14 May 2010 Standards Influenced Research Information Systems Interoperability
15. Unified Modeling Language (UML) UML is a standardized general-purpose modeling language in the field of software engineering. UML is not a development method; however, it was designed to be compatible with the leading object-oriented software development methods. UML includes a set of graphical notation techniques to create visual models of software-intensive systems. 15 May 2010 Standards Influenced Research Information Systems Interoperability
16. UML Diagram Types May 2010 16 Standards Influenced Research Information Systems Interoperability
17. Domain Analysis Model Diagrams 17 May 2010 17 Standards Influenced Research Information Systems Interoperability
18. Biomedical Research Integrated Domain Group 18 May 2010 Standards Influenced Research Information Systems Interoperability
19. From Data Requirements to HL7 Message May 2010 19 Standards Influenced Research Information Systems Interoperability
20. Requirements Mapping to BRIDG May 2010 20 Standards Influenced Research Information Systems Interoperability
21. BRIDG Subset to CTRR DAM May 2010 21 Standards Influenced Research Information Systems Interoperability
22. CTRR DAM to CTRR HL7 Message RMIM May 2010 22 Standards Influenced Research Information Systems Interoperability
23. CTRR HL7 Message RMIM to HMD May 2010 23 Standards Influenced Research Information Systems Interoperability
24. CTRR HL7 MESSAGE HMD TO CTRR.XSD May 2010 24 Standards Influenced Research Information Systems Interoperability
25. From Requirements to HL7 Message May 2010 25 Standards Influenced Research Information Systems Interoperability
29. May 2010 29 Standards Influenced Research Information Systems Interoperability
30. AbdulMalik Shakir Information Management Strategist City of Hope 1500 E. Duarte Road Duarte, CA 91010 Office: (626) 256-4673 x63160 Mobile: (626) 644-4491 Email: AShakir@COH.org May 2010 30 Standards Influenced Research Information Systems Interoperability
Editor's Notes
Talking Points:Areas covered include but are not limited to: protocols, studies, study sites, organization and org roles, people and people roles, study subjects, study activities (e.g. subject enrollment, specimen collection, lab work, etc.) , products, study design, documents, regulatory artifacts