1. A proposal for interoperable health information exchange with two Esperantos: ICF and LOINC® originally presented at: Daniel J. Vreeman, PT, DPT, MSc Assistant Research Professor, Indiana University School of Medicine Associate Director of Terminology Services, Regenstrief Institute, Inc Clinical LOINC Meeting 07/2010Copyright © 2010

2. Quick Refresher on ICF A Brief Introduction

3. LOINC/ICF Modeling Timeline Jan 2005 – ICF/LOINC first discussed Dec 2006 – 2-day workgroup meeting Dec 2006 – Preparation of exemplar LOINC modeling for each ICF component Jan 2007 – Presentation, discussion, refinement of draft at Clinical LOINC Committee Meeting July 2007 – ICF Conference June 2009 – Renewed interest from NCHS June 2010 – Presentation at ICF Conference

4. What is ICF? Classification of health and health-related domains Newest member of WHO Family of International Classifications (ICF, ICHI, etc) Classified from body, individual, and societal perspectives – List of body functions and structures – List of domains of activity and participation Puts disability in a new light – common experience Can express both enabling and limiting factors World Health Organziation. ICF Introduction. Available at: http://www.who.int/classifications/icf/http://www.who.int/classifications/icf/

5. ICF 101 Components Body Functions &Structures Activities&Participation Environmental Factors BarriersFacilitatorsFunctionsStructuresCapacityPerformance

6. ICF 101 Interaction of Components Health Condition (disorder/disease) Environmental Factors Personal Factors Body function&structure (Impairment) Activities(Limitation)Participation(Restriction)

9. Qualifiers Measures assigned after the component category code Placed after the decimal Denote the magnitude of the level of health (e.g. severity of the problem) Without qualifiers, an ICF code has no inherent meaning Can have up to 4 kinds of qualifiers per item (optional)

10. Generic Qualifier Scale

12. Even More Possible Qualifiers

13. Activities/Participation Domain

14. A Proposal for Effective use of ICF and LOINC Making complementary strengths productive

15. General Observations No computer-interpretable version of ICF Links with other vocabularies (UMLS, SNOMED) don’t address qualified codes Several ICF item collections – Full version, short version, ICF-CY, ICF core sets, more… Challenge: ICF classification blends several observation question/answer pairs into 1 code – d410.1302 (changing basic body position) is really 4 “observations”

16. Goals Send a person (or population)’s ICF classification using same machinery as other health data – To reach ICF’s goals, you need to share data Maximize strengths of each terminology (minimize duplication of effort) Be informed by real world use – Need some interested parties! Facilitate addressing challenges in ICF use – Relationship to standardized assessments and clinical measures

17. Original Option 1 Simplest Approach: One LOINC code – NNNN-N:Functioning Classification:Imp:^Patient:Pt:Ord:ICF – Expected “answer” in OBX-5 would be a ICF classification Problems with Simplest Approach – Still have blending of question/answer in OBX-5 – No indications of sets

18. Original Option 2 Full LOINC Modeling including panels for ICF Sets Example: d420 – Transferring oneself – N-N:Transferring oneself.Performance:Imp:^Patient:Pt:Ord:ICF – N-N:Transferring oneself.Capacity:Imp:^Patient:Pt:Ord:ICF – Expected “answers” in OBX-5 would be the ICF qualifiers 0 – No setup or physical help from staff 1 – Setup help only 2 – One person physical assist 3 – Two+ person physical assist 8 – ADL activity itself did not occur during entire 7 days

19. Original Option 2 Problems with this approach – Labor intensive Each ICF component + qualifier combination would be a different LOINC code (assessing different attributes) Keeping up with sets would be very difficult – Some modeling challenges (e.g. anatomy) – Negotiating IP issues

20. New Inspiration

21. Clinical Genomics Model

22. Further Inspiration

23. HL7 CDA Framework for Questionnaire Assessments Specifies a document package representing the full assessment “form” For each observation/answer, enables concurrent transmission of: – Model of Use (LOINC) Exact measurement, as on the assessment – Model of Meaning (SNOMED, ICF) [optional] Representation of the conceptual assertion in another (standard) terminology/classification – Supporting Clinical Observations (LOINC, SNOMED) [optional] Data from the EHR that supports the assessment decision

24. Proposed ICF Result Package in LOINC ICF classification panel ICF collection, population descriptor, observation time period, other descriptors of the observation period ICF classification panel ICF collection, population descriptor, observation time period, other descriptors of the observation period ICF classification results panel ICF component, any applicable qualifiers, fully-qualified ICF item ICF classification results panel ICF component, any applicable qualifiers, fully-qualified ICF item ICF supporting clinical observations panel Any supporting clinical measurements for that ICF classification (direct measures, assessment scores, etc) ICF supporting clinical observations panel Any supporting clinical measurements for that ICF classification (direct measures, assessment scores, etc) 1 to many 0 to many

25. Example ICF Result Package in LOINC R/O/ C Example Answers NN-N ICF classification panel NN-N ICF classification collection RFull NN-N Population description OClinic population >65 years NN-N Duration of observation period OPoint in time NN-N ICF classification results panel R NN-N ICF code stem Rd450 NN-N ICF functioning classification Od450.12 NN-N Activities and participation performance qualifier C1 – MILD difficulty NN-N Activities and participation capacity without assistance qualifier C2 – MODERATE difficulty NN-N ICF supporting clinical observations panel O 59460-6 Morse Fall Risk Total 55 4195703 Mean walking speed 24H 0.9 m/sec 1 to N 0 to N

26. Benefits of Nested Model Uses HL7-LOINC messaging framework while minimizing redundant modeling Accommodates ‘meta-data’ about the result package Flexes to accommodate large or small sets of ICF codes Enables explicit connection between ICF classification and supporting clinical data Accommodates sending alternate identifiers (e.g. UMLS or SNOMED) for ICF components Could also use the ICF classification result panel in another context – nested under a regular clinical observation to convey the higher level interpretation of that result

27. Next Steps Looking for collaborators with live systems that have a need to exchange ICF classifications electronically – And want to used established messaging standards Comments/Suggestions from LOINC Committee