Query Health Concept-to-Codes (C2C) SWG Meeting #9

1. Query Health Concept-to-Codes (C2C) SWGMeeting #9 February 7, 2012

2. Today’s Agenda

3. Proposed Timeline Meeting times extended from 2:30-4:00pm TODAY • Presentation • S&I Repository • Presentation • RELMA (LOINC) • 3M • NY Presbyterian Hospital Vocab Team • Presentation • AHIMA • LexEVS and CTS2 • Jacob Reider - ONC • Tasks • Introductions • Scope • Proposed Approach • Identify SME and presentation timeline for next few meetings • Presentation • hQuery • i2b2 • Presentation • I2b2 (Cont.) • Intermountain Health • DOQS (Data Warehousing / Mapping) • Tasks • Discussion of presentation summaries and extraction of key themes • Presentation • DOQS (Data Warehousing / Mapping) Cont. • PopMedNet • NLM • Presentation • Ibeza • CDISC SHARE • Presentation • NQF –Value Set presentation • Begin Overview of Next steps • Overview of Constrains and Criteria Coordinate offline activities to summarize approaches and develop draft deliverable from presentations

4. Overview of ONC HIT Standards Committee Vocabulary Recommendations Marjorie Rallins, DPM, Director, Specifications, Standards & Informatics, AMA, Physician Consortium for Performance Improvement Floyd Eisenberg, MD Senior Vice President, Health IT, National Quality Forum

5. Outline • Background & Mission • Scope • Definitions • Recommendations • Examples • Challenges & Discussion

6. Background & Mission • Plethora of vocabulary standards • HITSC focused on parsimony • Clinical Quality and Vocabulary WG Mission – Evaluate and recommend a minimum set of vocabulary standards that apply to the fundamental concepts in Quality Data Model v.3 (QDM)

7. Scope • Scope: • Reporting of clinical-quality measures • Facilitate standardized information exchange • Out of Scope: • Intra-organization information management • Reporting to other external entities

8. Desiderata for Standard Vocabularies • Circa 1998, JJ Cimino MD, described desiderata for the design of a healthcare vocabulary; • Seminal work • http://www.ncbi.nlm.nih.gov/pubmed/9865037 • Desiderata contributed to WG considerations

9. Content (comprehensive strategy to address gaps) Unique identifier Polyhierarchy Formal definitions (semantic network) Reject NEC, NOS Evolve gracefully Concept orientation Concept permanence (no deletions; provide history) Multiple levels of granularity/detail Consistency in meaning along the heirarchy Desiderata

10. Desiderata for Standard Vocabularies • Interdisciplinary relevance • Minimum necessary Maturity • Logical (hierarchical data model vs. flat structure) • Technical (eg meaningless identifiers)

11. Desiderata for Standard Vocabularies • Maximum expected useful Life Expectancy • Quality of current and ongoing duration • Maximum ability to accommodate Innovation • Serves the maximum number of needs, eg: • Intra-organizational clinical and administrative needs • Quality reporting • Reporting to public health agencies • Safety reporting

12. Transition Vocabularies -Rationale • Requiring the immediate, exclusive use of some standard vocabularies might be so burdensome as to compromise clinical-quality measure (CQM) reporting. • Identify acceptable transition vocabularies for specific data categories of the Quality Data Model (QDM)—to support CQM reporting. • Scope: Recommendations for transition vocabularies do not apply beyond the domain of CQM reporting.

13. Recommended SNOMED CT LOINC RxNorm ICF UCUM CVX CDC PHIN VADS (HL7) ISO 639 PHDC Payor Typology Transition ICD-9-CM ICD-10-CM ICD-10-PCS Current Procedural Terminology, CPT® HCPCS Vocabulary Summary

14. Recommended SNOMED CT LOINC RxNorm ICF UCUM CVX CDC PHIN VADS (HL7) ISO 639 PHDC Payor Typology Transition ICD-9-CM ICD-10-CM ICD-10-PCS Current Procedural Terminology, CPT® HCPCS Vocabulary Summary

15. Definitions: SNOMED CT Systematized Nomenclature of MedicineClinical Terms® A comprehensive clinical terminology developed by the College of American Pathologists (CAP); now owned and maintained by International Health Terminology Standards Development Organization; > 310,000 active concepts > 790,000 active descriptions or names & synonyms > 920,000 relationships -Released semi-annually in Jan & July -Developed & maintained by clinicians

16. Concepts Hierarchies/Trees Parent/child relationships Relationships between concepts Clinical finding (disorders and findings) Procedure Body structure Substance Organism Qualifier value Situation with explicit context Physical object (devices) Observable entity Staging and scales Several others…. Definitions: SNOMED CT

17. Definitions: SNOMED CT • Incorporated into healthcare applications • Manual lookup and coding • Transparent to the user

18. Definitions: LOINC Logical Observation Identifiers Names and Codes® A universal code system that facilitates exchange, pooling and processing of results; Laboratory LOINC – Lab results and observations Clinical LOINC – Clinical results and observations Name partitioned into segments to coordinate with messaging standards Developed and maintained by the Regenstrief Institute

19. Definitions: LOINC If an observation is a question and the observation value is an answer… LOINC provides codes for questions Other terminologies provide codes for answers1 1https://loinc.org/slideshows/lab-loinc-tutorial/files/loinc-overview-and-introduction-current.pdf/index_ html?portal_status_message=Welcome%21+You+are+now+logged+in.

20. Definitions: LOINC What is my patient’s hemoglobin level? 718-7:Hemoglobin:MCnc:Pt:Bld:Qn LAB LOINC How fast does my patient usually walk? 41959-8:Walking speed:Vel:1W^mean:^Patient:Qn:Calculate2 Clinical LOINC Answers in SNOMED CT: 165447008 mean corpuscular hemoglobin concentration (MCHC) - low (finding) 16526500walks 30-59 meters in 1 minute (finding) 2https://loinc.org/slideshows/lab-loinc-tutorial/files/loinc-overview-and-introduction-current.pdf/index_ html?portal_status_message=Welcome%21+You+are+now+logged+in.

21. Definitions: RxNorm RxNorm: A standardized nomenclature that provides names and identifiers for clinical drugs Scope: Clinical drugs: administered to patients for therapeutic or diagnostic intent; eg Injectable solution vs Powder for dilution Purpose: Allow various systems using different drug nomenclatures to share data efficiently at the appropriate level of abstraction Produced by the National Library of Medicine (NLM). Semantic Clinical Drug (SCD CUI) for reporting performance measures

22. Definitions: CVX, ICF, PHDC, PHIN VADS

23. Definitions, ISO, UCUM

24. Definition: Quality Data Model • The Quality Data Model (QDM) is an “information model” that clearly defines concepts used in quality measures and clinical care and is intended to enable automation of electronic health record (EHR) use. It provides a way to describe clinical concepts in a standardized format so individuals (i.e., providers, researchers, measure developers) monitoring clinical performance and outcomes can clearly and concisely communicate necessary information. • The QDM describes information so that EHR and other clinical electronic system vendors can consistently interpret and easily locate the data required 1 1http://www.qualityforum.org/Projects/h/QDS_Model/Quality_Data_Model.aspx

25. Recommendation

26. Recommendation

27. Recommendation

28. Recommendation

29. Recommendation

30. Recommendation

31. Recommendation

32. Recommendation

33. Recommendation

34. Recommendation

35. Transition Vocabularies *Final Date, relevant for reporting of quality measure results only. Not relevant for other purposes, eg, claims reporting.

36. Transition Vocabularies *Final Date, relevant for reporting of quality measure results only. Not relevant for other purposes, eg, claims reporting..

37. Examples Demonstrate with examples- • ”Fictitious/mock” measures - used for demonstration purposes only • no association with guidelines, standards of care, measure steward • Demonstrate use of vocabularies rather than comprehensive QDM modeling and logic

38. Measure 1 • Percentage of patients age 18 years and older with a diagnosis of peripheral vascular disease, with symptoms of neuropathy, who received an assessment of foot sensation using a standardized assessment tool with findings communicated to primary care physician

39. Measure 1 • Percentage of patients age 18 years and older with a diagnosis of peripheral vascular disease, with symptoms of neuropathy who received an assessment of footsensationusing a standardized assessment tool with findings communicated to primary care physician

40. Percentage of patients age 18 years and older with a diagnosis of peripheral vascular disease, with symptoms of neuropathy who received an assessment of footsensationusing a standardized assessment tool with findings communicated to primary care

41. Measure 2 • Percentage of patients age 18 years and older with a diagnosis of peripheral vascular disease who have a foot ulcer and received a culture and sensitivity and were prescribed a 3rd generation cephalosporin

42. Measure 2 • Percentage of patients age 18 years and older with a diagnosis of peripheral vascular disease who have a foot ulcer and received a culture and sensitivity and were prescribed a 3rd generation cephalosporin

43. Percentage of patients age 18 years and older with a diagnosis of peripheral vascular disease who have a foot ulcer and received a culture and sensitivity and were prescribed a 3rd generation cephalosporin

44. Challenges • Gaps in terminology, eg LOINC, SNOMED CT • Transition recommendations, adoption, traction rather than gaps

45. Current SWG Tasksand Next Steps

46. Current Focus and Next Steps Dec 2011– February 2012 Current SWG Focus Conduct Environmental Scan C2C Output Summary of Various Approaches taken by Organizations Identification of Key Themes and Industry Best Practices Standards Tools Distributed Query Networks List of Constraints to analyze Best Practices for QH within the Technical framework Value Sets Next Steps* Suggested Outputs Suggested Inputs Task Team Feb 2012 - TBD Develop Technical Expression of C2C C2C Output / Recommendation Technical Expression of C2C Approach as it Aligns with the Reference Implementation C2C / Technical Selection of Existing Value Set in Alignment with the QH CEDD Align Proposed Technical Expression with Existing Value Set(s) and Vocabulary Task Force Recommendations Technical Expression of C2C Approach Technical Identify and assign Value Sets for a core set of data elements within the Harmonized QH CEDD as part of the Cross Walk Harmonized CEDD and Selected Value Set Clinical CEDD Identified Value Set Representations for core set of DataElement in the CEDD Reference implementation Guidance for QH Identify standardized approach to store and access Value Set(s) Value Set Representation Technical * Steps are not in sequential order

47. Criteria and Constraints • The approach must be easily implemented as part of the Technical Framework. • The Reference Implementation has to easily be able to use the mappings and the Value Sets . • Utilize NQF as starter Value Sets per Jacob Reider’s recommendation • Additional Value Sets can be identified and included as needed • Value set representation should utilize NQF and the IHE SVS • Integrating the Healthcare Enterprise -Sharing Value Sets (IHE SVS) Profile can be thought of as a Value Set Repository that houses Value Sets • IHE SVS provides a standardized, easy to use, RESTful interface to the value set • Potential mechanisms to import Value Sets as part of the Reference Implementation should be identified (ex. - Excel or another format?) • Each participating organization within the query network should consider operational best practices for ongoing updates and maintenance of Value Set • Value Set Owners are expected to perform ongoing maintenance of Value Sets