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OpenMRS Concept Management Tutorial
- 1. Andrew S. Kanter,MD MPH FACMIa,b,c a Intelligent Medical Objects, Inc., Chicago, USA b Department of Biomedical Informatics, Columbia University, New York, NY, USA c Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA Ellen Ball Partners In Health, Boston, USA OpenMRS Concept Management OpenMRS Worldwide Summit 9 December 2015 Singapore
- 2. Topics • Terminology 101 •OpenMRS data model and concepts • Controlled terminology and reference mappings • Management of concept dictionary • Usage on forms and reports • Future
- 3. Introduction and Disclosure •Andy ([email protected]) • OpenMRS Leadership (Terminology and Meta Data Lead) • Direct Columbia International eHealth Lab • Department of Biomedical Informatics • Department of Epidemiology/MSPH • Board Member/Director of Clinical Integration for Intelligent Medical Objects (IMO) •Ellen ([email protected]) •Implemented OpenMRS at Partners In Health Haiti, Rwanda, Lesotho, Malawi, Peru, Liberia, and Sierra Leone
- 4. Terminology 101 Terminology aboutterminology (independent of OpenMRS)
- 5. Why vocabulary matters… ●Clinical users of EHRs resist the constraints of structured documentation ● Users and administrators underestimate the complexity and difficulty of data mining ● Data is dirty, misplaced, and/or incomplete ● Humans think conceptually, systems store data literally ● Everything we want to do depends on how meaning is recorded in the information system. Clinical intent is paramount and you get one chance to capture it correctly!
- 6. Terminology Reporting/data mining Clinical datamodel Decision support Clinical data entry/review Informatics Infrastructure
- 7. The Interoperability-Adoption Tug-of-War ●Interoperability requires standards and limited scope ● Adoption favors customization and local preferences producing broad scope
- 8. Terminology about Terminology ●Concepts and Concept Dictionary ● Descriptions—strings, terms, lexicals, CONCEPT_NAME ● Words—keywords, index terms ● Relationships—maps, CONCEPT_REFERENCE_MAP ● Administrative codes ● Reference terminology ● Interface terminology ● Groups—value sets, convenience sets
- 9. Terminology about Terminology(cont) ● Domains ● Granularity—broader vs. more specific ● Pre-coordination ● Post-coordination
- 10. Concepts ● The actualmeaning is a phrase or even a paragraph. ● Developed at the right level for the user ● Severe right knee pain ● Liver dysfunction ● Can have many different descriptions but all have the same meaning ● Assigned a non-sensical numeric identifier ● Meaning often developed through relationships to other concepts ● One description often flagged as the default name
- 11. Concepts ● Goal: defaultdescription (fully specified name) sufficient to understand the concept ● Unambiguously defined ● Have one domain ● Can provide more semantics around concept than default description ● Fully specified name includes appended domain, e.g., cough (finding) vs. cough (symptom)
- 12. Descriptions ● A collectionof text strings or terms ● perennial allergic rhinitis ● seasonal allergies (hay fever) ● allergic rhinitis, seasonal ● hay fever ● perennial rhinitis ● perennial allergies ● …
- 13. Descriptions ● May needcontext for full understanding ● Fever ● Patient reported they felt feverish ● Patient reported they took their temperature with thermometer ● Healthcare provider took temperature and was elevated to… ● Acronym - Careful— ARV = “Anti-rabies vaccination” or “Antiretroviral”? ● Pragmatics ● Brain tumor ● malignant neoplasm of brain/Neoplasm of brain/Brain mass ● Breast CA ● Breast cancer / Breast carcinoma
- 14. Description attributes ● Uniquecode ● Audience ● MD, ancillary health, patients ● Length (cell phone, etc.) ● Search friendly (word order important) ● Display to user vs. recognize as mapped to concept ● Locale, language, country, etc.
- 15. Case style ● Rightcase** ● CHF (congestive heart failure) ● Sentence case* ● Spine fracture ● Title case ● Spine Fracture ● Upper case ● SPINE FRACTURE
- 16. Words ● Definition ● Notobvious ● Alphanumerics separated by non-alphanumerics ● What about apostrophes like Alzheimer’s or peau d’orange? ● Words ensure consistency with searching ● Not every concept will have a description with all misspellings or word variants ● Hepatic failure vs. liver failure
- 17. Relationships and Mappings ●One of the defining features of an ontology, i.e., relationships between concepts ● Drawing the lines between concepts or between concepts and codes ● Relationship types ● Can be more complex than parent-child (Is-A) ● “Severe anemia” is narrower-than Anemia ● Other examples, has-location, has-severity, has-laterality
- 18. User interface terminology (descriptions) AMI(alternate term) Myocardial infarction, acute (entry term) Acute MI (alternate term) Acute myocardial infarction (preferred) Reference terminology Acute ischemic heart disease Ischemic heart disease Structural disorder of the heart myocardial disease heart disease disease of cardiovascular system Myocardial infarction Mycardial necrosis Concepts Acute myocardial infarction Words Heart, cardiac, myocardium, myocardial, infarction, CV, attack, AMI, acute, …
- 19. Mappings (type ofrelationship) ● One or more external codes mapped to each concept ● ICD10 code B54.9 ● SNOMED code 2423424211 ● UMLS code C0018621 ● Need relationship type ● Is it broader than, narrower than, same as…? ● Important for inference
- 20. Mappings and Inference ●Malaria ● Same as SNOMED CT 61462000 (Malaria) ● Same as ICD-10 B54 (Unspecified malaria) ● Severe malaria ● Narrower than SNOMED CT 61462000 (Malaria) ● In both eyes ● Narrower than SNOMED CT 54485002 (ophthalmic use)
- 21. Concept-oriented terminologydescriptions concepts Named relationships Descriptionattributes external codes
- 22. Administrative terminology ● Usedprimarily for classification ● Major examples include: ● ICD (ICD-10-WHO, ICD-10-CM, etc.) ● CPT® ● Not particularly good for capturing clinical data ● Often used for billing and reimbursement and some reporting
- 23. Administrative terminology ● ICD-10-CMis now mandated for use in the US as of 10/15 ● Differences between ICD-9-CM, ICD-10 and ICD-10-CM ● 13,000 ICD-9-CM to 68,000+ for ICD-10-CM ● 3-5 digits for ICD-9 compared to 3-7 for ICD-10 ● ICD-9 had only a few alpha codes, all ICD-10 codes start with a letter ● Combination codes for conditions and common symptoms or manifestations and for poisonings and external causes ● Added laterality
- 24. Reference terminology ● Concept-based ●Controlled medical terminology ● Often ontological ● Major examples include: ● SNOMED CT ● RxNorm
- 26. Interface terminology ● Listof terms or phrases ● Supports clinician entry into electronic systems ● Multiple descriptions may mean the same “concept” ● May have unique identifiers ● Major examples include: ● IMO Problem (IT), Procedure (IT) ● Vanderbilt Terminology
- 27. Groups ● Used forproviding a list for user selection ● Used for providing Allergen class-ingredients ● Can be published value set for quality reporting ● Extensional value sets used for meaningful use ● Asthma, active diagnosis with set list of ICD or SNOMED CT codes ● Can be programmatic for decision support ● Intensional value set based on logic such as ● All children of SNOMED code xxxxx ● Includes with children A, B, C but excludes D
- 28. Pre-coordination ● More userfriendly ● Examples ● Acinar cell carcinoma of the pancreas ● Severe right knee pain ● Recurrent intravascular papillary endothelial hyperplasia of the right middle finger ● Recurrent intravascular papillary endothelial hyperplasia of the right ring finger……. ● Combinatorial explosion
- 29. Post-coordination ● Clinical conceptassembled at point of care ● Core concept identified ● Location selected ● Optional severity
- 30. Examples Pre-coordination Post-coordination Acinar cellcarcinoma of the pancreas carcinoma of pancreas + acinar cell carcinoma Severe right knee pain knee pain + right + severe Recurrent intravascular papillary endothelial hyperplasia of the right middle finger intravascular papillary endothelial hyperplasia + middle finger structure + right
- 31. Terminology Process 1. Coreterminology content development including mapping to standards (code mapping) 2. Specialized domain content development (including subsetting of content, expansion of content, etc.) 3. Mapping of user requirements to specific concepts (field mapping) 4. Deployment of content within the software platform (including searching within forms, data capture tools, etc.) 5. Meta-data modeling and information modeling including schema design 6. Ontolological work including building of aggregate indicators and measures (including maps to standard quality measures, etc.) 7. Reporting/Analysis using common algorithms, formulae and concepts 8. Transactional translation or tagging for on-the-fly encoding of concepts including natural language processing
- 32. Class Introductions •Name, role,and organization •Goal for tutorial •Describe problem
- 33.
- 34. OpenMRS concept dictionary •Acollection of concepts •CIEL, PIH, Kenya, etc. •Forks, subsets, and supersets •Local or central management
- 35. Concept creation workflow Paperform, list of data fields, or indicators Concept analysis in existing forms Propose new concept in CIEL or use existing concept Add language, description, synonyms, and mappings
- 36.
- 37. What is anOpenMRS concept?
- 38. Data model: Concepts •concept_id •class •datatype •description •names •fully specified vs preferred name • synonyms • locale
- 39. Data model: Conceptclasses
- 40. Data model: Codedanswers
- 41. Data model: Conveniencesets, etc.
- 42. Data model: Conceptdata type
- 43.
- 44. Data model: Conceptname type
- 45. Data model: Locale ●ISO Language code (en, fr, es, ht, etc) ● Language+country Anemia (en-US), Anaemia (en-GB), Anémie (fr) ● UTF-8
- 46.
- 47. OpenMRS Model: person table:cause_of_death concept concept.causeOfDeath = 9713 global_property table: property_value might be concept concept.cd4 = 5497 person_attribute_type table: name = Civil status format = org.openmrs.concept format_key = 1054
- 48. OpenMRS and TerminologyModel Concept Names (Interface) Concept Codes (Interface) Reference Terms Reference Sources Reference Relationships ICD-10-WHO SNOMED CT LOINC IS-A Has … Concept Map Drugs (Interface)
- 49.
- 50. Leveraging Reference Maps Reasonsfor using shared concepts
- 51. Why not justuse ICD-10 or SNOMED? • Admin/Reference terms change which require changing reports and forms • Clinicians don’t use terms like • Other disease of blood & blood-forming organ • SNOMED is post-coordinated • Hard to say fracture of RIGHT arm
- 52. So why shouldOpenMRS share concepts? • Interoperability of data between applications and between organizations • Ability to share forms, data collection tools • Ability to share reports • Ability to share decision support rules
- 53.
- 54. Leveraging Maps forReporting • There are multiple CIEL concepts mapped to the same ICD or SNOMED code • Use Reference_Reference_Map to build subsumption queries • CIEL/OCL to add map for particular value sets
- 55.
- 56. Managing a conceptdictionary Strategies, translation, etc.
- 57. Concept management scenarios Standalone Allconcepts managed locally PIH Malawi Master/Slave Concepts maintained on central server CIEL with subscription PIH Haiti with mds PIH Rwanda with sync Central Curation Open Concept Lab (OCL)
- 58. CIEL Concept Dictionary •Contains most diseases, procedures and medications (>49,000 concepts) • Mapped to SNOMED CT, ICD-10, 3BT, RxNorm, LOINC and CVX codes. • Several Languages: SNOMED CT 49,514 ICD-10-WHO 40,015 RxNORM 5,599 LOINC 390 3BT 7,703 68,275 en 4001 vi 62 bn 30 rw 32,630 es 2,737 fr 51 ru 29 ht 11,760 nl 242 sw 51 ti 13 am 7 om
- 60. CIEL Included inAppliances
- 61. 311 users in40+ countries CIEL Dictionary via Dropbox
- 62. Dropbox has allversions
- 63. Terminology-related Modules • MetadataSharing Module (MDS) • Validation Module • Terminology Service Bureau
- 64.
- 65.
- 66. Terminology Service Bureau-50,000 concepts
- 67.
- 68.
- 69. Interface Terms forAfrica SNOMED CT English French Kinyarwanda Swahili 271737000 Anemia Anémie Kubura amaraso Upungufu wa damu 87282003 Intestinal parasites Parasitoses intestinales Inzoka Minyoo 61462000 Malaria Paludisme Malariya Homa ya malaria 2492009 Malnutrition Malnutrition Indwara z’imirire mibi Utapia mlo 14189004 Measles Rougeole Iseru Ukambi
- 70. Working with forms HTMLform entry, custom modules
- 71.
- 72.
- 73. Searching DB usingICD or Text
- 74. Example form usingset for UI
- 75. Data model: Conveniencesets, etc.
- 76. Future Open Concept Lab,sustainability
- 77. Open Concept Lab-Jonathan Payne • Beta customer is Kenya EMR • Working with Kenyan Community and ITECH • 9 months behind schedule • Focusing on API then UI • Initial Beta testing complete
- 78. Open MRS OpenMRSSubscription Subscription Process • CreateOCL user to get an OCL API token • Install OCL Subscription Module in your OpenMRS instance and configure to subscribe to a specific source • On first synchronization, pulls entire dictionary • On subsequent synchronization, pulls latest changes only (e.g. new concepts, updates, deletes, retires) • Does NOT overwrite local concepts or concept metadata (based on concept and concept metadata UUIDs) Open Concept Lab OCL API OCL Subscription Module
- 79. Open Concept Lab(OCL)
- 83. OpenHIE and Terminology Management Terminology Management Service 2 1 2 1 • OCLas source of content for the TS. • Requires local TS. • Appropriate for high- volume, real-time transactions (e.g. code validation, lookups, transformations, etc.). • OCL provides canonical source(s) to HIE, subscription service, & collaborative management tool. • NOT for real-time, high- volume transactions. • Alleviates need for local service.
- 84. Terminology Sustainability • Lookingfor additional community leadership (Judy, Jonathan, etc.) • Basic support and funding from Columbia is running out • Looking for sustaining support ($150K/y) • Partnering with OCL/IMO
- 85. Proposed OCL SustainabilityModel FREE BASIC PREMIUM ENTERPRISE Target • Existing CIEL User-base • Researchers, harmonization, terminology geeks • Dictionary managers, e.g. AMPATH, PIH, CIEL • Governments or institutions managing terminology as a core service; require guaranteed level of service Features • Access to all OCL functionality for CIEL dictionary only • Limits on the number of subsets you can create/manage • OpenMRS Subscription to CIEL dictionary • Includes access to CIEL community content • Limited API access • Access to major terminology sources in addition to CIEL (ICD-10, LOINC, SNOMED, etc.) • No limit on collections • Ability to propose content for curation in one of the “managed” dictionaries (i.e. CIEL) • Create your own sources • Full API Access • Guaranteed level of service for terminology curation • Assistance importing local/proprietary terminology sources • Configuration of organizational workspace • Additional training and services available Initial User Base • OpenMRS + CIEL Subscriptions: >100 • MCL: 16k lookups/searchers; 2k unique visitors in last year • THRIVE/WHO • Partners In Health • Kenya Ministry of Health
- 86. OCL Roadmap 2015 Q3 •OCL Launched with Kenya MOH! • Basic functionality complete: –Full-text search –Create users and organizations –Build your own sources and create/edit concepts and mappings –Export of sources using AWS • CIEL dictionary imported • All functionality implemented through APIs • OpenMRS subscription to a single source (e.g. CIEL dictionary) 2015 Q4 • Begin implementing sustainability model and signing up paid clients • Optimized search (e.g. better weighting of search terms to improve likelihood of finding the correct result) • Full support for creating and managing collections (i.e. references to concepts from other sources) • Import WHO ICD-10 source • CIEL transition to managing dictionary on OCL instead of in OpenMRS • Secured access to OCL website and API (e.g. https encryption) • Stability and performance improvements (esp. imports, exports) Potential Future Features • FHIR API compatibility • Import additional sources, including SNOMED CT, LOINC • RSS feeds of changes to sources, collections, and concepts • Social functionality • Improved organization management - better control of access to content for members of an organization • Ability for users to "star" sources, collections, and concepts • Collection/source comparisons • Ability for users to "follow" organizations or other users
- 87. Resources ● Open ConceptLab (OCL) – http://openconceptlab.com ● Maternal Concept Lab (MCL) – http://maternalconceptlab.com ● ICD10 (2016) ○ English http://apps.who.int/classifications/icd10/browse/2016/en ○ French http://apps.who.int/classifications/icd10/browse/2016/fr ● LOINC - https://loinc.org/ ● SNOMED CT- http://http://browser.ihtsdotools.org/ ● OpenMRS modules - https://modules.openmrs.org ○ Metadata Sharing (MDS) ○ Validation ○ Groovy