Transcript
Andrew S. Kanter, MD MPH FACMIa,b,c
a Intelligent Medical Objects, Inc., Chicago, USAb 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 BallPartners In Health, Boston, USA
OpenMRS Concept Management
OpenMRS Worldwide Summit
9 December 2015
Singapore
Topics
• Terminology 101
• OpenMRS data model and concepts
• Controlled terminology and reference mappings
• Management of concept dictionary
• Usage on forms and reports
• Future
Introduction and Disclosure• Andy (ask2164@cumc.columbia.edu)
• 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 (eball@pih.org)
•Implemented OpenMRS at Partners In Health Haiti,
Rwanda, Lesotho, Malawi, Peru, Liberia, and Sierra Leone
Terminology 101
Terminology about terminology (independent of OpenMRS)
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!
Terminology
Reporting/data mining
Clinical data model
Decision support
Clinical data entry/review
Informatics Infrastructure
The Interoperability-Adoption Tug-of-War
● Interoperability requires standards and limited scope
● Adoption favors customization and local preferences producing broad scope
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
Terminology about Terminology (cont)
● Domains
● Granularity—broader vs. more specific
● Pre-coordination
● Post-coordination
Concepts● The actual meaning 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
Concepts● Goal: default description (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)
Descriptions● A collection of text strings or terms
● perennial allergic rhinitis
● seasonal allergies (hay fever)
● allergic rhinitis, seasonal
● hay fever
● perennial rhinitis
● perennial allergies
● …
Descriptions● May need context 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
Description attributes● Unique code
● 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.
Case style
● Right case**
● CHF (congestive heart failure)
● Sentence case*
● Spine fracture
● Title case
● Spine Fracture
● Upper case
● SPINE FRACTURE
Words● Definition
● Not obvious
● 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
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
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
ConceptsAcute myocardial infarction
Words
Heart, cardiac, myocardium, myocardial, infarction, CV, attack, AMI, acute, …
Mappings (type of relationship)
● 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
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)
Concept-oriented terminologydescriptions
concepts
Named relationships
Description attributes
external codes
Administrative terminology● Used primarily 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
Administrative terminology● ICD-10-CM is 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
Reference terminology● Concept-based
● Controlled medical terminology
● Often ontological
● Major examples include:
● SNOMED CT
● RxNorm
Interface terminology● List of 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
Groups
● Used for providing 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
Pre-coordination● More user friendly
● 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
Post-coordination● Clinical concept assembled at point of care
● Core concept identified
● Location selected
● Optional severity
Examples
Pre-coordination Post-coordination
Acinar cell carcinoma 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
Terminology Process1. Core terminology 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
Class Introductions
•Name, role, and organization
•Goal for tutorial
•Describe problem
OpenMRS
Concepts and Data Model
OpenMRS concept dictionary
•A collection of concepts
•CIEL, PIH, Kenya, etc.
•Forks, subsets, and supersets
•Local or central management
Concept creation workflow
Paper form,
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
Which concepts?
What is an OpenMRS concept?
Data model: Concepts
•concept_id
•class
•datatype
•description
•names
• fully specified vs preferred name
• synonyms
• locale
Data model: Concept classes
Data model: Coded answers
Data model: Convenience sets, etc.
Data model: Concept data type
Example numeric concept
Data model: Concept name type
Data model: Locale● ISO Language code (en, fr, es, ht, etc)
● Language+country
Anemia (en-US), Anaemia (en-GB),
Anémie (fr)
● UTF-8
OpenMRS Model
Visit
Encounter
Obs
Concept
visit_id
encounter_id
obs_id
person_id
concept_id
value_coded
value_numeric
value_text
value_boolean
value_drug
value_datetime
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
OpenMRS and Terminology Model
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)
Data model: Drugs
Leveraging Reference Maps
Reasons for using shared concepts
Why not just use 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
So why should OpenMRS 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
Immunization Decision Support
Leveraging Maps for Reporting
• 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
Reporting using maps
Managing a concept dictionary
Strategies, translation, etc.
Concept management scenarios
StandaloneAll concepts
managed locally
PIH Malawi
Master/SlaveConcepts maintained
on central server
CIEL with subscription
PIH Haiti with mds
PIH Rwanda with sync
Central CurationOpen Concept Lab
(OCL)
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
CIEL Included in Appliances
311 users in 40+ countries
CIEL Dictionary via Dropbox
Dropbox has all versions
Terminology-related Modules
• Metadata Sharing Module (MDS)
• Validation Module
• Terminology Service Bureau
Metadata Sharing Module (MDS)
Validation Module
Terminology Service Bureau- 50,000 concepts
Terminology Service Bureau
Terminology Service Bureau
Interface Terms for Africa
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
Working with forms
HTML form entry, custom modules
Example form
HTML form entry
Searching DB using ICD or Text
Example form using set for UI
Data model: Convenience sets, etc.
Future
Open Concept Lab, sustainability
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
OpenMRS
Op
enM
RS
Sub
scri
pti
on
Subscription Process
• Create OCL 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 APIOCL Subscription
Module
Open Concept Lab (OCL)
OpenHIE and Terminology
Management Terminology Management
Service
2
1
2
1
• OCL as 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.
Terminology Sustainability
• Looking for 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
Proposed OCL Sustainability ModelFREE 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
OCL Roadmap2015 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
Resources● Open Concept Lab (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
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