OpenMRS Concept Management Tutorial

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 ([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

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


● 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


● 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

OpenMRS Concept Management Tutorial

Software