# 1 clinical element models (cems) sharp f2f meeting mayo clinic june 21, 2010 stanley m huff, md
TRANSCRIPT
# 1
Clinical Element Models (CEMs)
SHARP F2F MeetingMayo Clinic
June 21, 2010
Stanley M Huff, MD
# 2
A Simple Model
Use of detailed clinical models in SHARP
• Guide for data normalization widgets
• Target for structured output from NLP
• Logical structure for data payload in NHIN Connect services
• Reference for data that participates in the phenotype logic and queries
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Model Classes Created
• Patient, Employee, Provider, Organization, ContactParty, PatientContact (visit), ServiceDeliveryLocation, AdmitDiagnosis
• HealthIssue (Problem), Allergy, Intolerance, Document• Order
– OrderLab, OrderLabMicro, OrderBloodProduct
– OrderMedAmb, OrderMedCont, OrderMedInt, OrderMedPCA, OrderMedReg
– OrderNutrition, OrderRadiology, OrderNursing, OrderRepiratory, OrderTherapies
• LabObs, MicroLabObs, Assert, Eval, Meas, Proc• Qualifiers, Modifiers (Subject), Attributions, Panels
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Model Subtypes Created
• Number of models created - 4384– Laboratory models – 2933– Evaluations – 210– Measurements – 353– Assertions – 143– Procedures – 87– Qualifiers, Modifiers, and Components
• Statuses – 26• Date/times – 27• Others – 400+
– Panels – 79
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Access to the models
• Send me an email and I will send you a zip file–[email protected]
• Web browser–www.clinicalelement.com
–Works best with Mozilla Firefox browser
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70
What if there is no model?
Dry Weight:Site #1
kg
Weight:Site #2
DrykgWetIdeal
70
7070
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Relational database implications
How would you calculate the desired weight loss during the hospital stay?
Patient Identifier
Date and Time Observation Type Observation Value
Units
123456789 7/4/2005 Dry Weight 70 kg
123456789 7/19/2005 Current Weight 73 kg
Patient Identifier
Date and Time Observation Type
Weight type Observation Value
Units
123456789 7/4/2005 Weight Dry 70 kg
123456789 7/19/2005 Weight Current 73 kg
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Model Centered Data Representation
Models
Models and Concepts
SNOMED ICD-10RxNormFDBLOINC CPT
SNOMED ICD-10RxNormFDBLOINC CPT
LexGrid Terminology Server
Context SpecificMapping Tables
ECIS Thesaurus
MayoThesaurus
InternalTerminology(ECIDS)
IHThesaurus
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We assume that the model is used in
association with a terminology server.
Model and TerminologyModel and Terminology
MedicationOrder {MedicationOrder {
drug PenVK,drug PenVK,
dose 250,dose 250,
route Oral,route Oral,
frequency Q6H,frequency Q6H,
startTime 09/01/95 10:01,startTime 09/01/95 10:01,
endTime 09/11/95 23:59,endTime 09/11/95 23:59,
orderedBy Don Jones, M.D.,orderedBy Don Jones, M.D.,
orderNumber A234567 }orderNumber A234567 }
Instance dataInstance data
MedicationOrder ::= SET {MedicationOrder ::= SET {
drug Drug,drug Drug,
dose Decimal,dose Decimal,
route DrugRoute,route DrugRoute,
frequency DrugFrequency,frequency DrugFrequency,
startTime DateTime,startTime DateTime,
endTime DateTime,endTime DateTime,
orderedBy Clinician,orderedBy Clinician,
orderNumber OrderNumber}orderNumber OrderNumber}
ModelModel
If the medicationOrder.drug is_a “antibiotic” then notify the infection control officer.
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Concept Semantic Network
Drugs
Antibiotics Analgesics Cardiovascular
Penicillins AminoglycosidesCephalosporins
Pen VK Amoxicillin Nafcillin
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Denormalized Semantic Network
Drugs has-child AntibioticsDrugs has-child AnalgesicsDrugs has-child CardiovascularAntibiotics has-child PenicillinsAntibiotics has-child CephalosporinsAntibiotics has-child AminoglycosidesPenicillins has-child Pen VKPenicillins has-child AmoxicillinPenicillins has-child Nafcillin
Drugs has-member Antibiotics Drugs has-member PenicillinsDrugs has-member Pen VKDrugs has-member AmoxicillinDrugs has-member Nafcillin
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Mods and Quals of the Value Choice
• Mods - Component CE’s which change the meaning of the Value Choice.
• Quals - Component CE’s which give more information about the Value Choice.
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A Panel containing 2 Observations
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The use of Qualifiers
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The use of Modifiers
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XML Model with Term Binding
<cetype name="BloodPressurePanel" kind="panel"> <key code="BloodPressurePanel_KEY_ECID" />
<item name="systolicBloodPressureMeas" type="SystolicBloodPressureMeas" card="0-1" /> <item name="diastolicBloodPressureMeas" type="DiastolicBloodPressureMeas" card="0-1" /> <item name="meanArterialPressureMeas" type="MeanArterialPressureMeas" card="0-1" /> <qual name="methodDevice" type="MethodDevice" card="0-1" /> <qual name="bodyLocationPrecoord" type="BodyLocationPrecoord" card="0-1" /> <qual name="bodyPosition" type="BodyPosition" card="0-1" /> <qual name="relativeTemporalContext" type="RelativeTemporalContext" card="0-M" /> <qual name="patientPrecondition" type="PatientPrecondition" card="0-M" /> <mod name="subject" type="Subject" card="0-1" /> <att name="observed" type="Observed" card="0-1" /> <att name="reportedReceived" type="ReportedReceived" card="0-1" /> <att name="verified" type="Verified" card="0-1" /> …</cetype>
The name of this model
Binding to a single “observable” concept
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Binding to a “domain” (value set)
<constraint path="qual.methodDevice.data.cwe.domain" value="BloodPressureMeasurementDevice_DOMAIN_ECID" />
<constraint path="qual.bodyLocationPrecoord.data.cwe.domain" value="BloodPressureBodyLocationPrecoord_DOMAIN_ECID" />
Path to the coded element
The name of the terminology “domain” that the element is “bound” to
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Compiler
CEML
Source
File
CEML
Source
File
CETranslator
CETranslator
“In Memory” Form“In Memory” Form
HTMLHTML
UML?UML?
openEHR Archetype?openEHR Archetype?
HL7 RIM Static Models?HL7 RIM Static Models?
Java ClassJava Class
XML TemplateXML Template
OWL?OWL?
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Decomposition Mapping
data 138 mmHg
SystolicBPRightArmSittingSystolicBPRightArmSittingObs
data 138 mmHg
quals
SystolicBPSystolicBPObs
data Right Arm
BodyLocationBodyLocation
data Sitting
PatientPositionPatientPosition
Precoordinated Model (User Interface Model)
Post coordinated Model (Storage Model)
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How much data in a single record?
• “Chest pain made worse by exercise”– Two events, but very close association– Normally would go into a single finding
• “Ate a meal at a restaurant and 30 minutes later he felt nauseated, and then an hour later he began vomiting blood.”– Discrete events with known time and potential causal
relationships– May need to be represented by multiple associated
findings
• Semantic links are used to represent relationships between distinct event instances
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Representation of Semantic Links
InstanceId 1 Relationship InstanceId 2
(123) Nausea followed-by (987) Vomiting
• Semantic links can also have certainty and attribution– Certainty– Attribution (who or what asserted the relationship,
when, and why?)
Area 6 Discussion and Planning
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Detailed Model
Facility a
Normalized Data Instances
EDW Staging
ETL
ETL + Rules
Analytic Health
Repository
Decision Support
HTACER QI CDS
Canonical EMR+Normalized
Data Instances
Facility b
Normalized Data
Instances
Using NHIN for transmitting data
Terminology Services (including CEMs)
Terminology, Models, Logic, NLP Semantics, etc.
And the Internet for managing Content Internet
NHIN
NLP WidgetsNLP WidgetsNLP WidgetsNLP WidgetsNormalization Normalization
WidgetsWidgetsNLP WidgetsNLP WidgetsNLP WidgetsNLP WidgetsNormalization Normalization
WidgetsWidgets
Discussion• Evaluation projects
– Sharing data through NHIN Connect and/or NHIN Direct• What, who, when, where?
– Comparison of data processed through SHARP to data in existing Mayo and Intermountain data trust, EDW, AHR
• What, who, when, where?– Others?
• Evaluation of NLP outputs and value? Focus on a specific domain: X-rays, operative notes, progress notes, sleep studies?
• Questions– What is the target set of normalization widgets that we want to build?– Can we do the evaluations on de-identified data?– Do we need patient consent to do the evaluations?– Others?
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