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Clinical Element Models (CEMs)

SHARP F2F MeetingMayo Clinic

June 21, 2010

Stanley M Huff, MD

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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–stan.huff@imail.org

• 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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