1 Organization, Roles, and Skills Methodology Standards Analysis Tool Evaluation Terminology...

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Organization, Roles, and SkillsMethodologyStandards AnalysisTool Evaluation

Terminology Collaboration

Business Plan

Project IdentificationMission Effect AnalysisFinancial Effect AnalysisRisk Analysis

Business CaseGoals and ObjectivesHigh-Level RequirementsArchitecture

Process DesignFunctional RequirementsNon-Functional RequirementsInfrastructure DeploymentSystem ConfigurationTesting

Phased Implementation

Solution Outline ValidationWhitepaper

Knowledge and Vocabulary Management

Methodology

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Data Standards Development

Map Local Terms to Standards and

Information Model

DocumentData

Requirements

Collect Local Terms

Document and resolve/

disposition issues and gaps

Develop Information

Model

Validate/Refine Information

Model

Approve Enterprise Data

Standards

Identify Domain and

Other Applicable Data standards

Bind Enterprise Data Standards and Information

Model to the Enterprise Data Model

Derive Enterprise Data

Standards

Publish

Communicate

Store

Document Relevant

Meta Data

Distribute

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Change Proposal Process

Access

Search/Browse

Propose Change

Notify Change Proposal

Review DispositionNotify

Disposition

Collaborate/ApproveVocabulary Engineer

Data Stewardship TeamData Governance

Publish

Communicate

Store

Distribute

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Tools

Author and Edit Map Search Browse

ProposeExport

Report Security and AdministrationNotify Publish

Import Manage Proposal

Workflow

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System Context

Operational Systems

Clinical Administrative

Electronic Medical Records

Laboratory Systems

Patient Accounting

Revenue Recognition

Enterprise Learning System

Ordering Systems

Other

External Vocabularies

CPT

LOINC

SNOMED CT

ICD-9

Other

ICD-O

Radiology Systems

Claims and Remittance

WARS

Research and Collaborating Organizations

World Health Organization

HL7

NCICB

NCBO

IBM

caBIG

Analytic Systems

Enterprise Data Trust

Department of Nursing

MAGIC

Finance

Other

DSS

Data Modeling Environment

Enterprise Knowledge and

Vocabulary Management Environment

Models, Vocabularies, Value Sets, and Metadata

Models, Terms, Definition, Synonyms, Examples, etc.

Vocabularies

Models, Vocabularies,Value Sets,

and Metadata

Models,Vocabularies, Value Sets,

and Metadata

User Access point to search and navigate all Metadata, Models, and

Vocabulary (TBD)

Enterprise Managed Meta Data Environment

Vocabularies and Value SetsVocabularies

U Pitt Other

Human Resource Systems

Other

UMLS Metathesaurus

NCI Metathesaurus

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System Context

Operational Systems



Laboratory Systems

Patient Accounting

Revenue Recognition


Ordering Systems

Other


CPT

LOINC

SNOMED CT

ICD-9

Other

ICD-O

Radiology Systems


WARS



HL7

NCICB

NCBO

IBM

caBIG

Analytic Systems



MAGIC

Finance

Other

DSS






Vocabularies


and Metadata


and Metadata


Vocabulary (TBD)



U Pitt Other


Other

UMLS Metathesaurus

NCI Metathesaurus

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System Context

Operational Systems



Laboratory Systems

Patient Accounting

Revenue Recognition


Ordering Systems

Other


CPT

LOINC

SNOMED CT

ICD-9

Other

ICD-O

Radiology Systems


WARS



HL7

NCICB

NCBO

IBM

caBIG

Analytic Systems



MAGIC

Finance

Other

DSS






Vocabularies


and Metadata


and Metadata


Vocabulary (TBD)



U Pitt Other


Other

UMLS Metathesaurus

NCI Metathesaurus

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System Context

Operational Systems



Laboratory Systems

Patient Accounting

Revenue Recognition


Ordering Systems

Other


CPT

LOINC

SNOMED CT

ICD-9

Other

ICD-O

Radiology Systems


WARS



HL7

NCICB

NCBO

IBM

caBIG

Analytic Systems



MAGIC

Finance

Other

DSS






Vocabularies


and Metadata


and Metadata


Vocabulary (TBD)



U Pitt Other


Other

UMLS Metathesaurus

NCI Metathesaurus

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System Context

Operational Systems



Laboratory Systems

Patient Accounting

Revenue Recognition


Ordering Systems

Other


CPT

LOINC

SNOMED CT

ICD-9

Other

ICD-O

Radiology Systems


WARS



HL7

NCICB

NCBO

IBM

caBIG

Analytic Systems



MAGIC

Finance

Other

DSS






Vocabularies


and Metadata


and Metadata


Vocabulary (TBD)



U Pitt Other


Other

UMLS Metathesaurus

NCI Metathesaurus

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System Context

Operational Systems



Laboratory Systems

Patient Accounting

Revenue Recognition


Ordering Systems

Other


CPT

LOINC

SNOMED CT

ICD-9

Other

ICD-O

Radiology Systems


WARS



HL7

NCICB

NCBO

IBM

caBIG

Analytic Systems



MAGIC

Finance

Other

DSS






Vocabularies


and Metadata


and Metadata


Vocabulary (TBD)



U Pitt Other


Other

UMLS Metathesaurus

NCI Metathesaurus

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Terminology Management

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Why Terminology Management?

• Expansion and growth

• Localized decision making for system selection and configuration

• Multiple versions of the electronic medical record

• Fragmentation of patient information within the medical record, something that Dr. Plummer’s unified paper medical record was created to eliminate

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• Differing medical records, clinical systems, and terminology have resulted in diverse clinical processes in the delivery of care.

• Provides considerable challenge as we seek• Enterprise-wide improvements in outcomes

and safety of care• Provision of the best of the entire Mayo Clinic

for each patient• Efficiencies of operation and public reporting

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Standardization of

• Clinical Systems

• Policies

• Core Clinical Processes

• Terminology

Develop and access standardized evidence-based protocols and guidelines

Promote accuracy and Consistency of Patient Care Delivery

Increase Access to Patient Data

Decrease Costs

Improve Patient Outcomes

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“…no matter where a patient is at Mayo Clinic, that patient should

know all the Mayo Clinic resources are at his or her disposal.”

“…a promise to our patients, staff, and other customers that we are organized and function as a system with a single purpose: our mission. And the mission, as we all know, is to provide the best

care to every patient every day…”

- Glenn Forbes, M.D.

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Clinical Examples

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Clinical Notes Document Naming

• Problem• Many different ways to view clinical note

documentation (nearly 10 systems!)• Standards are implemented at a site, not

enterprise level • Record review is inefficient and complex

• How do I navigate?• Do I have the entire record?• How do we aggregate data? Can we?

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• Scope• Develop enterprise naming standard for

Clinical Notes Documents in EMR.• Develop standardized value sets for each

component of naming standard

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Local Terms External StandardsMayo Standard

AnesthesiologyAnesthesiology

Anesthesiology -Pain Clinic

Anesthesia

Domain standardHealth Care Provider Taxonomy Code Set

SNOMED CTMayo Vocabulary Backbone

Anesthesiology

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Vital Signs

• Need• Identify and apply best practices (policies,

processes, and terminology) across Mayo Clinic to promote accuracy and consistency of care delivery

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Vital Signs - Scope

• Height and Weight

• Temperature

• Respiratory Rate

• Pulse

• Blood Pressure

• Oxygen Saturation

• Pain Score

• Body Mass Index, Body Surface Area

• Head Circumference

• Fetal heart tone/rate monitoring with qualifiers (OB patients)

• Central Venous Pressure plus monitored

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Vital Signs

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Nursing Assessments

• Business Need• Identify standard value sets for use by EMR

applications • Provide a semantic context for the value sets

and align the model to the Enterprise Data Model

• Document a gap analysis between existing and standard terminologies to identify areas for further work

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Business Information Model

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Enterprise Context

Enterprise Context

EDMConcept

UnifiedModel

New

Evaluation

Evaluation Type

Evaluation Purpose

Clinical Impression

Judgement

Observation

Results

Assessment Reason

Patient Issue

Evidence-Based Guideline

Usual Care

Assessment

Outcome

Patient Centric Assessment

Injury

Disease

Signs and Symptoms

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Unified Nursing Assessment Model

EDMConcept

UnifiedModel

ProblemSpecific

Self-Care Management Factor

Patient Assessment FactorPatient Environment Assessment Factor

Behavioral Factor

Patient Centric Assessment

Physical Assessment Factor Psychological Assessment Factor

Pain Assessment

Skin Alteration Assessment

Healthcare Provider

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Problem-Specific Models

UnifiedModel

ProblemSpecific

Reassessment

Assessment Frequency

Pain Assessment

Classification

Patient General StatePain Assessment Dimension


Skin Alteration Dimension

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Data Model to Vocabulary

Skin Alteration Dimension

Skin Color

Skin Condition

Neonate Skin Color Value Set Non-Neonate Skin Color Value Set


Vocabulary

DataModel

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Inpatient Pain Management

• Problem• Inpatient pain service wanted to proactively find

patients with unresolved pain, reduce dependency on manually generated referrals

• Solution• Reported pain scores recorded in EMR• Data replicated into analytic databases• Nightly report was generated to identify patients

whose reported pain scores did not fall below a specified value

• Clinical guidelines were applied • Multi-disciplinary provides patient care (Clinical

Nurse Specialists, Pharmacists, Pain Clinic)

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Inpatient Pain Management

• Solution illustrates• Simple use of controlled terminology for

patient focused data capture and inference (data)

• Information delivered to multi-specialty practice team about a dynamic patient population (information)

• Actions taken by multidisciplinary team (knowledge driven care)

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Problem List

• Problem• ICD 9 standard (for billing) does not

adequately meet the needs of the practice to define a clinical problem

• Limits workflow and automated decision support

• Would like to map terms to multiple standards

• Approach• Enterprise data modeling• Process analysis and design• Data and system requirements

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Race and Ethnicity

• Need for enterprise standardization• Research

• Meet internal and external (e.g., funding agencies) research requirements

• Education• Conform to The US Department of

Education (USDOE) accreditation requirements

• Practice• Collect the data necessary to assure

diversity does not create disparities in care and every patient receives the best care at Mayo

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Laboratory

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Laboratory – System Integration

Transactions to:RES Type:13ASTM From:MNL On:10/02/2001

TX Seq Transaction Data

MSH|^~&\|Antrim|MNL|A7023328|MML|200110020001|C7023328|ORU^R01||P|2.2

PID|1|000133443|23660011|00041753443|HANSEN^JEANE M ||19251012|F|| |||1001:PD00011R||||

ORC|RE|K5863087

OBR|1|K5863087||9387^PTH Whole Molecule, |||200110011413|||C7023328^Immanuel-St Josephs Hosp^507-625-4031|N|||||^STOROLE Storvic||L4562352405|1001:PD00011R||||C|CH|A||^^^^^R~R

OBX|1|ST|2238^Calcium^ROCLIS||8.9|mg/dL|8.9-10.1|N|||F|19960208|||

NTE|1|N^|8.9-10.1

OBX|2|ST|7596^Calcium, S^ROCLIS||DNR|mmol/L|2.2-2.5|N|||F|19960208|||

NTE|1|N^|2.2-2.5 (Females > or = 19 years)

OBX|3|ST|2239^Creatinine^ROCLIS||5.8|mg/dL|0.6-0.9|h|||F|19890216|||


OBX|4|ST|2240^Phosphorus^ROCLIS||3.9|mg/dL|2.5-4.5|N|||F|19890811|||

NTE|1|N^|2.5-4.5

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ORC|RE|K5863087



NTE|1|N^|8.9-10.1






NTE|1|N^|2.5-4.5

40






ORC|RE|K5863087



NTE|1|N^|8.9-10.1






NTE|1|N^|2.5-4.5

41






ORC|RE|K5863087



NTE|1|N^|8.9-10.1






NTE|1|N^|2.5-4.5

42






ORC|RE|K5863087



NTE|1|N^|8.9-10.1






NTE|1|N^|2.5-4.5

43






ORC|RE|K5863087



NTE|1|N^|8.9-10.1






NTE|1|N^|2.5-4.5

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Referral Optimization ProjectEnterprise Data Trust

Institutional Appointment Reporting Categories

EnterpriseCategory

Code

Enterprise Category Code Description

MCR Reporting Categories MCJ Reporting Categories

MCA Reporting Categories

ADM Administrative Administrative Non-patient Non-Patient

UND Undifferentiated Slot Only OPEN OPEN

CON Consult Consult/Limited Exam Consultation/PAME Consult/PAME

ME Multi-System Evaluation Multi-system Evaluation Evaluation Direct

SV Subsequent Visit Subsequent Visit Return Visit/ Acute Illness Established

VIRT Virtual Visit Virtual Visit Virtual Visit (Future) Virtual Visit (Future)

OTH Other Other (Receptionist Only Visit, Research Visit,

Educational Visit), Procedure (Blood Test,

Procedure/Diagnostic Testing, Radiology, Specimen

Collection, Therapy)

Ancillary Other – Registration, Receptionist Visit, Procedure, Ancillary

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Patient Focused Data Capture

Point of careknowledge execution

Practice Based Evidence

Evidence Based Practice

ClinicalGuidelines

Clinically DerivedKnowledge Bases

ExpertSystems

TransactionalDatabases

Inform

Research, evaluation, & performance measurementStorage and Processing

Consolidate with other evidence, other knowledge bases

Analytic Data Repositories

Replication

and modelingData Inference

KnowledgeManagement

Decisionsupport

Vision

Terminology

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Questions?

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