Huff # 1

SOA at Intermountain Healthcare: New IDEAs and Progress Towards a New Platform

SOA in HealthcareJuly 13, 2011

Stanley M. Huff, MD

# 2

Acknowledgements

• Tom Oniki• Joey Coyle• Craig Parker• Yan Heras• Cessily Johnson• Roberto Rocha• Lee Min Lau• Alan James• Many, many, others…

Intermountain Medical Center

Outpatient Pavilion

Heart and Lung Hospital

Main Tower

Women’s and

Newborn

Cancer Center

Intermountain Healthcare

• 24 hospitals• 2,488 inpatient beds• 123,447 Acute admissions• 98,674 Ambulatory

surgeries• 160,306 Homecare visits• 502,327 Acute patient

days• 5,817,392 Outpatient

visits• 429,949 emergency room

visits• 38,103 inpatient surgeries

Homer Warner and HELP

• The first version of the HELP (Health Evaluation through Logical Processing) system was built in 1967

• From its inception, the HELP system was built primarily to provide advanced decision support

Dr. Homer Warner

Patient

Core Assumptions

‘The complexity of modern medicine exceeds the inherent limitations of the unaided human mind.’~ David M. Eddy, MD, Ph.D.

‘... man is not perfectible. There are limits to man’s capabilities as an information processor that assure the occurrence of random errors in his activities.’~ Clement J. McDonald, MD

Clinical System Approach

Intermountain can only provide the highest quality, lowest cost

health care with the use of advanced clinical decision

support systems integrated into frontline workflow

233

581567 569 567

437

477

355

271 271 280

89 90 91 92 93 94 95 96 97 98 99(3)

Year

0

100

200

300

400

500

600

0

100

200

300

400

500

600

To

tal #

mo

der

ate

+ se

vere

AD

Es

• Rates today (2008-9) at about 230 per year

• Generates >$1 million per year in net cost reductions at LDS Hospital alone

• Rates today (2008-9) at about 230 per year

• Generates >$1 million per year in net cost reductions at LDS Hospital alone

Adverse Drug Events

Neo-natal intensive care unit (NICU) admits by weeks gestation

6.66

3.36

2.47 2.65

3.44

4.26

37 38 39 40 41 42

Weeks gestation

0

2

4

6

8

10

Per

cen

t N

ICU

ad

mis

sio

ns

0

2

4

6

8

10

Deliveries w/o Complications, 2002 - 2003

8,001 18,988 33,185 19,601 4,505 258n =

Elective inductions < 39 weeks

5.55.1

6.6 6.3 65.3

8.2

5.4 5.76.6 6.6

7.9

6.4

7.6 7.6

4.6

3.5

4.55

26.726.9

29 29.2

25.3

27.6

20.4

19.1

16.5

15.2

8.4

10.7

8.1

6.85.9 6.1 6

5.1

6.3

Jan 01 MarMay Ju

lSep Nov

Jan 02 MarMay Ju

l

Jan 03 MarMay Ju

lSep Nov

Jan 04 MarMay Ju

l

0

5

10

15

20

25

30

% e

lect

ive

ind

uct

ion

s <

39 w

eeks

0

5

10

15

20

25

30

382372

490415

430435

422455

430382

356337

372366

455n = 423453

473476 512

475602

557667

564637

578541

573533

505501

474536

562545

535500

Labor & delivery variable cost

Jan 20

03 Feb Mar Apr

May Jun

Jul

Aug

Sep Oct

Nov

DecJa

n 2004 Feb Mar Apr

May

1000

1200

1400

1600

1800

2000

Ave

rag

e co

mb

ined

var

iab

le c

ost

($)

1000

1200

1400

1600

1800

2000

Expected maternal and fetal combined variable costGoal: hold increase to no more than 6.85%Actual combined variable cost

ARDS … evidence in action

ARDS ventilator management:

• Survival 9.5% � 44%

• ~$120,000 less cost per case!

Defining the best practice clinical protocol

Physician compliance

Decision Support Modules

• Antibiotic Assistant

• Ventilator weaning

• ARDS protocols

• Nosocomial infection monitoring

• MRSA monitoring and control

• Prevention of Deep Venous Thrombosis

• Infectious disease reporting to public health

• Diabetic care

• Pre-op antibiotics

• ICU glucose protocols

• Ventilator disconnect

• Infusion pump errors

• Lab alerts

• Blood ordering

• Order sets

• Patient worksheets

• Post MI discharge meds

Huff # 15

Infrastructure Vision• Rapid application development environment

• Dynamic workflow configuration

• Standard data models and terminology

• Decision support authoring and execution

• Knowledge asset management– Rules, alerts, protocols, reminders, reports

• End user preferences– Common lists, Hot text

• Service Oriented Architecture/Enterprise Service Bus

Strategic Goals

• Minimum goal: Be able to share applications, reports, alerts, protocols, and decision support with ALL GE customers

• Maximum goal: Be able to share applications, reports, alerts, protocols, and decision support with anyone in the WORLD

Order Entry API (adapted from Harold Solbrig)

MUMPSDatabase

Application

Service

Interface

Data

VA OrderEntry

VAOrder

Services

COS

Update Medication Order

Update PharmacyOrderWHERE orderNumber = “4674” …

Order Entry API – Different Client, Same Service (adapted from Harold Solbrig)

MUMPSDatabase

Application

Service

Interface

Data

Update Medication Order

Update PharmacyOrderWHERE orderNumber = “4674” …

Deptof

Defense

VAOrder

Services

COS

Deptof

Defense

Order Entry API – Different Server, Same Client (adapted from Harold Solbrig)

GERepository

OracleTables

Application

Service

Interface

Data

Update Medication Order

Update PharmacyOrderWHERE orderNumber = “4674” …

COS

GEServices

Order Entry API (adapted from Harold Solbrig)

Application

Service

Interface

Data

COS

. . .

What Is Needed to Create a New Paradigm?

• Standard set of detailed clinical data models coupled with…

• Standard coded terminology

• Standard API’s (Application Programmer Interfaces) for healthcare related services

• Open sharing of models, coded terms, and API’s

# 22

What are detailed clinical models?

Why do we need them?

# 23

A diagram of a simple clinical model

data 138 mmHg

quals

SystolicBPSystolicBPObs

data Right Arm

BodyLocationBodyLocation

data Sitting

PatientPositionPatientPosition

Clinical Element Model for Systolic Blood Pressure

# 24

Need for a standard model

•A stack of coded items is ambiguous (SNOMED CT)– Numbness of right arm and left leg

• Numbness (44077006)• Right (24028007)• Arm (40983000)• Left (7771000)• Leg (30021000)

– Numbness of left arm and right leg• Numbness (44077006)• Left (7771000)• Arm (40983000)• Right (24028007)• Leg (30021000)

# 25

70

What if there is no model?

Hct, manual:Site #1

%

Hct :Site #2

Manual%Auto

37

7037

70Hct, auto : %35

Estimated

HL7 V2.X Messages

• Site 1:OBX|1|CE|4545-0^Hct, manual ||37||%|OBX|1|CE|4544-3^Hct, auto ||35||%|

• Site 2:OBX|1|CE|20570-8^Hct ||37||%|….|manual|OBX|1|CE|20570-8^Hct ||35||%|….|auto|

# 27

Model fragment in XML

Pre-coordinated representation<observation><cd>Hct, manual (LOINC 4545-0 ) </cd><value>37 % </value>

</observation>Post-coordinated (compositional) representation<observation><cd>Hct (LOINC 20570-8) </cd><qualifier><cd>Method </cd><value>Manual </value>

<qualifier><value>37 % </value>

</observation>

# 28

Relational database implications

If the patient’s hematocrit is <= 35 then ….

Patient Identifier

Date and Time Observation Type Observation Value

Units

123456789 7/4/2005 Hct, manual 37 %

123456789 7/19/2005 Hct, auto 35 %

Patient Identifier

Date and Time Observation Type

Weight type Observation Value

Units

123456789 7/4/2005 Hct manual 37 %

123456789 7/19/2005 Hct auto 35 %

# 29

Isosemantic Models

data 37 %

HematocritManual (LOINC 4545-0)HematocritManualModel

data 37 %

quals

Hematocrit (LOINC 20570-8)HematocritModel

data Manual

Hematocrit MethodHematocritMethodModel

Precoordinated Model

Post coordinated Model (Storage Model)

# 30

More complicated items:

• Signs, symptoms

• Diagnoses

• Problem list

• Family History

• Use of negation – “No Family Hx of Cancer”

• Description of a heart murmur

• Description of breath sounds– “Rales in right and left upper lobes”

– “Rales, rhonchi, and egophony in right lower lobe”

What do we model?

• All data in the patient’s EMR, including:– Allergies– Problem lists– Laboratory results– Medication and diagnostic orders– Medication administration– Physical exam and clinical measurements– Signs, symptoms, diagnoses– Clinical documents– Procedures– Family history, medical history and review of symptoms

# 32

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+

How are the models used?

• Data entry screens, flow sheets, reports, ad hoc queries– Basis for application access to clinical data

• Computer-to-Computer Interfaces– Creation of maps from departmental/foreign system models

to the standard database model

• Core data storage services– Validation of data as it is stored in the database

• Decision logic– Basis for referencing data in decision support logic

• Does NOT dictate physical storage strategy

# 34

Model Source Expression (CDL)

model BloodPressurePanel is panel{

key code(BloodPressurePanel_KEY_ECID);

statement SystolicBloodPressureMeas systolicBloodPressureMeas optionalsystolicBloodPressureMeas.methodDevice.conduct(methodDevice)systolicBloodPressureMeas.bodyLocationPrecoord.conduct(bodyLocationPrecoord)systolicBloodPressureMeas.bodyPosition.conduct(bodyPosition)systolicBloodPressureMeas.relativeTemporalContext.conduct(relativeTemporalContext)systolicBloodPressureMeas.subject.conduct(subject)systolicBloodPressureMeas.observed.conduct(observed)systolicBloodPressureMeas.reportedReceived.conduct(reportedReceived)systolicBloodPressureMeas.verified.conduct(verified);

statement DiastolicBloodPressureMeas diastolicBloodPressureMeas optional….

statement MeanArterialPressureMeas meanArterialPressureMeas optional….

qualifier MethodDevice methodDevice optional;md.code.domain(BloodPressureMeasurementDevice_DOMAIN_ECID);

qualifier BodyLocationPrecoord bodyLocationPrecoord optional;blp.code.domain(BloodPressureBodyLocationPrecoord_DOMAIN_ECID);

modifier Subject subject optional;

attribution Observed observed optional;attribution ReportedReceived reportedReceived optional;attribution Verified verified optional;

}

So that is the vision of the future, what is

happening right now?

Huff # 35

DataWarehouse

IHC

DataWarehouse

IHC

Care Flow(Outpatient)

GEHCMisys Lab

GE/AGFA Radiology

Tamtron Anatomic Pathology

McKesson Pharmacy

ARUP Blood Bank

Blood Gas Machines

Dictaphone

Varis Oncology

MRS Mammography

GE/Logicare ER

Computrition Dietary

HDM &Medrec

3M

HELP(Inpatient HIS)

3M

Health DataDictionary

3M

Health DataDictionary

3M

Billing &Financial

IHC

Registration,Scheduling

ADT, Billing,Case Mix

ADT, Billing

ADT, Orders, Results, Billing

ADT, Results,OrdersRegistration,Scheduling

Tuxedo

DataStage

CDRDatabase(HEMS) 3M

CDRDatabase(HEMS) 3M

eGateInterfaceEngineSun

ClinicalWorkstation

3M

ADT, Orders, Results, Billing

HELP2

CDIHC

HELPDatabase

HELPDatabase

Application Explosion• 4000+ applications in the organization• Applications being purchased or built include

approximately 80% redundancy of functionality

• All new applications require duplication of data• One example of data duplication

– 49 copies of patient registration data– 294 million patient records online– 288 million or 97% are duplicate copies– 125,000 registration updates/day or 6.1 million total data updates

daily

Data Explosion

Information Delivery Enterprise Architecture

Desktop Subcommittee

IDEA Governance StructureEARB

Chair: Chief Technology Officer

IDEA SubcommitteeChair: Enterprise Software Architect

MEMBERSPMO, HELP1, HELP2, Migration,

Financial, Tactical, eBusiness, Clinical Operations, Interfaces,

EDW, ECIS, Informatics, Security, Select Health, Operations, RIM,

KTMI, HWCIR

IDEA GOVERNANCE

Security Architecture

Subcommittee

Database Architecture

Subcommittee

RESPONSIBILITES

•Provides strategic oversight and guidance for IDEA

•Empowers IDEA subcommittee to specifying standards, practices,

guidelines and tools•Approval of IDEA subcommittee

proposals•Monitors and is accountable for adherence to approved standards,

practices, guidelines and tools

Fostering ExcellenceWorkgroup

Exception Handling

Workgroup

AuditingWorkgroup

RESPONSIBILITES

•Establish the Information Delivery Enterprise Architecture by specifying standards, practices,

and guidelines and tools•Build consensus and document software

standards, processes, tools, and infrastructure to be approved by IDEA Governance

•Provides stewardship for respective teams•Brings forth gaps, issues and solutions for

IDEA

A Picture

Something More Concise

IDEA Enterprise Service Bus

Intermountain

Application

New 3rd

Party

Application

New 3rd

Party

Data Repository

Intermountain

Central Data Rep

Nursing ‘Medication Charting’ workflow

Physician “Note Writing” workflow

Clinician ‘Data Review’ workflow

Huff # 45

Potential Benefits

• Low risk

• Incremental changes - no “big bang” changes

• Gradual implementation of ESB

• Transition based on particular modules– Results review, text documents, allergies,

documentation, order entry

• Slowly increasing use of the new database– Opportunity to tune performance

Huff # 46

Questions?