Transcript Health Information Resources at Intermountain Health Care

Integration of Health Information
Resources into Electronic Health
Records Using HL7
Guilherme Del Fiol, MD, MS
Biomedical Informatics Department, University of Utah
Intermountain Healthcare, Salt Lake City, UT
James J. Cimino, MD
Department of Biomedical Informatics, Columbia
University, New York, NY
Saverio Maviglia, MD, MSc
Partners Healthcare System, Boston, MA
Outline
• Background
• HL7 infobutton standard
• Demonstration participants
– Infobutton Managers
– Information resource providers
• Live demonstration
Infobuttons
Background
Information for Decision-Making
?
MRSA
Addressing Information Needs
with Infobuttons
• Clinical information systems evoke
information needs
• Clinician’s computer has access to
resources
• Context can be used to predict need
• Context can be used to automate
retrieval
Context-Dependent Information Needs
?
Age
Sex
Role Training
!
Task
Context
Data
Institution
Infobuttons vs. Infobutton Manager
Resource s
Clinical System
Infobutton
Query
Knowledge
Base
Context
Infobutton
Manager
Page
of
Hyperlinks
Infobutton standard
Overview
Why do we need a standard?
• There is not a common integration
language
– Parameter names
– Terminologies used for content
search retrieval
• Hundreds of resources available
– Not designed for infobutton
integration: suboptimal results
– Labor intensive integration: just a few
are actually used
Multiple ways of
“asking” the same question
What is the dose of
azithromycin ?
i
http://resource1.com/
search = “azithromycin AND dose”
http://resource2.com/
query = "azithromycin"[MeSH Terms]
AND dose[All Fields]
http://resource3.com/
searchConcept = 3333 ^ azithromycin
filter = 11 ^ dosage
No standard in place
API
http://resource1.com/search.cgi?
Resource 1
search = “azithromycin AND dose”
http://resource2.com/
Clinical
Information
System
i
API
Infobutton
Manager
query = "azithromycin"[MeSH Terms]
AND dose[All Fields]
API
Resource 2
http://www.resource3.com/search.cgi?
searchConcept = 3333 ^ azithromycin
filter = 11 ^ dosage
API
Resource 3
Standard-based integration
HL7
Electronic
Health
Record
i
Columbia
HL7 HL7
Intermountain
HL7
HL7
Resource 1
HL7
Resource 2
Partners
HL7
Resource 3
Key points
• XML and URL-based syntax
• Recommends adoption of a set of
standard terminologies (e.g.,
RxNorm, LOINC, SNOMED-CT,
MeSH)
– Aligned with national initiatives
• Flexible requirements to allow
faster adoption
Example
• The user is looking at a problem
list of a female, 94 years-old
patient with Heart Failure. The
user clicks on an infobutton that
presents a series of questions. The
user selects “How do I treat Heart
Failure?”
<gender code=“F"
displayName=“Female"/>
<age value=“94" unit=“a"/>
<taskContext code=“PROBLISTREV"/>
<mainSearchCriteria code="428“
codeSystem="2.16.840.1.113883.6.103"
<informationRecipient>
displayName=“Heart
Failure"/>
<subTopic
code="Q000628"
<patient>
codeSystem="2.16.840.1.113883.6.177"
<language
code=“eng"/>
<patient> displayName="therapy"/>
<informationRecipient>
<patientContext>
<gender code=“F"
displayName=“Female"/>
<age value=“94" unit=“a"/>
<taskContext code=“PROBLISTREV"/>
<mainSearchCriteria code="428"
codeSystem="2.16.840.1.113883.6.103"
displayName=“Heart Failure"/>
<subTopic code="Q000628"
codeSystem="2.16.840.1.113883.6.177"
displayName="therapy"/>
URL-based message
• Simpler implementation
– Support industry backwards
compatibility
– Faster adoption
• Rules for automated conversion
– URL can be automatically derived
from XML model
age.v=56
age.u=a
administrativeGenderCode.c=F
mainSearchCriteria.c.c=2823-3
mainSearchCriteria.c.cs=2.16.840.1.113883.6.1
taskContext.c.c=LABRREV
mainSearchCriteria.c.dn=Serum potassium
mainSearchCriteria.c.ot=K
interpretationCode.c.c=L
http://www.e-resource.com/api?
patientPerson.administrativeGenderCode.c=F
age.v=56&age.u=a
taskContext.c=LABRREV
mainSearchCriteria.c=2823-3
mainSearchCriteria.cs=2.16.840.1.113883.6.1
mainSearchCriteria.dn=Serum potassium
mainSearchCriteria.c.ot=K
Demonstration
Participants
Content providers
• ACP PIER
• Clin-eguide (Wolters Kluwer Health)
• Dynamed (Ebsco)
• Lexicomp
• Micromedex (Thomson Healthcare)
• UpToDate
Infobutton Managers
• Intermountain Healthcare
– First production version in 2001
– Infobutton Manager since 2005
– Medication order entry, problem list,
lab results
– 1,000+ users per month
– Knowledge base: resources and
questions configured in XML files
Infobutton Managers
• Columbia University
– Concept of interest translated into
controlled terminology
– Related concepts identified
– Topics/questions matched to concept
classes and other context parameters
– XML table of topics (along with
javascript) returned to the user
– Links are initiated from user’s browser
Infobutton Managers
• Columbia University – usage
– Infobuttons available since 1996
– Infobutton manager version 1 2002
– Available in:
• WebCIS: lab results, micro results, sensitivity
results, inpatient drugs, outpatient drugs,
problem list
• Eclipsys: lab orders, drug orders, nursing orders
• Regenstrief Medical Records System: drug orders
• NY State Psych Institute: drug orders
• NextGen: lab results
– 700+ users per month
– 2100+ uses per month
Infobutton Managers
• Columbia University – benefits
– Easy to use: 92%
– Question on list >50% of time: 89%
– Answered question: 69%
– Useful: 77%
– Helpful >50% of time: 90%
– Positive effect on care: 74%
Infobutton Managers
• Partners Healthcare
– Live since 2002
– Medication order entry, problem list,
lab results (8 clinical apps)
– Federated search engine for 2 library portals
– 50K sessions by 5K unique users per month
•
•
•
•
•
60% RN, 15% MD, 11% PharmD
1-50% of patient encounters
90% medication queries
Median session duration under 15 seconds!
85-90% success rate
– Resources and context triggers configured in
SQL/Access – no terminology or lexical
analysis
http://www.hl7.org/v3ballot/html/
welcome/environment/index.htm