1. 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

2. Outline Background HL7 infobutton standard Demonstration participants
Infobutton Managers
Information resource providers
Live demonstration

3. Infobuttons
Background

4. Information for Decision-Making?
MRSA
On-line resources are much more likely to have the available information, in a bibliographic database, an electronic text book, etc

5. 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

6. Context-Dependent Information Needs? !
Institution
Data
Task
Age
Sex
Training
Role
Context

10. Infobuttons vs. Infobutton Manager
Clinical System
Resource s
Infobutton
Manager
Context
Query
Knowledge
Base
Page of
Hyperlinks

11. Infobutton standard
Overview

12. 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

13. Multiple ways of “asking” the same question
What is the dose of azithromycin ? i
search = “azithromycin AND dose”
query = "azithromycin"[MeSH Terms] AND dose[All Fields]
searchConcept = 3333 ^ azithromycin filter = 11 ^ dosage

14. i No standard in place Resource 1 Clinical Information Infobutton
API
search = “azithromycin AND dose”
query = "azithromycin"[MeSH Terms] AND dose[All Fields]
Clinical
Information
System
Infobutton
Manager
Resource 2 i
API
API
searchConcept = 3333 ^ azithromycin filter = 11 ^ dosage
Resource 3
API

15. Standard-based integration
Resource 1
Columbia
HL7
HL7
Electronic Health Record
Intermountain i
HL7
HL7
Resource 2
HL7
Partners
HL7
Resource 3
HL7

16. 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

17. 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?”

18. <gender code=“F" displayName=“Female"/>
<age value=“94" unit=“a"/>
<taskContext code=“PROBLISTREV"/>
<mainSearchCriteria code="428“ codeSystem=" " displayName=“Heart Failure"/>
<mainSearchCriteria code="428“ codeSystem=" " displayName=“Heart Failure"/>
<informationRecipient>
<patient>
<language code=“eng"/>
<subTopic code="Q000628" codeSystem=" " displayName="therapy"/>

19. <patientContext>
<gender code=“F" displayName=“Female"/>
<age value=“94" unit=“a"/>
<taskContext code=“PROBLISTREV"/>
<mainSearchCriteria code="428" codeSystem=" " displayName=“Heart Failure"/>
<subTopic code="Q000628" codeSystem=" " displayName="therapy"/>

20. URL-based message Simpler implementation
Support industry backwards compatibility
Faster adoption
Rules for automated conversion
URL can be automatically derived from XML model

21. age.v=56
age.u=a
administrativeGenderCode.c=F
mainSearchCriteria.c.c= mainSearchCriteria.c.cs= mainSearchCriteria.c.dn=Serum potassium
mainSearchCriteria.c.ot=K
taskContext.c.c=LABRREV
interpretationCode.c.c=L

22.
patientPerson.administrativeGenderCode.c=F
age.v=56&age.u=a
taskContext.c=LABRREV
mainSearchCriteria.c=2823-3
mainSearchCriteria.cs=
mainSearchCriteria.dn=Serum potassium
mainSearchCriteria.c.ot=K

23. Demonstration
Participants

24. Content providers ACP PIER Clin-eguide (Wolters Kluwer Health)
Dynamed (Ebsco)
Lexicomp
Micromedex (Thomson Healthcare)
UpToDate

25. 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

26. 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

27. Infobutton Managers Columbia University – usage
Infobuttons available since 1996
Infobutton manager version
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

28. 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%

29. 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

30. http://www.hl7.org/v3ballot/html/ welcome/environment/index.htm