Computer-based Support for Improving Patient Medication Management James J. Cimino Chief, Laboratory for Informatics Development National Institutes of Health Clinical Center Senior Scientist, Lister Hill Center for Biomedical Communications National Library of Medicine Informatics Grand Rounds Dartmouth-Hitchcock Medical Center May 16, 2008
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Computer-based Support for Improving Patient Medication Management James J. Cimino Chief, Laboratory for Informatics Development National Institutes of.
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Computer-based Support for Improving Patient Medication Management
James J. CiminoChief, Laboratory for Informatics Development
National Institutes of Health Clinical Center
Senior Scientist, Lister Hill Center for Biomedical CommunicationsNational Library of Medicine
Informatics Grand RoundsDartmouth-Hitchcock Medical Center
May 16, 2008
Challenges to Medication Management
• Lack of information about the patient– Patient’s condition– Patient’s co-morbidities– Medications the patient is supposed to take– Medications the patient is actually taking
• Access to medical knowledge– Knowing about availability of knowledge resources– Knowing how to use knowledge resources– Effort to use knowledge resources
Solutions
• Medication reconciliation– Collect information from disparate sources– Present information to support decision making
• Infobuttons– Anticipate user’s information needs– Automate access to appropriate resources– Automate retrieval from these resources
The Challenge of Medication Reconciliation
Stop
Stop
Stop
Stop
Go
StopGo
Stop
Go
?
Many a Slip ‘Twixt the Cup and the Lip
Patient is Supposed to Take
Patient is not Supposed to Take
Patient is Taking
Reports
Taking
Doesn’t
Report Taking
Reports
Taking
Doesn’t
Report Taking
Patient is not Taking
Reports
Taking
Doesn’t
Report Taking
Reports
Taking
Doesn’t
Report Taking
Stop
Stop
Stop
Stop
Problems and Solutions
• Errors due to:– Not starting medications the patient should be taking– Starting medications the patient shouldn’t be taking– Not communication starts/stops to next caregiver– Not communicating changes to patients
• Beers, et al. J Am Geriatric Society 1990:– 83% of hospital admission histories missed one or
more medications– 46% missed three or more
• Problems occur at all transitions in care:– “Continue all outpatient medications”
Electronic Health Records to the Rescue!
Stop
Stop
Stop
Stop
Go
StopGo
Stop
Go
?
Computer Assisted Medication Reconciliation
• Poon et al.: JAMIA 2006:– Preadmission Medication List– Grouped medications by generic names
• Text sources
• Multiple sources
• Substitutions might occur
• Confusing chronology
• Information overload!
Our Approach to Medication Reconciliation
• Multiple inpatient and outpatient systems
• Natural language processing to get codes
• Medical knowledge base to group codes
• Chronological presentation
Methods• All recent admissions for one physician (JJC)
• Multiple inpatient and outpatient resources
• Carol Friedman’s Medical Language Extraction and Encoding (MedLEE)
• US National Library of Medicine’s Unified Medical Language System (UMLS)
• Columbia’s Medical Entities Dictionary (MED)
• American Hospital Formulary Service (AHFS) classification
• Evaluation of ability to capture, code and organize
1. Prior Clinic Note2. Prior Outpatient Medications3. Admission Note4. Admission Note Plan5. Admission Orders6. Admission Pharmacy Orders7. Active Orders at Discharge8. Discharge Pharmacy Orders9. Discharge Instructions10. Discharge Plan11. Clinic Note after Discharge12. Outpatient Medications after Discharge
Discussion• Data from multiple coded and narrative sources
can be coded automatically and merged into a single form
• The UMLS and MED are both needed for coding to a single terminology (AHFS)
• Further work on MedLEE and the MED are needed
• Drugs tend to group into one per class; allows for change from one generic to another
• Chronology by drug class can highlight changes in medication plans
• Changes can be intended or unintended, but should not be ignored
• The next step is medication reconciliation
http://www.dbmi.columbia.edu/cimino/medrec/
Next Step: High-Quality Decision Making
• Providing patient information evokes additional information needs
• These needs are stereotypical
• Resources exist to address these needs
• If we can predict the needs, we can provide links
• Information available in the context can be used to target the resources
Health Knowledge for Decision Support
Health Knowledge for Decision Support
?
Infobuttons
Anticipate Need and Provide Queries
i
Information Needs of CIS Users
• Common tasks may have common needs
• System knows:– Who the user is– Who the patient is– What the user is doing– What information the user is looking at
• We can predict the specific need
• User is sitting at a computer!
• We can automate information retrieval
First Attempt: The Medline Button
• CIS on mainframe
• BRS/Colleague (Medline) on same mainframe
• Get them to talk to each other
• Search using diagnoses and procedures
First Attempt: The Medline Button
• CIS on mainframe
• BRS/Colleague (Medline) on same mainframe
• Get them to talk to each other
• Search using diagnoses and procedures• Technical success
• Practical failure
Education at the Moment of Need
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Education at the Moment of Need
UnderstandInformation
Needs
1i
Education at the Moment of Need
Get InformationFrom EMR
UnderstandInformation
Needs
1
2
i
Education at the Moment of Need
Get InformationFrom EMR
ResourceSelection
UnderstandInformation
Needs
1
2
3
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Education at the Moment of Need
Get InformationFrom EMR
ResourceSelection
ResourceTerminology
UnderstandInformation
Needs
1
24
3
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Education at the Moment of Need
Get InformationFrom EMR
ResourceSelection
ResourceTerminology
UnderstandInformation
Needs
AutomatedTranslation
1
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3
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Education at the Moment of Need
Get InformationFrom EMR
ResourceSelection
ResourceTerminology
QueryingUnderstandInformation
Needs
AutomatedTranslation
1
254
6
3
i
Education at the Moment of Need
Get InformationFrom EMR
ResourceSelection
ResourceTerminology
Querying
Presentation
UnderstandInformation
Needs
AutomatedTranslation
1
254
6
3
7
i
Infobuttons vs. Infobutton Manager
Pageof
Hyperlinks
InfobuttonClinical System Resourc
e
InfobuttonManager
ContextQuery
KnowledgeBase
s
Usage in Lab Contexts
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500
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Aug-0
2
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2
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3
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-03
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3
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3
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-04
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5
Feb-0
6
May
-06
Aug-0
6
Nov-0
6
Feb-0
7
May
-07
Aug-0
7
HR-LabDetail
IM-LabDetail
Usage in In-Patient Drug Contexts
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HR-InPatientDrugs
IM-InPatientDrugs
Usage in Diagnosis Context
0
100
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Aug
-02
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HR-Diagnoses
IM-Diagnoses
Usage in Lab Order Entry Context
0
20
40
60
80
100
120
140
Aug-0
2
Nov-0
2
Feb-0
3
May
-03
Aug-0
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6
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-06
Aug-0
6
Nov-0
6
Feb-0
7
May
-07
Aug-0
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HR-LabOrder
IM-LabOrder
Usage in InPat Drug Order Entry
0
50
100
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200
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300
350
Aug
-02
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Feb
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HR-DrugOrder
IM-DrugOrder
The Coumadin Story
• Chair of Medicine wants link to Coumadin protocol
• First, I have to find the guidelines
The Coumadin Story
• Chair of Medicine wants link to Coumadin protocol
• First, I have to find the guidelines
• Then I have to add the question to the IM table
The Coumadin Story
• Chair of Medicine wants link to Coumadin protocol• First, I have to find the guidelines• Then I have to add the question to the IM table
• Finally, I link the question to the context
The Coumadin Story
• Chair of Medicine wants link to Coumadin protocol• First, I have to find the guidelines• Then I have to add the question to the IM table• Finally, I link the question to the context
• Voilá!
New York Presbyterian Hospital (Eclipsys)
NY Office of Mental Health (Psykes)
NY Office of Mental Health (Psykes)
Regenstrief Medical Record System
Cryststal Run Healthcare (NextGen)
AMIA 2007 Demo Participants
• Health care & academic institutions– Intermountain Healthcare, Columbia University,
Conclusions• Diverse medication data can be automatically
integrated
• Organizing data by time and drug class can highlight possible errors
• Infobuttons can anticipate and resolve clinicians’ information needs
• Institution-specific tailoring is required
• International standard will stimulate wider adoption
• Librarian Infobutton Tailoring Environment will put the Infobutton Manager on autopilot
Acknowledgments
• Medication Reconcilliation– Carol Friedman for use of MedLEE– Jianhua Li for programming– Tiffani Bright for background research– US National Library of Medicine
• Infobuttons– Jianhua Li for programming– Many student contributors– Guilherme Del Fiol– Noemie Elhadad– National Library of Medicine