Transcript Medication Reconcilliation Using Natural Language

Medication Reconciliation Using
Natural Language Processing and
Controlled Terminologies
James J. Cimino, Tiffani J. Bright, Jianhua Li
Department of Biomedical Informatics
Columbia University College of Physicians and Surgeons
New York, New York, USA
The Challenge of Medication Reconciliation
Go
Stop
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Many a Slip ‘Twixt the Cup and the Lip
Stop
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Patient is
Supposed to Take
Patient is
Taking
Patient is not
Taking
Patient is not
Supposed to Take
Reports
Taking
Doesn’t
Report Taking
Reports
Taking
Doesn’t
Report Taking
Reports
Taking
Doesn’t
Report Taking
Reports
Taking
Doesn’t
Report Taking
Problems and Solutions
• Errors due to:
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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!
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Computer Assisted Medication Reconciliation
• Poon et al.: JAMIA 2006:
– Preadmission Medication List
– Grouped medications by generic names
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Text sources
Mutiple 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
Data Sources
Data Source
1. Prior Clinic Note
2. Prior Outpatient Medications
3. Admission Note
4. Admission Note Plan
5. Admission Orders
6. Admission Pharmacy Orders
7. Active Orders at Discharge
8. Discharge Pharmacy Orders
9. Discharge Instructions
10. Discharge Plan
11. Clinic Note after Discharge
12. Outpatient Medications after Discharge
System Data Type
WebCIS Narrative
Coded
WebCIS
WebCIS Narrative
WebCIS Narrative
Coded
Eclipsys
Coded
WebCIS
Coded
Eclipsys
Coded
WebCIS
Eclipsys Narrative
WebCIS Narrative
WebCIS Narrative
Coded
WebCIS
Results
• 70 patient records reviewed
• 30 hospitalizations identified
• 17 met inclusion criteria
• MedLEE found 623/653 (95.4%) medications
• Total of 1533 medications (444 unique) in MED
Medications by Source
Prior Clinic Note *
Prior Outpatient Medications
Admission Note *
Admission Note Plan *
Admission Orders
Admission Pharmacy Orders
157
211
102
41
88
152
Records
with Data
17
13
14
12
8
14
Active Orders at Discharge
93
8
11.6
Discharge Pharmacy Orders
Discharge Instructions *
Discharge Plan *
Clinic Note After Discharge *
171
60
123
140
14
7
16
16
12.2
8.6
7.7
8.8
Outpatient Medications after Discharge
225
13
17.3
Data Source
* Narrative text
Meds
Meds per
Patient
9.2
16.2
7.3
3.4
11.0
10.9
MedLEE Terms Found
48 Other Meds
(8%)
30 Non-Med,
(5%)
545 UMLS
(87%)
MED Terms
16 non-AHFS
(1.0%)
1517 AHFS
(99.0%)
Mapped to UMLS
8 Other Meds
(4%):
INH, MVI, asa,
Os-Cal,
darvocet, hctz,
niacin, toprol
4 Non-Med
(3%): cream,
antiinflammatory, lotion,
lozenge, po
169 UMLS
(93%)
Mapped to AHFS
2 non-AHFS
(0.5%):
oxygen,
medication
442 AHFS
(99.5%)
Transition from Outpatient to Inpatient
Patient #9
201204:
Anticoagulants
240400:
Cardiac
Drugs
240800:
Hypotensive Agents
Prior Clinic Note
coumadin
verapamil
cozaar
Prior Outpatient
Medications
Coumadin
5 mg Tab
Verapamil
180 mg
Extended
Release
Tablet
Losartan
Potassium
100 mg
Tablet
Admission Note
coumadin
verapamil
cozaar
Admission Note
Plan
coumadin
Verapamil
SR Oral
240 MG
Losartan Oral
50 MG
VERAPAMIL
SR TAB
240 MG
LOSARTAN
POTASSIUM
TAB 50
MG
Admission Orders
Warfarin
Sodium
Oral 10
MG
Admission
Pharmacy Orders
WARFARIN
TAB 5 MG
10
MILLIGRA
M
280000:
CNS
Agents
281604:
Antidepressants
cymbalta
Pregabalin
50mg Capsule
cymbalta
Transition from Outpatient to Inpatient
Patient #9
201204:
Anticoagulants
240400:
Cardiac
Drugs
240800:
Hypotensive Agents
Admission
Pharmacy Orders
WARFARIN
TAB 5 MG 10
MILLIGRAM
VERAPAMIL
SR TAB 240
MG
LOSARTAN
POTASSIUM
TAB 50 MG
Active Orders
at Discharge
Verapamil
SR Oral
240 MG
Losartan Oral
50 MG
Discharge
Pharmacy Orders
VERAPAMIL
SR TAB
240 MG
LOSARTAN
POTASSIUM
TAB 50 MG
280000:
CNS
Agents
281604:
Antidepressants
DULOXETINE CAP
20 MG
Discharge
Instructions
cymbalta
Discharge Plan
cymbalta
Clinic Note After
Discharge
Outpatient
Medications after
Discharge
coumadin
verapamil
Coumadin 5
mg Tab
Verapamil
180 mg Extended
Release Tab
cymbalta
Losartan
Potassium 100
mg Tablet
Pregabalin
50mg
Capsule
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
Conclusions
• Diverse medication data can be automatically
integrated
• Organizing data by time and drug class can
highlight possible errors
Acknowledgements
• Carol Friedman for use of MedLEE
• US National Library of Medicine:
Research Grant 5R01LM007593-05
Training Grant LM07079-1