medication reconciliation using natural language processing and controlled terminologies james j....
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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
Stop
Stop
Stop
Stop
Go
StopGo
Stop
Go
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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
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Computer Assisted Medication Reconciliation
• Poon et al.: JAMIA 2006:– Preadmission Medication List– Grouped medications by generic names
• 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
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
Data SourcesData Source System Data Type
NarrativeCoded
NarrativeNarrative
CodedCodedCodedCoded
NarrativeNarrativeNarrative
Coded
WebCISWebCISWebCISWebCISEclipsysWebCISEclipsysWebCISEclipsysWebCISWebCISWebCIS
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
Data Source Meds Recordswith Data
Meds perPatient
Prior Clinic Note * 157 17 9.2Prior Outpatient Medications 211 13 16.2Admission Note * 102 14 7.3Admission Note Plan * 41 12 3.4Admission Orders 88 8 11.0
Admission Pharmacy Orders 152 14 10.9
Active Orders at Discharge 93 8 11.6
Discharge Pharmacy Orders 171 14 12.2
Discharge Instructions * 60 7 8.6Discharge Plan * 123 16 7.7
Clinic Note After Discharge * 140 16 8.8
Outpatient Medications after Discharge 225 13 17.3
* Narrative text
169 UMLS (93%)
8 Other Meds (4%):
INH, MVI, asa, Os-Cal,
darvocet, hctz, niacin, toprol
4 Non-Med (3%): cream, antiinflam-
matory, lotion, lozenge, po
MedLEE Terms Found30 Non-Med,
(5%)48 Other Meds (8%)
545 UMLS (87%)
Mapped to UMLS
MED Terms
442 AHFS (99.5%)
2 non-AHFS (0.5%): oxygen,
medication
16 non-AHFS (1.0%)
1517 AHFS (99.0%)
Mapped to AHFS
Patient #9201204:
Anticoag-ulants
240400: Cardiac Drugs
240800: Hypoten-
sive Agents
280000: CNS
Agents
281604: Antidep-ressants
Prior Clinic Note coumadin verapamil cozaar cymbalta
Prior Outpatient Medications
Coumadin 5 mg Tab
Verapamil180 mg
Extended Release Tablet
LosartanPotassium
100 mgTablet
Pregabalin 50mg Capsule
Admission Note coumadin verapamil cozaar cymbalta
Admission Note Plan
coumadin
Admission Orders
Warfarin Sodium Oral 10
MG
Verapamil SR Oral 240 MG
Losartan Oral 50 MG
Admission Pharmacy Orders
WARFARIN TAB 5 MG
10 MILLIGRA
M
VERAPAMIL SR TAB 240 MG
LOSARTAN POTAS-
SIUM TAB 50
MG
Transition from Outpatient to Inpatient
Patient #9201204:
Anticoag-ulants
240400: Cardiac Drugs
240800: Hypoten-
sive Agents
280000: CNS
Agents
281604: Antidep-ressants
Admission Pharmacy Orders
WARFARINTAB 5 MG 10MILLIGRAM
VERAPAMILSR TAB 240
MG
LOSARTAN POTASSIUMTAB 50 MG
Active Orders at Discharge
Verapamil SR Oral 240 MG
Losartan Oral 50 MG
DischargePharmacy Orders
VERAPAMIL SR TAB 240 MG
LOSARTANPOTASSIUMTAB 50 MG
DULOXET-INE CAP 20 MG
Discharge Instructions
cymbalta
Discharge Plan cymbalta
Clinic Note After Discharge
coumadin verapamil cymbalta
OutpatientMedications after
Discharge
Coumadin 5mg Tab
Verapamil180 mg Exte-
ndedRelease Tab
LosartanPotassium 100
mg Tablet
Pregabalin50mg
Capsule
Transition from Outpatient to Inpatient
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
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