Automated detection of look-alike/sound-alike medication errors.
OBJECTIVE
The development and evaluation of an algorithm for detecting potential medication errors due to look-alike/sound-alike (LASA) drug names are described.


CONCLUSIONS
A computer algorithm that detects potential LASA errors by analyzing medication orders and diagnostic claims data was developed. The algorithm flags a potential error when (1) a medication order is not justified by a diagnosis documented in the patient's record, (2) another medication whose orthographic similarity to the index drug exceeds a specified threshold exists, and (3) the latter drug has an indication that matches an active documented diagnosis. A review of medication orders and diagnostic claims at a large health system identified cases in which cycloserine was ordered but cyclosporine was the intended treatment. Subsequent review of all cycloserine orders over a 7-year period indicated that 11 of 16 orders were erroneous, prompting placement of an alert regarding the potential for LASA errors involving cycloserine and cyclosporine in the electronic order-entry system. Automated detection and confirmation of LASA errors via chart review can be used retrospectively to identify problematic pairs of drug names and to assess associated error rates within a healthcare system. The same techniques can be used to prevent errors in real time through indication alerts if accurate diagnostic information is available at the time of order entry.


CONCLUSIONS
Automated methods involving the use of medication orders, diagnostic claims, and indications can be used to detect and prevent LASA errors.
University of Illinois at Chicago, Chicago, IL.
Christine
C
Rash-Foanio
University of Illinois at Chicago, Chicago, IL.
William
W
Galanter
Takeda Pharmaceuticals, Deerfield, IL.
Michelle
M
Bryson
University of Illinois at Chicago, Chicago, IL.
Suzanne
S
Falck
Chicago, IL.
King Lup
KL
Liu
Harvard Medical School, Boston, MA.|Center for Patient Safety Research and Practice, Brigham.|Women's Hospital, Boston, MA.
Gordon D
GD
Schiff
Institute for Safe Medication Practices, Horsham, PA.
Allen
A
Vaida
Department of Communication Studies and Center for Communication and Health, Northwestern University, Chicago, IL. bruce.lambert@northwestern.edu.
Bruce L
BL
Lambert
D000293:Adolescent; D000328:Adult; D000368:Aged; D000465:Algorithms; D005260:Female; D006801:Humans; D008297:Male; D050316:Medical Order Entry Systems; D008508:Medication Errors / Q000517:prevention & control* / Q000706:statistics & numerical data; D008875:Middle Aged; D012189:Retrospective Studies; D017751:Safety Management / Q000379:methods*; D012984:Software; D055815:Young Adult
Systematized Nomenclature of Medicine; cycloserine; cyclosporine; electronic prescribing; medication errors; patient harm