Checking it twice: an evaluation of checklists for detecting medication errors at the bedside using a chemotherapy model.
OBJECTIVE
To determine what components of a checklist contribute to effective detection of medication errors at the bedside.


METHODS
High-fidelity simulation study of outpatient chemotherapy administration.


METHODS
Usability laboratory.


METHODS
Nurses from an outpatient chemotherapy unit, who used two different checklists to identify four categories of medication administration errors.


METHODS
Rates of specified types of errors related to medication administration.


RESULTS
As few as 0% and as many as 90% of each type of error were detected. Error detection varied as a function of error type and checklist used. Specific step-by-step instructions were more effective than abstract general reminders in helping nurses to detect errors. Adding a specific instruction to check the patient's identification improved error detection in this category by 65 percentage points. Matching the sequence of items on the checklist with nurses' workflow had a positive impact on the ease of use and efficiency of the checklist.


CONCLUSIONS
Checklists designed with explicit step-by-step instructions are useful for detecting specific errors when a care provider is required to perform a long series of mechanistic tasks under a high cognitive load. Further research is needed to determine how best to assist clinicians in switching between mechanistic tasks and abstract clinical problem solving.
White
Rachel E
RE
Healthcare Human Factors Group, Centre for Global eHealth Innovation, University Health Network, Toronto, Canada. rachel.white@uhn.on.ca
Trbovich
Patricia L
PL
Easty
Anthony C
AC
Savage
Pamela
P
Trip
Katherine
K
Hyland
Sylvia
S
D000554:Ambulatory Care Facilities; D000970:Antineoplastic Agents / Q000627:therapeutic use*; D057189:Checklist / Q000592:standards*; D006801:Humans; D008508:Medication Errors / Q000517:prevention & control*; D017146:Models, Organizational; D009864:Ontario
D000970:Antineoplastic Agents