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Checking it twice: an evaluation of checklists for detecting medication errors at the bedside using a chemotherapy model
  1. Rachel E White1,
  2. Patricia L Trbovich1,
  3. Anthony C Easty2,
  4. Pamela Savage3,
  5. Katherine Trip3,
  6. Sylvia Hyland4
  1. 1Healthcare Human Factors Group, Centre for Global eHealth Innovation, University Health Network, Toronto, Canada
  2. 2Healthcare Human Factors Group, Centre for Global eHealth Innovation, University Health Network, University of Toronto, Mount Sinai Hospital, Toronto, Canada
  3. 3Princess Margaret Hospital, University Health Network, Toronto, Canada
  4. 4Institute for Safe Medication Practices Canada, Toronto, Canada
  1. Correspondence to Ms Rachel E White, Healthcare Human Factors Group, Centre for Global eHealth Innovation, University Health Network, 4th Floor, R Fraser Elliott Building, 190 Elizabeth Street, Toronto, Ontario M5G 2C4, Canada; rachel.white{at}


Objective To determine what components of a checklist contribute to effective detection of medication errors at the bedside.

Design High-fidelity simulation study of outpatient chemotherapy administration.

Setting Usability laboratory.

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

Main outcome measures 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.

  • Medication error
  • medication safety
  • checklist
  • double check
  • error detection

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  • Funding This research was conducted under a research grant from the Canadian Patient Safety Institute (Grant # RFA0506284).

  • Competing interests None.

  • Ethics approval Ethics approval was provided by the University Health Network, Research Ethics Board, Toronto, Ontario, Canada.

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