Cognitive tests predict real-world errors: the relationship between drug name confusion rates in laboratory-based memory and perception tests and corresponding error rates in large pharmacy chains

Abstract

Background: Drug name confusion is a common type of medication error and a persistent threat to patient safety. In the USA, roughly one per thousand prescriptions results in the wrong drug being filled, and most of these errors involve drug names that look or sound alike. Prior to approval, drug names undergo a variety of tests to assess their potential for confusability, but none of these preapproval tests has been shown to predict real-world error rates.

Objectives: We conducted a study to assess the association between error rates in laboratory-based tests of drug name memory and perception and real-world drug name confusion error rates.

Methods: Eighty participants, comprising doctors, nurses, pharmacists, technicians and lay people, completed a battery of laboratory tests assessing visual perception, auditory perception and short-term memory of look-alike and sound-alike drug name pairs (eg, hydroxyzine/hydralazine).

Results: Laboratory test error rates (and other metrics) significantly predicted real-world error rates obtained from a large, outpatient pharmacy chain, with the best-fitting model accounting for 37% of the variance in real-world error rates. Cross-validation analyses confirmed these results, showing that the laboratory tests also predicted errors from a second pharmacy chain, with 45% of the variance being explained by the laboratory test data.

Conclusions: Across two distinct pharmacy chains, there is a strong and significant association between drug name confusion error rates observed in the real world and those observed in laboratory-based tests of memory and perception. Regulators and drug companies seeking a validated preapproval method for identifying confusing drug names ought to consider using these simple tests. By using a standard battery of memory and perception tests, it should be possible to reduce the number of confusing look-alike and sound-alike drug name pairs that reach the market, which will help protect patients from potentially harmful medication errors.

Keywords: Human error; Human factors; Medication safety; Patient safety.

Figure 1

The battery of laboratory memory and perception tests. In the backward masking test, participants attempted to identify a visually presented drug name that was immediately concealed by a visual mask (a row of XXX's). In the progressive demasking test, participants tried to detect a visually presented drug name that was gradually revealed from behind an obscuring visual mask (a row of ###'s). In the speech-in-noise test, participants attempted to identify an orally presented drug name played in background multitalker babble. In the short-term memory test, participants attempted to remember a visually presented drug name after solving a complex math problem. At the end of each trial on each test, participants made two responses: (1) a free recall response in which participants typed the target drug name that they saw or heard and (2) a two-alternative forced-choice response in which participants chose between the target drug name and a competitor drug name.

Figure 2

The predicted error rates relative to the real-world error rates. The predicted error rates were derived from the final regression model, which included laboratory test errors, laboratory test near misses and word attributes. The regression line represents the least-squares best-fitting line from the final regression model.

Figure 3

The predicted error rates relative to the real-world error rates from the second pharmacy chain. The predicted error rates were derived from the final regression model, which included laboratory test errors, laboratory test near misses and word attributes. The regression line represents the least-squares best-fitting line from the final regression model.