By the Institute of Safe Medication Practices
The implementation of information technology in medication-use systems is widely accepted as a way to reduce adverse drug events by decreasing human error (Mahoney, Berrard-Collins, Coleman, Amaral, & Cotter, 2007). Technology examples include computerized order entry systems, clinical decision support systems, robotic dispensing, profiled automated dispensing cabinets (ADCs), smart infusion pumps, and barcode scanning of medications during compounding, dispensing, ADC restocking, and administration. These technologies are meant to support human cognitive processes and, thus, have great potential to combat the shortcomings of manual medication systems and improve clinical decisions and patient outcomes. This is accomplished through precise controls, automatically generated cues and recommendations to help the user respond appropriately, prompts that promote the correct sequence of work or ensure the collection of critical information, and alerts to make the user aware of potential errors.
Information technology to support clinical decision-making does not replace human activity but rather changes it, often in unintended or unanticipated ways (Parasuraman & Manzey, 2010). Instances of misuse and disuse, often to work around technology issues, and new sources of errors after technology implementation, have been well documented. Errors can also be caused by over-reliance and trust in the proper function of technology (Goddard, Roudsari, & Wyatt, 2012). The technology can occasionally malfunction, misdirect the user, or provide incorrect information or recommendations that lead the user to change a previously correct decision or follow a pathway that leads to an error. Over-reliance on technology can result in serious consequences for patients. In its recent Safety Bulletin (ISMP Canada, 2016), our sister organization, ISMP Canada, highlighted human over-reliance on technology based on its analysis of an event reported to a Canadian national reporting system. In the article, they discussed two related cognitive limitations: automation bias and automation complacency.
An elderly patient was admitted to the hospital with new-onset seizures. Admission orders included the anticonvulsant phenytoin (handwritten using the brand name DILANTIN), 300 mg orally every evening. Before the pharmacy closed, a pharmacy staff member entered the Dilantin order into the pharmacy computer so that the medication could be obtained from an ADC in the patient care unit overnight. In the pharmacy computer, medication selection for order entry was performed by typing the first 3 letters of the medication name (“dil” in this case) and then choosing the desired medication name from a drop-down list. The computer list contained both generic and brand names. The staff member was interrupted while entering the order. When this task was resumed, dilTIAZem 300 mg was selected instead of Dilantin 300 mg.