Medication Error Research
This project involved Medication Error Research. Medication errors make up a large part of the number of errors that occur in the healthcare system. Studies have revealed that on the average there are 1-2 medication errors for every ten prescriptions that are filled. Deficiencies in information underlay many of these errors. These deficiencies in information relate to similar labeling and packaging, look-alike brand names, and sound-alike brand names. This research has focused on the information that is contained in the actual words of the drug names, and how the format of the text of the drug name is portrayed on the drug container and the prescription label. Different formats have been created that break up the drug name into parts that help identify the dissimilarities between drug names. For instance, the formats such as LEVOXINE, LEVOXINE, and LEVOXINE use large fonts and color to break the drug names up. These different formats have been used in sorting tasks in which pharmacists must sort stacks of prescription labels into slots labeled with the drug name. The speed at which prescription labels can be sorted and the number of errors associated with the placement of incorrect prescription cards into the wrong slot have been quantified. It is the goal of this research to identify the format that produces the quickest sort time and the fewest number of errors with the least amount of variation between subjects. It is hoped that this research will help identify ways to reduce medication errors.
In this photo you can see graduate student, Aaron Ross, discussing the apparatus he built for conducting the prescription label sorting task. Here are close ups of the sorting bins.
Results of the Medication Error Research Study
The data from this research show that using medication labels with the formatLEVOXINE produce the fewest number of medication errors. With this format yellow highlight is used to breakup the drug name. The data also show that using medication labels with the format LEVOXINE produce the fastest sort times. With this format red text is used to breakup the drug name. The use of yellow highlight had the smallest standard deviation for medication errors, while the use of red text had the smallest standard deviation for sort time. The use of yellow highlight and red text in medication labels both show promise in reducing the number of medication errors and increasing the efficiency of pharmacy operations.
The results of this study can be applied to the current operations of pharmacies. In hospital pharmacies medications are pulled from bins that are marked by labels containing only the medication name. When these bins are stocked, the medication name is the only piece of information that is used to identify the correct bin. Also, when medications are obtained from the bins, the label is again the only piece of information that is used to identify the correct bin. The results of this study could be used to redesign the labels of bins, which contain medications that have names similar to other medications. Pharmaceutical companies may also use the information from this study to redesign the package labels of medications that have names similar to other medications. Any pharmacy operation that uses the medication name to identify a medication could benefit from the redesign of medication labels based on the information from this study.
This research was meant to help identify ways to reduce the number of medication errors. It was identified by this study that the use of different sized text and color in the design of medication labels does help to reduce the number of errors. Further studies may look closer at the sort times between yellow highlight and red text label designs. Also, further studies may identify the amount of contrast that is needed when using yellow highlight or red text in medication labels. Research on the location of the medication word on the medication labels may provide relevant information on the reduction of medication errors. New information is the key in understanding and preventing medication errors.
The medication error research study was performed by Aaron Ross - a recent graduate of our Industrial Engineering Master of Science program. Aaron's specialization was in the area of Human Factors and Ergonomics. If you have questions concerning this research project, you may contact Dr. Simon Hsiang.