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The PSNet Collection: All Content

The AHRQ PSNet Collection comprises an extensive selection of resources relevant to the patient safety community. These resources come in a variety of formats, including literature, research, tools, and Web sites. Resources are identified using the National Library of Medicine’s Medline database, various news and content aggregators, and the expertise of the AHRQ PSNet editorial and technical teams.

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Displaying 1 - 7 of 7 Results
Rozenblum R, Rodriguez-Monguio R, Volk LA, et al. Jt Comm J Qual Patient Saf. 2019;46:3-10.
Clinical decision support (CDS) tools help identify and reduce medication errors but are limited by the rules and types of errors programmed into their alerting logic and their high alerting rates and false positives, which can contribute to alert fatigue. This retrospective study evaluates the clinical validity and value of using a machine learning system (MedAware) for CDS as compared to an existing CDS system. Chart-reviewed MedAware alerts were accurate (92%) and clinically valid (79.7%). Overall, 68.2% of MedAware alerts would not have been generated by the CDS tool and estimated cost savings associated with the adverse events potentially prevented via MedAware alerts were substantial ($60/drug alert).
Kron K, Myers S, Volk LA, et al. Am J Health-syst Pharm. 2018;75:774-783.
Misinterpretation of medication instructions can lead to medication administration errors and patient harm. Current computerized provider order entry for medications does not support best practices for medication instructions. This study describes an expert panel process to delineate how to include the indication—the reason for prescribing the medication—in the medication instructions. Experts recommend that prescribing begin with the indication for the medication, with decision support that promotes selection of the optimal medication. The authors emphasize the importance of a streamlined electronic prescribing process. A past PSNet perspective discussed integrating clinician decision support systems to improve medication safety.
Seoane-Vazquez E, Rodriguez-Monguio R, Alqahtani S, et al. Expert Opin Drug Saf. 2017;16:1103-1109.
This experimental study found that including the approved indication along with the generic name reduced medication errors associated with look-alike and sound-alike drug pairs. The authors advocate for incorporating this information into medication prescribing.
Szeinbach S, Seoane-Vazquez E, Parekh A, et al. Int J Qual Health Care. 2007;19:203-9.
Medication errors may originate at each step of the prescribing process, and a prior study conducted in the inpatient setting demonstrated that nearly 4% of medication orders may be dispensed incorrectly. In this study, community pharmacists were surveyed regarding their perceptions of the frequency of dispensing errors and factors contributing to errors. Respondents felt that dispensing errors were relatively frequent and were more likely when pharmacists were overworked, a sentiment supported by prior research. Bar coding has been advocated as one means of potentially reducing drug dispensing errors.