… with medication ordering errors . … King CR, Abraham J, Fritz BA, et al. Predicting self-intercepted medication …

… for safer and more appropriate prescribing. … Galanter W, Eguale T, Gellad W, et al. Personal formularies …

Look-alike and sound-alike (LASA) drugs are a well-established source of medication errors that place patients at risk for adverse drug events. Prior research has shown that these medications can be automatically identified using diagnostic codes at the time of electronic prescribing. Using electronic health record data on medication orders and diagnostic claims data from a single academic medical center as well as data on medication indications, researchers developed an algorithm to identify LASA prescribing errors. Although the algorithm was able to identify LASA prescribing errors that may not have been found by other means, the positive predictive value was 12.1% and the false-positive rate was greater than 75%. The authors advocate for further research to improve specificity and sensitivity of this approach. A past WebM&M commentary discussed a case involving the mix-up of two medications with similar names.

Having multiple patient records open in the electronic health record increases the potential risk of wrong-patient actions. This randomized trial tested two different electronic health record configurations: one allowed up to four patient records to be open at a time, and the other allowed only one to be open. Among the 3356 clinicians with nearly 4.5 million order sessions, there were no significant differences in wrong-patient orders. However, the investigators noted that clinicians in the multiple records group placed most orders with just one record open. A post hoc analysis determined that the rate of errors increased when orders were placed with multiple records open. A related editorial highlights the tradeoffs between safety and efficiency and argues for examining the context of the two configurations, including throughput and clinician satisfaction. A previous PSNet perspective discussed assessing and improving the safety of electronic health records.

… J Am Med Info Asso … Alerts designed to notify providers of … Amato MG; Kim H; Ai A; Cimino JJ; Desai BR; El-Kareh R; Galanter W; Longhurst CA; Malhotra S; Radecki RP; Samal L; …

This simulation study compared computerized medication order entry between two commercial electronic health records and a prototype designed for safe prescribing. Physicians using the prototype had fewer errors compared to either commercial platform, highlighting the need to improve electronic health record usability in order to enhance medication safety.

Although electronic prescribing has been shown to reduce prescribing errors, the impact on adverse drug events remains less certain. Overriding of drug–drug interaction alerts and inclusion of free-text notes that contain inaccurate information within electronic prescriptions suggests that safe prescribing requires more than an electronic system. To improve the safety of electronic prescribing, the authors make several broad recommendations. They suggest including drug indications on prescriptions, ensuring a readily available and accurate medication list, notifying pharmacies when previously prescribed medications are canceled, using standard prescription instructions, improving decision support, and promoting consideration of nondrug options. A previous WebM&M commentary discussed an incident involving an electronic prescribing error. The Moore Foundation provides free access to this article.

Safe diagnosis is a complex challenge that requires multidisciplinary approaches to achieve lasting improvement. The authors worked with a multidisciplinary panel to build a 10-element framework outlining steps that support conservative diagnosis. Recommendation highlights include a renewed focus on history-taking and physician examination, as discussed in a PSNet perspective. They also emphasize the importance of continuity between clinicians and patients to build trust and foster timely diagnosis. Taken together with recommendations for enhanced communication between specialist and generalist clinicians and more judicious use of diagnostic testing, this report is a comprehensive approach to reducing overdiagnosis and overtreatment.

… of the American Medical Informatics Association : JAMIA … J Am Med Inform Assoc … Opening multiple patients' charts in …

… of the American Medical Informatics Association : JAMIA … J Am Med Inform Assoc … Clinical decision support (CDS) …

Although computerized provider order entry (CPOE) has been shown to prevent some medication errors, implementing these systems may introduce new errors. This observational study analyzed voided clinician orders to determine if they represented true medication ordering errors identified by the canceling provider. Investigators interviewed ordering and voiding providers and reviewed patients' medical records. They found that the positive predictive value of canceled orders representing true medication ordering errors was 93.1%. The reasons for order cancellation were more accurately reported during provider interviews rather than in the reasons reported within the CPOE system. Common ordering errors included duplicate orders and incorrectly composed orders. A past PSNet perspective discussed the impact of CPOE on patient safety.

… of the American Medical Informatics Association : JAMIA … J Am Med Inform Assoc … Wrong-patient errors can occur during …

… of the American Society of Health-System Pharmacists … Am J Health Syst Pharm … Look-alike and sound-alike medications …

Although computerized provider order entry has been found to prevent some medication errors, simulation studies have also demonstrated that electronic prescribing platforms can introduce or fail to prevent medication errors. This retrospective electronic health record analysis examined medication orders that were canceled. Weekend and overnight orders were less likely to be voided than weekday or daytime orders. Pharmacist, nurse, and student orders were more likely to be canceled than physician orders. Comparing the clinician-provided reason for voiding an order with the more comprehensive information in the medical record, physicians found that clinicians' reported reasons for voiding orders were largely inaccurate. The authors suggest there is unrealized potential to characterize medication ordering errors using voided-order data.

Computerized provider order entry (CPOE) systems can effectively prevent many prescribing errors, but their overall safety benefit has not yet been fully realized. More widespread implementation of these systems has revealed new safety concerns. A prior study funded by the US Food and Drug Administration found that many of the safety issues associated with CPOE could be ascribed to poor usability of the systems, the lack of interoperability, and failure to track and learn from concerns identified by users. This follow-up study analyzed more than 1300 CPOE error reports to further classify the types of errors and their impact on patient care. Investigators determined that patients experienced delays in receiving medications due to these errors and were at risk of receiving duplicate medications or incorrect doses of medications. Similar to previous studies, the most common types of CPOE errors included problems with transmitting orders to the correct site of care, incorrect dose, or duplicate orders that were not detected by the system. A WebM&M commentary discussed an error that led to patient harm due to an incorrect default CPOE order.

Look-alike and sound-alike drug names are a concerning source of confusion and medication errors. Although drug names currently undergo tests to assess their potential for confusion prior to approval, these tests have not reliably predicted real-world error rates. This study describes the development and validation of four drug name memory and perception laboratory tests. Eighty participants completed the tests and their results were analyzed against actual errors in two large outpatient pharmacy chains. The laboratory tests performed very well, demonstrating a strong association between drug name confusion errors seen during testing and those observed in real-world experience. The authors suggest that regulators and drug companies consider using these tests prior to approval of new drug names.

Clinicians use thousands of prescription medications during routine care, and new medications are regularly incorporated into practice. Confusion between medications with names that appear or sound similar is a common cause of medication errors. This observational study sought to determine whether a computerized provider order entry system—with an alert that prompted providers to enter the indication when certain medications were ordered and required users to click "OK" to ignore the alert, to add the drug to a problem list, or to cancel the order—identified drug name confusion errors. These alerts intercepted 1.4 drug name confusion errors per 1000 alerts. While authors recommend that these alerts be implemented to decrease medication errors, they suggest narrowing the number of medications selected to prompt alerts to reduce risk of alert fatigue. A previous AHRQ WebM&M commentary describes an incident involving a look-alike drug error and reviews strategies to enhance safety of medication selection.

Wrong-patient errors have long been a risk in hospitals. In one seminal case, a patient underwent an invasive procedure intended for another patient with a similar name. In the era of electronic medical records, errors such as entering notes or ordering medications for the wrong patient may occur as a consequence of multitasking. This AHRQ-funded study evaluated the effectiveness of an alert system, which required entry of an appropriate clinical diagnosis, at preventing wrong-patient medication errors in a computerized provider order entry system. Although the system did correctly identify and prevent incorrect prescriptions, 4000 alerts were required to prevent a single error. Other studies have successfully used forcing functions, or simply placing the patient's photograph on the order screen, to prevent wrong-patient errors.

Strategies to prevent medication errors are an ongoing focus in patient safety. Computerized provider order entry, medication reconciliation, avoidance of drug–drug interactions, and bar-coded medication administration are a few areas generating significant attention. This review discusses an alternate approach to medication safety, focusing on prevention of prescribing unnecessary medications at the outset. The authors provide a set of principles that urge clinicians to: think beyond drugs, practice more strategic prescribing, maintain heightened awareness about side effects, exercise skepticism about new drugs, work with patients for a shared agenda, and consider long-term impacts of medications prescribed. Each of these principles is discussed and sets the background for a recommendation to shift current paradigms in prescribing from "newer and more is better" to "fewer and more time tested is best."

… International journal of medical informatics … Int J Med Inform … A decision support system, added to an …