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This commentary presents two cases highlighting common medication errors in retail pharmacy settings and discusses the importance of mandatory counseling for new medications, use of standardized error reporting processes, and the role of clinical decision support systems (CDSS) in medical decision-making and ensuring medication safety.

Trauma staff at The Alfred Hospital use a computerized decision support system to guide the care of patients during the critical first 60 minutes of resuscitation. Known as the Trauma Reception and Resuscitation System (TR&R®), this program generates prompts based on more than 40 algorithms and real-time clinical data, including patient vital signs and information entered by a trauma nurse. Displayed on a large overhead monitor, these prompts are used by clinicians to direct the care of trauma patients and to facilitate documentation and communication.

Chin DL, Wilson MH, Trask AS, et al. J Med Syst. 2020;44:185.
Clinical decision support (CDS) alerts can improve patient safety, and prior research suggests that monitoring alert overrides can identify errors. The researchers describe a novel approach to using existing CDS systems to detect medication prescribing errors based on drug-drug interaction and allergy alert overrides. Dose alert overrides had high sensitivity to detect medication prescribing errors occurring in an inpatient setting.
Staines A, Amalberti R, Berwick DM, et al. Int J Qual Health Care. 2021;33:mzaa050.
The authors of this editorial propose a five-step strategy for patient safety and quality improvement staff to leverage their skills to support patients, staff, and organizations during the COVID-19 pandemic. It includes (1) strengthening the system and environment, (2) supporting patient, family and community engagement and empowerment, (3) improving clinical care through separation of workflows and development of clinical decision support, (4) reducing harm by proactively managing risk for patients with and without COVID-19, and (5) enhancing and expanding the learning system to develop resilience.
Vidrine R, Zackoff M, Paff Z, et al. Jt Comm J Qual Patient Saf. 2020;46:299-307.
Early recognition and treatment of sepsis is a critical safety issue. The authors of this study aimed to reduce the frequency of delayed sepsis recognition in a pediatric intensive care unit (PICU) through the use of an automated clinical decision support tool (CDS) prompting multidisciplinary sepsis huddles. After a two-year period, the average number of days between episodes of delayed sepsis recognition improved from one episode every 9 days to one every 28 days, and the median time to antibiotics decreased from 1.53 hours to 1.05 hours, representing a significant reduction.
Three patients were at the same hospital over the course of a few months for vascular access device (VAD) placement and experienced adverse outcomes. The adverse outcomes of two of them were secondary to drugs given for sedation, while the third patient’s situation was somewhat different. Vascular access procedures are extremely common and are relatively short but may require the use of procedural sedation, which is usually very well tolerated but can involve significant risk, as these cases illustrate.
Aaron S, McEvoy DS, Ray S, et al. J Am Med Inform Assoc. 2019;26:37-43.
Although clinical decision support is an important safety tool, unintended consequences include frequent alerts with resultant alert fatigue and overrides. This observational study investigated whether override comments for clinical decision rules could be used to determine if a rule was broken. Investigators discovered that malfunctions were prevalent in clinical decision support. While the frequency of comments did not predict the presence of a rule malfunction, strongly negative comments were associated with erroneous decision support. The authors recommend routine monitoring of alert override comments to identify errors related to clinical decision support. A past WebM&M commentary recommended employing human factors engineering to make clinical decision support more effective.
Liberman AL, Newman-Toker DE. BMJ Qual Saf. 2018;27:557-566.
Patient safety measurement remains challenging. This article describes a framework to address gaps in measuring diagnostic error. The authors propose utilizing big data to develop diagnostic performance dashboards and benchmarking tools that support proactive learning and improvement strategies.
Brought to the emergency department from a nursing facility with confusion and generalized weakness, an older woman was found to have an elevated troponin level but no evidence of ischemia on her ECG. A consulting cardiologist recommended treating the patient with three anticoagulants. The next evening, she became acutely confused and a CT scan revealed a large intraparenchymal hemorrhage with a midline shift.
Wright A, Hickman T-TT, McEvoy D, et al. J Am Med Inform Assoc. 2016;23:1068-1076.
Although clinical decision support is a key patient safety strategy, it may also have unintended consequences. Investigators analyzed clinical decision support system malfunctions and surveyed chief medical informatics officers about such incidents. Nearly all health systems experience decision support malfunctions, and the majority of respondents' health systems had at least one within the last 12 months. Detailed examination of several specific cases found that software updates, differences in data fields and codes, unintended enabling and disabling of rules, and technical problems with other systems all resulted in decision support malfunctions. These vulnerabilities often remain undetected and lead to irrelevant or erroneous alerts, which in turn contribute to alert fatigue. The authors suggest that clinical decision support requires more robust testing and monitoring to reach its potential as a patient safety tool.
Murff HJ, FitzHenry F, Matheny ME, et al. JAMA. 2011;306:848-55.
Many adverse event identification methods cannot detect errors until well after the event has occurred, as they rely on screening administrative data or review of the entire chart after discharge. Electronic medical records (EMRs) offer several potential patient safety advantages, such as decision support for averting medication or diagnostic errors. This study, conducted in the Veterans Affairs system, reports on the successful development of algorithms for screening clinicians' notes within EMRs to detect postoperative complications. The algorithms accurately identified a range of postoperative adverse events, with a lower false negative rate than the Patient Safety Indicators. As the accompanying editorial notes, these results extend the patient safety possibilities of EMRs to potentially allow for real time identification of adverse events.
Metzger J, Welebob E, Bates DW, et al. Health Aff (Millwood). 2010;29:655-663.
Computerized provider order entry (CPOE) has provided significant safety benefits in research studies, especially when combined with clinical decision support to prevent common prescribing errors. However, CPOE's "real-world" performance has been mixed, with high-profile studies documenting a variety of unintended consequences. This AHRQ-funded study used simulated patient records to evaluate the ability of eight commercial CPOE modules to prevent medication errors. The overall results were disappointing, as CPOE failed to prevent many medication errors—including fully half of potentially fatal errors, which are considered never events. The individual CPOE products varied significantly in their ability to detect potential errors. Some hospitals did achieve superior performance, which the authors ascribe to greater experience with CPOE and implementation of more advanced decision support tools. Another recent article found that reminders within CPOE systems resulted in only small improvements in adherence to recommended care processes. Taken together, these studies imply that CPOE implementation may not result in large immediate effects on safety and quality in typical practice settings.
Newman-Toker DE, Pronovost PJ. JAMA. 2009;301:1060-2.
Studies from autopsy data and malpractice claims consistently identify diagnostic errors as a prominent cause of preventable morbidity and mortality, but as yet error prevention has focused on other areas of patient safety. This commentary discusses individual and systems factors that lead to diagnostic error and proposes steps toward minimizing such problems. In particular, the authors recommend focusing on misdiagnosis-related harm in specific clinical scenarios and using information technology to build decision support into routine clinician work flow. An AHRQ WebM&M perspective discussed cognitive biases that lead to diagnostic error.
Bonis PA, Pickens GT, Rind DM, et al. Int J Med Inform. 2008;77:745-53.
This study discovered that hospitals providing access to a popular clinical knowledge support system (called "UpToDate") were associated with improved health outcomes and shorter length of stay. However, use of the application itself may only be a marker rather than a direct cause of a hospital's favorable outcomes.
McGregor JC, Weekes E, Forrest GN, et al. J Am Med Inform Assoc. 2006;13:378-84.
Clinical decision support systems (CDSS) are being increasingly incorporated into electronic medical record systems. In this quasi-randomized study conducted at an academic medical center, the CDSS combined laboratory and pharmacy data to provide guidance on appropriate antimicrobial therapy to the hospital's antibiotic management team. The antibiotic management team made significantly more interventions on patients randomized to the intervention arm, resulting in cost savings for the hospital. The CDSS was also more efficient, saving the team nearly 1 hour per day. A prior systematic review revealed that CDSS have been broadly effective at changing provider behavior, but their effect on patient outcomes remains to be determined.