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Cox C, Fritz Z. BMJ. 2022;377:e066720.

As more patients are gaining access to their electronic health records, including clinician notes, the language clinicians use can shape how patients feel about their health and healthcare provider. This commentary describes how some words and phrases routinely used in provider notes, such as “deny” or “non-compliant”, may inadvertently build distrust with the patient. The authors recommend medical students and providers reconsider their language to establish more trusting relationships with their patients.

Kelman B. Kaiser Health News. April 29, 2022.

Technological solutions harbor unique risks that can result in patient harm. This article shares a response to reports of automated dispensing cabinet (ADC) menu selection limitations that contribute to mistakes. The piece suggests the implementation of a 5-letter search requirement prior to removing a medication from an ADC. It provides an update on industry response to this forcing function recommendation.
Kuske S, Willmeroth T, Schneider J, et al. BMJ Open Qual. 2022;11:e001741.
Comprehensive implementation of reporting and learning systems (RLS, also known as incident reporting systems) is important for its successful use as a patient safety improvement tool. This study aimed to develop a set of “implementation patient safety indicator(s) sets” to monitor the extent to which an RLS has been implemented in hospitals. Implementation outcomes include acceptability, adoption, appropriateness, implementation costs, feasibility, fidelity, penetration, and sustainability. Study participants rated acceptability and sustainability as most relevant to successful implementation.
Schnock KO, Roulier S, Butler J, et al. J Patient Saf. 2022;18:e407-e413.
Patient safety dashboards are used to communicate real-time patient data to appropriately augment care. This study found that higher usage of an electronic patient safety dashboard resulted in lower 30-day readmission rates among patients discharged from adult medicine units compared to lower usage groups.
Frisch NK, Gibson PC, Stowman AM, et al. Am J Emerg Med. 2022;Epub Feb 21.
Electronic health records (EHR) can improve patient care and safety but are not without potential risks. A cyberattack led to a 25-day shutdown of a hospital’s EHR that necessitated a rapid shift to manual processes. This article outlines the laboratory service’s processes during the shutdown, including patient safety and error reduction, billing, and maintaining compliance with regulatory policies.
Alboksmaty A, Beaney T, Elkin S, et al. The Lancet Digital Health. 2022;4:e279-e289.
The COVID-19 pandemic led to a rapid transition of healthcare from in-person to remote and virtual care. This review assessed the safety and effectiveness of pulse oximetry in remote patient monitoring (RPM) of patients at home with COVID-19. Results show RPM was safe for patients in identifying risk of deterioration. However, it was not evident whether remote pulse oximetry was more effective than other virtual methods, such as virtual visits, monitoring consultations, or online or paper diaries.
Blijleven V, Hoxha F, Jaspers MWM. J Med Internet Res. 2022;24:e33046.
Electronic health record (EHR) workarounds arise when users bypass safety features to increase efficiency. This scoping review aimed to validate, refine, and enrich the Sociotechnical EHR Workaround Analysis (SEWA) framework. Multidisciplinary teams (e.g. leadership, providers, EHR developers) can now use the refined SEWA framework to identify, analyze and resolve unsafe workarounds, leading to improved quality and efficiency of care.
Tee QX, Nambiar M, Stuckey S. J Med Imaging Radiat Oncol. 2022;66:202-207.
Diagnostic errors in radiology can result in treatment delays and contribute to patient harm. This article provides an overview of the common cognitive biases encountered in diagnostic radiology that can contribute to diagnostic error, and strategies to avoid these biases, such as the use of a cognitive bias mitigation strategy checklist, peer feedback, promoting a just culture, and technology approaches including artificial intelligence (AI).
Giardina TD, Choi DT, Upadhyay DK, et al. J Am Med Inform Assoc. 2022;29:1091-1100.
Most patients can now access their provider visit notes via online portals and many have reported mistakes such as diagnostic errors or missed allergies. This study asked patients who may be “at-risk” for diagnostic error about perceived concerns in their visit notes. Patients were more likely to report having concerns if they did not trust their provider and did not have a good feeling about the visit. Soliciting patient concerns may be one way to improve transparency regarding diagnostic errors and trust in providers.

ECRI. Plymouth Meeting, PA. March 2022.

The global COVID-19 pandemic has exacerbated patient safety concerns. ECRI presents the top ten patient concerns for 2022, including staffing challenges, human factors in telehealth, and supply chain disruptions.
Lam D, Dominguez F, Leonard J, et al. BMJ Qual Saf. 2022;Epub Mar 22.
Trigger tools and incident reporting systems are two commonly used methods for detecting adverse events.  This retrospective study compared the performance of an electronic trigger tool plus manual screening versus existing incident reporting systems for identifying probable diagnostic errors among children with unplanned admissions following a prior emergency department (ED) visit. Of the diagnostic errors identified by the trigger tool and substantiated by manual review, less than 10% were identified through existing incident reporting systems.
Gonzalez-Smith J, Shen H, Singletary E, et al. NEJM Catalyst. 2022;3.
Clinical decision support (CDS) helps clinicians select appropriate medications, arrive at a correct diagnosis, and improve intraoperative decision making. Through interviews with health system executives, clinicians, and artificial intelligence (AI) experts, this study presents multiple perspectives on selection and adoption of AI-CDS in healthcare. Four emerging trends are presented: (1) AI must solve a priority problem; (2) the tool must be tested with the health system’s patient population; (3) it should generate a positive return on investment; and (4) it should be implemented efficiently and effectively.
Reese T, Wright A, Liu S, et al. Am J Health Syst Pharm. 2022;Epub Feb 10.
Computerized decision support alerts for drug-drug interactions are commonly overridden by clinicians. This study examined fifteen well-known drug-drug interactions and identified risk factors that could reduce risk in the majority of interactions (e.g., medication order timing, medication dose, and patient factors).

Errors in medication management and administration are major threats to patient safety. This piece explores issues with opioid and nursing-sensitive medication safety as well as medication safety in older adults. Future research directions in medication safety are also discussed.

Domingo J, Galal G, Huang J. NEJM Catalyst. 2022;3.
Failure to follow up on abnormal diagnostic test results can cause delays in patients receiving appropriate care. This hospital used an artificial intelligence natural language processing system to identify radiology reports requiring follow-up. The system triggered automated notifications to the patient and ordering provider, and tracked follow-ups to completion. System development, deployment and next steps are detailed.