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Salwei ME, Hoonakker PLT, Carayon P, et al. Hum Factors. 2022;Epub Apr 4.
Clinical decision support (CDS) systems are designed to improve diagnosis. Researchers surveyed emergency department physicians about their evaluation of human factors-based CDS systems to improve diagnosis of pulmonary embolism. Although perceived usability was high, use of the CDS tool in the real clinical environment was low; the authors identified several barriers to use, including lack of workflow integration.
Wang L, Goh KH, Yeow A, et al. J Med Internet Res. 2022;24:e23355.
Alert fatigue is an increasingly recognized patient safety concern. This retrospective study examined the association between habit and dismissal of indwelling catheter alerts among physicians at one hospital in Singapore. Findings indicate that physicians dismissed 92% of all alerts and that 73% of alerts were dismissed in 3 seconds or less. The study also concluded that a physician’s prior dismissal of alerts increases the likelihood of dismissing future alerts (habitual dismissal), raising concerns that physicians may be missing important alerts.
Van De Sijpe G, Quintens C, Walgraeve K, et al. BMC Med Inform Decis Mak. 2022;22:48.
Clinical decision support systems (CDSS) can help identify potential drug-drug interactions (DDI), but they can lead to alert fatigue and threaten patient safety. Based on an analysis of DDI alerts and survey data regarding physician experience using the DDI module in the CDSS, researchers identified barriers (i.e., lack of patient-specific characteristics and DDI-specific screening intervals) that contribute to false-positive alerts and alert fatigue.
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;79:1086-1095.
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).
Fischer H, Hahn EE, Li BH, et al. Jt Comm J Qual Patient Saf. 2022;48:222-232.
While falls are common in older adults, there was a 31% increase in death due to falls in the U.S. from 2007-2016, partially associated with the increase in older adults in the population. This mixed methods study looked at the prevalence, risk factors, and contributors to potentially harmful medication dispensed after a fall/fracture of patients using the Potentially Harmful Drug-Disease Interactions in the Elderly (HEDIS DDE) codes. There were 113,809 patients with a first time fall; 35.4% had high-risk medications dispensed after their first fall. Interviews with 22 physicians identified patient reluctance to report falls and inconsistent assessment, and documentation of falls made it challenging to consider falls when prescribing medications.
Berntsson K, Eliasson M, Beckman L. BMC Nurs. 2022;21:24.
Safe and accurate telephone triage is of critical importance, particularly during the COVID-19 pandemic. This Swedish study evaluated district nurses’ experiences and perceptions of patient safety at a national nurse advice triage call center. Interviews with nurses resulted in an overall theme of “being able to make the right decision” based on the categories of “communication” and “assessment.”
McDonald EG, Wu PE, Rashidi B, et al. JAMA Intern Med. 2022;182:265-273.
Deprescribing is one intervention to reduce the risk of adverse drug events, particularly in older adults and people taking five or more medications. In this cluster randomized trial, older adults (≥65 years) taking at least five medications at hospital admission were randomly assigned to intervention (personalized reports of deprescribing opportunities) or control. Despite an increase in deprescribing in both groups, there was no difference in adverse drug events or adverse drug withdrawal events.
Orenstein EW, Kandaswamy S, Muthu N, et al. J Am Med Inform Assoc. 2021;28:2654-2660.
Alert fatigue is a known contributor to medical error. In this cross-sectional study, researchers found that custom alerts were responsible for the majority of alert burden at six pediatric health systems. This study also compared the use of different alert burden metrics to benchmark burden across and within institutions.
Sibbald M, Monteiro SD, Sherbino J, et al. BMJ Qual Saf. 2022;31:426-433.
Diagnostic safety remains a patient safety priority. This randomized study including emergency medicine and internal medicine physicians as well as medical students found that electronic differential diagnostic support increased the likelihood that the correct diagnosis appeared in the differential, regardless of whether the tool was used early or late in the diagnostic process.
Maxwell E, Amerine J, Carlton G, et al. Am J Health Syst Pharm. 2021;78:s88-s94.
Clinical decision support (CDS) tools are intended to enhance care decision and delivery processes. This single-site retrospective study evaluated whether a CDS tool can reduce discharge prescription errors for patients receiving a medication substitution at admission. Findings indicate that use of CDS did not result in a decrease in discharge prescription omissions, duplications, or inappropriate medication reconciliation.
Slikkerveer M, van de Plas A, Driessen JHM, et al. J Patient Saf. 2021;17:e587-e592.
Anticoagulants, such as low-molecular-weight heparin (LMWH), are known to be high-risk for adverse drug events. This cross-sectional study identified prescribing errors – primarily lack of dosage adjustment for body weight and/or renal function – among one-third of LMWH users admitted to one hospital over a five-month period.
Koeck JA, Young NJ, Kontny U, et al. Pediatric Drugs. 2021;23:223-240.
Pediatric patients are at risk for medication prescribing errors due to weight-based dosing. This review analyzed 70 interventions aimed at reducing weight-based prescribing errors. Findings indicate that bundled interventions are most effective, and that interventions should include substitute or engineering controls (e.g., computerized provider order entry) along with administrative controls (e.g., expert consultation).
Cattaneo D, Pasina L, Maggioni AP, et al. Drugs Aging. 2021;38:341-346.
Older adults are at increased risk of hospitalization due to COVID-19 infections. This study examined the potential severe drug-drug interactions (DDI) among hospitalized older adults taking two or more medications at admission and discharge. There was a significant increase in prescription of proton pump inhibitors and heparins from admission to discharge. Clinical decision support systems should be used to assess potential DDI with particular attention paid to the risk of bleeding complications linked to heparin-based DDIs.
Vasey B, Ursprung S, Beddoe B, et al. JAMA Netw Open. 2021;4:e211276.
This study explored the role of machine-learning based clinical decision support (CDS) algorithms to support (rather than replace) human decision-making and the impact on diagnostic performance. This systematic review of 37 studies found limited evidence that the use of machine learning-based CDS systems contributes to improved diagnostic performance among clinicians. Interobserver agreement, user feedback, and clinician override were the most commonly reported outcomes. The authors emphasize the importance of further evaluation of human-computer interaction.
Kostopoulou O, Tracey C, Delaney BC. J Am Med Inform Assoc. 2021;28:1461-1467.
In addition to being used for patient-specific clinical purposes, data within the electronic health record (EHR) may be used for other purposes including epidemiological research. Researchers in the UK developed and tested a clinical decision support system (CDSS) to evaluate changes in the types and number of observations that primary care physicians entered into the EHR during simulated patient encounters. Physicians documented more clinical observations using the CDSS compared to the standard electronic health record. The increase in documented clinical observations has the potential to improve validity of research developed from EHR data.
Co Z, Holmgren AJ, Classen DC, et al. Appl Clin Inform. 2021;12:153-163.
Medication errors occur frequently in ambulatory care settings. This article describes the development and testing of an ambulatory medication safety evaluation tool, which is based on an inpatient version administered by The Leapfrog Group. Pilot testing at seven clinics around the US indicates that clinics struggled in areas of advanced decision support such as drug age and drug monitoring, and that most clinics lacked EHR-based medication reconciliation functions.
Shah SN, Amato MG, Garlo KG, et al. J Am Med Inform Assoc. 2021;28:1081-1087.
Clinical decision support (CDS) alerts can improve patient safety, and prior research suggests that monitoring alert overrides can identify errors. Over a one-year period, this study found that medication-related CDS alerts associated with renal insufficiency were nearly always deemed inappropriate and were all overridden. These findings highlight the need for improvements in alert design, implementation, and monitoring of alert performance to ensure alerts are patient-specific and clinically appropriate.  
Friebe MP, LeGrand JR, Shepherd BE, et al. Appl Clin Inform. 2020;11:865-872.
The prescribing of potentially inappropriate medications, particularly among older adults, is an ongoing quality and safety concern. Among adults 65 years and older, this study found that clinical decision support integrated with a new electronic health record system significantly reduced potentially inappropriate medications.