Patricia Ann Zrelak

Early basic life support and defibrillation using automated external defibrillators (AEDs) are key for improving survival in those suffering an out-of-hospital sudden cardiac arrest. To improve survival, access to AEDs by lay responders is growing, and use is included in basic cardiac life support training. These devices are considered extremely safe, evidenced by the paucity of medical literature on AED misuse and expert opinion. However, it’s crucial to point out that even medical personnel can make errors in their use. This case study of AED misuse during a community event and narrative literature review underscores the potential for errors in using an AED, which could cause considerable patient harm. To prevent errors in AED use, it is important to train on (1) equipment in use or likely to be encountered in the field, (2) how to dump an electric charge, especially when using a fully automated machine, (3) the need to follow specific machine instructions, (4) proper application of the defibrillator pads (including one-piece pads with metronome), (5) the need to assess the patient and not rely entirely on the AED prompts, which can contain false alerts and inappropriate instruction, and (6) the need for closed-loop communication, even when participating in a community event.

In this editorial, journal editors highlight the importance of articles, such as the one by Winterbottom et al (2022), that demonstrate the impact of rapid response systems (RRS) in improving patient outcomes.

Background: The Poisson distribution is used to find the probability of an event occurring over an interval of time, distance, area, or volume. Problem: It is a helpful statistical tool, especially when evaluating rare events, and is underused in nursing practice. Approach: A single-group study design is used to demonstrate use of the Poisson distribution in determining whether a change in the number of discrete events is due to random variation or reflects a change in practice patterns and in determining the probability of seeing the number of observed events. Outcomes: Steps demonstrate how one can easily use the Poisson distribution to answer common questions. Conclusion: Use of the Poisson distribution can help nurses make better informed decisions about observed variations in care, especially when the data are not normally distributed, and can prevent undue concern when fluctuations in the number of events are associated with random fluctuations.

Objective: To reweight the Agency for Healthcare Research and Quality Patient Safety for Selected Indicators Composite (Patient Safety Indicator [PSI] 90) from weights based solely on the frequency of component PSIs to those that incorporate excess harm reflecting patients' preferences for outcome‐related health states.Data Sources: National administrative and claims data involving hospitalizations in nonfederal, nonrehabilitation, acute care hospitals.Study Design: We estimated the average excess aggregate harm associated with the occurrence of each component PSI using a cohort sample for each indicator based on denominator‐eligible records. We used propensity scores to account for potential confounding in the risk models for each PSI and weighted observations to estimate the “average treatment effect in the treated” for those with the PSI event. We fit separate regression models for each harm outcome. Final PSI weights reflected both the disutilities and the frequencies of the harms.Data Collection/Extraction Methods: We estimated PSI frequencies from the 2012 Healthcare Cost and Utilization Project State Inpatient Databases with present on admission data and excess harms using 2012–2013 Centers for Medicare & Medicaid Services Medicare Fee‐for‐Service data.Principal Findings: Including harms in the weighting scheme changed individual component weights from the original frequency‐based weighting. In the reweighted composite, PSIs 11 (“Postoperative Respiratory Failure”), 13 (“Postoperative Sepsis”), and 12 (“Perioperative Pulmonary Embolism or Deep Vein Thrombosis”) contributed the greatest harm, with weights of 29.7%, 21.1%, and 20.4%, respectively. Regarding reliability, the overall average hospital signal‐to‐noise ratio for the reweighted PSI 90 was 0.7015. Regarding discrimination, among hospitals with greater than median volume, 34% had significantly better PSI 90 performance, and 41% had significantly worse performance than benchmark rates (based on percentiles).Conclusions: Reformulation of PSI 90 with harm‐based weights is feasible and results in satisfactory reliability and discrimination, with a more clinically meaningful distribution of component weights.

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Little is known about the risk of angioedema with low-dose alteplase administration in the treatment of thrombotically occluded central vascular access devices (CVADs). To identify potential cases, the US Food and Drug Administration Adverse Event Reporting System database was searched. Between March 15, 2001, and August 15, 2018, there were 568 low-dose alteplase reports. Of these, 11 appear to be related to complications associated with a device or device occlusion that resulted in an angioedema-like reaction. This suggests that angioedema is a potential complication of alteplase when used for declotting CVADs-a complication that nurses should know how to recognize and treat.

Lack of early stroke recognition and delays in seeking emergency care by persons experiencing a stroke severely limit acute treatment options. Sparse and sometimes conflicting evidence suggests sex differences in care-seeking behaviors in stroke, stroke knowledge, perceptions of stroke symptoms, and the importance of physical location at the time of stroke and of having a witnessed stroke. To explore specific sex-based differences in stroke presentation and associated care-seeking behaviors. Descriptive study based on a convenience sample of 60 patients with stroke admitted to an academic medical center in Northern California. Impact of the patient's sex on 1) time to presentation (early [≤ 4.5 hours] vs late [> 4.5 hours]); 2) perception of symptoms and clinical signs; 3) stroke knowledge and decision making; 4) physical location at the time of stroke; and 5) bystander presence and assistance with decision making. There was a discrepancy between how patients perceive symptoms and their medical findings on physical examination. Although most patients had at least one sign or symptom associated with nationally used stroke recognition acronyms, both sexes delayed care because they did not perceive their symptoms as urgent. Early-presenting men were more likely to have a higher stroke severity score at admission, receive alteplase, arrive by Emergency Medical Services, and have a witnessed stroke. Both early- and late-presenting women reported more nonfocal symptoms than did men. This study suggests that there are sex-based differences in symptom perception and care-seeking behavior in acute ischemic stroke.

In 2008, we conducted a retrospective cross-sectional study to determine the test characteristics of the Agency for Healthcare Research and Quality patient safety indicator (PSI) for hospital-acquired pressure ulcer (PU). We sampled 1,995 inpatient records that met PSI 3 criteria and 4,007 records assigned to 14 DRGs with the highest empirical rates of PSI 3, which did not meet PSI 3 criteria, from 32 U.S. academic hospitals. We estimated the positive predictive value (PPV), sensitivity, and specificity of PSI 3 using both the software version contemporary to the hospitalizations (v3.1) and an approximation of the current version (v4.4). Of records that met PSI 3 version 3.1 criteria, 572 (PPV 28.3%; 95% CI 23.6-32.9%) were true positive. PU that was present on admission (POA) accounted for 76% of the false-positive records. Estimated sensitivity was 48.2% (95% CI 41.0-55.3%) and specificity 71.4% (95% CI 68.3-74.5%). Reclassifying records based on reported POA information and PU stage to approximate version 4.4 of PSI 3 improved sensitivity (78.6%; 95% CI 62.7-94.5%) and specificity (98.0; 95% CI 97.1-98.9%). In conclusion, accounting for POA information and PU staging to approximate newer versions of the PSI software (v4.3) moderately improves validity.