Journal of Patient Safety最新文献

Objectives: We aimed to investigate the value of adding a video monitoring (VM) system with falls and costs for patients at high risk.

Methods: We conducted a retrospective, historically controlled study of adults (≥18 y old) at high risk of fall admitted at the University of Miami Hospital and Clinics from January 1 to November 30, 2020 (pre-VM) and January 1 to November 30, 2021 (post-VM); in-person sitters were available in both periods. Fall risk assessment was conducted on admission and at every nursing shift; we defined patients as high risk if their Morse Fall Scale was ≥60. We conducted a multivariable logistic regression model to evaluate the association of period (pre- versus post-VM) with falls and performed a cost analysis.

Results: Our primary cohort consisted of 9,034 patients at high risk of falls, 4,207 (46.6%) in the pre-VM and 4,827 (53.4%) in the post-VM period. Fall rates were higher in the pre- than the post-VM periods (3.5% versus 2.7%, P = 0.043). After adjustment, being admitted during the post-VM period was associated with a lower odds of fall (odds ratio [95% confidence interval], 0.49 [0.37-0.64], P < 0.001). The median adjusted hospital cost (in 2020 dollars) was $1,969 more for patients who fell than for patients who did not (interquartile range, $880-$2,273). Considering start-up and ongoing costs, we estimate VM implementation to partly replace in-person monitoring has potential annual cost savings of >$800,000 for a hospital similar to ours.

Conclusions: Video monitoring to augment in-person sitters is an effective fall prevention initiative for patients at high risk of falls, which is likely also cost-effective.

Objectives: Community-dwelling older adults taking 5 or more medications are at risk for medication-related harm. Managing multiple medications is a challenging task for patients and caregivers. Community-dwelling older adults self-manage their medications with minimal healthcare professional supervision. Although organizations, such as the Food and Drug Administration, often issue guidelines to ensure medication safety, how older adults understand and mitigate the risk of harm from medication use in the home environment is poorly understood.

Methods: We conducted semistructured interviews with community-dwelling older adults 65 years and older who took 5 or more prescription medications to explore medication safety strategies they use. We also compared 2 organizations' medication safety guidelines for areas of concordance and discordance.

Results: A total of 28 older adults were interviewed. Four overarching themes of medication management strategies emerged: collaborating with prescribers, collaborating with pharmacists, learning about medications, and safe practices at home. Study findings revealed that older adults followed some of the published guidelines by the 2 government organizations, although there were some areas of discord. Some of the strategies used were unintentionally against the recommended guidelines. For example, older adults tried weaning themselves off their medications without notifying their providers.

Conclusions: Older adults and their caregivers in our study used strategies different from those recommended by government organizations in managing medications to enhance drug safety. Patient-provider collaboration and positive patient outcomes can be improved by understanding and respecting strategies older adults use at home. Future studies must effectively incorporate older adults' perspectives when developing medication safety guidelines.

Background: Over the past decade, the implementation of simulation education in health care has increased exponentially. Simulation-based education allows learners to practice patient care in a controlled, psychologically safe environment without the risk of harming a patient. Facilitators may identify medical errors during instruction, aiding in developing targeted education programs leading to improved patient safety. However, medical errors that occur during simulated health care may not be reported broadly in the simulation literature.

Objective: The aim of the study is to identify and categorize the type and frequency of reported medical errors in healthcare simulation.

Methods: Systematic review using search engines, PubMed/MEDLINE, CINAHL, and SCOPUS from 2000 to 2020, using the terms "healthcare simulation" AND "medical error." Inclusion was based on reported primary research of medical errors occurring during simulated health care. Reported errors were classified as errors of commission, omission, systems related, or communication related.

Results: Of the 1105 articles screened, only 20 articles met inclusion criteria. Errors of commission were the most reported (17/20), followed by systems-related errors (13/20), and errors of omission (12/20). Only 7 articles reported errors attributed to communication. Authors in 16 articles reported more than one type of error.

Conclusions: Simulationists and patient safety advocates must continually identify systems-related errors and training deficits that can lead to inaction, improper action, and poor communication. Recent dialogs in the simulation community have also underscored the potential benefits of developing a registry of errors across simulation centers, with a goal of aggregating, analyzing, and disseminating insights from various simulation exercises.

Objectives: Safety incidents (SIs) are an indicator of quality in health and social care services. Safety incident research has largely focused on acute health care settings. We aimed to examine the association of organizational, environmental, and staffing characteristics of residential care facilities (RCFs) and severity of regulatory SI notifications.

Methods: This was a retrospective analysis of SI notifications to the regulator for social care in Ireland received in 2018 and 2019. The mean risk rating of SI notifications for each RCF was used as the outcome. Regression analysis was conducted for the association of RCF characteristics (beds, staff to bed ratio, staff full-time equivalent (FTE), nurse to bed ratio, nurse FTE, number of RCF operated by the service provider, non-statutory or statutory provider) and the outcome, separately for nursing homes and residential disability services.

Results: A total of 53,268 SI notifications were received. One thousand nine hundred RCFs were operational during the period: 594 (31.3%) for RCF-Nursing home and 1304 (68.7%) for RCF-Disability. For nursing homes, in the most adjusted model, the number of RCF operated by a provider ( β coefficient [95% confidence interval] = 0.508 [0.223-0.793]) was positively associated with mean risk rating of SI. For disability services, the following characteristics were positively associated in the most adjusted model: beds (0.081; 0.060-0.101), staff to bed ratio (0.068; 0.017-0.120), nurse to bed ratio (0.356; 0.044-0.667), staff FTE (0.029; 0.015-0.042), and number of RCF operated by a provider (0.067; 0.050-0.084).

Conclusions: Various modifiable organizational, environmental, and staffing characteristics and severity of SI notifications were associated in this study, most of which were related to RCF-Disability. Policymakers and providers of social care services should be cognizant of the relationship of these characteristics and severity of SI, when designing and planning residential care.

Objective: The aim of the study is to identify the hospitalized children at risk of peripheral intravenous catheter (PIVC) complications by severity prediction.

Methods: The study included the data of 301 hospitalized children with PIVC complications in 2 tertiary teaching hospitals. A researcher-designed tool was used to collect risk factors associated with PIVC complications. Predictors of PIVC complications at univariate analysis and multivariable logistic regression analysis by backward stepwise. A nomogram was constructed based on the results of the final multivariable model, making it possible to estimate the probability of developing complications.

Results: A total of 182 participants (60.5%) had a moderate injury from PIVC complications. Multivariable logistic regression analysis indicated that the vascular condition, limb immobilization, needle adjustment in venipuncture, infusion length, infusion speed, and insertion site were independent predictors. The nomogram for assessing the severity of PIVC complications indicated good predictive accuracy (area under the curve = 0.79) and good discrimination (concordance index = 0.779). Decision curve analysis demonstrated that the nomogram was a good clinical value with a wide range of threshold probabilities (4%-100%).

Conclusions: The risk prediction model has good predictive performance, and the nomogram provides an easy-to-use visualization to identify the severity of PIVC complications and guide timely nursing care management.

Objective: This study aims to examine the effects of different preoperative waiting times on anxiety and pain levels in patients undergoing outpatient surgery for breast diseases, providing insights for clinical interventions during the perioperative phase.

Methods: Patients who underwent outpatient surgery at a hospital breast center in Ningbo between January 2021 and December 2021 were selected. Their anxiety levels at the time when they entered the preoperative preparation room and when they ended the postoperative waiting period for the rapid frozen section procedure were assessed using the State Anxiety Inventory (S-AI) questionnaire, and their pain levels at the end of the postoperative waiting period were assessed using the short-form McGill Pain Questionnaire. The patients enrolled were divided into 3 groups according to the preoperative waiting time: <2 hours (T1 group), 2 to 4 hours (T2 group), and >4 hours (T3 group); there were 150 patients in each group, and the anxiety and pain levels were compared between the groups.

Results: At the time of entering the preoperative preparation room, patients' S-AI score T1 = T2 ( P > 0.05), both T1 and T2 < T3 ( P < 0.05); however, at the time of the postoperative waiting period, patients' S-AI score was T1 < T2 < T3 ( P < 0.05), and the postoperative waiting period patients' short-form McGill Pain Questionnaire scores were T1 = T2 < T3 ( P < 0.05).

Conclusions: The perioperative anxiety and pain levels of patients undergoing outpatient breast surgery increased with the prolongation of preoperative waiting time; 4 hours was the critical time point for change, after which the anxiety and pain levels of patients increased significantly.