View clinical trials related to Medical Errors.
Filter by:This study aims to determine whether the use of two sterile towels for drying after surgical handwashing results in fewer contamination events compared to the use of only one towel among healthcare personnel. This randomized, multicenter, superiority-controlled trial will enroll up to 72 healthcare workers and surgical residents from three hospitals in Bogotá, Colombia. A fluorescent product will simulate bacteria, and contamination will be assessed by evaluating the presence of fluorescent cream after hand drying technique with either two or one surgical sterile towel. Data will be collected through REDCap and deidentified. Differences in the proportion of contamination between the two groups will be assessed using an exact Fischer test, and confounding variables will be included in the analysis through logistic multivariate regression, with a significance level set a priori at 0.05. Results will be submitted for publication in a peer-reviewed journal.
This is a multi-site, cluster-randomized controlled trial to test the effectiveness of patient photographs displayed in electronic health record (EHR) systems to prevent wrong-patient order errors. The study will be conducted at three academic medical centers that utilize two different EHR systems. Because EHR systems have different functionality for displaying patient photographs, two different study designs will be employed. In Allscripts EHR, a 2-arm randomized trial will be conducted in which providers are randomized to view order verification alerts with versus without patient photographs when placing electronic orders. In Epic EHR, a 2x2 factorial trial will be conducted in which providers are randomized to one of four conditions: 1) no photograph; 2) photograph displayed in the banner only; 3) photograph displayed in a verification alert only; or 4) photograph displayed in the banner and verification alert. The main hypothesis of this study is that displaying patient photographs in the EHR will significantly reduce the frequency of wrong-patient order errors, providing health systems with the evidence needed to adopt this safety practice. We will use the Wrong-Patient Retract-and-Reorder (RAR) measure, a valid, reliable, and automated method for identifying wrong-patient orders, as the primary outcome measure. The RAR measure identifies orders placed for a patient that are retracted within 10 minutes, and then reordered by the same provider for a different patient within the next 10 minutes. These are near-miss errors, self-caught by the provider before they reach the patient and cause harm. In one study, the RAR measure identified more than 5,000 wrong-patient orders in 1 year, with a rate of 58 wrong-patient errors per 100,000 orders. Real-time telephone interviews with clinicians determined that the RAR measure correctly identified near-miss errors in 76.2% of cases. Thus, the RAR measure provides sufficient valid and reliable outcome data for this study.