Medical errors

Predictions under interventions are estimates of what a person's risk of an outcome would be if they were to follow a particular treatment strategy, given their individual characteristics. Such predictions can give important input to medical decision-making. However, evaluating the predictive performance of interventional predictions is challenging. Standard ways of evaluating predictive performance do not apply when using observational data, because prediction under interventions involves obtaining predictions of the outcome under conditions that are different from those that are observed for a subset of individuals in the validation dataset...

BACKGROUND: The background to this article is a polarized media debate about ritual violence against children in German speaking countries. Two opposing positions have formed, which are unable to engage in a reasonable exchange with each other. OBJECTIVE: The article therefore aims to contribute to bridging the differences and argues, above all in the interests of patient well-being, for positioning oneself beyond polarization and to reflect on an evidence-base in treatment as well as in scientific discourse...

Wrong dose calculation medication errors are widespread in pediatric patients mainly due to weight-based dosing. PediPain app is a clinical decision support tool that provides weight- and age- based dosages for various analgesics. We hypothesized that the use of a clinical decision support tool, the PediPain app versus pocket calculators for calculating pain medication dosages in children reduces the incidence of wrong dosage calculations and shortens the time taken for calculations. The study was a randomised controlled trial comparing the PediPain app vs...

Atrial fibrillation (AF) poses a significant risk of stroke due to thrombus formation, which primarily occurs in the left atrial appendage (LAA). Medical image-based computational fluid dynamics (CFD) simulations can provide valuable insight into patient-specific hemodynamics and could potentially enhance personalized assessment of thrombus risk. However, the importance of accurately representing the left atrial (LA) wall dynamics has not been fully resolved. In this study, we compared four modeling scenarios; rigid walls, a generic wall motion based on a reference motion, a semi-generic wall motion based on patient-specific motion, and patient-specific wall motion based on medical images...

BACKGROUND: Though financial hardship is a well-documented adverse effect of standard-of-care cancer treatment, little is known about out-of-pocket costs and their impact on patients participating in cancer clinical trials. This study explored the financial effects of cancer clinical trial participation. METHODS: This cross-sectional analysis used survey data collected in December 2022 and May 2023 from individuals with cancer previously served by Patient Advocate Foundation, a nonprofit organization providing social needs navigation and financial assistance to US adults with a chronic illness...

Introduction In recent years, artificial intelligence (AI) in medical imaging has undergone unprecedented innovation and advancement, sparking a revolutionary transformation in healthcare. The field of radiology is particularly implicated, as clinical radiologists are expected to interpret an ever-increasing number of complex cases in record time. Machine learning software purchased by our institution is expected to help our radiologists come to a more prompt diagnosis by delivering point-of-care quantitative analysis of suspicious findings and streamlining clinical workflow...

Given the persistent safety incidents in operating rooms (ORs) nationwide (approx. 4,000 preventable harmful surgical errors per year), there is a need to better analyze and understand reported patient safety events. This study describes the results of applying the Team Strategies and Tools to Enhance Performance and Patient Safety (TeamSTEPPS) supported by the Teamwork Evaluation of Non-Technical Skills (TENTS) instrument to analyze patient safety event reports at one large academic medical center. Results suggest that suboptimal behaviors stemming from poor communication, lack of situation monitoring, and inappropriate task prioritization and execution were implicated in most reported events...

RATIONALE & OBJECTIVE: Patients treated with dialysis are commonly prescribed multiple medications (polypharmacy), including some potentially inappropriate medications (PIMs). PIMs are associated with an increased risk of medication harm (eg, falls, fractures, hospitalization). Deprescribing is a solution that proposes to stop, reduce, or switch medications to a safer alternative. Although deprescribing pairs well with routine medication reviews, it can be complex and time-consuming...

BACKGROUND & AIM: Cardiovascular disease (CVD) is the most important cause of death in the world and has a potential impact on health care costs, this study aimed to evaluate the performance of machine learning survival models and determine the optimum model for predicting CVD-related mortality. METHOD: In this study, the research population was all participants in Tehran Lipid and Glucose Study (TLGS) aged over 30 years. We used the Gradient Boosting model (GBM), Support Vector Machine (SVM), Super Learner (SL), and Cox proportional hazard (Cox-PH) models to predict the CVD-related mortality using 26 features...

PURPOSE: Management reasoning is a distinct subset of clinical reasoning. We sought to explore features to be considered when designing assessments of management reasoning. METHODS: This is a hybrid empirical research study, narrative review, and expert perspective. In 2021, we reviewed and discussed 10 videos of simulated (staged) physician-patient encounters, actively seeking actions that offered insights into assessment of management reasoning. We analyzed our own observations in conjunction with literature on clinical reasoning assessment, using a constant comparative qualitative approach...

INTRODUCTION: Medication errors are an unnecessary cost to a healthcare system and patients of a country. This review aimed to systematically identify published cost variables used to calculate the cost of medication errors and to explore any updates on findings already known on calculating the cost of medication errors during the past 10 years. METHODS: A systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines...

INTRODUCTION: Patients exhibiting signs of hyperactive delirium with severe agitation (HDSA) may require sedating medications for stabilization and safe transport to the hospital. Determining the patient's weight and calculating the correct weight-based dose may be challenging in an emergency. A fixed dose ketamine protocol is an alternative to the traditional weight-based administration, which may also reduce dosing errors. The objective of this study was to evaluate the frequency and characteristics of adverse events following pre-hospital ketamine administration for HDSA...

OBJECTIVE: Machine learning (ML) is increasingly employed to diagnose medical conditions, with algorithms trained to assign a single label using a black-box approach. We created an ML approach using deep learning that generates outcomes that are transparent and in line with clinical, diagnostic rules. We demonstrate our approach for autism spectrum disorders (ASD), a neurodevelopmental condition with increasing prevalence. METHODS: We use unstructured data from the Centers for Disease Control and Prevention (CDC) surveillance records labeled by a CDC-trained clinician with ASD A1-3 and B1-4 criterion labels per sentence and with ASD cases labels per record using Diagnostic and Statistical Manual of Mental Disorders (DSM5) rules...

BACKGROUND AND OBJECTIVES: Nurses tend to exhibit higher rates of presenteeism compared to other professions. Presenteeism can cause the work performance of nurses to suffer, jeopardizing their own and their patients' safety and leading to decreased quality of care and increased risks of errors. However, there is a lack of a validated assessment tool for presenteeism in Taiwan. Thus, the purpose of this study was to develop a Nursing Staff Presenteeism Scale (NSPS). METHODS: To develop questionnaire items, participants from three medical centers in Taiwan were recruited...

OBJECTIVE: Oscillometric finger pressing is a smartphone-based blood pressure (BP) monitoring method. Finger photoplethysmography (PPG) oscillations and pressure are measured during a steady increase in finger pressure, and an algorithm computes systolic BP (SP) and diastolic BP (DP) from the measurements. The objective was to assess the impact of finger artery viscoelasticity on the BP computation. METHODS: Nonlinear viscoelastic models relating transmural pressure (finger BP - applied pressure) to PPG oscillations during finger pressing were developed...

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BACKGROUND: Understanding the factors that contribute to diagnostic errors is critical if we are to correct or prevent them. Some scholars influenced by the default interventionist dual-process theory of cognition (dual-process theory) emphasise a narrow focus on individual clinician's faulty reasoning as a significant contributor. In this paper, we examine the validity of claims that dual process theory is a key to error reduction. METHODS: We examined the relationship between a clinical experience (staff and resident physicians) and viewing time on accuracy for categorising chest X-rays (CXRs) and electrocardiograms (ECGs)...

Long chain 3-hydroxyacyl-CoA dehydrogenase (LCHADD) is the only fatty acid oxidation disorder to develop a progressive chorioretinopathy resulting in vision loss; newborn screening (NBS) for this disorder began in the United States around 2004. We compared visual outcomes among 40 participants with LCHADD or trifunctional protein deficiency diagnosed symptomatically to those who were diagnosed via NBS or a family history. Participants completed ophthalmologic testing including measures of visual acuity, electroretinograms (ERG), fundal imaging, contrast sensitivity, and visual fields...

UNLABELLED: Objectives: The objectives were to evaluate blood additives that combined lithium heparin (LH)-salt with glyceraldehyde (GLY) or d-mannose (MAN) for preserving glucose levels in plasma samples and to simultaneously determine the compatibility of these additives with 14 other biochemical tests. METHODS: Blood samples from 40 subjects, equally divided into healthy and diabetic groups, were collected using five different additives. The three most effective additives, LH/GLY, LH/MAN, and LH/GLY/MAN, were selected for ensuring the best preservation of glucose levels and compatibility with 14 biochemical tests...

BACKGROUND: To overcome the limitations of relying on data from a single institution, many researchers have studied data linkage methodologies. Data linkage includes errors owing to legal issues surrounding personal information and technical issues related to data processing. Linkage errors affect selection bias, and external and internal validity. Therefore, quality verification for each connection method with adherence to personal information protection is an important issue. This study evaluated the linkage quality of linked data and analyzed the potential bias resulting from linkage errors...