Medication incidents in primary care medicine: protocol of a study by the Swiss Federal Sentinel Reporting System.

BACKGROUND/RATIONALE: Patient safety is a major concern in healthcare systems worldwide. Although most safety research has been conducted in the inpatient setting, evidence indicates that medical errors and adverse events are a threat to patients in the primary care setting as well. Since information about the frequency and outcomes of safety incidents in primary care is required, the goals of this study are to describe the type, frequency, seasonal and regional distribution of medication incidents in primary care in Switzerland and to elucidate possible risk factors for medication incidents. Label="METHODS AND ANALYSIS" ="METHODS"/> <AbstractText STUDY DESIGN AND SETTING: We will conduct a prospective surveillance study to identify cases of medication incidents among primary care patients in Switzerland over the course of the year 2015. PARTICIPANTS: Patients undergoing drug treatment by 167 general practitioners or paediatricians reporting to the Swiss Federal Sentinel Reporting System. INCLUSION CRITERIA: Any erroneous event, as defined by the physician, related to the medication process and interfering with normal treatment course. EXCLUSION CRITERIA: Lack of treatment effect, adverse drug reactions or drug-drug or drug-disease interactions without detectable treatment error. PRIMARY OUTCOME: Medication incidents. RISK FACTORS: Age, gender, polymedication, morbidity, care dependency, hospitalisation. STATISTICAL ANALYSIS: Descriptive statistics to assess type, frequency, seasonal and regional distribution of medication incidents and logistic regression to assess their association with potential risk factors. Estimated sample size: 500 medication incidents. LIMITATIONS: We will take into account under-reporting and selective reporting among others as potential sources of bias or imprecision when interpreting the results. ETHICS AND DISSEMINATION: No formal request was necessary because of fully anonymised data. The results will be published in a peer-reviewed journal. TRIAL REGISTRATION NUMBER: NCT0229537.

Automatic Segmentation of the Eye in 3D Magnetic Resonance Imaging: A Novel Statistical Shape Model for Treatment Planning of Retinoblastoma.

PURPOSE: Proper delineation of ocular anatomy in 3-dimensional (3D) imaging is a big challenge, particularly when developing treatment plans for ocular diseases. Magnetic resonance imaging (MRI) is presently used in clinical practice for diagnosis confirmation and treatment planning for treatment of retinoblastoma in infants, where it serves as a source of information, complementary to the fundus or ultrasonographic imaging. Here we present a framework to fully automatically segment the eye anatomy for MRI based on 3D active shape models (ASM), and we validate the results and present a proof of concept to automatically segment pathological eyes. METHODS AND MATERIALS: Manual and automatic segmentation were performed in 24 images of healthy children's eyes (3.29 ± 2.15 years of age). Imaging was performed using a 3-T MRI scanner. The ASM consists of the lens, the vitreous humor, the sclera, and the cornea. The model was fitted by first automatically detecting the position of the eye center, the lens, and the optic nerve, and then aligning the model and fitting it to the patient. We validated our segmentation method by using a leave-one-out cross-validation. The segmentation results were evaluated by measuring the overlap, using the Dice similarity coefficient (DSC) and the mean distance error. RESULTS: We obtained a DSC of 94.90 ± 2.12% for the sclera and the cornea, 94.72 ± 1.89% for the vitreous humor, and 85.16 ± 4.91% for the lens. The mean distance error was 0.26 ± 0.09 mm. The entire process took 14 seconds on average per eye. CONCLUSION: We provide a reliable and accurate tool that enables clinicians to automatically segment the sclera, the cornea, the vitreous humor, and the lens, using MRI. We additionally present a proof of concept for fully automatically segmenting eye pathology. This tool reduces the time needed for eye shape delineation and thus can help clinicians when planning eye treatment and confirming the extent of the tumor.

Implementing evidence-based patient and family education on oral anticoagulation therapy: a community-based participatory project.

AIMS AND OBJECTIVES: This study aimed at developing and implementing evidence-based patient and family education on oral anticoagulation therapy. BACKGROUND: The number of persons with chronic diseases who live at home is increasing. They have to manage multiple diseases and complex treatments. One such treatment is oral anticoagulation therapy, a high risk variable dose medication. Adherence to oral anticoagulation therapy is jeopardised by limited information about the medications, their risk and complications, the impact of individual daily routine and the limited inclusion of family members in education. Hence, improved and tailored education is essential for patients and families to manage oral anticoagulation therapy at home. DESIGN AND METHODS: A community-based participatory research design combined with the Precede-Proceed model was used including a systematic literature review, posteducation analysis, an online nurse survey, a documentation analysis and patient/family interviews. The study was conducted between April 2010-December 2012 at a department of general internal medicine in a teaching hospital in Switzerland. Participants were the department's nursing and medical professionals including the patients and their families. RESULTS: The evidence-based patient and family education on oral anticoagulation therapy emerged comprising a learning assessment, teaching units, clarification of responsibilities of nurse professionals and documentation guidelines. CONCLUSION AND CLINICAL RELEVANCE: The inclusion of the whole department has contributed to the development and implementation of this evidence-based patient family education on oral anticoagulation therapy, which encompasses local characteristics and patient preferences. This education is now being used throughout the department.

Méta-analyses d'essais randomisés sur données individuelles dans le traitement des cancers ORL non métastatiques : principes, résultats, perspectives [Individual patient data meta-analyses of randomized trials for the treatment of non-metastatic head and neck squamous cell carcinomas: Principles, results and perspectives].

Meta-analyses are considered as an important pillar of evidence-based medicine. The aim of this review is to describe the main principles of a meta-analysis and to use examples of head and neck oncology to demonstrate their clinical impact and methodological interest. The major role of individual patient data is outlined, as well as the superiority of individual patient data over meta-analyses based on published summary data. The major clinical breakthrough of head and neck meta-analyses are summarized, regarding concomitant chemotherapy, altered fractionated chemotherapy, new regimens of induction chemotherapy or the use of radioprotectants. Recent methodological developments are described, including network meta-analyses, the validation of surrogate markers. Lastly, the future of meta-analyses is discussed in the context of personalized medicine.

Glutamine and antioxidants in the critically ill patient: a post hoc analysis of a large-scale randomized trial.

BACKGROUND: The recent large randomized controlled trial of glutamine and antioxidant supplementation suggested that high-dose glutamine is associated with increased mortality in critically ill patients with multiorgan failure. The objectives of the present analyses were to reevaluate the effect of supplementation after controlling for baseline covariates and to identify potentially important subgroup effects. MATERIALS AND METHODS: This study was a post hoc analysis of a prospective factorial 2 × 2 randomized trial conducted in 40 intensive care units in North America and Europe. In total, 1223 mechanically ventilated adult patients with multiorgan failure were randomized to receive glutamine, antioxidants, both glutamine and antioxidants, or placebo administered separate from artificial nutrition. We compared each of the 3 active treatment arms (glutamine alone, antioxidants alone, and glutamine + antioxidants) with placebo on 28-day mortality. Post hoc, treatment effects were examined within subgroups defined by baseline patient characteristics. Logistic regression was used to estimate treatment effects within subgroups after adjustment for baseline covariates and to identify treatment-by-subgroup interactions (effect modification). RESULTS: The 28-day mortality rates in the placebo, glutamine, antioxidant, and combination arms were 25%, 32%, 29%, and 33%, respectively. After adjusting for prespecified baseline covariates, the adjusted odds ratio of 28-day mortality vs placebo was 1.5 (95% confidence interval, 1.0-2.1, P = .05), 1.2 (0.8-1.8, P = .40), and 1.4 (0.9-2.0, P = .09) for glutamine, antioxidant, and glutamine plus antioxidant arms, respectively. In the post hoc subgroup analysis, both glutamine and antioxidants appeared most harmful in patients with baseline renal dysfunction. No subgroups suggested reduced mortality with supplements. CONCLUSIONS: After adjustment for baseline covariates, early provision of high-dose glutamine administered separately from artificial nutrition was not beneficial and may be associated with increased mortality in critically ill patients with multiorgan failure. For both glutamine and antioxidants, the greatest potential for harm was observed in patients with multiorgan failure that included renal dysfunction upon study enrollment.

Implementation of bayesian therapeutic drug monitoring in modern patient care

The variability observed in drug exposure has a direct impact on the overall response to drug. The largest part of variability between dose and drug response resides in the pharmacokinetic phase, i.e. in the dose-concentration relationship. Among possibilities offered to clinicians, Therapeutic Drug Monitoring (TDM; Monitoring of drug concentration measurements) is one of the useful tool to guide pharmacotherapy. TDM aims at optimizing treatments by individualizing dosage regimens based on blood drug concentration measurement. Bayesian calculations, relying on population pharmacokinetic approach, currently represent the gold standard TDM strategy. However, it requires expertise and computational assistance, thus limiting its large implementation in routine patient care. The overall objective of this thesis was to implement robust tools to provide Bayesian TDM to clinician in modern routine patient care. To that endeavour, aims were (i) to elaborate an efficient and ergonomic computer tool for Bayesian TDM: EzeCHieL (ii) to provide algorithms for drug concentration Bayesian forecasting and software validation, relying on population pharmacokinetics (iii) to address some relevant issues encountered in clinical practice with a focus on neonates and drug adherence. First, the current stage of the existing software was reviewed and allows establishing specifications for the development of EzeCHieL. Then, in close collaboration with software engineers a fully integrated software, EzeCHieL, has been elaborated. EzeCHieL provides population-based predictions and Bayesian forecasting and an easy-to-use interface. It enables to assess the expectedness of an observed concentration in a patient compared to the whole population (via percentiles), to assess the suitability of the predicted concentration relative to the targeted concentration and to provide dosing adjustment. It allows thus a priori and a posteriori Bayesian drug dosing individualization. Implementation of Bayesian methods requires drug disposition characterisation and variability quantification trough population approach. Population pharmacokinetic analyses have been performed and Bayesian estimators have been provided for candidate drugs in population of interest: anti-infectious drugs administered to neonates (gentamicin and imipenem). Developed models were implemented in EzeCHieL and also served as validation tool in comparing EzeCHieL concentration predictions against predictions from the reference software (NONMEM®). Models used need to be adequate and reliable. For instance, extrapolation is not possible from adults or children to neonates. Therefore, this work proposes models for neonates based on the developmental pharmacokinetics concept. Patients' adherence is also an important concern for drug models development and for a successful outcome of the pharmacotherapy. A last study attempts to assess impact of routine patient adherence measurement on models definition and TDM interpretation. In conclusion, our results offer solutions to assist clinicians in interpreting blood drug concentrations and to improve the appropriateness of drug dosing in routine clinical practice.