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.

Privacy as a Tradeoff: Introducing the Notion of Privacy Calculus for Context-Aware Mobile Applications

Evidences collected from smartphones users show a growing desire of personalization offered by services for mobile devices. However, the need to accurately identify users' contexts has important implications for user's privacy and it increases the amount of trust, which users are requested to have in the service providers. In this paper, we introduce a model that describes the role of personalization and control in users' assessment of cost and benefits associated to the disclosure of private information. We present an instantiation of such model, a context-aware application for smartphones based on the Android operating system, in which users' private information are protected. Focus group interviews were conducted to examine users' privacy concerns before and after having used our application. Obtained results confirm the utility of our artifact and provide support to our theoretical model, which extends previous literature on privacy calculus and user's acceptance of context-aware technology.

Privacy-friendly Business Models for Location-Based Mobile Services

This paper presents a theoretical model to analyze the privacy issues around location based mobile business models. We report the results of an exploratory field experiment in Switzerland that assessed the factors driving user payoff in mobile business. We found that (1) the personal data disclosed has a negative effect on user payoff; (2) the amount of personalization available has a direct and positive effect, as well as a moderating effect on user payoff; (3) the amount of control over user's personal data has a direct and positive effect, as well as a moderating effect on user payoff. The results suggest that privacy protection could be the main value proposition in the B2C mobile market. From our theoretical model we derive a set of guidelines to design a privacy-friendly business model pattern for third-party services. We discuss four examples to show the mobile platform can play a key role in the implementation of these new business models.

From 'Security for Privacy' to 'Privacy for Security'

This article envisions the use of context-awareness to improve single sign-on solutions (SSO) for mobile users. The attribute-based SSO is expected to increase users' perceived ease of use of the system and service providers' authentication security of the application. From these two features we derive two value propositions for a new business model for mobile platforms. The business model can be considered as an instantiation of the privacy-friendly business model pattern presented in our previous work, reinforcing our claim that privacy-friendly value propositions are possible and can be used to obtain a competitive advantage.

Business Model Considerations for Privacy Protection in a Mobile Location Based Context

In this paper we discuss the main privacy issues around mobile business models and we envision new solutions having privacy protection as a main value proposition. We construct a framework to help analyze the situation and assume that a third party is necessary to warrant transactions between mobile users and m-commerce providers. We then use the business model canvas to describe a generic business model pattern for privacy third party services. This pattern is then illustrated in two different variations of a privacy business model, which we call privacy broker and privacy management software. We conclude by giving examples for each business model and by suggesting further directions of investigation

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.