En quoi l’industrie pharmaceutique contribue-t-elle à l’amélioration de la qualité en antibiothérapie ?

Do studies made by the pharmaceutical industry contribute to improving quality in antibiotic therapy? In addition to conventional preclinical studies, structure-toxicity and pharmacotoxicological studies help select antibiotics that are better tolerated. Microbiological studies determine the antibacterial spectrum, the critical concentration values to sort clinical strains, and the incidence of resistance of these strains in Europe. Continuing efforts to achieve standardization are still necessary in order to carry out genuine European studies. A number of clinical recommendations (CPMP, ICH, ESCMID, FDA) have been issued in the past few years (investigations for drug interactions, choice of comparator, conduct of non-inferiority trials...) that standardize studies and make the results increasingly reliable. Can marketing contribute to improving quality in antibiotic therapy? Promotional documents, which have to be validated in France by the Publicity Commission so as to discourage drug misuse or over consumption, have progressively improved so as to communicate a message that is consistent with the summary of product characteristics and the recommendations for appropriate use. Medical training, partnership without reciprocal obligations, and sponsorship also contribute to a better quality of antibiotic therapy. Research is making progress: the genome of the main bacteria has been sequenced, and thanks to genomics and proteomics, in the near future there will be new antibiotics, free from any cross-resistance put on the market. This, combined with the production of detection kits for biological markers of infection and of new vaccines, should contribute to an improvement in the quality of antibiotic therapy.     

Le comité de retour d’expérience (CREX) : une méthode pour l’amélioration de la sécurité des soins

BackgroundAn experience feedback committee (CREX, Comité de Retour d’EXpérience) is a method which contributes to the management of safety of care in a medical unit. Originally used for security systems of civil aviation, the method has been adapted to health care facilities and successfully implemented in radiotherapy units and in other specialties.MethodsWe performed a brief review of the literature for studies reporting data on CREX established in hospitals. The review was performed using the main bibliographic databases and Google search results.ResultsThe CREX is designed to analyse incidents reported by professionals. The method includes monthly meetings of a multi-professional committee that reviews the reported incidents, chooses a priority incident and designates a “pilot” responsible for investigating the incident. The investigation of the incident involves a systemic analysis method and a written synthesis presented at the next meeting of the committee. The committee agrees on actions for improvement that are suggested by the analysis and follows their implementation. Systems for the management of health care, including reporting systems, are organized into three levels: the medical unit, the hospital and the country as a triple loop learning process. The CREX is located in the base level, short loop of risk management and allows direct involvement of care professionals in patient safety.ConclusionSafety of care has become a priority of health systems. In this context, the CREX can be a useful vehicle for the implementation of a safety culture in medical units.     

Actualité sur les déterminants de l’activité physique habituelle (APH) de l’enfant : mise à jour et implications pour les options de prise en charge et de prévention du surpoids/obésité infantile

With the steady rise in the prevalence of overweight/obesity and its comorbidities in the pediatric population, it seems necessary to watch and stimulate the engagement of a majority of children in a regular physical activity. To do this, it seems crucial to know and handle properly the determinants or influences of the habitual physical activity (HPA) of children, especially when it is about overweight/obesity children. This article is an update and a review of existing data on the determinants of HPA with reference to overweight/obesity in childhood. Current data suggest that self-efficacy and physical competence are key motivators and solid anchor points for the initiation and engagement of children in a regular physical activity. In particular, for overweight/obese children, intervention strategies should first concentrate on improving these psychosocial dimensions around which other physiological components (capacity factors) and environmental (reinforcement factors) could revolve. These strategies should involve a multidisciplinary professional team (epidemiologists, actiphysists, teachers, physicians, psychologists, urban planners, local councillors) not only pursuing the same objective but with sufficiently varied skills to be effective at their respective levels.     

Déterminants du temps nécessaire au contrôle qualité dans le cadre du programme de médicalisation des systèmes d’information (PMSI), dans le champ médecine,chirurgie et obstétrique (MCO) d’un centre hospitalier régional,par les techniciens d’information médicale

BackgroundSince 2008, in France, hospital funding is determined by the nature of activities provided (activity-based funding). Quality control of hospital activity coding is essential to optimize hospital remuneration. There is a need for reliable tools to allocate human resources wisely in order to improve these controls.MethodsThe main objective of this study was to identify the determinants of time needed by medical information technicians to control hospital activity coding in a Regional Hospital Center. From March 2016 to the beginning of January 2017, medical information technicians reported the time they spent on each quality control, and the time they needed when they had to code the entire stay. Multiple linear regressions were performed to identify the determinants of quality control or coding duration. A split sample validation was used: model was created on one half of the sample and validated on the remaining half.ResultsAmong the controls, 5431 were included in the analysis of determinants of control duration (2715 kept aside for model validation). Seven determinants have been identified (stay duration, level of complexity, month of control, type of control, medical information technician, rank of classing information, and major diagnostic category). The correlation coefficient between predicted and real control duration was 0.71 (P < 10^?4); 808 stays were included in the analysis of determinants of coding duration (404 kept aside for model validation). Two determinants have been identified. The correlation coefficient, between predicted and real coding duration, was 0.47 (P < 10^?3). We performed the same multiple regression, on 2017 activity data, to estimate the weight of each hospital activity pole, regarding quality control of hospital activity coding.ConclusionWe succeeded in modeling time needed for quality control of hospital stays. These results helped to estimate human resources required for quality control of each hospital pole. Nevertheless, the second analysis did not give satisfactory results: we failed in modeling time needed to code hospital stays.