A refutation of the practice style hypothesis: the case of antibiotics prescription by French general practitioners for acute rhinopharyngitis

Many researches in France or abroad have highlighted the medical practice variation (MPV)phenomenon, or even the inappropriateness of certain medical decisions. There is no consensus on the origin of this MPV between preference-centred versus opportunities and constraints approaches. This study principal purpose is to refute hypothesis which assume that physicians adopt for their patient a uniform practice style for each similar clinical decision beyond the time. More specifically, multilevel models are estimated: First to measure variability of antibiotics prescription by French general practitioners for acute rhinopharyngitis, a clinical decision making context with weak uncertainty, and to tests its significance; Second to prioritize its determinants, especially those relating to GP or its practice setting environment, by controlling visit or patient confounders. The study was based on the 2001 activity data, added by an ad hoc questionnaire, of a sample of 778 GPs arising from a panel of 1006 computerized French GPs. We observe that a great part of the total variation was due to intra-physician variability (70%). Hence, in the French general practice context, we find empirical support for the rejection of the ‘practice style’, the ’enthusiasm’ or the ‘surgical signature’ hypothesis. Thus, it is patients' characteristics that largely explain the prescription, even if physicians' characteristics (area of practice, level of activity, network participation, participation in ongoing medical training) and environmental factors (recent visit from pharmaceutical sales representatives) also exert considerable influence. The latter suggest that MPV are partly caused by differences in the type of dissemination or diffusion of information. Such findings may help us to develop and identify facilitators for promoting a better use of antibiotics in France and, more generally, for influencing GPs practice when it is of interest.Medical practice variation, Multilevel analysis, Upper respiratory tract infections, Rhinopharyngitis, Antibiotics, General practitioners, Panel, France

Routine HIV Screening in France: Clinical Impact and Cost-Effectiveness

BACKGROUND. In France, roughly 40,000 HIV-infected persons are unaware of their HIV infection. Although previous studies have evaluated the cost-effectiveness of routine HIV screening in the United States, differences in both the epidemiology of infection and HIV testing behaviors warrant a setting-specific analysis for France. METHODS/PRINCIPAL FINDINGS. We estimated the life expectancy (LE), cost and cost-effectiveness of alternative HIV screening strategies in the French general population and high-risk sub-populations using a computer model of HIV detection and treatment, coupled with French national clinical and economic data. We compared risk-factor-based HIV testing ("current practice") to universal routine, voluntary HIV screening in adults aged 18-69. Screening frequencies ranged from once to annually. Input data included mean age (42 years), undiagnosed HIV prevalence (0.10%), annual HIV incidence (0.01%), test acceptance (79%), linkage to care (75%) and cost/test (€43). We performed sensitivity analyses on HIV prevalence and incidence, cost estimates, and the transmission benefits of ART. "Current practice" produced LEs of 242.82 quality-adjusted life months (QALM) among HIV-infected persons and 268.77 QALM in the general population. Adding a one-time HIV screen increased LE by 0.01 QALM in the general population and increased costs by €50/person, for a cost-effectiveness ratio (CER) of €57,400 per quality-adjusted life year (QALY). More frequent screening in the general population increased survival, costs and CERs. Among injection drug users (prevalence 6.17%; incidence 0.17%/year) and in French Guyana (prevalence 0.41%; incidence 0.35%/year), annual screening compared to every five years produced CERs of €51,200 and €46,500/QALY. CONCLUSIONS/SIGNIFICANCE. One-time routine HIV screening in France improves survival compared to "current practice" and compares favorably to other screening interventions recommended in Western Europe. In higher-risk groups, more frequent screening is economically justifiable.Haute Autorite de Sante; the Institut de Veille Sanitaire; Sidaction; the Agence Nationale de Recherches sur le SIDA et les hepatites virales; the National Institute of Allergy and Infectious Diseases (R01 AI042006, K24 AI062476, P30 AI42851); the National Institute of Mental Health (R01 MH65869); the National Institute on Drug Abuse (R01 DA015612

Addressing marine and coastal governance conflicts at the interface of multiple sectors and jurisdictions

Marine and coastal activities are closely interrelated, and conflicts among different sectors can undermine management and conservation objectives. Governance systems for fisheries, power generation, irrigation, aquaculture, marine biodiversity conservation, and other coastal and maritime activities are typically organized to manage conflicts within sectors, rather than across them. Based on the discussions around eight case studies presented at a workshop held in Brest in June 2019, this paper explores institutional approaches to move beyond managing conflicts within a sector. We primarily focus on cases where the groups and sectors involved are heterogeneous in terms of: the jurisdiction they fall under; their objectives; and the way they value ecosystem services. The paper first presents a synthesis of frameworks for understanding and managing cross-sectoral governance conflicts, drawing from social and natural sciences. We highlight commonalities but also conceptual differences across disciplines to address these issues. We then propose a novel analytical framework which we used to evaluate the eight case studies. Based on the main lessons learned from case studies, we then discuss the feasibility and key determinants of stakeholder collaboration as well as compensation and incentive schemes. The discussion concludes with future research needs to support policy development and inform integrated institutional regimes that consider the diversity of stakeholder interests and the potential benefits of cross-sectoral coordination

The Changing Landscape for Stroke\ua0Prevention in AF: Findings From the GLORIA-AF Registry Phase 2

Background GLORIA-AF (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients with Atrial Fibrillation) is a prospective, global registry program describing antithrombotic treatment patterns in patients with newly diagnosed nonvalvular atrial fibrillation at risk of stroke. Phase 2 began when dabigatran, the first non\u2013vitamin K antagonist oral anticoagulant (NOAC), became available. Objectives This study sought to describe phase 2 baseline data and compare these with the pre-NOAC era collected during phase 1. Methods During phase 2, 15,641 consenting patients were enrolled (November 2011 to December 2014); 15,092 were eligible. This pre-specified cross-sectional analysis describes eligible patients\u2019 baseline characteristics. Atrial fibrillation disease characteristics, medical outcomes, and concomitant diseases and medications were collected. Data were analyzed using descriptive statistics. Results Of the total patients, 45.5% were female; median age was 71 (interquartile range: 64, 78) years. Patients were from Europe (47.1%), North America (22.5%), Asia (20.3%), Latin America (6.0%), and the Middle East/Africa (4.0%). Most had high stroke risk (CHA2DS2-VASc [Congestive heart failure, Hypertension, Age  6575 years, Diabetes mellitus, previous Stroke, Vascular disease, Age 65 to 74 years, Sex category] score  652; 86.1%); 13.9% had moderate risk (CHA2DS2-VASc = 1). Overall, 79.9% received oral anticoagulants, of whom 47.6% received NOAC and 32.3% vitamin K antagonists (VKA); 12.1% received antiplatelet agents; 7.8% received no antithrombotic treatment. For comparison, the proportion of phase 1 patients (of N = 1,063 all eligible) prescribed VKA was 32.8%, acetylsalicylic acid 41.7%, and no therapy 20.2%. In Europe in phase 2, treatment with NOAC was more common than VKA (52.3% and 37.8%, respectively); 6.0% of patients received antiplatelet treatment; and 3.8% received no antithrombotic treatment. In North America, 52.1%, 26.2%, and 14.0% of patients received NOAC, VKA, and antiplatelet drugs, respectively; 7.5% received no antithrombotic treatment. NOAC use was less common in Asia (27.7%), where 27.5% of patients received VKA, 25.0% antiplatelet drugs, and 19.8% no antithrombotic treatment. Conclusions The baseline data from GLORIA-AF phase 2 demonstrate that in newly diagnosed nonvalvular atrial fibrillation patients, NOAC have been highly adopted into practice, becoming more frequently prescribed than VKA in Europe and North America. Worldwide, however, a large proportion of patients remain undertreated, particularly in Asia and North America. (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients With Atrial Fibrillation [GLORIA-AF]; NCT01468701

Ecosystem Services Assessment for the Conservation of Mangroves in French Guiana Using Fuzzy Cognitive Mapping

In 2016, the French government adopted a law for biodiversity, setting an objective of protecting 55,000 hectares of mangroves. This objective is particularly important to French Guiana, which shelters almost 60% of French mangrove ecosystems, and where mangroves occupy three quarters of the coastline. The coast of French Guiana is also where issues associated with demographic and economic dynamics concentrate. There is thus a need to plan for an economic development that is compatible with the objective of protecting mangrove ecosystems. Ecosystem services (ES) assessment can support such decision-making, informing on the costs and benefits associated with alternative mangrove conservation strategies. While the many services provided by mangrove ecosystems are well documented worldwide, the extent to which these can be encountered in the specific case of French Guiana is currently only very partially known. Relying on the Fuzzy cognitive mapping (FCM) approach, we collected and compared the perception of multiple and heterogeneous groups of stakeholders, of the functioning of the mangrove social-ecological system at the scale of French Guiana. Results, allow to identify mangroves ES and threats particularly influenced by the high sedimentary dynamism of the shoreline. This generates two distinct components of the mangrove social-ecological system: mud banks where ecosystem services are spatially and temporally unstable, and associated with perceived constraints for key coastal activities, and estuarine mangroves where the ecosystem services usually described in the literature on mangroves can be found. Disservices associated with mangrove ecosystems were also identified as a key interaction. This can inform the research needs that should support sustainable development trajectories, fully accounting for the protection of French Guianese mangrove ecosystems

Évaluer individuellement l'efficacité et l'efficience attendue des thérapeutiques dans l'aide à la décision médicale grâce à l'Intelligence Artificielle (IA) : quels enjeux éthiques ?

International audienceMobiliser l’intelligence artificielle (IA) dans l’aide à la décision médicale devrait faciliterla recherche d’informations sur les données scientifiques disponibles. Cela permettrait égalementd’estimer les résultats attendus des différentes options thérapeutiques en termes d’efficacité(balance bénéfice/risque) et d’efficience (ratio coût/efficacité), en fonction des caractéristiquespersonnelles du patient, ce qui était impossible jusqu’à présent. Nous nous demandons si cetteestimation individualisée implique une évolution des modèles de décision qui prévalent dans lesoutils utilisés actuellement et qui s’appuient sur les principes de l’EBM et de l’utilitarisme.Méthode : Une première étape consiste à établir un inventaire des outils actuellementdéveloppés. Une seconde étape consiste à définir à partir de cet inventaire une séried’interrogations éthiques.Résultats : Ces nouvelles technologies n’impliquent pas d’évolution des modèles de décision. Ellesrendent au contraire possible leur renforcement dans des proportions jusqu’à présent limitéespar les capacités informationnelles des acteurs. Les controverses éthiques qu’elles soulèvent nesont donc pas nouvelles. En revanche, elles sont accentuées par ces nouvelles possibilités

Assessing Individual Cost-Effectiveness Ratios (ICER) associated with health care using AI based-clinical decision support systems: which ethical issues?

We are interested here in the possibilities offered by Artificial intelligence (AI) technologies in the health care sector and in particular in supporting medical decisions. Combining AI technologies with clinical decision support systems enable to provide clinicians with new information that was impossible to generate instantly till now. Indeed, it make it possible to estimate the impact of patients' clinical and socio-demographic characteristics in terms of effectiveness (benefit/risk balance) and efficiency (incremental cost/effectiveness ratio (ICER)). For example, patients' age, their health histories and comorbidities may have an impact on both the expected benefits of treatments (e.g., life expectancy and quality of life gains, risks of complications or adverse effects, etc.) and on costs (e.g., hospitalisation costs in case of serious health events, costs of adjuvant treatments, etc.). So far, economists have estimated average ICERs for target populations, also called "populations of indication" because the only available efficacy data are average efficiency data. First, we address the question whether estimating individualized ICERs would be consistent with the classical utilitarian framework, as well as with Paretian welfare economics framework. Theoretically, estimating individualized ICERs would make it possible to better attain the objective of maximizing utility associated with health care under budgetary constraints. Second, we address the question of the social acceptability of medical decisions based on an individualized ICERs. This would imply that a treatment for a given indication could be recommended for some individuals, but not for others. AI based-clinical decision support systems might reinforce implementation of utilitarian justice models by overcoming the current limitations pertaining to the information capacities of the actors. These avenues may therefore raise ethical controversies, that are maybe not unprecedented but certainly intensified. Thereby they make it even more necessary to organise institutional discussions on the ethical frameworks that must be favoured

Assessing Individual Cost-Effectiveness Ratios (ICER) associated with health care using AI based-clinical decision support systems: which ethical issues?

We are interested here in the possibilities offered by Artificial intelligence (AI) technologies in the health care sector and in particular in supporting medical decisions. Combining AI technologies with clinical decision support systems enable to provide clinicians with new information that was impossible to generate instantly till now. Indeed, it make it possible to estimate the impact of patients' clinical and socio-demographic characteristics in terms of effectiveness (benefit/risk balance) and efficiency (incremental cost/effectiveness ratio (ICER)). For example, patients' age, their health histories and comorbidities may have an impact on both the expected benefits of treatments (e.g., life expectancy and quality of life gains, risks of complications or adverse effects, etc.) and on costs (e.g., hospitalisation costs in case of serious health events, costs of adjuvant treatments, etc.). So far, economists have estimated average ICERs for target populations, also called "populations of indication" because the only available efficacy data are average efficiency data. First, we address the question whether estimating individualized ICERs would be consistent with the classical utilitarian framework, as well as with Paretian welfare economics framework. Theoretically, estimating individualized ICERs would make it possible to better attain the objective of maximizing utility associated with health care under budgetary constraints. Second, we address the question of the social acceptability of medical decisions based on an individualized ICERs. This would imply that a treatment for a given indication could be recommended for some individuals, but not for others. AI based-clinical decision support systems might reinforce implementation of utilitarian justice models by overcoming the current limitations pertaining to the information capacities of the actors. These avenues may therefore raise ethical controversies, that are maybe not unprecedented but certainly intensified. Thereby they make it even more necessary to organise institutional discussions on the ethical frameworks that must be favoured

Assessing Individual Cost-Effectiveness Ratios (ICER) associated with health care using AI based-clinical decision support systems: which ethical issues?

We are interested here in the possibilities offered by Artificial intelligence (AI) technologies in the health care sector and in particular in supporting medical decisions. Combining AI technologies with clinical decision support systems enable to provide clinicians with new information that was impossible to generate instantly till now. Indeed, it make it possible to estimate the impact of patients' clinical and socio-demographic characteristics in terms of effectiveness (benefit/risk balance) and efficiency (incremental cost/effectiveness ratio (ICER)). For example, patients' age, their health histories and comorbidities may have an impact on both the expected benefits of treatments (e.g., life expectancy and quality of life gains, risks of complications or adverse effects, etc.) and on costs (e.g., hospitalisation costs in case of serious health events, costs of adjuvant treatments, etc.). So far, economists have estimated average ICERs for target populations, also called "populations of indication" because the only available efficacy data are average efficiency data. First, we address the question whether estimating individualized ICERs would be consistent with the classical utilitarian framework, as well as with Paretian welfare economics framework. Theoretically, estimating individualized ICERs would make it possible to better attain the objective of maximizing utility associated with health care under budgetary constraints. Second, we address the question of the social acceptability of medical decisions based on an individualized ICERs. This would imply that a treatment for a given indication could be recommended for some individuals, but not for others. AI based-clinical decision support systems might reinforce implementation of utilitarian justice models by overcoming the current limitations pertaining to the information capacities of the actors. These avenues may therefore raise ethical controversies, that are maybe not unprecedented but certainly intensified. Thereby they make it even more necessary to organise institutional discussions on the ethical frameworks that must be favoured

Assessing Individual Cost-Effectiveness Ratios (ICER) associated with health care using AI based-clinical decision support systems: which ethical issues?

We are interested here in the possibilities offered by Artificial intelligence (AI) technologies in the health care sector and in particular in supporting medical decisions. Combining AI technologies with clinical decision support systems enable to provide clinicians with new information that was impossible to generate instantly till now. Indeed, it make it possible to estimate the impact of patients' clinical and socio-demographic characteristics in terms of effectiveness (benefit/risk balance) and efficiency (incremental cost/effectiveness ratio (ICER)). For example, patients' age, their health histories and comorbidities may have an impact on both the expected benefits of treatments (e.g., life expectancy and quality of life gains, risks of complications or adverse effects, etc.) and on costs (e.g., hospitalisation costs in case of serious health events, costs of adjuvant treatments, etc.). So far, economists have estimated average ICERs for target populations, also called "populations of indication" because the only available efficacy data are average efficiency data. First, we address the question whether estimating individualized ICERs would be consistent with the classical utilitarian framework, as well as with Paretian welfare economics framework. Theoretically, estimating individualized ICERs would make it possible to better attain the objective of maximizing utility associated with health care under budgetary constraints. Second, we address the question of the social acceptability of medical decisions based on an individualized ICERs. This would imply that a treatment for a given indication could be recommended for some individuals, but not for others. AI based-clinical decision support systems might reinforce implementation of utilitarian justice models by overcoming the current limitations pertaining to the information capacities of the actors. These avenues may therefore raise ethical controversies, that are maybe not unprecedented but certainly intensified. Thereby they make it even more necessary to organise institutional discussions on the ethical frameworks that must be favoured