Inequity in access to personalized medicine in France: Evidences from analysis of geo variations in the access to molecular profiling among advanced non-small-cell lung cancer patients: Results from the IFCT Biomarkers France Study

In this article, we studied geographic variation in the use of personalized genetic testing for advanced non-small cell lung cancer (NSCLC) and we evaluated the relationship between genetic testing rates and local socioeconomic and ecological variables. We used data on all advanced NSCLC patients who had a genetic test between April 2012 and April 2013 in France in the frame of the IFCT Biomarqueurs-France study (n = 15814). We computed four established measures of geographic variation of the sex-adjusted rates of genetic testing utilization at the “départment” (the French territory is divided into 94 administrative units called ‘départements’) level. We also performed a spatial regression model to determine the relationship between département-level sex-adjusted rates of genetic testing utilization and economic and ecological variables. Our results are the following: (i) Overall, 46.87% lung cancer admission patients obtained genetic testing for NSCLC; département-level utilization rates varied over 3.2-fold. Measures of geographic variation indicated a relatively high degree of geographic variation. (ii) there was a statistically significant relationship between genetic testing rates and per capita supply of general practitioners, radiotherapists and surgeons (negative correlation for the latter); lower genetic testing rates were also associated with higher local poverty rates. French policymakers should pursue effort toward deprived areas to obtain equal access to personalized medicine for advanced NSCLC patients

Essais sur les incitations et les motivations des médecins

Nous étudions les propriétés incitatives des contrats des médecins dans différents contextes et en mobilisant différentes méthodes. Au chapitre 1, nous proposons un modèle ``principal-agent’’ dans lequel il existe une sélection adverse sur l’altruisme des agents, une responsabilité limitée et une technologie fournie par le régulateur et pouvant améliorer la qualité de l’effort des médecins. Dans un tel contexte (caractérisant le secteur de la santé avec un accès à la médecine personnalisée par exemple), nous montrons que les contrats optimaux impliquent des salaires plus élevés pour les agents altruistes et une technologie d'amélioration de l’effort de meilleure qualité pour les agents égoïstes. Au chapitre 2, nous proposons une expérience dans laquelle les médecins peuvent accéder gratuitement ou à un coût donné à des techniques de médecine personnalisée. Nous évaluons pour différents systèmes de paiement, la probabilité que les médecins prennent la décision d'un accès payant à la médecine personnalisée, et nous nous concentrons également sur la manière dont ils utilisent ces technologies, selon que leur accès est gratuit ou coûteux. Nous trouvons que les médecins ont tendance à mieux utiliser les techniques de médecine personnalisée lorsqu’ils l’ont acquis à un coût. Au chapitre 3, nous étudions les propriétés incitatives des systèmes de rémunération à la performance. En utilisant la même expérience du chapitre 2, nous trouvons que les systèmes de paiement à la performance renforcent l’attention des médecins sur ce qui est pertinent pour le patient, mais sont associés à une érosion de leur motivation intrinsèque.We study incentive properties of healthcare providers' contracts in different contexts and using a range of methods. In Chapter 1, we propose a ``regulator-agent'' model with adverse selection on altruism, limited liability and a possible effort enhancing input provided by the regulator. In such a context (characterizing the healthcare sector with a free access to personalized medicine, for example), we show that the optimal contracts entail higher salaries for the altruistic agents and higher effort-enhancing technology for selfish agents. In Chapter 2, we propose an experiment in which healthcare providers can access for free or at a given cost, personalized medicine techniques. For different payment systems, we assess the likelihood of making the decision to access personalized medicine when it is paid. We also focus on how healthcare providers use these technologies, depending on whether their access is free or costly. We find that healthcare providers tend to make better use of personalized medicine techniques when they acquire it at a cost. In Chapter 3, we study incentive properties of performance pay systems. Using the same experiment as in Chapter 2, we find that performance-based systems increase healthcare providers' attention on what is relevant to the patient. It however destroys their intrinsic motivation

Healthcare providers’ payments with personalized medicine

International audienc

Regulation and Altruism

We study optimal contracts in a regulator-agent setting with joint production, altruistic and selfish agents, and uneasy outcome measurement. Such a setting represents sectors of activities such as education and health care provision. The agents and the regulator jointly produce an outcome for which they all care to some extent that is varying from agent to agent. Some agents, the altruistic ones, care more than the regulator does while others, the selfish agents, care less. Moral hazard is present due to the agent’s effort that is not contractible. Adverse selection is present too since the regulator cannot a priori distinguish between altruistic and selfish agents. Contracts consist of a simple transfer from the regulator to the agents together with the regulator’s input in the joint production. We show that a screening contract is not optimal when we face both moral hazard and adverse selection

Regulation and altruism

We study optimal contracts in a regulator–agent setting with joint production, altruistic and selfish agents, limited liability, and uneasy outcome measurement. Such a setting represents sectors of activities such as education and healthcare provision. The agents and the regulator jointly produce an outcome for which they all care to some extent that is varying from agent to agent. Some agents, the altruistic ones, care more than the regulator does while others, the selfish agents, care less. Moral hazard is present due to both the agent's effort and the joint outcome that are not contractible. Adverse selection is present too since the regulator cannot a priori distinguish between altruistic and selfish agents. Contracts consist of a simple transfer from the regulator to the agents together with the regulator's input in the joint production. We show that, under the conditions of our setting and when we face both moral hazard and adverse selection, the regulator maximizes welfare with a menu of contracts, which specify higher transfers for the altruistic agents and higher regulator's inputs for the selfish agents

Regulation and Altruism

We study optimal contracts in a regulator-agent setting with joint production, altruistic and selfish agents, and uneasy outcome measurement. Such a setting represents sectors of activities such as education and health care provision. The agents and the regulator jointly produce an outcome for which they all care to some extent that is varying from agent to agent. Some agents, the altruistic ones, care more than the regulator does while others, the selfish agents, care less. Moral hazard is present due to the agent’s effort that is not contractible. Adverse selection is present too since the regulator cannot a priori distinguish between altruistic and selfish agents. Contracts consist of a simple transfer from the regulator to the agents together with the regulator’s input in the joint production. We show that a screening contract is not optimal when we face both moral hazard and adverse selection

Protocol for validation of the Global Scales for Early Development (GSED) for children under 3 years of age in seven countries

Introduction Children's early development is affected by caregiving experiences, with lifelong health and well-being implications. Governments and civil societies need population-based measures to monitor children's early development and ensure that children receive the care needed to thrive. To this end, the WHO developed the Global Scales for Early Development (GSED) to measure children's early development up to 3 years of age. The GSED includes three measures for population and programmatic level measurement: (1) short form (SF) (caregiver report), (2) long form (LF) (direct administration) and (3) psychosocial form (PF) (caregiver report). The primary aim of this protocol is to validate the GSED SF and LF. Secondary aims are to create preliminary reference scores for the GSED SF and LF, validate an adaptive testing algorithm and assess the feasibility and preliminary validity of the GSED PF. Methods and analysis We will conduct the validation in seven countries (Bangladesh, Brazil, Côte d'Ivoire, Pakistan, The Netherlands, People's Republic of China, United Republic of Tanzania), varying in geography, language, culture and income through a 1-year prospective design, combining cross-sectional and longitudinal methods with 1248 children per site, stratified by age and sex. The GSED generates an innovative common metric (Developmental Score: D-score) using the Rasch model and a Development for Age Z-score (DAZ). We will evaluate six psychometric properties of the GSED SF and LF: concurrent validity, predictive validity at 6 months, convergent and discriminant validity, and test-retest and inter-rater reliability. We will evaluate measurement invariance by comparing differential item functioning and differential test functioning across sites. Ethics and dissemination This study has received ethical approval from the WHO (protocol GSED validation 004583 20.04.2020) and approval in each site. Study results will be disseminated through webinars and publications from WHO, international organisations, academic journals and conference proceedings. Registration details Open Science Framework https://osf.io/ on 19 November 2021 (DOI 10.17605/OSF.IO/KX5T7; identifier: osf-registrations-kx5t7-v1)

Protocol for validation of the Global Scales for Early Development (GSED) for children under 3 years of age in seven countries.

IntroductionChildren's early development is affected by caregiving experiences, with lifelong health and well-being implications. Governments and civil societies need population-based measures to monitor children's early development and ensure that children receive the care needed to thrive. To this end, the WHO developed the Global Scales for Early Development (GSED) to measure children's early development up to 3 years of age. The GSED includes three measures for population and programmatic level measurement: (1) short form (SF) (caregiver report), (2) long form (LF) (direct administration) and (3) psychosocial form (PF) (caregiver report). The primary aim of this protocol is to validate the GSED SF and LF. Secondary aims are to create preliminary reference scores for the GSED SF and LF, validate an adaptive testing algorithm and assess the feasibility and preliminary validity of the GSED PF.Methods and analysisWe will conduct the validation in seven countries (Bangladesh, Brazil, Côte d'Ivoire, Pakistan, The Netherlands, People's Republic of China, United Republic of Tanzania), varying in geography, language, culture and income through a 1-year prospective design, combining cross-sectional and longitudinal methods with 1248 children per site, stratified by age and sex. The GSED generates an innovative common metric (Developmental Score: D-score) using the Rasch model and a Development for Age Z-score (DAZ). We will evaluate six psychometric properties of the GSED SF and LF: concurrent validity, predictive validity at 6 months, convergent and discriminant validity, and test-retest and inter-rater reliability. We will evaluate measurement invariance by comparing differential item functioning and differential test functioning across sites.Ethics and disseminationThis study has received ethical approval from the WHO (protocol GSED validation 004583 20.04.2020) and approval in each site. Study results will be disseminated through webinars and publications from WHO, international organisations, academic journals and conference proceedings.Registration detailsOpen Science Framework https://osf.io/ on 19 November 2021 (DOI 10.17605/OSF.IO/KX5T7; identifier: osf-registrations-kx5t7-v1)