Building a Logic Model to Foster Engagement and Learning Using the Case of a Province-Wide Multispecies Antimicrobial Use Monitoring System.

Successfully designing and implementing a program is complex; it requires a reflexive balance between the available resources and the priorities of various stakeholders, both of which change over time. Logic models are theory-based evaluation approaches used to identify and address key challenges of a program. This article describes the process of building a logic model on advanced theories in complexity studies. The models aim to support a province-wide multispecies monitoring system of antimicrobial use (AMU), designed in collaboration with the animal health sector in Quebec (Canada). Based on a rigorous theoretical foundation, the logic model is built in three steps: (1) mapping, a narrative review of literature on similar programs in other jurisdictions; (2) framing, iterative consultations with project members to elaborate the logic model; (3) shaping, hypotheses based on the logic model. The model emerges from the reflexive balancing of current scientific knowledge and empirical insights to gather relevant information about stakeholders from interdisciplinary experts that led a 3-year consensus-building process within the community. Recognizing the challenge of unpacking theories for practical use, we illustrate how the process of an "open" logic model building could enable governance coordination in complex processes. Logic models are useful for evaluating public, private, and academic partnerships in One Health programs that characterize an adaptive governance process.

Breast Cancer Risk Estimation and Personal Insurance: A Qualitative Study Presenting Perspectives from Canadian Patients and Decision Makers.

Genetic stratification approaches in personalized medicine may considerably improve our ability to predict breast cancer risk for women at higher risk of developing breast cancer. Notwithstanding these advantages, concerns have been raised about the use of the genetic information derived in these processes, outside of the research and medical health care settings, by third parties such as insurers. Indeed, insurance applicants are asked to consent to insurers accessing their medical information (implicitly including genetic) to verify or determine their insurability level, or eligibility to certain insurance products. This use of genetic information may result in the differential treatment of individuals based on their genetic information, which could lead to higher premium, exclusionary clauses or even the denial of coverage. This phenomenon has been commonly referred to as "Genetic Discrimination" (GD). In the Canadian context, where federal Bill S-201, An Act to prohibit and prevent genetic discrimination, has recently been enacted but may be subject to constitutional challenges, information about potential risks to insurability may raise issues in the clinical context. We conducted a survey with women in Quebec who have never been diagnosed with breast cancer to document their perspectives. We complemented the research with data from 14 semi-structured interviews with decision-makers in Quebec to discuss institutional issues raised by the use of genetic information by insurers. Our results provide findings on five main issues: (1) the reluctance to undergo genetic screening test due to insurability concerns, (2) insurers' interest in genetic information, (3) the duty to disclose genetic information to insurers, (4) the disclosure of potential impacts on insurability before genetic testing, and (5) the status of genetic information compared to other health data. Overall, both groups of participants (the women surveyed and the decision-makers interviewed) acknowledged having concerns about GD and reported a need for better communication tools discussing insurability risk. Our conclusions regarding concerns about GD and the need for better communication tools in the clinical setting may be transferable to the broader Canadian context.

A Syst-OMICS Approach to Ensuring Food Safety and Reducing the Economic Burden of Salmonellosis.

The Salmonella Syst-OMICS consortium is sequencing 4,500 Salmonella genomes and building an analysis pipeline for the study of Salmonella genome evolution, antibiotic resistance and virulence genes. Metadata, including phenotypic as well as genomic data, for isolates of the collection are provided through the Salmonella Foodborne Syst-OMICS database (SalFoS), at https://salfos.ibis.ulaval.ca/. Here, we present our strategy and the analysis of the first 3,377 genomes. Our data will be used to draw potential links between strains found in fresh produce, humans, animals and the environment. The ultimate goals are to understand how Salmonella evolves over time, improve the accuracy of diagnostic methods, develop control methods in the field, and identify prognostic markers for evidence-based decisions in epidemiology and surveillance.

Genetics and Personal Insurance: the Perspectives of Canadian Cancer Genetic Counselors.

Genetic discrimination in the context of genetic testing has been identified as a concern for symptomatic and asymptomatic individuals for more than three decades. Genetic counselors are often the health care professionals who discuss risks and benefits of genetic testing with patients, thereby making them most appropriate to address patient concerns about genetics and personal insurance (i.e., life, life as related to mortgage or group insurance, disability, critical illness and travel). A pilot study was conducted to ascertain the current practices of Canadian cancer genetic counselors in regard to their discussions with patients about genetic testing and access to personal insurance. Among the 36 counselors surveyed, 100 % reported discussing the issue of genetic testing and personal insurance with their patients. Several factors influenced the content, depth and length of these discussions including age, cancer status, family members, and patients' current and future insurance needs. Counselors reported discussing with patients the possible impact of genetic test results on access to personal insurance, possible access and use of patient genetic information by insurance companies, and whom patients should contact if they have additional questions. The most commonly reported inquiries from patients included questions about the possible impact of genetic testing on their ability to obtain insurance, and the insurability of family members. While 28 % of counselors reported having been contacted by an insurer requesting access to patient information, only one counselor was aware of or could recall the outcome of such a request. This pilot study revealed that issues concerning genetics and personal insurance are commonly discussed in Canadian cancer genetic counseling sessions. Counselors furthermore expressed a need for additional educational resources on the topic of genetics and personal insurance for themselves and their patients.

Genetic discrimination and life insurance: a systematic review of the evidence.

BACKGROUND: Since the late 1980s, genetic discrimination has remained one of the major concerns associated with genetic research and clinical genetics. Europe has adopted a plethora of laws and policies, both at the regional and national levels, to prevent insurers from having access to genetic information for underwriting. Legislators from the United States and the United Kingdom have also felt compelled to adopt protective measures specifically addressing genetics and insurance. But does the available evidence really confirm the popular apprehension about genetic discrimination and the subsequent genetic exceptionalism? METHODS: This paper presents the results of a systematic, critical review of over 20 years of genetic discrimination studies in the context of life insurance. RESULTS: The available data clearly document the existence of individual cases of genetic discrimination. The significance of this initial finding is, however, greatly diminished by four observations. First, the methodology used in most of the studies is not sufficiently robust to clearly establish either the prevalence or the impact of discriminatory practices. Second, the current body of evidence was mostly developed around a small number of 'classic' genetic conditions. Third, the heterogeneity and small scope of most of the studies prevents formal statistical analysis of the aggregate results. Fourth, the small number of reported genetic discrimination cases in some studies could indicate that these incidents took place due to occasional errors, rather than the voluntary or planned choice, of the insurers. CONCLUSION: Important methodological limitations and inconsistencies among the studies considered make it extremely difficult, at the moment, to justify policy action taken on the basis of evidence alone. Nonetheless, other empirical and theoretical factors have emerged (for example, the prevalence and impact of the fear of genetic discrimination among patients and research participants, the (un)importance of genetic information for the commercial viability of the private life insurance industry, and the need to develop more equitable schemes of access to life insurance) that should be considered along with the available evidence of genetic discrimination for a more holistic view of the debate.