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ABSTRACT

Migrant workers face significant barriers of knowledge, language, cost, and status in accessing adequate healthcare in their host countries. Hospitals routinely encounter migrant workers whose need for long-term medical care may trigger the prospect of work termination and repatriation. These workers often lack the knowledge and power to determine, on their own, whether to stay for treatment or how to be sent home safely. While employment contracts and country-specific employment policies offer some guidance, they are not clear on the conditions under which hospitals can support or endorse such medical repatriation. In this paper, I will extend the ethical framework on medical repatriation in Kuczewski (AJOB 2012), by analysing challenging cases in Singapore that involve transient migrant workers with non-work-related health conditions. My analysis will draw on recent research into migrant vulnerability in multicultural contexts and the ethics of just repatriation.

First, I will outline Kuczewski’s ethical framework, which focuses on the medical repatriation of undocumented migrants. Based on the mission and values of hospitals, it specifies three necessary conditions under which repatriation is ethical. These conditions relate to the patient’s best interest, the hospital’s due diligence, and the patient’s informed consent. Second, I will examine the challenges of applying these three conditions to transient migrant workers. The challenges arise partly from the distinctive migration projects and employment conditions of such workers, who are unusually dependent on others and disempowered in host countries. Hospitals also face potential conflicts between their organisational norms, employer practices, and state policies. Through an analysis of a series of difficult cases, I seek to clarify the ethical role of hospitals in repatriating transient migrant workers and propose some practical guidelines.

 

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Monday, 06 February 2023, 1pm to 2pm @ BDI Seminar Room LG 0-1, Old Road Campus, Headington, OX3 7LF

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Richard Doll Seminar- Triangulation of evidence in aetiological epidemiology: principles, prospects and limitations.

Tuesday, 21 February 2023, 1pm to 2pm @ Richard Doll Lecture Theatre, Richard Doll Building, Old Road Campus, OX3 7LF

Aetiological epidemiology is concerned with the identification of causal influences on disease risk. Randomized controlled trials are, when possible, the cornerstone of knowledge as to whether interventions based on aetiological studies are merited. It is not feasible to subject all of the many candidate causes to large-scale RCTs, however, even in situations where they are in principle possible. Triangulation of evidence is an approach that attempts to formally combine findings from different domains to strengthen causal inference. Triangulation embraces the variety of evidence thesis, that inferential strength depends not only on the quantity of available evidence, but also on its variety: the greater the variety, the stronger the resulting support. An essential condition is that the systematic errors and biases are unrelated across different study types. For example, the effect of raising circulating HDL cholesterol on the risk of coronary heart disease can be estimated from RCTs or through Mendelian randomization using genetic variants related to HDL level. Both the results of RCTs and Mendelian randomization studies could be biased. However, the potential biases in one study design would not influence estimates from the other approach: the biases are unrelated to each other. In observational epidemiology approaches that can be applied include the use of negative control exposures or outcomes; the deliberate use of data from contexts in which confounding structures differ; the use of instrumental variables and related approaches, such as regression discontinuity; quasi-experimental studies; the estimation of the expected magnitude of associations generated by confounding and the incorporation of mechanistic data, amongst others. Pre-registration of protocols for the triangulation of evidence increases confidence in the findings produced.