Beskrivelse
The course will introduce students to a range of perspectives on health data, including how data is generated, and used by patients, clinicians, and health-care institutions. In particular, we will discuss how data relates to experience and to aspects of behavioural change across a range of clinical conditions. Teaching will unfold around four paradigmatic cases.Learning outcomes:
Students can identify how symptoms and expressions of illness/impairment from different perspectives can be embedded in health data.
Students can describe different ways of generating health data (e.g. in questionnaires, observations, smartphone apps) and analyse how the data can inform patients and clinicians about health and illness.
Students can analyse how the collection of health data can impact patients’ experiences of their own health.
Students can describe the broader impact of collecting health data, and critically reflect on potential unintended consequences.
Indhold
The course will introduce students to a range of perspectives on health data, including how data is generated, and used by patients, clinicians, and health-care institutions. In particular, we will discuss how data relates to experience and to aspects of behavioural change across a range of clinical conditions. Teaching will unfold around four paradigmatic cases.
Through the case of autism spectrum conditions, students will be introduced to different approaches to health data: from the ethical dimensions of widespread early screening, to how the autistic community has been central in shaping diagnostic criteria and affecting the international research agenda, through participatory research engagement. By taking ownership in identifying relevant health data, the autistic perspective/experience is now prioritised in both diagnostic practices and clinical care. This results in a more dynamic conceptualization of disability and constituting autism as an (increasingly) acceptable social identity for many.
The second case covered will be pain, which is both an indicator of the need for medical intervention and a complex medical condition. Measures of pain and their ability to capture the patient experience of pain is widely discussed. Through examples of extensive self-reported pain data used to screen and describe chronic pain patients across their trajectory in a specialized pain clinic, students will be introduced to discussions of how data produces categorizations and impacts the experience of pain.
Third, we will look at emerging technologies to generate health-data. Smartphones, wearable devices and other ‘at home’ monitors can now provide novel streams of data, which promise objective, detailed information on patients’ health, and health-related behaviours. For example, app-based smartphone tracking has been used to examine how much adults with depression move around their environment, and their level of social engagement. In-bed commercial sensors have been used as tools to diagnose sleep disorders. Body movements assessed via smartphone accelerometers have been used to examine Parkinson’s disease symptoms.
Fourth, we will turn to the broader societal issues raised by the COVID-19 pandemic. The main health intervention has been behavioural: the introduction of society-wide legislation and regulation that implements physical distancing, thereby reducing the risk for the propagation of virus. The development of the disease and the changes in behaviour are being tracked with various means, from surveys and mobile phone use, to formal tests for infection and antibodies. This presents a unique case for exploring the use of health and behavioural data in a nationwide setting with enormous economic and political implications. How and for whom are these data collected, and what perspectives are represented? What is the relation between health, data and behaviour?