Digital health: A sociomaterial approach

Sociotechnical imaginaries in academic medicine strategic planning: a document analysis

Purpose Along with other industries, healthcare is becoming increasingly digitized. Our study explores how the field of academic medicine is preparing for this digital future. Method Active strategic plans available in English were collected from faculties of medicine in Canada (n = 14), departments in medical schools (n = 17), academic health science centres (n = 23) and associated research institutes (n = 5). In total, 59 strategic plans were subjected to a practice-oriented form of document analysis, informed by the concept of sociotechnical imaginaries. Results On the one hand, digital health is discursively treated as a continuation of the academic medicine vision, with expansions of physician competencies and of research institutes contributions. These imaginaries do not necessarily disrupt the field of academic medicine as currently configured. On the other hand, there is a vision of digital health pursuing a robust sociotechnical future with transformative implications for how care is conducted, what forms of knowledge are prioritized, how patients and patienthood will be understood, and how data work will be distributed. This imaginary may destabilize existing distributions of knowledge and power. Conclusions Looking through the lens of sociotechnical imaginaries, this study illuminates strategic plans as framing desirable futures, directing attention towards specific ways of understanding problems of healthcare, and mobilizing the resources to knit together social and technical systems in ways that bring these visions to fruition. There are bound to be tensions as these sociotechnical imaginaries are translated into material realities. Many of those tensions and their attempted resolutions will have direct implications for the expectations of health professional graduates, the nature of clinical learning environments, and future relationships with patients. Sociology of digital health and science and technology studies can provide useful insights to guide leaders in academic medicine shaping these digital futures.

Speed, accuracy, and efficiency: The promises and practices of digitization in pathology

Digitization is often presented in policy discourse as a panacea to a multitude of contemporary problems, not least in healthcare. How can policy promises relating to digitization be assessed and potentially countered in particular local contexts? Based on a study in Denmark, we suggest scrutinizing the politics of digitization by comparing policy promises about the future with practitioners' experience in the present. While Denmark is one of the most digitalized countries in the world, digitization of pathology has only recently been given full policy attention. As pathology departments are faced with an increased demand for pathology analysis and a shortage of pathologists, Danish policymakers have put forward digitization as a way to address these challenges. Who is it that wants to digitize pathology, why, and how does digitization unfold in routine work practices? Using online search and document analysis, we identify actors and analyze the policy promises describing expectations associated with digitization. We then use interviews and observations to juxtapose these expectations with observations of everyday pathology practices as experienced by pathologists. We show that policymakers expect digitization to improve speed, patient safety, and diagnostic accuracy, as well as efficiency. In everyday practice, however, digitization does not deliver on these expectations. Fulfillment of policy expectations instead hinges on the types of artificial intelligence (AI) applications that are still to be developed and implemented. Some pathologists remark that AI might work in the easy cases, but this would leave them with only the difficult cases, which they consider too burdensome. Our particular mode of juxtaposing policy and practice throws new light on the political work done by policy promises and helps to explain why the discipline of pathology does not seem to easily lend itself to the digital embrace.

'It's not as good as the face-to-face contact': A sociomaterialist analysis of the use of virtual care among Canadian gay, bisexual and queer men during the COVID-19 pandemic

The COVID-19 pandemic led to the widespread adoption of virtual care-the use of communication technologies to receive health care at home. We explored the differential impacts of the rapid transition to virtual care during the COVID-19 pandemic on health-care access and delivery for gay, bisexual and queer men (GBQM), a population that disproportionately experiences sexual and mental health disparities in Canada. Adopting a sociomaterial theoretical perspective, we analysed 93 semi-structured interviews with GBQM (n = 93) in Montreal, Toronto and Vancouver, Canada, conducted between November 2020 and February 2021 (n = 42) and June-October 2021 (n = 51). We focused on explicating how the dynamic relations of humans and non-humans in everyday virtual care practices have opened or foreclosed different care capacities for GBQM. Our analysis revealed that the rapid expansion and implementation of virtual care during the COVID-19 pandemic enacted disruptions and challenges while providing benefits to health-care access among some GBQM. Further, virtual care required participants to change their sociomaterial practices to receive health care effectively, including learning new ways of communicating with providers. Our sociomaterial analysis provides a framework that helps identify what works and what needs to be improved when delivering virtual care to meet the health needs of GBQM and other diverse populations.

Reconciling healthism and techno-solutionism: An observational study of a digital mental health trial

In a growing trend in digital psychiatry, algorithmic systems are used to determine correlations between data that is collected using wearable devices and self-reports of mood. They then offer recommendations for behaviour modification for improved mood. The present study consists of observations of the development of one of these systems. Descriptions of the trial emphasise the powerful role of the intrinsically motivated, responsible participant on one hand and the empowering machine learning (ML)-based technology on the other. This conceptualisation is shown to extend the neoliberal paradox of a freedom that, to be maintained, must be continually adjusted through discipline. Because of the paradoxical nature of this formulation, laboratory members disagree about the balance of agency between the objective machine learning system and the empowered participant. The guides who help participants interpret ML outputs and implement system recommendations are ascribed a replaceable role in formal accounts. Observations of this guidance practice make clear not only the important role played by guides but also how their work is relegated to the technological side of the broader formulation of the trial and further how this conceptualisation affects the way they conduct their work.

Evaluation of Digitalisation in Healthcare and the Quantification of the "Unmeasurable"

Evaluating healthcare digitalisation, where technology implementation and adoption transforms existing socio-organisational processes, presents various challenges for outcome assessments. Populations are diverse, interventions are complex and evolving over time, meaningful comparisons are difficult as outcomes vary between settings, and outcomes take a long time to materialise and stabilise. Digitalisation may also have unanticipated impacts. We here discuss the limitations of evaluating the digitalisation of healthcare, and describe how qualitative and quantitative approaches can complement each other to facilitate investment and implementation decisions. In doing so, we argue how existing approaches have focused on measuring what is easily measurable and elevating poorly chosen values to inform investment decisions. Limited attention has been paid to understanding processes that are not easily measured even though these can have significant implications for contextual transferability, sustainability and scale-up of interventions. We use what is commonly known as the McNamara Fallacy to structure our discussions. We conclude with recommendations on how we envisage the development of mixed methods approaches going forward in order to address shortcomings.