Scripting the Use of Medical Technology – The Case of Data-based Clinical Decision Support Systems
From Isabelle Hanlon
Abstract:Newly developed Clinical Decision Support Systems (CDSSs), which are supposed to provide information or support decisions, are increasingly systemically opaque and thus less comprehensible for the physician. It becomes more and more unclear to the clinical user and to the developers themselves what data sources and what information are the fundaments of these technologies and how the technology is computing its reasoning on this data. To better comprehend the reasoning of these technologies for the actors engaged it is not only necessary to better understand the inner processes of the technology but also to get more insights into the assumptions the technology is built on. This, again, requires a better understanding of the imagination and ideas about the ways of use which are inscribed into the technology during its development. To exemplify this, I used a case study of the development of a CDSS meant to support treatment decisions in cardiology, a CDSS that is at least partly not based on expert knowledge, that means knowledge from medical experts and/or clinical guidelines but uses techniques of machine learning or simulation. It receives its way of reasoning from recognizing patterns within the data this engine is operating with. This can possibly lead to new findings and discoveries that are not based on pre-existing knowledge and not represented by clinical guidelines but on (potential) correlations between data points in a data corpus. In combining and extending the theoretical concepts of situational scenarios in technology development as well as the notion of scripts written into technology I am going to show that the building of the CDSS-prototype and the negotiation about the components of future situations of use co-evolved and led to specific scripts influencing the envisioned user to use the technology in particular ways and receive recommendations based on a so-called virtual patient, a data corpus “representing” the real patient under treatment. In the case study it was particularly the engineers’ perspective and less the clinicians’ one about the application context that got implemented, which ended in less recognition of the patients’ role in the consultation as well as an assumed passivity on the part of the clinician as recipient of information delivered by the technology.
I am a Doctoral Researcher at the Department of Sociology of Technology and Innovation at the Technical University of Berlin. I have a special interest in the development and application processes of artificially intelligent machines, in particular within medical and health contexts. At present, I am part of a research project that focusses on the social construction of human-robot co-work by means of prototype work settings in the care and healthcare sector. My doctor’s thesis is about trust in artificially intelligent machines in health work contexts. Here, I am using the examples of assisting medical robots and systems of decision support.