Normal use


Both accident investigations and research into errors in healthcare focus on what went wrong. We have investigated ‘normal’ practice in healthcare: what actually happens day-in-day-out, getting the job done and making patients better, i.e. when things go right. This includes not only understanding the way things are done, but also the potential for mistakes to happen, and how error can be, and is, avoided on a daily basis. It is important that normal practice is understood so that appropriate design decisions can be made, and as a basis for evaluating whether medical devices appropriately support the tasks being done. It also matters in understanding where errors emerge from, as well as issues that are broader than error and safety such as how the experience of the person using the device can influence its use. We have studied the everyday use of devices in clinical settings such as on hospital wards but also by patients using devices at home and on the move.

Unremarkable errors: investigating the unremarkable, routine and normal

Unremarkable simply means that something is not remarked upon. This could be because it is not noticed, it is uninteresting, it is assumed to be normal or the person does not want to draw attention to it. We have found this area to be both important and enlightening for healthcare. We have examined unremarkable errors in normal work, made disruptive device interactions visible, and highlighted routine issues in clinicians’ work and from the patient’s perspective. We have applied theory from ‘unremarkable computing’ to healthcare. We propose a research agenda that focuses on the unremarkable and routine that aims to make computing invisible-in-use.

Home haemodialysis: patients’ experiences of home haemodialysis technology

We have interviewed patients who use haemodialysis in their own homes to find out about their experiences. Our work shows that the design of future machines needs to better take into account specific things that people find particularly difficult with the process, or with fitting dialysis into their lives. As a result of our research we have developed specific recommendations for the future design of home haemodialysis equipment. We have presented our findings to groups of professionals responsible for kidney care, as well as in blog posts for patient groups and carers giving them strategies for managing technology use.

Understanding mobile contexts: using qualitative situated methods in the design of mobile medical technologies

Medical devices are increasingly used as part of patients’ daily lives, so new methods are needed to ensure they are easy to use in these non-medical contexts. To address this, our research has delved into understanding the real life use of Type 1 Diabetes technologies in people’s everyday lives, using qualitative situated methods. These methods go beyond the scope of the current human factors standards such as ISO 62366. We have increased the awareness of manufacturers and diabetes charities about these methods. We are now applying them to the design and development of new Type 1 diabetes technologies, through collaborations and a new consultancy set up for the purpose.

Infusion use: infusion device use and management

We have built a picture of how, in various contexts, UK hospitals are using and managing infusion devices: pumps that deliver medication to patients. Smart pumps, which can alert nurses when unusual infusion values are set, are only occasionally used in UK hospitals, despite their potential benefits for safety. There are important barriers preventing smart pumps being used including existing contracts, and those making the decisions needing to be convinced that the benefit is worth the effort needed to adopt them. The Singleton Hospital is using the research as a driver to introduce smart pump software.

Diverse use of devices: use of infusion devices in different contexts

We have identified important differences between the assumptions made during design about how infusion devices will be used and the ways that they are actually used in practice; identified important differences in the ways that infusion devices are used in different contexts, and for different purposes; and developed and shared a set of resources that illustrate the variations in the ways that devices are used.

Resilience strategies: learning from things going right

Most of the time things go right. Understanding why can be as important as understanding why things do go wrong, but is often ignored. By better understanding and sharing the way people adapt what they do to avoid making mistakes we can help make healthcare safer. We have developed a new concept: ‘resilience strategies’ to refer to the informal and inventive actions people take to avoid making mistakes and/or to improve performance. We have identified different types of resilience strategy, creating a categorisation scheme for them. We have also developed frameworks for analysing and understanding these strategies including how and why they work. We are now using this knowledge to help understand how patients and healthcare practitioners self-manage. This will lead to improvements in the design and use of medical devices.

Fieldwork for healthcare

Fieldwork for healthcare is a very challenging research area, for which there was little support: a gap we have now filled. We have made it easier for new researchers and practitioners to do healthcare fieldwork studies by collecting case studies and experiences from international experts, sharing these through a published graduate guidebook. We have also identified guidance and strategies for overcoming the problems of doing fieldwork for healthcare, writing a second graduate guidebook on this. We have also fostered a supportive international research community in fieldwork for healthcare.

Distributed Cognition – DiCoT: an accessible method for understanding technology use in healthcare

Distributed Cognition is a theory about how our mental processes work that extends cognition from the thoughts in our head to include the way we use objects in the world to represent information too. We have made it easier to apply Distributed Cognition to understand the way people work in healthcare. In particular, we have developed a method called DiCoT that supports analysts studying healthcare contexts in using Distributed Cognition to understand those contexts. We have shown that DiCoT can give valuable insights in a variety of such contexts, from hospital wards to patients’ homes, and for a variety of different devices including infusion pumps, blood glucose meters and haemodialysis machines.