Understanding safety-critical interactions with a home medical device through Distributed Cognition.

As healthcare shifts from the hospital to the home, it is becoming increasingly important to understand how patients interact with home medical devices, to inform the safe and patient-friendly design of these devices. Distributed Cognition (DCog) has been a useful theoretical framework for understanding situated interactions in the healthcare domain. However, it has not previously been applied to study interactions with home medical devices. In this study, DCog was applied to understand renal patients' interactions with Home Hemodialysis Technology (HHT), as an example of a home medical device. Data was gathered through ethnographic observations and interviews with 19 renal patients and interviews with seven professionals. Data was analyzed through the principles summarized in the Distributed Cognition for Teamwork methodology. In this paper we focus on the analysis of system activities, information flows, social structures, physical layouts, and artefacts. By explicitly considering different ways in which cognitive processes are distributed, the DCog approach helped to understand patients' interaction strategies, and pointed to design opportunities that could improve patients' experiences of using HHT. The findings highlight the need to design HHT taking into consideration likely scenarios of use in the home and of the broader home context. A setting such as home hemodialysis has the characteristics of a complex and safety-critical socio-technical system, and a DCog approach effectively helps to understand how safety is achieved or compromised in such a system.

Patients' and carers' experiences of interacting with home haemodialysis technology: implications for quality and safety.

BACKGROUND: Little is known about patients' and carers' experiences of interacting with home haemodialysis (HHD) technology, in terms of user experience, how the design of the technology supports safety and fits with home use, and how the broader context of service provision impacts on patients' use of the technology. METHODS: Data were gathered through ethnographic observations and interviews with 19 patients and their carers associated with four different hospitals in the UK, using five different HHD machines. All patients were managing their condition successfully on HHD. Data were analysed qualitatively, focusing on themes of how individuals used the machines and how they managed their own safety. RESULTS: Findings are organised by three themes: learning to use the technology, usability of the technology, and managing safety during dialysis. Home patients want to live their lives fully, and value the freedom and autonomy that HHD gives them; they adapt use of the technology to their lives and their home context. They also consider the machines to be safe; nevertheless, most participants reported feeling scared and having to learn through mistakes in the early months of dialysing at home. Home care nurses and technicians provide invaluable support. Although participants reported on strategies for anticipating problems and keeping safe, perceived limitations of the technology and of the broader system of care led some to trade off safety against immediate quality of life. CONCLUSIONS: Enhancing the quality and safety of the patient experience in HHD involves designing technology and the broader system of care to take account of how individuals manage their dialysis in the home. Possible design improvements to enhance the quality and safety of the patient experience include features to help patients manage their dialysis (e.g. providing timely reminders of next steps) and features to support communication between families and professionals (e.g. through remote monitoring).

Understanding infusion administration in the ICU through Distributed Cognition.

To understand how healthcare technologies are used in practice and evaluate them, researchers have argued for adopting the theoretical framework of Distributed Cognition (DC). This paper describes the methods and results of a study in which a DC methodology, Distributed Cognition for Teamwork (DiCoT), was applied to study the use of infusion pumps by nurses in an Intensive Care Unit (ICU). Data was gathered through ethnographic observations and interviews. Data analysis consisted of constructing the representational models of DiCoT, focusing on information flows, physical layouts, social structures and artefacts. The findings show that there is significant distribution of cognition in the ICU: socially, among nurses; physically, through the material environment; and through technological artefacts. The DiCoT methodology facilitated the identification of potential improvements that could increase the safety and efficiency of nurses' interactions with infusion technology.