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• Hussain and Weibel [15], who used DiCoT to explore the information flow of infection control information in critical care and consider the design of a novel touch screen and badge reader. • Sarcevic and Ferraro [23], who examined the efficiency of electronic documentation in a fast-paced medical setting through the lens of distributed cognition, using cognitive ethnography to understand the information flow among team members and how information was shared, stored and documented. 2.2. Two use cases using distributed cognition for health informatics We present two use cases at different stages of the project life cycle: the first case at the formative stage of the project life cycle where we are still developing an understanding of the key determinants for what, how, when and why patients use patient- held information about their medication (PHIMed); the second is an example of a study at the summative stage of a project life cycle where we evaluate the design and use of infusion devices already in practice. Use case 1: Patient-held information about their medication (PHIMed) PHIMed is defined as any patient-held information such that an editable list of current medications can be carried, regardless of whether or not other functionalities are also available; this can include paper and electronic tools [24]. Patients can be concerned about receiving appropriate treatment, especially where information breakdowns might occur in a fragmented healthcare system. For example, general practitioner surgeries, hospitals, and community pharmacies do not routinely share data in the National Health Service, increasing the chance of error. PHIMed helps fill the gaps and prevent errors. A specific example is that as a result of viewing a patient’s PHIMed a community pharmacist stopped the patient purchasing an over the counter medication which would have been unsafe for them to use. [25] However, how PHIMed is best used, whether it affects patient outcomes and its key determinants for success are not known. Distributed cognition was selected as the theory for investigating design and use of PHIMed. Distributed cognition seemed like a good fit since we are interested in the design and use of an artefact (i.e. PHIMed), how this may play a role in supporting cognition and decision making of healthcare professionals and patients, and how the use of PHIMed could have wider effects on the system such as improving resilience to errors and enhancing patient activation. DiCoT is being used to provide concepts and constructs to inspire thoughts and questions that we might not have asked without the theory. Early on in the study we discussed the application of the theory and used it to brainstorm whether and how concepts and constructs might be applicable (see Table 1 for examples). These early ideas informed data gathering and analysis, but importantly will also be tested by empirical data. In this way DiCoT supported sense making at the very early stages of the project lifecycle, helping us to generate questions and explore potential determinants of success for PHIMed that can then be tested. D.Furniss etal. /DistributedCognition:UnderstandingComplexSociotechnical Informatics80