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BackgroundAutomated insulin delivery (AID) systems have been shown to be safe and effective in reducing hyperglycemia and hypoglycemia but are not universally available, accessible, or affordable. Therefore, user-driven open-source AID systems are becoming increasingly popular. ObjectiveThis study aims to investigate the motivations for which people with diabetes (types 1, 2, and other) or their caregivers decide to build and use a personalized open-source AID. MethodsA cross-sectional web-based survey was conducted to assess personal motivations and associated self-reported clinical outcomes. ResultsOf 897 participants from 35 countries, 80.5% (722) were adults with diabetes and 19.5% (175) were caregivers of children with diabetes. Primary motivations to commence open-source AID included improving glycemic outcomes (476/509 adults, 93.5%, and 95/100 caregivers, 95%), reducing acute (443/508 adults, 87.2%, and 96/100 caregivers, 96%) and long-term (421/505 adults, 83.3%, and 91/100 caregivers, 91%) complication risk, interacting less frequently with diabetes technology (413/509 adults, 81.1%; 86/100 caregivers, 86%), improving their or child’s sleep quality (364/508 adults, 71.6%, and 80/100 caregivers, 80%), increasing their or child’s life expectancy (381/507 adults, 75.1%, and 84/100 caregivers, 84%), lack of commercially available AID systems (359/507 adults, 70.8%, and 79/99 caregivers, 80%), and unachieved therapy goals with available therapy options (348/509 adults, 68.4%, and 69/100 caregivers, 69%). Improving their own sleep quality was an almost universal motivator for caregivers (94/100, 94%). Significant improvements, independent of age and gender, were observed in self-reported glycated hemoglobin (HbA1c), 7.14% (SD 1.13%; 54.5 mmol/mol, SD 12.4) to 6.24% (SD 0.64%; 44.7 mmol/mol, SD 7.0; P

BackgroundMost commercial activity trackers are developed as consumer devices and not as clinical devices. The aim is to monitor and motivate sport activities, healthy living, and similar wellness purposes, and the devices are not designed to support care management in a clinical context. There are great expectations for using wearable sensor devices in health care settings, and the separate realms of wellness tracking and disease self-monitoring are increasingly becoming blurred. However, patients’ experiences with activity tracking technologies designed for use outside the clinical context have received little academic attention. ObjectiveThis study aimed to contribute to understanding how patients with a chronic disease experience activity data from consumer self-tracking devices related to self-care and their chronic illness. Our research question was: “How do patients with heart disease experience activity data in relation to self-care and chronic illness?” MethodsWe conducted a qualitative interview study with patients with chronic heart disease (n=27) who had an implanted cardioverter-defibrillator. Patients were invited to wear a FitBit Alta HR wearable activity tracker for 3-12 months and provide their perspectives on their experiences with step, sleep, and heart rate data. The average age was 57.2 years (25 men and 2 women), and patients used the tracker for 4-49 weeks (mean 26.1 weeks). Semistructured interviews (n=66) were conducted with patients 2–3 times and were analyzed iteratively in workshops using thematic analysis and abductive reasoning logic. ResultsOf the 27 patients, 18 related the heart rate, sleep, and step count data directly to their heart disease. Wearable activity trackers actualized patients’ experiences across 3 dimensions with a spectrum of contrasting experiences: (1) knowing, which spanned gaining insight and evoking doubts; (2) feeling, which spanned being reassured and becoming anxious; and (3) evaluating, which spanned promoting improvements and exposing failure. ConclusionsPatients’ experiences could reside more on one end of the spectrum, could reside across all 3 dimensions, or could combine contrasting positions and even move across the spectrum over time. Activity data from wearable devices may be a resource for self-care; however, the data may simultaneously constrain and create uncertainty, fear, and anxiety. By showing how patients experience self-tracking data across dimensions of knowing, feeling, and evaluating, we point toward the richness and complexity of these data experiences in the context of chronic illness and self-care.

In both popular and academic discussions of the use of algorithms in clinical practice, narratives often draw on the decisive potentialities of algorithms and come with the belief that algorithms will substantially transform healthcare. We suggest that this approach is associated with a logic of disruption. However, we argue that in clinical practice alongside this logic, another and less recognised logic exists, namely that of continuation : here the use of algorithms constitutes part of an established practice. Applying these logics as our analytical framing, we set out to explore how algorithms for clinical decision-making are enacted by political stakeholders, healthcare professionals, and patients, and in doing so, study how the legitimacy of delegating to an algorithm is negotiated and obtained. Empirically we draw on ethnographic fieldwork carried out in relation to attempts in Denmark to develop and implement Patient Reported Outcomes (PRO) tools – involving algorithmic sorting – in clinical practice. We follow the work within two disease areas: heart rehabilitation and breast cancer follow-up care. We show how at the political level, algorithms constitute tools for disrupting inefficient work and unsystematic patient involvement, whereas closer to the clinical practice, algorithms constitute a continuation of standardised and evidence-based diagnostic procedures and a continuation of the physicians' expertise and authority. We argue that the co-existence of the two logics have implications as both provide a push towards the use of algorithms and how a logic of continuation may divert attention away from new issues introduced with automated digital decision-support systems. [ABSTRACT FROM AUTHOR]

Aims: An emerging group of people with type 1 diabetes are not waiting for commercial solutions, choosing to manage their condition with open‐source artificial pancreas systems (APS). Our aim was to explore their perspectives on the future of APS. Methods: Semi‐structured telephone interviews were conducted (in Australia, October 2018 to January 2019) with 23 adults with type 1 diabetes currently using open‐source APS. Interviews were recorded, transcribed and analysed thematically. Results: Participants described five key features of open‐source APS they value: compatibility, user‐led design, customisability, ability to evolve faster and community‐driven. They attributed the success of the open‐source APS movement to benefits they derive from these features: choice, solutions that meet their needs, ownership, staying one step ahead and real‐time support. They expressed hope that future commercial products and healthcare would benefit from their learnings and from collaboration with the open‐source APS community. Conclusions: Participants believed that there will always be a place for the open‐source community. It will continue to build on and advance commercial products, respond to user needs, offering a higher degree of control and customisation than afforded by commercial products and generating optimism for the future. Participants desired that future commercial diabetes technologies would be inspired by the open‐source community and developed collaboratively with people with diabetes. [ABSTRACT FROM AUTHOR]

Patient-reported outcome data have moved from the realm of research to center stage in efforts to provide patient-centered care. In a Danish context, health authorities are seeking to promote and standardize the use of patient-reported outcome data. This involves normative articulations of what counts as meaningful data work in a healthcare system characterized by intensified data-sourcing. Based on ethnographic material, I suggest that an assemblage of actors, both human and technological, has accomplished the articulation of meaningful data work, with patient-reported outcome as being dependent on the active application of data in clinical trajectories--in contrast to supplying data "passively" for secondary use for research or governance. This normative articulation of "Active patient-reported outcome" legitimizes the Danish patient-reported outcome assemblage by showing alignment of the concerns of patients, clinicians and health authorities. At the same time, "Active patient-reported outcome" foreshadows challenges in making data work meaningful in local practice. [ABSTRACT FROM AUTHOR]