The cost of diagnosis and early support in patients with cognitive decline.

OBJECTIVE: Recent research indicates considerable heterogeneity in the provision of memory assessment services (MAS). However, little is known on the extent of variation in the costs of the services MAS provide. We investigated the costs of supporting patients with suspected dementia, including assessment and support over the following 6 months. METHODS: Clinic costs were estimated on the basis of an organisational survey reporting staff roll, grade and activities. Costs of primary health and social care were estimated from questionnaire data reported by carers of patients at baseline, 3 and 6 months after referral. RESULTS: Mean monthly staff costs at MAS were £73 000. Imaging at assessment costs an additional £3500 per month. Monthly clinic cost per new patient assessed varied from £320 to £5400 across clinics. Additional primary health and social care costs of £130-220 a month between baseline and 6 months were reported by carers. Costs of pharmacological and non-pharmacological treatments reported by carers were small. Informal care costs dwarfed health and social care costs when valued at a modest unit cost. The overall mean cost of supporting a patient for 6 months varied from £1600 to £2500 dependent on assumptions regarding the proportion of MAS intervention and review costs accrued at 6 months. CONCLUSIONS: There is considerable variation in the intensity and associated costs of services provided by MAS. Further research should ascertain to what extent such variation is associated with differences in patient outcomes. Copyright © 2016 John Wiley & Sons, Ltd.

Technology integrated health management for dementia.

Pioneering advances have been made in Internet of Things technologies (IoT) in healthcare. This article describes the development and testing of a bespoke IoT system for dementia care. Technology integrated health management (TIHM) for dementia is part of the NHS England National Test Bed Programme and has involved trailing the deployment of network enabled devices combined with artificial intelligence to improve outcomes for people with dementia and their carers. TIHM uses machine learning and complex algorithms to detect and predict early signs of ill health. The premise is if changes in a person's health or routine can be identified early on, support can be targeted at the point of need to prevent the development of more serious complications.

Exploring barriers to participation and adoption of telehealth and telecare within the Whole System Demonstrator trial: a qualitative study.

BACKGROUND: Telehealth (TH) and telecare (TC) interventions are increasingly valued for supporting self-care in ageing populations; however, evaluation studies often report high rates of non-participation that are not well understood. This paper reports from a qualitative study nested within a large randomised controlled trial in the UK: the Whole System Demonstrator (WSD) project. It explores barriers to participation and adoption of TH and TC from the perspective of people who declined to participate or withdrew from the trial. METHODS: Qualitative semi-structured interviews were conducted with 22 people who declined to participate in the trial following explanations of the intervention (n = 19), or who withdrew from the intervention arm (n = 3). Participants were recruited from the four trial groups (with diabetes, chronic obstructive pulmonary disease, heart failure, or social care needs); and all came from the three trial areas (Cornwall, Kent, east London). Observations of home visits where the trial and interventions were first explained were also conducted by shadowing 8 members of health and social care staff visiting 23 people at home. Field notes were made of observational visits and explored alongside interview transcripts to elicit key themes. RESULTS: Barriers to adoption of TH and TC associated with non-participation and withdrawal from the trial were identified within the following themes: requirements for technical competence and operation of equipment; threats to identity, independence and self-care; expectations and experiences of disruption to services. Respondents held concerns that special skills were needed to operate equipment but these were often based on misunderstandings. Respondents' views were often explained in terms of potential threats to identity associated with positive ageing and self-reliance, and views that interventions could undermine self-care and coping. Finally, participants were reluctant to risk potentially disruptive changes to existing services that were often highly valued. CONCLUSIONS: These findings regarding perceptions of potential disruption of interventions to identity and services go beyond more common expectations that concerns about privacy and dislike of technology deter uptake. These insights have implications for health and social care staff indicating that more detailed information and time for discussion could be valuable especially on introduction. It seems especially important for potential recipients to have the opportunity to discuss their expectations and such views might usefully feed back into design and implementation.