The role of combinatorial health technologies in supporting older people with long-term conditions: Responsibilisation or co-management of healthcare?

Neoliberalism, austerity and health responsibilisation are increasingly informing policies and practices designed to encourage older patients to take responsibility for the management of their own healthcare. Combined with an ageing population, novel ways to address the increasing healthcare needs of older people have become a priority, with the emergence in recent years of new models of integrated care enhanced by combinatorial health technologies (CHTs). This paper presents qualitative findings from the evaluation of one programme, the Lancashire and Cumbria Innovation Alliance (LCIA) Test Bed, a programme funded by NHS England and conducted in England between 2016 and 2018. Drawing on data from patients, family carers, and staff members involved in the programme, this paper explores the extent to which CHTs, as part of the LCIA Test Bed programme, contributed to health responsibilisation amongst older people with complex health conditions. Through this programme, we find that relationships between patients, family carers and healthcare professionals combined to create a sense of reassurance and shared responsibility for all parties. Our findings suggest the need for a more nuanced approach to responsibilisation and self-management for older people living with complex health conditions. By focusing on co-management - and recognising the potential of CHTs to facilitate this approach - there is potential to increase patient confidence in managing their health condition, reduce carer burden, and enhance clinician satisfaction in their work roles. While neoliberal agendas are focused on self-management and self-responsibility of one's own health care, with technology as a facilitator of this, our findings suggest that the successful use of CHTs for older people with complex health conditions may instead be rooted in co-management. This paper argues that co-management may be a more successful model of care for patients, carers and clinicians.

Use of acoustic emission to identify novel candidate biomarkers for knee osteoarthritis (OA).

Our objective was to determine the efficacy and feasibility of a new approach for identifying candidate biomarkers for knee osteoarthritis (OA), based on selecting promising candidates from a range of high-frequency acoustic emission (AE) measurements generated during weight-bearing knee movement. Candidate AE biomarkers identified by this approach could then be validated in larger studies for use in future clinical trials and stratified medicine applications for this common health condition. A population cohort of participants with knee pain and a Kellgren-Lawrence (KL) score between 1-4 were recruited from local NHS primary and secondary care sites. Focusing on participants' self-identified worse knee, and using our established movement protocol, sources of variation in AE measurement and associations of AE markers with other markers were explored. Using this approach we identified 4 initial candidate AE biomarkers, of which "number of hits" showed the best reproducibility, in terms of within-session, day to day, week to week, between-practitioner, and between-machine variation, at 2 different machine upper frequency settings. "Number of hits" was higher in knees with KL scores of 2 than in KL1, and also showed significant associations with pain in the contralateral knee, and with body weight. "Hits" occurred predominantly in 2 of 4 defined movement quadrants. The protocol was feasible and acceptable to all participants and professionals involved. This study demonstrates how AE measurement during simple sit-stand-sit movements can be used to generate novel candidate knee OA biomarkers. AE measurements probably reflect a composite of structural changes and joint loading factors. Refinement of the method and increasing understanding of factors contributing to AE will enable this approach to be used to generate further candidate biomarkers for validation and potential use in clinical trials.

How effective and cost-effective are innovative combinatorial technologies and practices for supporting older people with long-term conditions to remain well in the community? An evaluation protocol for an NHS Test Bed in North West England.

INTRODUCTION: The Lancashire and Cumbria Innovation Alliance (LCIA) Test Bed is a partnership between the National Health Service in England, industry (led by Philips) and Lancaster University. Through the implementation of a combination of innovative health technologies and practices, it aims to determine the most effective and cost-effective ways of supporting frail older people with long-term conditions to remain well in the community. Among the Test Bed's objectives are to improve patient activation and the ability of older people to self-care at home, reduce healthcare system utilisation, and deliver increased workforce productivity. METHODS AND ANALYSIS: Patients aged 55 years and over are recruited to four cohorts defined by their risk of hospital admission, with long-term conditions including chronic obstructive pulmonary disease, dementia, diabetes and heart failure. The programme is determined on an individual basis, with a range of technologies available. The evaluation is adopting a two-phase approach: phase 1 includes a bespoke patient survey and a mass matched control analysis; and phase 2 is using observational interviews with patients, and weekly diaries, action learning meetings and focus groups with members of staff and other key stakeholders. Phase 1 data analysis consists of a statistical evaluation of the effectiveness of the programme. A health economic analysis of its costs and associated cost changes will be undertaken. Phase 2 data will be analysed thematically with the aid of Atlas.ti qualitative software. The evaluation is located within a logic model framework, to consider the processes, management and participation that may have implications for the Test Bed's success. ETHICS AND DISSEMINATION: The LCIA Test Bed evaluation has received ethical approval from the Health Research Authority and Lancaster University's Faculty of Health and Medicine Research Ethics Committee. A range of dissemination methods are adopted, including deliberative panels to validate findings and develop outcomes for policy and practice.

Timelines in the diagnostic evaluation of people with suspected amyotrophic lateral sclerosis (ALS)/motor neuron disease (MND)--a 20-year review: can we do better?

This paper examines diagnostic timelines for people suspected of having ALS/MND over a 20-year period, evaluates the impact of a 'fast track' diagnostic process and discusses typical causes of diagnostic delay. Key diagnostic timelines (dates of first symptom, diagnosis and death) were reviewed for people diagnosed between 1989 and 2008. Patients evaluated through a fast-track diagnostic process and those investigated through traditional neurology clinics were compared. Typical causes of diagnostic delay were investigated. Results showed that diagnostic timelines have been surprisingly consistent over this 20-year period. Time from first symptom to diagnosis hovered around 12 months, with the diagnosis typically being made around the midpoint (50% of total disease duration elapsed) of the disease pathway. The introduction of a fast-track process has not to date affected overall performance but has shortened times from referral to diagnosis. Diagnostic delays appear to be associated with clinical complexity and delays in referral, both within primary and secondary care services. In conclusion, more widespread implementation of fast-track processes could potentially reduce diagnostic delays. Educational interventions among health care professionals both in primary and secondary care may also help shorten diagnostic pathways.