"Trying to Find People to Fit the Tech…”: A Qualitative Exploration of the Lessons Learnt Introducing Artificial Intelligence-Based Technology into English Social Care

Digital technology is expected to improve care and address significant service pressures within the National Health Service and social care though evidence on how their implementation might be optimised is lacking. This study explores how one such example, home-based sensors with artificial intelligence capabilities, was implemented in English social care to identify changes in behaviour that indicate the onset of potentially more serious issues. Its focus was staff perspectives on decision-making processes and implementation, to inform recommendations for others exploring the potential of new and emerging technology. Qualitative data were collected from 18 semistructured interviews conducted across three sites delivering social care, with senior decision makers, operational leads, and care staff. We identified several issues with the selection process and implementation of AI-based technology in social care, including a lack of consensus around what success would look like, problems identifying and evaluating alternatives, and technical challenges to implementation, as well as obstacles to developing a longer-term, more preventative approach in a system experienced as focused on responding to acute needs. Ultimately, the research confirmed a number of recognised implementation challenges associated with training, resource, and acceptability to staff and patients. It added particular insights around the anxieties experienced by frontline staff and the cultural shift required of preventative interventions in a system geared to meeting acute crises. That many barriers are familiar suggests a particular need to focus on helping policymakers/local leaders avoid similar pitfalls in the future.

Undertaking rapid evaluations during the COVID-19 pandemic: Lessons from evaluating COVID-19 remote home monitoring services in England

Introduction Rapid evaluations can offer evidence on innovations in health and social care that can be used to inform fast-moving policy and practise, and support their scale-up according to previous research. However, there are few comprehensive accounts of how to plan and conduct large-scale rapid evaluations, ensure scientific rigour, and achieve stakeholder engagement within compressed timeframes. Methods Using a case study of a national mixed-methods rapid evaluation of COVID-19 remote home monitoring services in England, conducted during the COVID-19 pandemic, this manuscript examines the process of conducting a large-scale rapid evaluation from design to dissemination and impact, and reflects on the key lessons for conducting future large-scale rapid evaluations. In this manuscript, we describe each stage of the rapid evaluation: convening the team (study team and external collaborators), design and planning (scoping, designing protocols, study set up), data collection and analysis, and dissemination. Results We reflect on why certain decisions were made and highlight facilitators and challenges. The manuscript concludes with 12 key lessons for conducting large-scale mixed-methods rapid evaluations of healthcare services. We propose that rapid study teams need to: (1) find ways of quickly building trust with external stakeholders, including evidence-users;(2) consider the needs of the rapid evaluation and resources needed;(3) use scoping to ensure the study is highly focused;(4) carefully consider what cannot be completed within a designated timeframe;(5) use structured processes to ensure consistency and rigour;(6) be flexible and responsive to changing needs and circumstances;(7) consider the risks associated with new data collection approaches of quantitative data (and their usability);(8) consider whether it is possible to use aggregated quantitative data, and what that would mean when presenting results, (9) consider using structured processes & layered analysis approaches to rapidly synthesise qualitative findings, (10) consider the balance between speed and the size and skills of the team, (11) ensure all team members know roles and responsibilities and can communicate quickly and clearly;and (12) consider how best to share findings, in discussion with evidence-users, for rapid understanding and use. Conclusion These 12 lessons can be used to inform the development and conduct of future rapid evaluations in a range of contexts and settings.

Undertaking rapid evaluations during the COVID-19 pandemic: Lessons from evaluating COVID-19 remote home monitoring services in England.

Introduction: Rapid evaluations can offer evidence on innovations in health and social care that can be used to inform fast-moving policy and practise, and support their scale-up according to previous research. However, there are few comprehensive accounts of how to plan and conduct large-scale rapid evaluations, ensure scientific rigour, and achieve stakeholder engagement within compressed timeframes. Methods: Using a case study of a national mixed-methods rapid evaluation of COVID-19 remote home monitoring services in England, conducted during the COVID-19 pandemic, this manuscript examines the process of conducting a large-scale rapid evaluation from design to dissemination and impact, and reflects on the key lessons for conducting future large-scale rapid evaluations. In this manuscript, we describe each stage of the rapid evaluation: convening the team (study team and external collaborators), design and planning (scoping, designing protocols, study set up), data collection and analysis, and dissemination. Results: We reflect on why certain decisions were made and highlight facilitators and challenges. The manuscript concludes with 12 key lessons for conducting large-scale mixed-methods rapid evaluations of healthcare services. We propose that rapid study teams need to: (1) find ways of quickly building trust with external stakeholders, including evidence-users; (2) consider the needs of the rapid evaluation and resources needed; (3) use scoping to ensure the study is highly focused; (4) carefully consider what cannot be completed within a designated timeframe; (5) use structured processes to ensure consistency and rigour; (6) be flexible and responsive to changing needs and circumstances; (7) consider the risks associated with new data collection approaches of quantitative data (and their usability); (8) consider whether it is possible to use aggregated quantitative data, and what that would mean when presenting results, (9) consider using structured processes & layered analysis approaches to rapidly synthesise qualitative findings, (10) consider the balance between speed and the size and skills of the team, (11) ensure all team members know roles and responsibilities and can communicate quickly and clearly; and (12) consider how best to share findings, in discussion with evidence-users, for rapid understanding and use. Conclusion: These 12 lessons can be used to inform the development and conduct of future rapid evaluations in a range of contexts and settings.

Understanding the invisible workforce: lessons for general practice from a survey of receptionists.

INTRODUCTION: The significance of the role of receptionists during the recent shift to remote triage has been widely recognised and they will have a significant role to play in UK general practice as it continues to cope with a huge increase in demand exacerbated by the COVID-19 pandemic. To maximise their contribution, it is important the social and occupational characteristics of the modern receptionist are understood, alongside their attitudes towards the role and their perceptions of the support and training they receive . METHODS: We used convenience and cross-sectional sampling to survey the demographic characteristics of receptionists and various aspects of their role and responsibilities. This included the training received, specific tasks performed, job satisfaction, the importance of the role, and their interaction with clinical and non-clinical colleagues. We also captured data on the characteristics of their practice including the number of GPs and location. RESULTS: A total of 70 participants completed the survey (16 postal and 54 online responses) of whom the majority were white (97.2%), female (98.6%), and aged 40 and over (56.7%). The majority of the training focussed on customer service (72.9%), telephone (64.3%), and medical administration skills (58.6%). Just over a quarter had received training in basic triage (25.7%). A standard multiple regression model revealed that the strongest predictor of satisfaction was support from practice GPs (ß = .65, p <.001) there were also significant positive correlations between satisfaction and appreciation from GPs, r(68) = .609, p < .001. CONCLUSION: This study has provided a much-needed update on the demographics, duties, and job satisfaction of GP receptionists. The need for diversification of the workforce to reflect the range of primary care patients warrants consideration in light of continuing variation in access along lines of gender andethnicity. Training continues to focus on administrative duties not on the clinically relevant aspects of their role such as triage.

Patients' experiences of, and engagement with, remote home monitoring services for COVID-19 patients: A rapid mixed-methods study.

INTRODUCTION: Remote home monitoring models were implemented during the COVID-19 pandemic to shorten hospital length of stay, reduce unnecessary hospital admission, readmission and infection and appropriately escalate care. Within these models, patients are asked to take and record readings and escalate care if advised. There is limited evidence on how patients and carers experience these services. This study aimed to evaluate patient experiences of, and engagement with, remote home monitoring models for COVID-19. METHODS: A rapid mixed-methods study was carried out in England (conducted from March to June 2021). We remotely conducted a cross-sectional survey and semi-structured interviews with patients and carers. Interview findings were summarized using rapid assessment procedures sheets and data were grouped into themes (using thematic analysis). Survey data were analysed using descriptive statistics. RESULTS: We received 1069 surveys (18% response rate) and conducted interviews with patients (n = 59) or their carers (n = 3). 'Care' relied on support from staff members and family/friends. Patients and carers reported positive experiences and felt that the service and human contact reassured them and was easy to engage with. Yet, some patients and carers identified problems with engagement (e.g., hesitancy to self-escalate care). Engagement was influenced by patient factors such as health and knowledge, support from family/friends and staff, availability and ease of use of informational and material resources (e.g., equipment) and service factors. CONCLUSION: Remote home monitoring models place responsibility on patients to self-manage symptoms in partnership with staff; yet, many patients required support and preferred human contact (especially for identifying problems). Caring burden and experiences of those living alone and barriers to engagement should be considered when designing and implementing remote home monitoring services. PATIENT OR PUBLIC CONTRIBUTION: The study team met with service users and public members of the evaluation teams throughout the project in a series of workshops. Workshops informed study design, data collection tools and data interpretation and were conducted to also discuss study dissemination. Public patient involvement (PPI) members helped to pilot patient surveys and interview guides with the research team. Some members of the public also piloted the patient survey. Members of the PPI group were given the opportunity to comment on the manuscript, and the manuscript was amended accordingly.

EarLy Surveillance for Autoimmune diabetes: protocol for a qualitative study of general population and stakeholder perspectives on screening for type 1 diabetes in the UK (ELSA 1).

OBJECTIVE: Type 1 diabetes (T1D) is the most common form of diabetes in children, accounting for 96% of cases, with 29 000 children affected in the UK. Studies have recently identified immunotherapies that safely delay the development of T1D for at least 3 years, and further therapies are in development. General population screening programs in other countries can now accurately identify children with presymptomatic T1D who can be entered into prevention studies. The UK does not have such a system in place. We aim to explore whether parents and children in the UK would want to be part of such a program of testing for T1D in the general population, how they would want to be informed and participate in such a program, and how any barriers to recruitment and participation can be addressed. Additionally, the views of stakeholders who would be involved in the testing program will be collected and analyzed. RESEARCH DESIGN AND METHODS: We will interview parents/guardians and children aged 3-13 years about their views on screening for T1D. We will recruit purposefully to ensure representation across ethnicities and socioeconomic groups. Interviews will be transcribed, analyzed and used to inform iterative co-design work with additional families to address any issues raised. Similar qualitative work will be undertaken with professional stakeholders who would be involved in implementing any future screening program. Where possible, all aspects of this study will be performed remotely by phone or online to minimize infection risk. CONCLUSIONS: This qualitative study will provide the first insights into acceptability of testing and monitoring for T1D in the general population from the perspective of families and stakeholders in the UK. Co-design work will help establish the barriers and identify strategies to mitigate and overcome these issues, as an important step towards consideration of national testing for T1D.

Automated conflict resolution for patients with multiple morbidity being treated using more than one set of single condition clinical guidance: A case study.

BACKGROUND: The number of people in the UK with two or more conditions continues to grow and their clinical management is complicated by the reliance on guidance focused on a single condition. This leaves individual clinicians responsible for collating disparate information from patient management systems and care recommendations to manually manage the contradictions that exist in the simultaneous treatment of various conditions. METHODS/DESIGN: We have devised a modelling language based on BPMN that allows us to create computer interpretable representations of single condition guidance and incorporate patient data to detect the points of conflict between multiple conditions based on their transformation to logical constraints. This has been used to develop a prototype clinical decision support tool that we can use to highlight the causes of conflict between them in three main areas: medication, lifestyle and well-being, and appointment bookings. RESULTS: The prototype tool was used to discern contradictions in the care recommendations of chronic obstructive pulmonary disease and osteoarthritis. These were presented to a panel of clinicians who confirmed that the tool produced clinically relevant alerts that can advise clinicians of the presence of conflicts between guidelines relating to both clashes in medication or lifestyle advice. CONCLUSIONS: The need for supporting general practitioners in their treatment of patients remains and this proof of concept has demonstrated that by converting this guidance into computer-interpretable pathways we can use constraint solvers to readily identify clinically relevant points of conflict between critical elements of the pathway.

The impact of remote home monitoring of people with COVID-19 using pulse oximetry: A national population and observational study.

BACKGROUND: Remote home monitoring of people testing positive for COVID-19 using pulse oximetry was implemented across England during the Winter of 2020/21 to identify falling blood oxygen saturation levels at an early stage. This was hypothesised to enable earlier hospital admission, reduce the need for intensive care and improve survival. This study is an evaluation of the clinical effectiveness of the pre-hospital monitoring programme, COVID oximetry @home (CO@h). METHODS: The setting was all Clinical Commissioning Group (CCG) areas in England where there were complete data on the number of people enrolled onto the programme between 2nd November 2020 and 21st February 2021. We analysed relationships at a geographical area level between the extent to which people aged 65 or over were enrolled onto the programme and outcomes over the period between November 2020 to February 2021. FINDINGS: For every 10% increase in coverage of the programme, mortality was reduced by 2% (95% confidence interval:4% reduction to 1% increase), admissions increased by 3% (-1% to 7%), in-hospital mortality fell by 3% (-8% to 3%) and lengths of stay increased by 1·8% (-1·2% to 4·9%). None of these results are statistically significant, although the confidence interval indicates that any adverse effect on mortality would be small, but a mortality reduction of up to 4% may have resulted from the programme. INTERPRETATION: There are several possible explanations for our findings. One is that CO@h did not have the hypothesised impact. Another is that the low rates of enrolment and incomplete data in many areas reduced the chances of detecting any impact that may have existed. Also, CO@h has been implemented in many different ways across the country and these may have had varying levels of effect. FUNDING: This is independent research funded by the National Institute for Health Research, Health Services & Delivery Research programme (RSET Project no. 16/138/17; BRACE Project no. 16/138/31) and NHSEI. NJF is an NIHR Senior Investigator.

Impact of COVID-19 on the digital divide: a rapid review.

OBJECTIVE: The increased reliance on digital technologies to deliver healthcare as a result of the COVID-19 pandemic has meant pre-existing disparities in digital access and utilisation of healthcare might be exacerbated in disadvantaged patient populations. The aim of this rapid review was to identify how this 'digital divide' was manifest during the first wave of the pandemic and highlight any areas which might be usefully addressed for the remainder of the pandemic and beyond. DESIGN: Rapid review and narrative synthesis. DATA SOURCES: The major medical databases including PubMed and Embase and Google Scholar were searched alongside a hand search of bibliographies. ELIGIBILITY CRITERIA: Original research papers available in English which described studies conducted during wave 1 of the COVID pandemic and reported between 1 March 2020 and 31 July 2021. RESULTS: The search was described using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses and identified nine studies. The results are presented within a refined framework describing the three key domains of the digital divide: (1) digital access, within which one study described continuing issues with internet connectivity among vulnerable patients in the UK; (2) digital literacy, where seven studies described how ethnic minorities and the elderly were less likely to use digital technologies in accessing care; (3) digital assimilation, where one study described how video technologies can reduce feelings of isolation and another how elderly black males were the most likely group to share information about COVID-19 on social media platforms. CONCLUSIONS: During the early phase of the pandemic in the developed world, familiar difficulties in utilisation of digital healthcare among the elderly and ethnic minorities continued to be observed. This is a further reminder that the digital divide is a persistent challenge that needs to be urgently addressed when considering the likelihood that in many instances these digital technologies are likely to remain at the centre of healthcare delivery.