COVID-19 testing in English care homes and implications for staff and residents.

INTRODUCTION: Care home residents are at high risk of dying from coronavirus disease 2019 (COVID-19). Regular testing, producing rapid and reliable results is important in this population because infections spread quickly, and presentations are often atypical or asymptomatic. This study evaluated current testing pathways in care homes to explore the role of point-of-care tests (POCTs). METHODS: A total of 10 staff from eight care homes, purposively sampled to reflect care organisational attributes that influence outbreak severity, underwent a semi-structured remote videoconference interview. Transcripts were analysed using process mapping tools and framework analysis focussing on perceptions about, gaps within and needs arising from current pathways. RESULTS: Four main steps were identified in testing: infection prevention, preparatory steps, swabbing procedure and management of residents. Infection prevention was particularly challenging for mobile residents with cognitive impairment. Swabbing and preparatory steps were resource-intensive, requiring additional staff resource. Swabbing required flexibility and staff who were familiar to the resident. Frequent approaches to residents were needed to ensure they would participate at a suitable time. After-test management varied between sites. Several homes reported deviating from government guidance to take more cautious approaches, which they perceived to be more robust. CONCLUSION: Swab-based testing is organisationally complex and resource-intensive in care homes. It needs to be flexible to meet the needs of residents and provide care homes with rapid information to support care decisions. POCT could help address gaps but the complexity of the setting means that each technology must be evaluated in context before widespread adoption in care homes.

Attitudes towards Trusting Artificial Intelligence Insights and Factors to Prevent the Passive Adherence of GPs: A Pilot Study.

Artificial Intelligence (AI) systems could improve system efficiency by supporting clinicians in making appropriate referrals. However, they are imperfect by nature and misdiagnoses, if not correctly identified, can have consequences for patient care. In this paper, findings from an online survey are presented to understand the aptitude of GPs (n = 50) in appropriately trusting or not trusting the output of a fictitious AI-based decision support tool when assessing skin lesions, and to identify which individual characteristics could make GPs less prone to adhere to erroneous diagnostics results. The findings suggest that, when the AI was correct, the GPs' ability to correctly diagnose a skin lesion significantly improved after receiving correct AI information, from 73.6% to 86.8% (X2 (1, N = 50) = 21.787, p < 0.001), with significant effects for both the benign (X2 (1, N = 50) = 21, p < 0.001) and malignant cases (X2 (1, N = 50) = 4.654, p = 0.031). However, when the AI provided erroneous information, only 10% of the GPs were able to correctly disagree with the indication of the AI in terms of diagnosis (d-AIW M: 0.12, SD: 0.37), and only 14% of participants were able to correctly decide the management plan despite the AI insights (d-AIW M:0.12, SD: 0.32). The analysis of the difference between groups in terms of individual characteristics suggested that GPs with domain knowledge in dermatology were better at rejecting the wrong insights from AI.

Is the LITE version of the usability metric for user experience (UMUX-LITE) a reliable tool to support rapid assessment of new healthcare technology?

OBJECTIVE: To ascertain the reliability of a standardised, short-scale measure of satisfaction in the use of new healthcare technology i.e., the LITE version of the usability metric for user experience (UMUX-LITE). Whilst previous studies have demonstrated the reliability of UMUX-LITE, and its relationship with measures of likelihood to recommend a product, such as the Net Promoter Score (NPS) in other sectors no such testing has been undertaken with healthcare technology. MATERIALS AND METHODS: Six point-of-care products at different stages of development were assessed by 120 healthcare professionals. UMUX-LITE was used to gather their satisfaction in use, and NPS to declare their intention to promote the product. Inferential statistics were used to: i) ascertain the reliability of UMUX-LITE, and ii) assess the relationship between UMUX-LITE and NPS at different stages of products development. RESULTS: UMUX-LITE showed an acceptable reliability (α = 0.7) and a strong positive correlation with NPS (r = 0.455, p < .001). This is similar to findings in other fields of application. The level of product development did not affect the UMUX-LITE scores, while the stage of development was a significant predictor (R2 = 0.49) of the intention to promote. DISCUSSION AND CONCLUSION: Practitioners may apply UMUX-LITE alone, or in combination with the NPS, to complement interview and 'homemade' scales to investigate the quality of new products at different stages of development. This shortened scale is appropriate for use in the context of healthcare in which busy professionals have a minimal amount of time to support innovation.

The Lean and Agile Multi-dimensional Process (LAMP) - a new framework for rapid and iterative evidence generation to support health-care technology design and development.

Introduction: Health technology assessments (HTA) are tools for policymaking and resource allocation. Early HTAs are increasingly used in design and development of new technologies. Conducting early HTAs is challenging, due to a lack of evidence and significant uncertainties in the technology and the market. A multi-disciplinary approach is considered essential. However, an operational framework that can enable the integration of multi-dimensional evidence into commercialization remains lacking.Areas covered: We developed the Lean and Agile Multi-dimensional Process (LAMP), an early HTA framework, for embedding commercial decision-making in structured evidence generation activities, divided into phases. Diverse evidence in unmet needs, user acceptance, cost-effectiveness, and market competitiveness are being generated in increasing depth. This supports the emergence of design and value propositions that align technology capabilities and clinical and user needs.Expert opinion: We have been applying LAMP to working with medical device and diagnostic industry in the UK. The framework can be adapted to suit different technologies, decision needs, time scales, and resources. LAMP offers a practical solution to the multi-disciplinary approach. Methodologists drive the process by performing evidence generation and synthesis as and by enabling interactions between manufacturers, designers, clinicians, and other key stakeholders.

Designing medical technology for resilience: integrating health economics and human factors approaches.

INTRODUCTION: The slow adoption of innovation into healthcare calls into question the manner of evidence generation for medical technology. This paper identifies potential reasons for this including a lack of attention to human factors, poor evaluation of economic benefits, lack of understanding of the existing healthcare system and a failure to recognise the need to generate resilient products. Areas covered: Recognising a cross-disciplinary need to enhance evidence generation early in a technology's life cycle, the present paper proposes a new approach that integrates human factors and health economic evaluation as part of a wider systems approach to the design of technology. This approach (Human and Economic Resilience Design for Medical Technology or HERD MedTech) supports early stages of product development and is based on the recent experiences of the National Institute for Health Research London Diagnostic Evidence Co-operative in the UK. Expert commentary: HERD MedTech i) proposes a shift from design for usability to design for resilience, ii) aspires to reduce the need for service adaptation to technological constraints iii) ensures value of innovation at the time of product development, and iv) aims to stimulate discussion around the integration of pre- and post-market methods of assessment of medical technology.