A lifetime economic model of mortality and secondary care use for patients discharged from hospital following acute stroke.

BACKGROUND: The long-term health-economic consequences of acute stroke are typically extrapolated from short-term outcomes observed in different studies, using models based on assumptions about longer-term morbidity and mortality. Inconsistency in these assumptions and the methods of extrapolation can create difficulties when comparing estimates of life-time cost-effectiveness of stroke care interventions. AIMS: To develop a long-term model consisting of a set of equations to estimate the life-time effects of stroke care interventions to promote consistency in extrapolation of short-term outcomes. METHODS: Data about further admissions and mortality was provided for acute stroke patients discharged between 2013 and 2014 from a large English service. This was combined with data from UK life tables to create a set of parametric equations in a model that use age, sex, and modified Rankin Scores to predict the life-time risk of mortality and secondary care resource utilisation including ED attendances, non-elective admissions, and elective admissions. A cohort of 1,509 (male 51%; mean age 74) stroke patients had median follow-up of seven years and represented 7,111 post-discharge patient years. A logistic model estimated mortality within twelve months of discharge and a Gompertz model was used over the remainder of the lifetime. Hospital attendances were modelled using a Weibull distribution. Non-elective and elective bed days were both modelled using a log-logistic distribution. RESULTS: Mortality risk increased with age, dependency, and male sex. Although the overall pattern was similar for resource utilisation, there were different variations according to dependency and gender for ED attendances and non-elective/elective admissions. For example, 65-year-old women with a discharge mRS of 1 would gain an extra 6.75 life years compared to 65-year-old women with a discharge mRS of 3. Over their lifetime, 65-year-old women with a discharge mRS of 1 would experience 0.09 less ED attendances, 2.12 less non-elective bed days and 1.28 additional elective bed days than 65-year-old women with a discharge mRS of 3. CONCLUSIONS: Using long-term follow-up publicly available data from a large clinical cohort, this new model promotes standardised extrapolation of key outcomes over the life course, and potentially can improve the real-world accuracy and comparison of long-term cost-effectiveness estimates for stroke care interventions. DATA ASSESS STATEMENT: Data is available upon reasonable request from third parties.

Better understanding fall risk: AI-based computer vision for contextual gait assessment.

Contemporary research to better understand free-living fall risk assessment in Parkinson's disease (PD) often relies on the use of wearable inertial-based measurement units (IMUs) to quantify useful temporal and spatial gait characteristics (e.g., step time, step length). Although use of IMUs is useful to understand some intrinsic PD fall-risk factors, their use alone is limited as they do not provide information on extrinsic factors (e.g., obstacles). Here, we update on the use of ergonomic wearable video-based eye-tracking glasses coupled with AI-based computer vision methodologies to provide information efficiently and ethically in free-living home-based environments to better understand IMU-based data in a small group of people with PD. The use of video and AI within PD research can be seen as an evolutionary step to improve methods to understand fall risk more comprehensively.

Longitudinal health-related quality of life in people with thoracic aortic aneurysms.

BACKGROUND: Surgical intervention for thoracic aortic aneurysms is high risk. Understanding changes in health-related quality of life before and after endovascular stent grafting and open surgical repair can aid treatment decision-making. METHODS: The Effective Treatments for Thoracic Aortic Aneurysms ('ETTAA') study (ISRCTN04044627) was a longitudinal, observational study. Adults with new/existing arch or descending thoracic aortic aneurysms greater than or equal to 4 cm in diameter were followed from 2014 to 2022. Five domains of health-related quality of life (Mobility, Self-Care, Usual Activities, Pain/Discomfort, and Anxiety/Depression) were recorded using the EuroQoL, five dimensions, five levels ('EQ-5D-5L') questionnaire and analysed using a range of longitudinal mixed models. RESULTS: Of 886 thoracic aortic aneurysm participants, 824 completed at least 2 questionnaires. Patients had slightly worse health-related quality of life than age-matched norms. Without surgery, deterioration occurred over time in Mobility (0.072/year (95% c.i. 0.042 to 0.101), P < 0.001) and Self-Care (0.039/year (95% c.i. 0.018 to 0.061), P < 0.001) in both sexes and Pain/Discomfort in women (0.069/year (95% c.i. 0.020 to 0.118), P = 0.005). For 6 weeks after endovascular stent grafting, there was a significant impairment in Self-Care (0.214 (95% c.i. 0.112 to 0.316), P < 0.001) and (for women only) in Usual Activities (0.625 (95% c.i. 0.338 to 0.911), P < 0.001), which then returned to pre-endovascular stent grafting levels. Six weeks after open surgical repair, the impairment in health-related quality of life was greater (Mobility 0.492 (95% c.i. 0.314 to 0.669), Self-Care 0.474 (95% c.i. 0.364 to 0.583), Usual Activities 1.469 (95% c.i. 1.042 to 1.896), and Pain/Discomfort 0.561 (95% c.i. 0.363 to 0.760), all P < 0.001) and took longer to return to pre-open surgical repair levels, partly due to increased complications and longer hospitalization. Anxiety/Depression decreased after open surgical repair (-0.214 (95% c.i. -0.326 to -0.101), P < 0.001). Age, sex, frailty, smoking, New York Heart Association class, and chronic obstructive pulmonary disease were significantly associated with health-related quality of life. CONCLUSION: Without intervention, health-related quality of life declines as age increases. Changes in health-related quality of life should contribute to surgical treatment decision-making.

Assessment of Visual Attention in Teams with or without Dedicated Team Leaders: A Neonatal Simulation-Based Pilot Randomised Cross-Over Trial Utilising Low-Cost Eye-Tracking Technology.

BACKGROUND: Eye-tracking technology could be used to study human factors during teamwork. OBJECTIVES: This work aimed to compare the visual attention (VA) of a team member acting as both a team leader and managing the airway, compared to a team member performing the focused task of managing the airway in the presence of a dedicated team leader. This work also aimed to report differences in team performance, behavioural skills, and workload between the two groups using validated tools. METHODS: We conducted a simulation-based, pilot randomised controlled study. The participants included were volunteer paediatric trainees, nurse practitioners, and neonatal nurses. Three teams consisting of four team members were formed. Each team participated in two identical neonatal resuscitation simulation scenarios in a random order, once with and once without a team leader. Using a commercially available eye-tracking device, we analysed VA regarding attention to (1) a manikin, (2) a colleague, and (3) a monitor. Only the trainee who was the airway operator would wear eye-tracking glasses in both simulations. RESULTS: In total, 6 simulation scenarios and 24 individual role allocations were analysed. Participants in a no-team-leader capacity had a greater number of total fixations on manikin and monitors, though this was not significant. There were no significant differences in team performance, behavioural skills, and individual workload. Physical demand was reported as significantly higher by participants in the group without a team leader. During debriefing, all the teams expressed their preference for having a dedicated team leader. CONCLUSION: In our pilot study using low-cost technology, we could not demonstrate the difference in VA with the presence of a team leader.

Using Video Technology and AI within Parkinson's Disease Free-Living Fall Risk Assessment.

Falls are a major concern for people with Parkinson's disease (PwPD), but accurately assessing real-world fall risk beyond the clinic is challenging. Contemporary technologies could enable the capture of objective and high-resolution data to better inform fall risk through measurement of everyday factors (e.g., obstacles) that contribute to falls. Wearable inertial measurement units (IMUs) capture objective high-resolution walking/gait data in all environments but are limited by not providing absolute clarity on contextual information (i.e., obstacles) that could greatly influence how gait is interpreted. Video-based data could compliment IMU-based data for a comprehensive free-living fall risk assessment. The objective of this study was twofold. First, pilot work was conducted to propose a novel artificial intelligence (AI) algorithm for use with wearable video-based eye-tracking glasses to compliment IMU gait data in order to better inform free-living fall risk in PwPD. The suggested approach (based on a fine-tuned You Only Look Once version 8 (YOLOv8) object detection algorithm) can accurately detect and contextualize objects (mAP50 = 0.81) in the environment while also providing insights into where the PwPD is looking, which could better inform fall risk. Second, we investigated the perceptions of PwPD via a focus group discussion regarding the adoption of video technologies and AI during their everyday lives to better inform their own fall risk. This second aspect of the study is important as, traditionally, there may be clinical and patient apprehension due to ethical and privacy concerns on the use of wearable cameras to capture real-world video. Thematic content analysis was used to analyse transcripts and develop core themes and categories. Here, PwPD agreed on ergonomically designed wearable video-based glasses as an optimal mode of video data capture, ensuring discreteness and negating any public stigma on the use of research-style equipment. PwPD also emphasized the need for control in AI-assisted data processing to uphold privacy, which could overcome concerns with the adoption of video to better inform IMU-based gait and free-living fall risk. Contemporary technologies (wearable video glasses and AI) can provide a holistic approach to fall risk that PwPD recognise as helpful and safe to use.

Stroke survivor views on ambulance redirection as a strategy to increase access to thrombectomy in England.

Introduction: Intravenous thrombolysis and mechanical thrombectomy are effective time-sensitive treatments for selected cases of acute ischaemic stroke. While thrombolysis is widely available, thrombectomy can only be provided at facilities with the necessary equipment and interventionists. Suitable patients admitted to other hospitals require secondary transfer, causing delays to treatment. Pre-hospital ambulance redirection to thrombectomy facilities may improve access but treatment eligibility cannot be confirmed pre-hospital. Some redirected patients would travel further and be displaced without receiving thrombectomy. This study aimed to elicit stroke survivor and carer/relative views about the possible consequences of introducing a conceptual, idealised ambulance redirection pathway. Methods: Focus groups were undertaken using a topic guide describing four hypothetical ambulance redirection scenarios and their possible consequences: earlier treatment with thrombectomy; delayed diagnosis of non-stroke 'mimic' conditions; delayed thrombolysis treatment; and delayed diagnosis of haemorrhagic stroke. Meetings were audio recorded, transcribed verbatim and data analysed thematically using emergent coding. Results: Fifteen stroke survivors and carers/relatives participated in three focus groups. There was wide acceptance of possible low-risk consequences of ambulance redirection, including extended travel time, being further from home and experiencing longer hospital stays. Participants were more uncertain about higher-risk consequences, including delays in diagnosis/treatment for patients unsuitable for thrombectomy, but remained positive about ambulance redirection overall. Participants rationalised acceptance of higher-risk consequences by recognising that redirected patients would still access appropriate treatment, even if delayed. In addition, acceptance of ambulance redirection would be increased if there were robust clinical evidence showing net benefit over secondary transfer pathways. Conclusions: Participant views were generally supportive of ambulance redirection to facilitate access to thrombectomy. Further research is needed to demonstrate overall benefit in an NHS context.

Enhancing fall risk assessment: instrumenting vision with deep learning during walks.

BACKGROUND: Falls are common in a range of clinical cohorts, where routine risk assessment often comprises subjective visual observation only. Typically, observational assessment involves evaluation of an individual's gait during scripted walking protocols within a lab to identify deficits that potentially increase fall risk, but subtle deficits may not be (readily) observable. Therefore, objective approaches (e.g., inertial measurement units, IMUs) are useful for quantifying high resolution gait characteristics, enabling more informed fall risk assessment by capturing subtle deficits. However, IMU-based gait instrumentation alone is limited, failing to consider participant behaviour and details within the environment (e.g., obstacles). Video-based eye-tracking glasses may provide additional insight to fall risk, clarifying how people traverse environments based on head and eye movements. Recording head and eye movements can provide insights into how the allocation of visual attention to environmental stimuli influences successful navigation around obstacles. Yet, manual review of video data to evaluate head and eye movements is time-consuming and subjective. An automated approach is needed but none currently exists. This paper proposes a deep learning-based object detection algorithm (VARFA) to instrument vision and video data during walks, complementing instrumented gait. METHOD: The approach automatically labels video data captured in a gait lab to assess visual attention and details of the environment. The proposed algorithm uses a YoloV8 model trained on with a novel lab-based dataset. RESULTS: VARFA achieved excellent evaluation metrics (0.93 mAP50), identifying, and localizing static objects (e.g., obstacles in the walking path) with an average accuracy of 93%. Similarly, a U-NET based track/path segmentation model achieved good metrics (IoU 0.82), suggesting that the predicted tracks (i.e., walking paths) align closely with the actual track, with an overlap of 82%. Notably, both models achieved these metrics while processing at real-time speeds, demonstrating efficiency and effectiveness for pragmatic applications. CONCLUSION: The instrumented approach improves the efficiency and accuracy of fall risk assessment by evaluating the visual allocation of attention (i.e., information about when and where a person is attending) during navigation, improving the breadth of instrumentation in this area. Use of VARFA to instrument vision could be used to better inform fall risk assessment by providing behaviour and context data to complement instrumented e.g., IMU data during gait tasks. That may have notable (e.g., personalized) rehabilitation implications across a wide range of clinical cohorts where poor gait and increased fall risk are common.

Quantifying the cost savings and health impacts of improving colonoscopy quality: an economic evaluation.

OBJECTIVE: To estimate and quantify the cost implications and health impacts of improving the performance of English endoscopy services to the optimum quality as defined by postcolonoscopy colorectal cancer (PCCRC) rates. DESIGN: A semi-Markov state-transition model was constructed, following the logical treatment pathway of individuals who could potentially undergo a diagnostic colonoscopy. The model consisted of three identical arms, each representing a high, middle or low-performing trust's endoscopy service, defined by PCCRC rates. A cohort of 40-year-old individuals was simulated in each arm of the model. The model's time horizon was when the cohort reached 90 years of age and the total costs and quality-adjusted life-years (QALYs) were calculated for all trusts. Scenario and sensitivity analyses were also conducted. RESULTS: A 40-year-old individual gains 0.0006 QALYs and savings of £6.75 over the model lifetime by attending a high-performing trust compared with attending a middle-performing trust and gains 0.0012 QALYs and savings of £14.64 compared with attending a low-performing trust. For the population of England aged between 40 and 86, if all low and middle-performing trusts were improved to the level of a high-performing trust, QALY gains of 14 044 and cost savings of £249 311 295 are possible. Higher quality trusts dominated lower quality trusts; any improvement in the PCCRC rate was cost-effective. CONCLUSION: Improving the quality of endoscopy services would lead to QALY gains among the population, in addition to cost savings to the healthcare provider. If all middle and low-performing trusts were improved to the level of a high-performing trust, our results estimate that the English National Health Service would save approximately £5 million per year.

Contextualizing remote fall risk: Video data capture and implementing ethical AI.

Wearable inertial measurement units (IMUs) are being used to quantify gait characteristics that are associated with increased fall risk, but the current limitation is the lack of contextual information that would clarify IMU data. Use of wearable video-based cameras would provide a comprehensive understanding of an individual's habitual fall risk, adding context to clarify abnormal IMU data. Generally, there is taboo when suggesting the use of wearable cameras to capture real-world video, clinical and patient apprehension due to ethical and privacy concerns. This perspective proposes that routine use of wearable cameras could be realized within digital medicine through AI-based computer vision models to obfuscate/blur/shade sensitive information while preserving helpful contextual information for a comprehensive patient assessment. Specifically, no person sees the raw video data to understand context, rather AI interprets the raw video data first to blur sensitive objects and uphold privacy. That may be more routinely achieved than one imagines as contemporary resources exist. Here, to showcase/display the potential an exemplar model is suggested via off-the-shelf methods to detect and blur sensitive objects (e.g., people) with an accuracy of 88%. Here, the benefit of the proposed approach includes a more comprehensive understanding of an individual's free-living fall risk (from free-living IMU-based gait) without compromising privacy. More generally, the video and AI approach could be used beyond fall risk to better inform habitual experiences and challenges across a range of clinical cohorts. Medicine is becoming more receptive to wearables as a helpful toolbox, camera-based devices should be plausible instruments.

The impact of large core and late treatment trials: An update on the modelled annual thrombectomy eligibility of UK stroke patients.

INTRODUCTION: To support decisions about thrombectomy provision, we have previously estimated the annual UK population eligible for treatment as ∼10% of stroke admissions. Since then, eight further randomised trials that could alter the eligibility rate have reported in 2021-23. We updated our estimates of the eligible population from these trials and other recent studies. PATIENTS AND METHODS: An updated decision tree describing the EVT eligible population for UK stroke admissions was produced. Decision criteria were derived from the highest level of evidence available. For nodes where no specific RCT data existed, evidence was obtained from the latest systematic review(s) or the highest quality observational data. RESULTS: We estimate that 15,420 (approximately 15%) of admitted UK stroke patients are now eligible for thrombectomy, or 14,930 if advanced brain imaging using MRI/CT perfusion or collateral assessment were used in all patients. This is a 54% increase in our previous estimate in 2021. Over 50% of LAO strokes are now potentially eligible for thrombectomy. The increase in eligibility is principally due to a much larger cohort of later presenting and/or larger ischaemic core patients. CONCLUSION: Most previously independent LAO stroke patients presenting within 24 h, even in the presence of a large ischaemic core on initial non-contrast CT, should be considered for thrombectomy with use of advanced brain imaging in those presenting beyond 12 h to identify salvageable penumbral brain tissue. Treatment in most patients remains critically time-dependent and our estimates should be interpreted with this in mind.

Bathing Adaptations in the Homes of Older Adults (BATH-OUT-2): study protocol for a randomised controlled trial, economic evaluation and process evaluation.

BACKGROUND: The onset of disability in bathing is particularly important for older adults as it can be rapidly followed by disability in other daily activities; this may represent a judicious time point for intervention in order to improve health, well-being and associated quality of life. An important environmental and preventative intervention is housing adaptation, but there are often lengthy waiting times for statutory provision. In this randomised controlled trial (RCT), we aim to evaluate the effectiveness and cost-effectiveness of bathing adaptations compared to no adaptations and to explore the factors associated with routine and expedited implementation of bathing adaptations. METHODS: BATH-OUT-2 is a multicentre, two-arm, parallel-group RCT. Adults aged 60 and over who are referred to their local authority for an accessible level access shower will be randomised, using pairwise randomisation, 1:1, to receive either an expedited provision of an accessible shower via the local authority or a usual care control waiting list. Participants will be followed up for a maximum of 12 months and will receive up to four follow-ups in this duration. The primary outcome will be the participant's physical well-being, assessed by the Physical Component Summary score of the Short Form-36 (SF-36), 4 weeks after the intervention group receives the accessible shower. The secondary outcomes include the Mental Component Summary score of the SF-36, self-reported falls, health and social care resource use, health-related quality of life (EQ-5D-5L), social care-related quality of life (Adult Social Care Outcomes Toolkit (ASCOT)), fear of falling (Short Falls Efficacy Scale), independence in bathing (Barthel Index bathing question), independence in daily activities (Barthel Index) and perceived difficulty in bathing (0-100 scale). A mixed-methods process evaluation will comprise interviews with stakeholders and a survey of local authorities with social care responsibilities in England. DISCUSSION: The BATH-OUT-2 trial is designed so that the findings will inform future decisions regarding the provision of bathing adaptations for older adults. This trial has the potential to highlight, and then reduce, health inequalities associated with waiting times for bathing adaptations and to influence policies for older adults. TRIAL REGISTRATION: ISRCTN Registry ISRCTN48563324. Prospectively registered on 09/04/2021.

Costs of endovascular and open repair of thoracic aortic aneurysms.

BACKGROUND: Repair of thoracic aortic aneurysms with either endovascular repair (TEVAR) or open surgical repair (OSR) represents major surgery, is costly and associated with significant complications. The aim of this study was to establish accurate costs of delivering TEVAR and OSR in a cohort of UK NHS patients suitable for open and endovascular treatment for the whole treatment pathway from admission and to discharge and 12-month follow-up. METHODS: A prospective study of UK NHS patients from 30 NHS vascular/cardiothoracic units in England aged ≥18, with distal arch/descending thoracic aortic aneurysms (CTAA) was undertaken. A multicentre prospective cost analysis of patients (recruited March 2014-July 2018, follow-up until July 2019) undergoing TEVAR or OSR was performed. Patients deemed suitable for open or endovascular repair were included in this study. A micro-costing approach was adopted. RESULTS: Some 115 patients having undergone TEVAR and 35 patients with OSR were identified. The mean (s.d.) cost of a TEVAR procedure was higher £26 536 (£9877) versus OSR £17 239 (£8043). Postoperative costs until discharge were lower for TEVAR £7484 (£7848) versus OSR £28 636 (£23 083). Therefore, total NHS costs from admission to discharge were lower for TEVAR £34 020 (£14 301), versus OSR £45 875 (£43 023). However, mean NHS costs for 12 months following the procedure were slightly higher for the TEVAR £5206 (£11 585) versus OSR £5039 (£11 994). CONCLUSIONS: Surgical procedure costs were higher for TEVAR due to device costs. Total in-hospital costs were higher for OSR due to longer hospital and critical care stay. Follow-up costs over 12 months were slightly higher for TEVAR due to hospital readmissions.

Preparing for practice, the effects of repeated immersive simulation on the knowledge and self-efficacy of undergraduate nursing students: A mixed methods study.

AIM: The aim of this study was to compare the effects of two immersive simulation-based education instructional designs, immersive simulation with team deliberate practice and immersive repeated standard simulation, when delivered over the same time on the knowledge and self-efficacy of nursing students. BACKGROUND: Implementing immersive simulation-based education is not without its resource challenges, making it prohibitive for simulation educators to include it in their curricula. Subsequently, there is a need to identify instructional designs that meet these challenges. DESIGN: A two-stage mixed methods approach was used to compare the two instructional designs. METHODS: In stage one, data were collected using questionnaires and differences estimated using analysis of covariance. In stage two, data were collected from two focus groups and analysed using a qualitative content analysis approach. Data were collected as part of a doctoral study completed in 2019 and was analysed for this study between 2022 and 2023. The justification for this study was that the identification of effective designs for immersive simulation remains a key research priority following the increase in allowable simulation hours by the Nursing and Midwifery Council. RESULTS: In stage one, there was no statistical significance in the participant's knowledge or self-efficacy between the models. In stage two, four themes were identified: vulnerability, development of knowledge, development of self-efficacy and preparation for placement. In contrast to stage one, participants reported that the repeated nature of both designs reinforced their knowledge base increased their self-efficacy, reduced their anxiety levels, and helped them to prepare for placement. CONCLUSION: The results inferred that both designs had a positive impact on the participants. Overall, participants reported that it helped them prepare for placements. Based on the findings, wherever possible, repeated immersive simulation-based education designs should be used and not a standalone immersive simulation-based education scenarios. If resources allow, this could be either a repeated scenario, or if there are resource constraints to use, over the same time, immersive simulation with team deliberate practice, or a similar model. Thus, giving a potential return on investment, one that supports simulation educators making those sensitive decisions regarding the inclusion of immersive simulation with team deliberate practice in their curriculum. Further research is needed into this area to ascertain the design features that maximise this impact and support a move away from standalone scenarios to an approach that uses repetitive immersive simulation.

Developing and piloting an intervention to reduce colposcopy non-attendance and corresponding inequalities: a mixed-methods study.

BACKGROUND: Cervical cancer incidence and mortality is higher in lower income populations. Non-attendance for colposcopy following cervical screening is higher in deprived areas and younger patients. Diagnostic delays reduce the benefits of screening, increasing risk of pre-cancerous cells being undetected or treated later. We aimed to better understand drivers of colposcopy non-attendance and pilot a targeted intervention. Women and people with a cervix (referred to as patients in this paper) access colposcopy services. METHODS: For the service improvement audit, we collected qualitative data from Jan 24 to April 22, 2022, via telephone calls and interviews. The sample included patients who cancelled or did not attend their appointment and patients who attended their appointment. Interviews explored attendance barriers and enablers. Data were analysed thematically and reported, aligning with Consolidated Criteria for reporting Qualitative Studies' principles. The analysis informed development of a pilot intervention, implemented from Aug 8 to Oct 6, 2022, for all scheduled appointments. Patients were contacted by telephone pre-appointment as both a reminder and opportunity to identify and address attendance barriers. Barrier-specific pathways were developed to support attendance (eg, transport assistance). We compared descriptive non-attendance rates during the intervention period and pre-intervention. Audit permission was granted by Northumbria Clinical Audit Team and Caldicott approval obtained. FINDINGS: Data were collected from 20 of the 36 patients who did not attend between Jan 24, and April 22, 2022. Further data were gathered from 88 patients cancelling appointments and four colposcopy attendees. During the audit, ethnicity and gender identity were not routinely collected. Themes identified were administrative, forgetting, anxiety, work, childcare, and transport. During the pilot, 383 (65%) of all 595 patients with an appointment were successfully contacted. The overall non-attendance in 2022 pre-telephone intervention was 10% (195 of 1736 appointments). During the intervention, non-attendance was 8% (45 of 539 appointments). Non-attendance during the intervention was 12% (10 of 87 appointments) for patients aged 25-39 years in the 20% most deprived areas was, compared with 20% (64 of 319 appointments) before the intervention. INTERPRETATION: Identifying and addressing attendance barriers might improve non-attendance, particularly in younger and more deprived populations. This offers the prospect of improving the effectiveness of screening programmes alongside reducing inequalities in health-care access. The findings of this small-scale study are limited to NHS trust colposcopy service in the northeast of England, thus further formalised research is necessary. FUNDING: None.

Better informing everyday fall risk assessment: experimental studies with contemporary technologies.

BACKGROUND: Age-related mobility issues and frailty are a major public health concern because of an increased risk of falls. Subjective assessment of fall risk in the clinic is limited, failing to account for an individual's habitual activities in the home or community. Equally, objective mobility trackers for use in the home and community lack extrinsic (ie, environmental) data capture to comprehensively inform fall risk. We propose a contemporary approach that combines artificial intelligence (AI) and video glasses to augment current methods of fall risk assessment. METHODS: Two case studies were performed to provide a framework to assess extrinsic factors within fall risk assessment via video glasses. The first was AI-based detection of environment and terrain type. We developed convolutional neural networks (CNN) via a bespoke dataset (>145 000 images) captured from different settings (eg, offices, high streets) via free-licenced video on social media. AI automated a textual description to uphold privacy while describing the scene (eg, indoor and carpet). In the second case study, we provided video glasses to participants within a university campus (two men, 17 women; aged 21-60 years) to capture data for automatically labelling environment and objects (eg, fall hazards) via a CNN object detection algorithm. The case studies ran from Dec 5, 2022, to March 24, 2023. FINDINGS: To date, results show promise for the efficient, and accurate AI-based approach to better inform fall risk. Each component of the framework achieved at least 75% accuracy across a range of walks (indoor and outdoor and multiple terrains) from a dataset of 6283 new images. The AI achieved a mean average precision score of 0·93 for the identification of fall risk hazards. INTERPRETATIONS: The AI-based approach provides a contemporary means to better inform fall risk while providing an ethical means to uphold privacy. The proposed approach could have significant implications for improving overall health and quality of life, enabling ageing in place through habitual data collection with contemporary wearables to decentralise fall risk assessment. A limitation was the lack of data collection on older adults within real world, unscripted settings. However, the next phase of this research is the deployment of the AI on real-world data from a cohort of more than 40 participants within UK-based homes. FUNDING: National Institute of Health and Care Research (NIHR) Applied Research Collaboration (ARC) North-East and North Cumbria (NENC), Faculty of Engineering and Environment at Northumbria University.

Gait retraining to reduce falls: an experimental study toward scalable and personalised use in the home.

BACKGROUND: Age-related neurological conditions can result in poor mobility typified by gait abnormalities and falls, increasing risk of frailty and lowering quality of life. In the UK, the expense and inaccessibility of services to improve mobility through gait training (eg, auditory cueing) is a public health issue. Contemporary and scalable pervasive technologies for widespread public use could provide an affordable and accessible solution. We aimed to show the preliminary efficacy of a novel smartphone app that provides a personalised approach to mobility and gait assessment while facilitating gait training. METHODS: In this experimental study, we recruited participants aged 22-46 years with no physical functional impairments (ie, no age-related neurological condition and who could walk unaided) from Northumbria University staff (Newcastle upon Tyne, UK) between April 19, and May 26. Participants wore a smartphone on their lower back. Inertial data from the smartphone were recorded during two walks, one at a self-selected pace and the other with a personalised auditory cue via headphones (+10% pace on walk 1). Smartphone app functionality enabled the measurement of clinically relevant gait characteristics via a Python-based Cloud server. We compared smartphone-based mobility or gait characteristics with a gold-standard reference (Opal Mobility Lab, APDM). We used Pearson and intraclass correlation coefficients (ICC2,1) to examine agreement between the novel app and reference. The study ran from April 4 to July 21, 2023. This study received ethics approval from the Northumbria University Ethics committee, and all participants provided written informed consent. FINDINGS: Ten adults were recruited (six women and four men; mean age 27·4 years [SD 6·2], mean weight 79·6 kg [SD 12·7], mean height 174·7 cm [SD 7·9]). High levels of agreement were found between the smartphone app and reference, quantified by Pearson (≥0·858) and ICC values (≥0·911). The personalised cueing intervention increased the mean cadence by an average of 11%, which shows good participant adherence to cueing via an app. INTERPRETATION: Here, we propose a contemporary approach to increase the accessibility to a health-based intervention. Preliminary findings suggest the smartphone app is a suitable tool for personalised mobility or gait assessment while facilitating gait training. Use of a scalable app could be an accessible and affordable method for improving mobility to reduce falls in the home. Here, current limitations are the lack of investigation with the smartphone app for neurological gait assessment on older adults and the lack of information on participants app experience, but this will be included in future work. The pervasive use of smartphones enables a decentralised approach to overcoming issues such as frailty and logistical challenges of travelling to bespoke clinics. FUNDING: National Institute of Health and Care Research (NIHR) Applied Research Collaboration (ARC) North-East and North Cumbria (NENC); Faculty of Engineering and Environment at Northumbria University.

Robotic and laparoscopic gynaecological surgery: a prospective multicentre observational cohort study and economic evaluation in England.

OBJECTIVE: To compare the health-related quality of life and cost-effectiveness of robot-assisted laparoscopic surgery (RALS) versus conventional 'straight stick' laparoscopic surgery (CLS) in women undergoing hysterectomy as part of their treatment for either suspected or proven gynaecological malignancy. DESIGN: Multicentre prospective observational cohort study. SETTING: Patients aged 16+ undergoing hysterectomy as part of their treatment for gynaecological malignancy at 12 National Health Service (NHS) cancer units and centres in England between August 2017 and February 2020. PARTICIPANTS: 275 patients recruited with 159 RALS, 73 CLS eligible for analysis. OUTCOME MEASURES: Primary outcome was the European Organisation for Research and Treatment of Cancer Quality of Life measure (EORTC). Secondary outcomes included EuroQol-5 Dimension (EQ-5D-5L) utility, 6-minute walk test (6MWT), NHS costs using pounds sterling (£) 2018-2019 prices and cost-effectiveness. The cost-effectiveness evaluation compared EQ-5D-5L quality adjusted life years and costs between RALS and CLS. RESULTS: No difference identified between RALS and CLS for EORTC, EQ-5D-5L utility and 6MWT. RALS had unadjusted mean cost difference of £556 (95% CI -£314 to £1315) versus CLS and mean quality adjusted life year (QALY) difference of 0.0024 (95% CI -0.00051 to 0.0057), non-parametric incremental cost-effectiveness ratio of £231 667per QALY. For the adjusted cost-effectiveness analysis, RALS dominated CLS with a mean cost difference of -£188 (95% CI -£1321 to £827) and QALY difference of 0.0024 (95% CI -0.0008 to 0.0057). CONCLUSIONS: Findings suggest that RALS versus CLS in women undergoing hysterectomy (after adjusting for differences in morbidity) is cost-effective with lower costs and QALYs. Results are highly sensitive to the usage of robotic hardware with higher usage increasing the probability of cost-effectiveness. Non-inferiority randomised controlled trial would be of benefit to decision-makers to provide further evidence on the cost-effectiveness of RALS versus CLS but may not be practical due to surgical preferences of surgeons and the extensive roll out of RALS.

Investigating changes in mental health services utilisation in England and their impact on health outcomes and wellbeing during the COVID-19 pandemic: Protocol for a health data-linkage study.

INTRODUCTION: Linking routinely collected health care system data records for the same individual across different services and over time has enormous potential for the NHS and its patients. The aims of this data linkage study are to quantify the changes to mental health services utilisation in responses to the COVID-19 pandemic and determine whether these changes were associated with health-related outcomes and wellbeing among people living in the most deprived communities in North East and North Cumbria, England. METHODS AND ANALYSIS: We will assemble a retrospective cohort of people having referred or self-referred to NHS-funded mental health services or Improving Access to Psychological Therapies (IAPT) services between 23rd March 2019 and 22nd March 2020 in the most deprived areas in England. We will link together data from retrospective routinely collected healthcare data including local general practitioner (GP) practice data, Hospital Episode Statistics admitted patient care outpatients, and A&E, Community Services Data Set, Mental Health Services Data Set, and Improving Access to Psychological Therapies Data Set. We will use these linked patient-level data to 1) describe the characteristics of the cohort prior to the lockdown; 2) investigate changes to mental health services utilised between multiple time periods of the COVID-19 lockdown including out of lockdown; 3) explore the relationship between these changes and health outcomes/wellbeing and factors that confound and mediate this relationship among this cohort. STRENGTHS AND LIMITATIONS OF THIS STUDY: This study comprises a deprived population-based cohort of people having referred or self-referred to NHS-funded secondary mental health services or Improving Access to Psychological Therapies (IAPT) services over an extended period of the lockdown in England (2019-2022).This study will utilise a new longitudinal data resource that will link together detailed data from a cohort of individual participants and retrospective administrative data relating to the use of primary, secondary, and community care services.The study period covers pre-lockdown, different lockdown and post-lockdown, and out of lockdown periods up to March 2022.Routinely collected administrative data contain limited contextual information and represent an underestimate of total health outcomes for these individuals.Routinely collected datasets can often been incomplete or contain missing data, which can make it difficult to accurately analyse the data and draw meaningful conclusions.Intervention and treatment for mental health conditions are not wholly captured across these data sources and may impact health outcomes.