Development of an enhanced scoring system to predict ICU readmission or in-hospital death within 24 hours using routine patient data from two NHS Foundation Trusts.

RATIONALE: Intensive care units (ICUs) admit the most severely ill patients. Once these patients are discharged from the ICU to a step-down ward, they continue to have their vital signs monitored by nursing staff, with Early Warning Score (EWS) systems being used to identify those at risk of deterioration. OBJECTIVES: We report the development and validation of an enhanced continuous scoring system for predicting adverse events, which combines vital signs measured routinely on acute care wards (as used by most EWS systems) with a risk score of a future adverse event calculated on discharge from the ICU. DESIGN: A modified Delphi process identified candidate variables commonly available in electronic records as the basis for a 'static' score of the patient's condition immediately after discharge from the ICU. L1-regularised logistic regression was used to estimate the in-hospital risk of future adverse event. We then constructed a model of physiological normality using vital sign data from the day of hospital discharge. This is combined with the static score and used continuously to quantify and update the patient's risk of deterioration throughout their hospital stay. SETTING: Data from two National Health Service Foundation Trusts (UK) were used to develop and (externally) validate the model. PARTICIPANTS: A total of 12 394 vital sign measurements were acquired from 273 patients after ICU discharge for the development set, and 4831 from 136 patients in the validation cohort. RESULTS: Outcome validation of our model yielded an area under the receiver operating characteristic curve of 0.724 for predicting ICU readmission or in-hospital death within 24 hours. It showed an improved performance with respect to other competitive risk scoring systems, including the National EWS (0.653). CONCLUSIONS: We showed that a scoring system incorporating data from a patient's stay in the ICU has better performance than commonly used EWS systems based on vital signs alone. TRIAL REGISTRATION NUMBER: ISRCTN32008295.

AI-driven translations for kidney transplant equity in Hispanic populations.

Health equity and accessing Spanish kidney transplant information continues being a substantial challenge facing the Hispanic community. This study evaluated ChatGPT's capabilities in translating 54 English kidney transplant frequently asked questions (FAQs) into Spanish using two versions of the AI model, GPT-3.5 and GPT-4.0. The FAQs included 19 from Organ Procurement and Transplantation Network (OPTN), 15 from National Health Service (NHS), and 20 from National Kidney Foundation (NKF). Two native Spanish-speaking nephrologists, both of whom are of Mexican heritage, scored the translations for linguistic accuracy and cultural sensitivity tailored to Hispanics using a 1-5 rubric. The inter-rater reliability of the evaluators, measured by Cohen's Kappa, was 0.85. Overall linguistic accuracy was 4.89 ± 0.31 for GPT-3.5 versus 4.94 ± 0.23 for GPT-4.0 (non-significant p = 0.23). Both versions scored 4.96 ± 0.19 in cultural sensitivity (p = 1.00). By source, GPT-3.5 linguistic accuracy was 4.84 ± 0.37 (OPTN), 4.93 ± 0.26 (NHS), 4.90 ± 0.31 (NKF). GPT-4.0 scored 4.95 ± 0.23 (OPTN), 4.93 ± 0.26 (NHS), 4.95 ± 0.22 (NKF). For cultural sensitivity, GPT-3.5 scored 4.95 ± 0.23 (OPTN), 4.93 ± 0.26 (NHS), 5.00 ± 0.00 (NKF), while GPT-4.0 scored 5.00 ± 0.00 (OPTN), 5.00 ± 0.00 (NHS), 4.90 ± 0.31 (NKF). These high linguistic and cultural sensitivity scores demonstrate Chat GPT effectively translated the English FAQs into Spanish across systems. The findings suggest Chat GPT's potential to promote health equity by improving Spanish access to essential kidney transplant information. Additional research should evaluate its medical translation capabilities across diverse contexts/languages. These English-to-Spanish translations may increase access to vital transplant information for underserved Spanish-speaking Hispanic patients.

Could retaining the dental recall interval save NHS dentistry?

The World Health Assembly in May 2021 was a watershed moment in oral health, with the landmark resolution that designated oral diseases as non-communicable diseases (NCDs). This was strongly supported by a host of other NCDs in recognition of the common risk factor principle and acknowledgement of the fact that oral diseases do not occur in isolation from other NCDs, but are commonly associated with cardiovascular disease, diabetes/obesity, respiratory diseases, metabolic syndrome, a range of other inflammatory disorders and cancers. Regular monitoring and early detection would potentially intercept these NCDs and this could form a central plank of a revamped holistic 'health'- as opposed to 'disease'-oriented health care system.Consultation with patients and dentists reveals strong support for maintaining regular recall intervals, which maintains trust and optimises motivation and compliance. In-person visits could be minimised by using technology, such as remote consultations and longitudinal monitoring systems, making it adaptable to different health care settings and equitable, affordable, cost-effective and sustainable.A new paradigm with dentists as oral health professionals, and the mainstreaming of oral health and population-level prevention, means the future of health care can be guided by integration and workforce modification producing a surveillance-based, early interceptive, preventive model of care.

Comparative effectiveness of sotrovimab versus no treatment in non-hospitalised high-risk COVID-19 patients in north west London: a retrospective cohort study.

BACKGROUND: We assessed the effectiveness of sotrovimab vs no early COVID-19 treatment in highest-risk COVID-19 patients during Omicron predominance. METHODS: Retrospective cohort study using the Discover dataset in North West London. Included patients were non-hospitalised, aged ≥12 years and met ≥1 National Health Service highest-risk criterion for sotrovimab treatment. We used Cox proportional hazards models to compare HRs of 28-day COVID-19-related hospitalisation/death between highest-risk sotrovimab-treated and untreated patients. Age, renal disease and Omicron subvariant subgroup analyses were performed. RESULTS: We included 599 sotrovimab-treated patients and 5191 untreated patients. Compared with untreated patients, the risk of COVID-19 hospitalisation/death (HR 0.50, 95% CI 0.24, 1.06; p=0.07) and the risk of COVID-19 hospitalisation (HR 0.43, 95% CI 0.18, 1.00; p=0.051) were both lower in the sotrovimab-treated group; however, statistical significance was not reached. In the ≥65 years and renal disease subgroups, sotrovimab was associated with a significantly reduced risk of COVID-19 hospitalisation, by 89% (HR 0.11, 95% CI 0.02, 0.82; p=0.03) and 82% (HR 0.18, 95% CI 0.05, 0.62; p=0.007), respectively. CONCLUSIONS: Risk of COVID-19 hospitalisation in sotrovimab-treated patients aged ≥65 years and with renal disease was significantly lower compared with untreated patients. Overall, risk of hospitalisation was also lower for sotrovimab-treated patients, but statistical significance was not reached.

Qualitative study exploring the design of a patient-reported symptom-based risk stratification system for suspected head and neck cancer referrals: protocol for work packages 1 and 2 within the EVEREST-HN programme.

INTRODUCTION: Between 2009/2010 and 2019/2020, England witnessed an increase in suspected head and neck cancer (sHNC) referrals from 140 to 404 patients per 100 000 population. 1 in 10 patients are not seen within the 2-week target, contributing to patient anxiety. We will develop a pathway for sHNC referrals, based on the Head and Neck Cancer Risk Calculator. The evolution of a patient-reported symptom-based risk stratification system to redesign the sHNC referral pathway (EVEREST-HN) Programme comprises six work packages (WPs). This protocol describes WP1 and WP2. WP1 will obtain an understanding of language to optimise the SYmptom iNput Clinical (SYNC) system patient-reported symptom questionnaire for sHNC referrals and outline requirements for the SYNC system. WP2 will codesign key elements of the SYNC system, including the SYNC Questionnaire, and accompanying behaviour change materials. METHODS AND ANALYSIS: WP1 will be conducted at three acute National Health Service (NHS) trusts with variation in service delivery models and ensuring a broad mixture of social, economic and cultural backgrounds of participants. Up to 150 patients with sHNC (n=50 per site) and 15 clinicians (n=5 per site) will be recruited. WP1 will use qualitative methods including interviews, observation and recordings of consultations. Rapid qualitative analysis and inductive thematic analysis will be used to analyse the data. WP2 will recruit lay patient representatives to participate in online focus groups (n=8 per focus group), think-aloud technique and experience-based codesign and will be analysed using qualitative and quantitative approaches. ETHICS AND DISSEMINATION: The committee for clinical research at The Royal Marsden, a research ethics committee and the Health Research Authority approved this protocol. All participants will give informed consent. Ethical issues of working with patients on an urgent cancer diagnostic pathway have been considered. Findings will be disseminated via journal publications, conference presentations and public engagement activities.

Solving poverty or tackling healthcare inequalities? Qualitative study exploring local interpretations of national policy on health inequalities under new NHS reforms in England.

OBJECTIVES: Major reforms to the organisation of the National Health Service (NHS) in England established 42 integrated care systems (ICSs) to plan and coordinate local services. The changes are based on the idea that cross-sector collaboration is needed to improve health and reduce health inequalities-and similar policy changes are happening elsewhere in the UK and internationally. We explored local interpretations of national policy objectives on reducing health inequalities among senior leaders working in three ICSs. DESIGN: We carried out qualitative research based on semistructured interviews with NHS, public health, social care and other leaders in three ICSs in England. SETTING AND PARTICIPANTS: We selected three ICSs with varied characteristics all experiencing high levels of socioeconomic deprivation. We conducted 32 in-depth interviews with senior leaders of NHS, local government and other organisations involved in the ICS's work on health inequalities. Our interviewees comprised 17 leaders from NHS organisations and 15 leaders from other sectors. RESULTS: Local interpretations of national policy objectives on health inequalities varied, and local leaders had contrasting-sometimes conflicting-perceptions of the boundaries of ICS action on reducing health inequalities. Translating national objectives into local priorities was often a challenge, and clarity from national policy-makers was frequently perceived as limited or lacking. Across the three ICSs, local leaders worried that objectives on tackling health inequalities were being crowded out by other short-term policy priorities, such as reducing pressures on NHS hospitals. The behaviour of national policy-makers appeared to undermine their stated priorities to reduce health inequalities. CONCLUSIONS: Varied and vague interpretations of NHS policy on health inequalities are not new, but lack of clarity among local health leaders brings major risks-including interventions being poorly targeted or inadvertently widening inequalities. Greater conceptual clarity is likely needed to guide ICS action in future.

Comparing the effectiveness of computer-aided design/computer-aided manufacturing (CAD/CAM) of insoles manufactured from foam box cast versus direct scans on patient-reported outcome measures: a protocol for a double-blinded, randomised controlled trial.

INTRODUCTION: Custom insoles are a routine treatment for many foot pathologies, and the use of computer-aided design and computer-aided manufacturing (CAD/CAM) is well established within clinical practice in the UK. The method of foot shape capture used to produce insoles varies throughout orthotic services. This trial aims to investigate the effectiveness of two common shape-capture techniques on patient-reported outcomes in people who require insoles for a foot or ankle pathology. METHODS AND ANALYSIS: This double-blinded randomised controlled trial will involve two intervention groups recruited from a National Health Service orthotic service. Participants will be randomly assigned to receive a pair of custom CAD/CAM insoles, manufactured either from a direct digital scan or a foam box cast of their feet and asked to wear the insoles for 12 weeks. The primary outcome measure will be the Foot Health Status Questionnaire (FHSQ) pain subdomain, recorded at baseline (immediately after receiving the intervention), 4, 8 and 12 weeks post intervention. Secondary outcome measures will include FHSQ foot function and foot health subdomains recorded at baseline, 4, 8 and 12 weeks. The Orthotic and Prosthetic User Survey Satisfaction with Device will be recorded at 12 weeks. The transit times associated with each arm will be measured as the number of days for each insole to be delivered after foot shape capture. Tertiary outcome measures will include participant recruitment and dropout rates, and intervention adherence measured as the daily usage of the insoles over 12 weeks. The change in FHSQ scores for the subdomains and insole usage will be compared between the groups and time points, and between group differences in time in transit, cost-time analysis and environmental impact will be compared. ETHICS AND DISSEMINATION: Ethical approval was obtained from the Health Research Authority, London Stanmore Research Ethics Committee (22/LO/0579). Study findings will be submitted for publication in peer-reviewed journals, conference presentations and webinars. TRIAL REGISTRATION NUMBER: NCT05444192.

Effect of clinical engagement on value, standardisation, decision-making and savings in NHS product procurement.

BACKGROUND: UK healthcare expenditure is now £193.8 billion a year. The procurement function is seen as central to driving efficiencies within the NHS. This comes with an increasing onus on clinicians, including nurses and allied health professionals, to accept procurement outcomes to realise efficiency savings, with or without prior engagement. AIMS: This empirical study seeks to examine whether clinical engagement in the procurement of healthcare products in the NHS is necessary to achieve value, savings and standardisation; it will thereby address a gap in the research. METHODS: A multi-method qualitative case study design was used, which included a survey and eight semi-structured interviews. FINDINGS: Results identified three factors that influence the achievement of value, savings and standardisation around clinical engagement: micro-level processes for clinical engagement; clinical stakeholders and clinical procurement professionals as experts at the centre of procurement activity; and clinical value in standardisation. A shift away from standardisation to resilience was identified, resulting from current market supply pressures. CONCLUSION: This research brings empirically derived findings to address gaps in research, supports the benefit of clinical engagement through specific forums for collaboration at a trust level and provides a clinical/expert impact/preference matrix as a resource for procurement professionals to facilitate clinical engagement.

Taking a reading on NHS patient safety: views from the ombudsman.

John Tingle, Lecturer in Law, Birmingham Law School, University of Birmingham, discusses several reports where the Parliamentary and Health Service Ombudsman addresses some critical NHS patient safety issues.

An exploration of service use pattern changes and cost analysis following implementation of community perinatal mental health teams in pregnant women with a history of specialist mental healthcare in England: a national population-based cohort study.

BACKGROUND: The National Health Service in England pledged >£365 million to improve access to mental healthcare services via Community Perinatal Mental Health Teams (CPMHTs) and reduce the rate of perinatal relapse in women with severe mental illness. This study aimed to explore changes in service use patterns following the implementation of CPMHTs in pregnant women with a history of specialist mental healthcare in England, and conduct a cost-analysis on these changes. METHODS: This study used a longitudinal cohort design based on existing routine administrative data. The study population was all women residing in England with an onset of pregnancy on or after 1st April 2016 and who gave birth on or before 31st March 2018 with pre-existing mental illness (N = 70,323). Resource use and costs were compared before and after the implementation of CPMHTs. The economic perspective was limited to secondary mental health services, and the time horizon was the perinatal period (from the start of pregnancy to 1-year post-birth, ~ 21 months). RESULTS: The percentage of women using community mental healthcare services over the perinatal period was higher for areas with CPMHTs (30.96%, n=9,653) compared to areas without CPMHTs (24.72%, n=9,615). The overall percentage of women using acute care services (inpatient and crisis resolution teams) over the perinatal period was lower for areas with CPMHTs (4.94%, n=1,540 vs. 5.58%, n=2,171), comprising reduced crisis resolution team contacts (4.41%, n=1,375 vs. 5.23%, n=2,035) but increased psychiatric admissions (1.43%, n=445 vs. 1.13%, n=441). Total mental healthcare costs over the perinatal period were significantly higher for areas with CPMHTs (fully adjusted incremental cost £111, 95% CI £29 to £192, p-value 0.008). CONCLUSIONS: Following implementation of CPMHTs, the percentage of women using acute care decreased while the percentage of women using community care increased. However, the greater use of inpatient admissions alongside greater use of community care resulted in a significantly higher mean cost of secondary mental health service use for women in the CPMHT group compared with no CPMHT. Increased costs must be considered with caution as no data was available on relevant outcomes such as quality of life or satisfaction with services.

Challenging NHS Corporate Mentality: Hospital-Management and Bureaucracy in London's Pandemic.

Whilst NHS Health Service management is usually characterized by hierarchized bureaucracy and profit-driven competitiveness, the COVID-19 pandemic drastically disrupted these ways of working and allowed London-based non-clinical management to experience their roles otherwise. This paper is based on 35 interviews with senior non-clinical management at a London-based NHS Trust during 'Alpha phase' of Britain's pandemic response (May-August 2020), an oft-overlooked group in the literature. I will draw upon Graeber's theory of "total bureaucratization" to argue that though the increasing neo-liberalization of the health-services has hitherto contributed toward a corporate mentality, the pandemic gave managers a chance to experience more collaboration and freedom than usual, which ultimately led to more effective realization of decision-making and change. The pandemic has shown NHS managers that there are alternatives to neoliberal logics of competition and hierarchy, and that those alternatives actually result in happier and effectively, more capable staff.

Exposure to di-2-ethylhexyl phthalate and breast neoplasm incidence: A cohort study.

BACKGROUND: Phthalates are ubiquitous environmental endocrine disruptors. As the predominant phthalate, di-2-ethylhexyl phthalate (DEHP) has been considered possibly carcinogenic to humans but large-scale longitudinal evidence is needed to further clarify its carcinogenicity. OBJECTIVES: To examine the association between DEHP exposure and incidence of breast malignant neoplasm, carcinoma in situ and benign neoplasm. METHODS: A total of 273,295 women from UK Biobank cohort were followed up for a median of 13.5 years. Disease information was collected from National Health Service Cancer Registry and National Death Index. Baseline and yearly-average level of DEHP exposure were estimated for each individual by linking chemical monitoring record of European Environment Agency with home address of the participants by Kriging interpolation model. Cox proportional hazard model was employed to estimate the association between DEHP exposure and breast neoplasms. RESULTS: The median (IQR) of baseline and yearly-average DEHP concentration were 8000.25 (interquartile range: 6657.85-11,948.83) and 8000.25 (interquartile range: 1819.93-11,359.55) µg/L. The highest quartile of baseline DEHP was associated with 1.11 fold risk of carcinoma in situ (95 % CI, 1.00, 1.23, p < 0.001) and 1.27 fold risk of benign neoplasm (95 % CI, 1.05, 1.54, p < 0.001). As for yearly-average exposure, each quartile of DEHP was positively associated with higher risk of malignant neoplasm (HR, 1.05; 95 % CI, 1.03, 1.07, p < 0.001), carcinoma in situ (HR, 1.08; 95 % CI, 1.04, 1.11, p < 0.001) and benign neoplasm (HR, 1.13; 95 % CI, 1.07, 1.20, p < 0.001). Stratification analysis showed no significant modification effects on the DEHP-neoplasm relationship by menopausal status or ethnicity but a suggestive higher risk in younger women and those who underwent oral contraceptive pill therapy. In sensitivity analysis, the associations remained when excluding the cases diagnosed within 2 years post baseline. CONCLUSIONS: Real-world level of DEHP exposure was associated with higher risk of breast neoplasms. Because of the health risks associated with DEHP, its release to the environment should be managed.

Software with artificial intelligence-derived algorithms for analysing CT brain scans in people with a suspected acute stroke: a systematic review and cost-effectiveness analysis.

Background: Artificial intelligence-derived software technologies have been developed that are intended to facilitate the review of computed tomography brain scans in patients with suspected stroke. Objectives: To evaluate the clinical and cost-effectiveness of using artificial intelligence-derived software to support review of computed tomography brain scans in acute stroke in the National Health Service setting. Methods: Twenty-five databases were searched to July 2021. The review process included measures to minimise error and bias. Results were summarised by research question, artificial intelligence-derived software technology and study type. The health economic analysis focused on the addition of artificial intelligence-derived software-assisted review of computed tomography angiography brain scans for guiding mechanical thrombectomy treatment decisions for people with an ischaemic stroke. The de novo model (developed in R Shiny, R Foundation for Statistical Computing, Vienna, Austria) consisted of a decision tree (short-term) and a state transition model (long-term) to calculate the mean expected costs and quality-adjusted life-years for people with ischaemic stroke and suspected large-vessel occlusion comparing artificial intelligence-derived software-assisted review to usual care. Results: A total of 22 studies (30 publications) were included in the review; 18/22 studies concerned artificial intelligence-derived software for the interpretation of computed tomography angiography to detect large-vessel occlusion. No study evaluated an artificial intelligence-derived software technology used as specified in the inclusion criteria for this assessment. For artificial intelligence-derived software technology alone, sensitivity and specificity estimates for proximal anterior circulation large-vessel occlusion were 95.4% (95% confidence interval 92.7% to 97.1%) and 79.4% (95% confidence interval 75.8% to 82.6%) for Rapid (iSchemaView, Menlo Park, CA, USA) computed tomography angiography, 91.2% (95% confidence interval 77.0% to 97.0%) and 85.0 (95% confidence interval 64.0% to 94.8%) for Viz LVO (Viz.ai, Inc., San Fransisco, VA, USA) large-vessel occlusion, 83.8% (95% confidence interval 77.3% to 88.7%) and 95.7% (95% confidence interval 91.0% to 98.0%) for Brainomix (Brainomix Ltd, Oxford, UK) e-computed tomography angiography and 98.1% (95% confidence interval 94.5% to 99.3%) and 98.2% (95% confidence interval 95.5% to 99.3%) for Avicenna CINA (Avicenna AI, La Ciotat, France) large-vessel occlusion, based on one study each. These studies were not considered appropriate to inform cost-effectiveness modelling but formed the basis by which the accuracy of artificial intelligence plus human reader could be elicited by expert opinion. Probabilistic analyses based on the expert elicitation to inform the sensitivity of the diagnostic pathway indicated that the addition of artificial intelligence to detect large-vessel occlusion is potentially more effective (quality-adjusted life-year gain of 0.003), more costly (increased costs of £8.61) and cost-effective for willingness-to-pay thresholds of £3380 per quality-adjusted life-year and higher. Limitations and conclusions: The available evidence is not suitable to determine the clinical effectiveness of using artificial intelligence-derived software to support the review of computed tomography brain scans in acute stroke. The economic analyses did not provide evidence to prefer the artificial intelligence-derived software strategy over current clinical practice. However, results indicated that if the addition of artificial intelligence-derived software-assisted review for guiding mechanical thrombectomy treatment decisions increased the sensitivity of the diagnostic pathway (i.e. reduced the proportion of undetected large-vessel occlusions), this may be considered cost-effective. Future work: Large, preferably multicentre, studies are needed (for all artificial intelligence-derived software technologies) that evaluate these technologies as they would be implemented in clinical practice. Study registration: This study is registered as PROSPERO CRD42021269609. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Evidence Synthesis programme (NIHR award ref: NIHR133836) and is published in full in Health Technology Assessment; Vol. 28, No. 11. See the NIHR Funding and Awards website for further award information.

Stroke is a serious life-threatening medical condition caused by a blood clot or haemorrhage in the brain. Quick and effective management, including a brain scan, of the patients with suspected stroke can make a big difference in their outcome. Artificial intelligence-derived computer programmes exist that are intended to help with the interpretation of computed tomography scans of the brain in stroke. We undertook a thorough review of the existing research into the effectiveness and value for money of using these programmes to help doctors and other specialists to interpret computed tomography brain scans. We found very little evidence to tell us how well artificial intelligence-derived computer programmes work in practice. Some studies have looked at artificial intelligence-derived computer programmes on their own (i.e. not taken together with a doctor's judgement, as they were designed to be used). Other studies have looked at what happens to patients who are treated for stroke when artificial intelligence-derived computer programmes are used; these studies provide no information about whether using artificial intelligence-derived computer programmes may have led to patients who could have benefitted from treatment being missed. It is unclear how well artificial intelligence-derived software-assisted review works when added to current clinical practice.