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Resilience of the acute sector in recovery from COVID-19 pressures
The COVID-19 pandemic had a profound impact on the management and delivery of acute healthcare. To tackle the pandemic, hospitals redesigned their organisational models to provide a rapid increase in acute care assessment and treatment capacity for patients with COVID-19 whilst also trying to maintain delivery of care for patients with non-COVID-19 healthcare needs. This capacity to adjust and recover after COVID-19 might be shaped by both measures taken by acute hospitals and wider hospital pre-pandemic characteristics. The aim of this study is to examine how hospital characteristics in acute care are associated with recovery of elective activity after the height of the COVID-19 pandemic compared to pre-pandemic levels. Using patient-level data from Hospital Episode Statistics aggregated at monthly-trust level for all English National Health Service (NHS) acute hospital trusts in 2019 and 2021, we estimate the associations between hospital recovery rate and hospital pre-pandemic characteristics by employing linear regressions of the proportional change over time in elective activity against a set of explanatory variables related to supply factors (e.g., hospital size, workforce, type of hospital, regional location), demand factors (e.g., population need, patient case-mix) and time factors. On average, English NHS acute hospital trusts did not fully recover from the COVID-19 pandemic in 2021. The results show that the explanatory variables are not systematically associated with hospital recovery rate, excepting regional differences. Hospital trusts not located in London, especially in the North of England, are associated with a lower recovery (less resilience) of total elective activity and orthopaedic and vascular surgical elective activity. The implication for policy development is that the evolution of hospital recovery rates in elective activity varied across English regions, especially for high-volume and high-risk elective specialties, with better recovery in London than elsewhere.
Developing a digital phenotype to subdivide adult immunosuppressed COVID-19 outcomes within the English Primary Care Sentinel Network
Background: Adults classified as immunosuppressed have been disproportionately affected by the COVID-19 pandemic. Compared to the immunocompetent, certain patients are at increased risk of suboptimal vaccine response and adverse health outcomes if infected. However, there has been insufficient work to pinpoint where these risks concentrate within the immunosuppressed spectrum; surveillance efforts typically treat the immunosuppressed as a single entity, leading to wide confidence intervals. A clinically meaningful and computerised medical record (CMR) compatible method to subdivide immunosuppressed COVID-19 data is urgently needed. Methods: We conducted a rapid scoping review into COVID-19 mortality across UK immunosuppressed categories to assess if differential mortality risk was a viable means of subdivision. We converted the risk hierarchy that surfaced into a pilot digital phenotype—a valueset and series of ontological rules ready to extract immunosuppressed patients from CMR data and stratify outcomes of interest in COVID-19 surveillance dataflows. Results: The rapid scoping review returned COVID-19 mortality data for all immunosuppressed subgroups assessed and revealed significant heterogeneity across the spectrum. There was a clear distinction between heightened COVID-19 mortality in haematological malignancy and transplant patients and mortality that approached the immunocompetent baseline amongst cancer therapy recipients, autoimmune patients, and those with HIV. This process, complemented by expert clinical input, informed the curation of the five-part digital phenotype now ready for testing in real-world data; its ontological rules will enable mutually exclusive, hierarchical extraction with nuanced time and treatment conditions. Unique categorisations have been introduced, including ‘Bone Marrow Compromised’ and those dedicated to differentiating prescriptions related and unrelated to cancer. Codification was supported by existing reference sets of medical codes; absent or redundant codes had to be resolved manually. Discussion: Although this work is in its earliest phases, the development process we report has been highly informative. Systematic review, clinical consensus building, and implementation studies will test the validity of our results and address criticisms of the rapid scoping exercise they are predicated on. Conclusion: Comprehensive testing for COVID-19 has differentiated mortality risks across the immunosuppressed spectrum. This risk hierarchy has been codified into a digital phenotype for differentiated COVID-19 surveillance; this marks a step towards the needs-based management of these patients that is urgently required.
A Remotely Delivered GLP-1RA–Supported Specialist Weight Management Program in Adults Living With Obesity: Retrospective Service Evaluation
Background Limited access to specialist weight management services restricts the implementation of novel pharmacotherapies for obesity such as glucagon-like peptide-1 receptor agonists (GLP-1RAs) in the UK National Health Service (NHS). Second Nature, a commercial digital health company, offers a remotely delivered program combining a GLP-1RA medication (semaglutide) with digital behavioral support, potentially providing a scalable solution. However, evidence for long-term effectiveness in this real-world context is limited. Objective This study aimed to evaluate the 12-month effectiveness, feasibility, acceptability, and potential cost-effectiveness of the remotely delivered, semaglutide-supported weight management program by Second Nature. Methods This retrospective service evaluation analyzed data from participants who initiated the program between September and December 2023. The primary outcome was weight change at 12 months among participants with available data (completers). Secondary outcomes included retention, program engagement (measured by views of the Home screen in the app), behavioral changes, side effects, participant experience (qualitative analysis), and a comparative cost analysis against an NHS specialist weight management service. An “active subscription” was defined as maintaining a paid subscription for the full 12-month period. Descriptive statistics and paired 2-tailed t tests evaluated outcomes. Results Data from 341 participants were included at baseline (282/341, 82.7% women; mean age 49, SD 11.1 years; mean baseline BMI 37.9, SD 6.9 kg/m2). At 12 months, 39.6% (135/206) maintained an active subscription, while 60.4% (206/341) became inactive. Weight data at 12 months were available for 179 participants (52.5% of the baseline cohort; 100% of active and 19.4% of inactive participants). Among completers who maintained an active subscription, the mean weight loss was 20.0 kg (SD 8.7 kg; P<.001), representing 19.1% of starting weight. Overall, 77.7% (139/179) of completers achieved ≥10% weight loss and 61.5% (110/179) achieved ≥15%. Program engagement declined over time. Side effects also decreased, with 69.6% (81/116) of respondents reporting none by month 12. Most participants completing the 12-month survey reported positive (41/120, 34.2%) or neutral (68/120, 56.7%) experiences. Conclusions This evaluation suggests that remotely delivered GLP-1RA–supported weight management can achieve significant weight loss in participants remaining engaged for 12 months. However, the high rate of withdrawal limits generalizability. The program appears feasible, acceptable, and potentially cost-effective for completers. Further research, ideally in public health care settings using intent-to-treat analyses, is needed to confirm clinical outcomes, assess sustained results, and understand factors influencing retention.
Reforming the funding of long-Term care for older people: Costs and distributional impacts of planned changes in England
Reforms to the means tests in England for state-financed long-Term care were planned for implementation in 2025. They included a lifetime limit (cap) on how much an individual must contribute to their care, with the state meeting subsequent care costs. We present projections of the costs and distributional impacts of these reforms for older people, using two linked simulation models which draw on a wide range of data. We project that by 2038 public spending on long-Term care for older people in England would be about 14% higher than without the reforms. While the main direct beneficiaries of the lifetime cap would have been the better off who currently receive no state help with their care costs, the reforms also treated capital assets more generously than the current system, helping people with more modest incomes and wealth. When analysing the impacts of the reforms it is therefore important to consider the whole reform package. Our results depend on a range of assumptions, and the impacts of the reforms would be sensitive to the levels of the cap and other reformed parameters of the means test on implementation.
Relationship of cardiorenal risk factors with albuminuria based on age, smoking, glycaemic status and BMI: a retrospective cohort study of the UK Biobank data.
INTRODUCTION: Smoking is harmful, and its cessation is recommended to prevent chronic kidney disease, which often begins with abnormal leakage of albumin in the urine, called albuminuria. Smoking cessation's effect on albuminuria depends on the pack-years smoked, length of abstinence, body mass index (BMI) and glycosylated haemoglobin (HbA1c). Using the UK Biobank data, we examined the relationship between these cardiorenal variables and albuminuria. METHODS: For this study, we selected a UK Biobank cohort with urinary albumin concentration (UAC) in the first and second visits. Participants were divided into progressor and regressor groups, where progressors were defined as those with increased UAC value, and regressors were those with decreased UAC value. Three different logistic regression models were fitted. In model 1, with a cohort design, we explored the impact of a change in age, HbA1c and BMI between the first and second visits and the UAC. In model 2 and 3, in a cross-sectional design, we explored which cardiorenal risk factors were associated with a rise or fall of UAC at the time point of the second visit. Results are expressed in OR and 95% CI. RESULTS: The prevalence of albuminuria was highest in ex-smokers who started smoking between the ages of 13 and 18. With a mean duration of 51 months, there was no statistically significant relationship between smoking status and BMI with albuminuria. Each year of ageing and each unit of increase in HbA1c (mmol/mol) increased the odds of progression of albuminuria by 20% and 3%, respectively. In ex-smokers, at the time point of the second visit, each year of smoking increased, and each year of abstinence decreased the odds by 4% and 6%, respectively. CONCLUSION: Smokers should be supported to stop smoking and remain abstinent despite short-term weight gain. Childhood smoking should be actively discouraged.
Phenotype execution and modeling architecture to support disease surveillance and real-world evidence studies: English sentinel network evaluation
Objective: To evaluate Phenotype Execution and Modelling Architecture (PhEMA), to express sharable phenotypes using Clinical Quality Language (CQL) and intensional Systematised Nomenclature of Medicine (SNOMED) Clinical Terms (CT) Fast Healthcare Interoperability Resources (FHIR) valuesets, for exemplar chronic disease, sociodemographic risk factor, and surveillance phenotypes. Method: We curated 3 phenotypes: Type 2 diabetes mellitus (T2DM), excessive alcohol use, and incident influenza-like illness (ILI) using CQL to define clinical and administrative logic. We defined our phenotypes with valuesets, using SNOMED's hierarchy and expression constraint language, and CQL, combining valuesets and adding temporal elements where needed. We compared the count of cases found using PhEMA with our existing approach using convenience datasets. We assessed our new approach against published desiderata for phenotypes. Results: The T2DM phenotype could be defined as 2 intensionally defined SNOMED valuesets and a CQL script. It increased the prevalence from 7.2% to 7.3%. Excess alcohol phenotype was defined by valuesets that added qualitative clinical terms to the quantitative conceptual definitions we currently use; this change increased prevalence by 58%, from 1.2% to 1.9%. We created an ILI valueset with SNOMED concepts, adding a temporal element using CQL to differentiate new episodes. This increased the weekly incidence in our convenience sample (weeks 26-38) from 0.95 cases to 1.11 cases per 100 000 people. Conclusions: Phenotypes for surveillance and research can be described fully and comprehensibly using CQL and intensional FHIR valuesets. Our use case phenotypes identified a greater number of cases, whilst anticipated from excessive alcohol this was not for our other variable. This may have been due to our use of SNOMED CT hierarchy. Our new process fulfilled a greater number of phenotype desiderata than the one that we had used previously, mostly in the modeling domain. More work is needed to implement that sharing and warehousing domains.
Disparities in COVID-19 mortality amongst the immunosuppressed: A systematic review and meta-analysis for enhanced disease surveillance
Background: Effective disease surveillance, including that for COVID-19, is compromised without a standardised method for categorising the immunosuppressed as a clinical risk group. Methods: We conducted a systematic review and meta-analysis to evaluate whether excess COVID-associated mortality compared to the immunocompetent could meaningfully subdivide the immunosuppressed. Our study adhered to UK Immunisation against infectious disease (Green Book) criteria for defining and categorising immunosuppression. Using OVID (EMBASE, MEDLINE, Transplant Library, and Global Health), PubMed, and Google Scholar, we examined relevant literature between the entirety of 2020 and 2022. We selected for cohort studies that provided mortality data for immunosuppressed subgroups and immunocompetent comparators. Meta-analyses, grey literature and any original works that failed to provide comparator data or reported all-cause or paediatric outcomes were excluded. Odds Ratios (OR) and 95% confidence intervals (CI) of COVID-19 mortality were meta-analysed by immunosuppressed category and subcategory. Subgroup analyses differentiated estimates by effect measure, country income, study setting, level of adjustment, use of matching and publication year. Study screening, extraction and bias assessment were performed blinded and independently by two researchers; conflicts were resolved with the oversight of a third researcher. PROSPERO registration number is CRD42022360755. Findings: We identified 99 unique studies, incorporating data from 1,542,097 and 56,248,181 unique immunosuppressed and immunocompetent patients with COVID-19 infection, respectively. Compared to immunocompetent people (pooled OR, 95%CI), solid organ transplants (2.12, 1.50-2.99) and malignancy (2.02, 1.69-2.42) patients had a very high risk of COVID-19 mortality. Patients with rheumatological conditions (1.28, 1.13-1.45) and HIV (1.20, 1.05-1.36) had just slightly higher risks than the immunocompetent baseline. Case type, setting income and mortality data matching and adjustment were significant modifiers of excess immunosuppressed mortality for some immunosuppressed subgroups. Interpretation: Excess COVID-associated mortality among the immunosuppressed compared to the immunocompetent was seen to vary significantly across subgroups. This novel means of subdivision has prospective benefit for targeting patient triage, shielding and vaccination policies during periods of high disease transmission.
Postpandemic Sentinel Surveillance of Respiratory Diseases in the Context of the World Health Organization Mosaic Framework: Protocol for a Development and Evaluation Study Involving the English Primary Care Network 2023-2024
Background: Prepandemic sentinel surveillance focused on improved management of winter pressures, with influenza-like illness (ILI) being the key clinical indicator. The World Health Organization (WHO) global standards for influenza surveillance include monitoring acute respiratory infection (ARI) and ILI. The WHO’s mosaic framework recommends that the surveillance strategies of countries include the virological monitoring of respiratory viruses with pandemic potential such as influenza. The Oxford-Royal College of General Practitioner Research and Surveillance Centre (RSC) in collaboration with the UK Health Security Agency (UKHSA) has provided sentinel surveillance since 1967, including virology since 1993. Objective: We aim to describe the RSC’s plans for sentinel surveillance in the 2023-2024 season and evaluate these plans against the WHO mosaic framework. Methods: Our approach, which includes patient and public involvement, contributes to surveillance objectives across all 3 domains of the mosaic framework. We will generate an ARI phenotype to enable reporting of this indicator in addition to ILI. These data will support UKHSA’s sentinel surveillance, including vaccine effectiveness and burden of disease studies. The panel of virology tests analyzed in UKHSA’s reference laboratory will remain unchanged, with additional plans for point-of-care testing, pneumococcus testing, and asymptomatic screening. Our sampling framework for serological surveillance will provide greater representativeness and more samples from younger people. We will create a biomedical resource that enables linkage between clinical data held in the RSC and virology data, including sequencing data, held by the UKHSA. We describe the governance framework for the RSC. Results: We are co-designing our communication about data sharing and sampling, contextualized by the mosaic framework, with national and general practice patient and public involvement groups. We present our ARI digital phenotype and the key data RSC network members are requested to include in computerized medical records. We will share data with the UKHSA to report vaccine effectiveness for COVID-19 and influenza, assess the disease burden of respiratory syncytial virus, and perform syndromic surveillance. Virological surveillance will include COVID-19, influenza, respiratory syncytial virus, and other common respiratory viruses. We plan to pilot point-of-care testing for group A streptococcus, urine tests for pneumococcus, and asymptomatic testing. We will integrate test requests and results with the laboratory-computerized medical record system. A biomedical resource will enable research linking clinical data to virology data. The legal basis for the RSC’s pseudonymized data extract is The Health Service (Control of Patient Information) Regulations 2002, and all nonsurveillance uses require research ethics approval. Conclusions: The RSC extended its surveillance activities to meet more but not all of the mosaic framework’s objectives. We have introduced an ARI indicator. We seek to expand our surveillance scope and could do more around transmissibility and the benefits and risks of nonvaccine therapies.
The impact of COVID-19 lockdowns on primary care contact among vulnerable populations in England: a controlled interrupted time series study.
BACKGROUND: UK COVID-19 lockdowns significantly affected primary care access and delivery. Little is known about whether lockdowns disproportionally impacted vulnerable groups, including people who misuse substances, domestic violence or abuse victims, those with intellectual disability, and children with safeguarding concerns. AIM: To evaluate the impact of UK COVID-19 lockdowns on primary care contact rates among vulnerable groups. DESIGN & SETTING: Natural experimental design using all registered patients in the OpenSAFELY platform. METHOD: With approval from NHS England, we conducted controlled interrupted time-series analyses on 24million patients in England between September2019-September2021. RESULTS: Pre-pandemic, primary care consultation rates were 110.1 per 1000 patients per week. Following the initiation of the first lockdown (23/03/2020), there was a large reduction of 29-61 contacts per 1000 patients per week among vulnerable and general population groups. For patients with alcohol misuse, aged ≥14 years with intellectual disability, and children with safeguarding concerns, this reduction was significantly more extreme than corresponding general populations (relative rate difference -23.8 [95% confidence interval -39.8,-7.7], -24.6 [-38.8,-10.5], and -15.4 [-26.9,-3.8], respectively). Following the final lockdown (29/03/2021), all groups had consulting rates exceeding pre-pandemic rates (with increases more marked in vulnerable populations), except those only including children. CONCLUSION: Analyses suggested a larger short-term impact of the first COVID-19 lockdown on primary care contact for some vulnerable groups, compared to the general population; differential impacts persisted through subsequent lockdowns and beyond for some vulnerable groups. There is a need to examine drivers of these differences to enable more equitable primary care access and provision.
Improving GPs' knowledge of the benefits and harms of treatment to support decision making in multimorbidity: qualitative research and co-design of a novel electronic information resource
Background General practitioners (GPs) regularly prescribe prolonged treatments for long-term conditions. However, GPs may benefit from further understanding of the absolute benefits and harms of these treatments, enhancing their ability to engage in shared decision-making and manage multimorbidity and polypharmacy. Aim To produce and evaluate a website to provide information on the benefits and harms of treatments for long-term conditions in a way that can be understood by GPs and potentially integrated into their practice. Methods The study consisted of three parts. First, a qualitative interview study and framework analysis with GPs exploring their attitudes to and understanding of the quantitative benefits and harms of treatments. Second, a participatory co-design process to design the website, coupled with a pragmatic approach to evidence collation to provide clinical content. Finally, an exploratory evaluation study of the website using online focus groups. Results The interview study reported findings on GPs’ understanding of quantitative information on the benefits and harms of treatments which informed the co-design research. The co-design research resulted in the creation of a website, www.gpevidence.org, which presents complex scientific information on treatment effect sizes and the nature and quality of the relevant clinical evidence. The evaluation study showed that participating GPs were able to understand the clinical information on GP Evidence, and that in hypothetical scenarios this might change their prescribing practice. Some participants found some information confusing. There was limited evidence that this new information could be integrated into complex decision-making for multimorbidity and polypharmacy. Conclusion The aim of producing a website able to deliver information on the benefits and harms of treatments for long-term conditions to GPs was achieved. Further research is needed to evaluate the effect of GP Evidence in real-world practice.
How, why, for whom and when do help-seeking interventions for anxiety and depression work among older adults? A realist review
BACKGROUND: A quarter of older adults (aged ≥60 years) in the UK experience a mental health problem each year. Older adults may not seek help due to limited awareness of symptoms of mental ill-health; fear of losing independence; limited access to services. Stigmatised views linked to ageism may also influence help-seeking. AIM: To understand how, why, for whom and in what circumstances interventions to facilitate help-seeking for anxiety and/or depression work among community-dwelling older adults. METHOD: A realist review to identify and synthesise existing evidence of help-seeking interventions for anxiety and/or depression. Systematic search conducted in several databases including MEDLINE, EMBASE, Cochrane Library. A patient/public advisory group (PAG) and expert advisory group contributed to the study design, analysis and conduct. RESULTS: 1095 papers reviewed against inclusion/exclusion criteria; 80 papers identified for full text review and 42 papers included. A variety of interventions were identified including cognitive behavioural therapy, bibliotherapy and befriending, delivered by a diverse range of providers. Help-seeking interventions are complex due to interactions between attitudes, intentions, behaviours but also factors linked to inequalities. Interventions perform better when they support older adults to recognise a problem exists, promote personal agency, include culturally sensitive resources, and adopt a salutogenesis perspective that builds on individual strengths. Interventions are generally under-theorised when it comes to help-seeking. CONCLUSION: The review will generate a programme theory to inform future help-seeking initiatives and suggestions for interventions that may be more accessible to older adults and service users experiencing mental health difficulties.
The impact of weight loss interventions on disordered eating symptoms in people with overweight and obesity: a systematic review & meta-analysis
Background: It is unclear whether weight loss interventions worsen disordered eating in people living with overweight/obesity. We aimed to systematically evaluate the association between weight loss interventions and disordered eating. Methods: Six databases were searched from inception until September 2024. Trials of weight loss interventions in people with overweight/obesity were included if they reported a validated score for disordered eating on either the Eating Disorder Examination Interview or the Eating Disorder Examination Questionnaire pre- and post-intervention. Interventions included behavioural weight loss programmes (BWL) and pharmacotherapy licenced for weight loss, with or without concurrent psychological support, provided for at least 4 weeks. Pooled standardised mean differences (SMD) in scores of disordered eating were calculated using random effects meta-analyses. Risk of bias (RoB) was assessed using the Cochrane RoB 2 tool and the Newcastle–Ottawa scale for randomised and single-arm trials, respectively (PROSPERO ID: CRD42023404792). Findings: Thirty-eight studies with 66 eligible arms (61 interventions: 29 BWL, 11 BWL + pharmacotherapy, 20 BWL + psychological intervention, 1 pharmacotherapy + psychological intervention) and 3364 participants in total were included. The mean weight change was −4.7 kg (95% CI: −5.7, −3.7). Compared with baseline, disordered eating scores improved by −1.47 SMD units (95% CI: −1.67, −1.27, p < 0.001, I2 = 94%) at intervention completion (median of 4 months). Seven randomised trials that directly compared a weight loss intervention to no/minimal intervention reported an improvement of −0.49 SMD units (95% CI, −0.93, −0.04, p = 0.0035, I2 = 73%). Sub-group analyses showed: (a) disordered eating scores improved more in people with an eating disorder at baseline compared with people without high scores, (b) no clear evidence that the association depended upon intervention type, and (c) disordered eating scores improved more in trials rated at low overall RoB. Interpretation: Despite heterogeneity in effect size, weight loss interventions consistently improved disordered eating scores. These findings provide reassurance that weight loss interventions might not worsen disordered eating and may improve it. Funding: Novo Nordisk UK Research Foundation Doctoral Fellowship in Clinical Diabetes.
Addressing the Environmental Impact of Pharmaceuticals: A Call to Action
The contribution of health care to environmental and climate crises is significant, under-addressed, and with consequences for human health. This editorial is a call to action. Focusing on pharmaceuticals as a major environmental threat, we examine pharmaceutical impacts across their lifecycle, summarising greenhouse gas emissions, pollution, and biodiversity loss, and outlining challenges and opportunities to reduce this impact. We urge health care decision-makers and providers to urgently consider environmental factors in their decision-making relating to both policy, and practice, promoting actions such as rational prescribing, non-pharmaceutical interventions, and research and advocacy for sustainable production, procurement, and use.
Intervention development and optimisation of a multi-component digital intervention for the monitoring and management of hypertensive pregnancy: the My Pregnancy Care Intervention
Background: Hypertensive disorders of pregnancy affect around 10% of pregnancies and remain a major cause of maternal and foetal morbidity and mortality. Trials have shown that self-monitoring blood pressure during pregnancy is safe, but self-monitoring alone does not improve blood pressure control or pregnancy outcomes. This study aimed to develop and optimise a multicomponent intervention to support blood pressure monitoring, hypertension management and urine testing within current care pathways. Methods: Relevant literature, input from patient and public contributors (PPI) and stakeholder groups, and the researcher’s previous experience were used to develop an initial intervention. Think-aloud interviews and focus groups with women from diverse backgrounds with lived experience of hypertension in pregnancy and healthcare professionals provided feedback on the intervention prototype (n = 29). The MRC Framework for Developing Complex Interventions guided the processes to optimise the intervention’s acceptability and maximise engagement. A detailed tabulation of participants’ views and logic models was produced using the COM-B model of Behaviour Change. Results: The prototype intervention was acceptable and viable to both pregnant women with experience of hypertensive pregnancy and healthcare professionals. Emerging themes centred on how the intervention could be optimised within current National Health Service care pathways and the lives of pregnant women to support behaviour change. Key target behaviours to support the intervention included increasing understanding of blood pressure management, engagement with the intervention, monitoring blood pressure and urine and taking appropriate actions based on those readings. This informed the development of recommendations involving clear action timelines for women and evidence-based guidance to support decision-making by healthcare professionals. The findings were used to produce the multi-component My Pregnancy Care intervention, consisting of a smartphone application and an information leaflet to support blood pressure self-monitoring and proteinuria self-testing, self-management of antihypertensive medication and smartphone application use. Conclusions: This research provided comprehensive insight into the needs of pregnant women with hypertension and their healthcare teams regarding self-monitoring and management of blood pressure. This supported the development of a tailored multi-component digital intervention that addresses barriers to blood pressure self-management by being user-friendly, persuasive and acceptable. It is hoped that the intervention will support the monitoring and management process, collaboration between healthcare professionals and women, clinical action and improved clinical outcomes.
Uncertainty Quantification in Cost-effectiveness Analysis for Stochastic-based Infectious Disease Models: Insights from Surveillance on Lymphatic Filariasis.
Cost-effectiveness analyses (CEA) typically involve comparing effectiveness and costs of one or more interventions compared to standard of care, to determine which intervention should be optimally implemented to maximise population health within the constraints of the healthcare budget. Traditionally, cost-effectiveness evaluations are expressed using incremental cost-effectiveness ratios (ICERs), which are compared with a fixed willingness-to-pay (WTP) threshold. Due to the existing uncertainty in costs for interventions and the overall burden of disease, particularly with regard to diseases in populations that are difficult to study, it becomes important to consider uncertainty quantification whilst estimating ICERs. To tackle the challenges of uncertainty quantification in CEA, we propose an alternative paradigm utilizing the Linear Wasserstein framework combined with Linear Discriminant Analysis (LDA) using a demonstrative example of lymphatic filariasis (LF). This approach uses geometric embeddings of the overall costs for treatment and surveillance, disability-adjusted lifeyears (DALYs) averted for morbidity by quantifying the burden of disease due to the years lived with disability, and probabilities of local elimination over a time-horizon of 20 years to evaluate the cost-effectiveness of lowering the stopping thresholds for post-surveillance determination of LF elimination as a public health problem. Our findings suggest that reducing the stopping threshold from <1% to <0.5% microfilaria (mf) prevalence for adults aged 20 years and above, under various treatment coverages and baseline prevalences, is cost-effective. When validated on 20% of test data, for 65% treatment coverage, a government expenditure of WTP ranging from $500 to $3,000 per 1% increase in local elimination probability justifies the switch to the lower threshold as cost-effective. Stochastic model simulations often lead to parameter and structural uncertainty in CEA. Uncertainty may impact the decisions taken, and this study underscores the necessity of better uncertainty quantification techniques within CEA for making informed decisions.