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Preferences for multi-cancer tests (MCTs) in primary care: discrete choice experiments of general practitioners and the general public in England
Background: Multi-Cancer tests (MCTs) hold potential to detect cancer across multiple sites and some predict the origin of the cancer signal. Understanding stakeholder preferences for MCTs could help to develop appealing MCTs, encouraging their adoption. Methods: Discrete Choice Experiments (DCEs) conducted online in England. Results: GPs (n = 251) and the general public (n = 1005) preferred MCTs that maximised negative predictive value, positive predictive value, and could test for a larger number of cancer sites. A reduction of the NPV of 4.0% was balanced by a 12.5% increase in the PPV for people and a 32.5% increase in PPV for GPs. People from ethnic minority backgrounds placed less importance on whether MCTs can detect multiple cancers. People with more knowledge and experience of cancer placed substantial importance on the MCT being able to detect cancer at an early stage. Both GPs and members of the public preferred the MCT reported in the SYMPLIFY study to FIT, PSA, and CA125, and preferred the SYMPLIFY MCT to 91% (GPs) and 95% (people) of 2048 simulated MCTs. Conclusions: These findings provide a basis for designing clinical implementation strategies for MCTs, according to their performance characteristics.
Is “nature” a policy solution to mental health in schools?
The UK faces a growing youth mental health crisis (NHS, 2023; RCPsych 2025). Schools may play a key role in preventing these difficulties from worsening. The integration of nature-based programs (NbPs) into school settings has been proposed as a policy solution to address such mental health challenges but robust evidence is lacking (Lomax et al., 2024), particularly at the secondary school level. This Sprint utilised an implementation science framework to co-produce evidence on NbPs in secondary schools with stakeholders including policymakers from the Government’s Department for Education (DfE), young people, and educators. Using a range of methodologies we are evaluating effectiveness, amplifying stakeholder voices, and creating actionable, evidence-based education policy insights.
Variation in duration of repeat prescriptions: a primary care cohort study in England
Background Many patients receive repeat prescriptions for routine medications used to treat chronic conditions. Doctors typically issue repeat prescriptions with durations ranging from 28 to 84 days. There is currently no national guidance in England for the optimal prescription duration for routine medications. Aim To evaluate current prescription durations for five common routine medications in England; explore and visualise geographical variation; and identify practice factors that are associated with shorter prescribing duration to inform policy making. Design and setting A retrospective cohort study of NHS primary care prescribing data in England from December 2018 to November 2019. Method The prescription duration was analysed for five common routine medications in England; ramipril, atorvastatin, simvastatin, levothyroxine, and amlodipine. Variation was assessed between regional clinical commissioning groups (CCGs), and practice factors associated with different durations were identified. Results Of the common medications included, 28-day prescriptions accounted for 48.5% (2.5 billion) tablets/ capsules issued, while 43.6% were issued for 56 days. There was very wide regional variation (7.2%–95.0%) in the proportion of 28-day prescriptions issued by CCGs. Practice dispensing status was the most likely predictor of prescription duration; dispensing practices had a higher 28-day prescribing proportion than non-dispensing practices. The proportion of patients with chronic conditions and the electronic health record system used by a practice were also associated with prescription duration. Conclusion This analysis of OpenPrescribing data showed that repeat prescriptions of 28 days are common for patients taking routine medications for chronic conditions, particularly in dispensing practices. This provides data to inform the policy debate on current practice. Configuration of electronic health record systems offer an opportunity to implement and evaluate new policies on repeat prescription duration in England.
Cost-effectiveness of a novel AI technology to quantify coronary inflammation and cardiovascular risk in patients undergoing routine coronary computed tomography angiography
AIMS: Coronary computed tomography angiography (CCTA) is a first-line investigation for chest pain in patients with suspected obstructive coronary artery disease (CAD). However, many acute cardiac events occur in the absence of obstructive CAD. We assessed the lifetime cost-effectiveness of integrating a novel artificial intelligence-enhanced image analysis algorithm (AI-Risk) that stratifies the risk of cardiac events by quantifying coronary inflammation, combined with the extent of coronary artery plaque and clinical risk factors, by analysing images from routine CCTA. METHODS AND RESULTS: A hybrid decision-tree with population cohort Markov model was developed from 3393 consecutive patients who underwent routine CCTA for suspected obstructive CAD and followed up for major adverse cardiac events over a median (interquartile range) of 7.7(6.4-9.1) years. In a prospective real-world evaluation survey of 744 consecutive patients undergoing CCTA for chest pain investigation, the availability of AI-Risk assessment led to treatment initiation or intensification in 45% of patients. In a further prospective study of 1214 consecutive patients with extensive guidelines recommended cardiovascular risk profiling, AI-Risk stratification led to treatment initiation or intensification in 39% of patients beyond the current clinical guideline recommendations. Treatment guided by AI-Risk modelled over a lifetime horizon could lead to fewer cardiac events (relative reductions of 11%, 4%, 4%, and 12% for myocardial infarction, ischaemic stroke, heart failure, and cardiac death, respectively). Implementing AI-Risk Classification in routine interpretation of CCTA is highly likely to be cost-effective (incremental cost-effectiveness ratio £1371-3244), both in scenarios of current guideline compliance, or when applied only to patients without obstructive CAD. CONCLUSIONS: Compared with standard care, the addition of AI-Risk assessment in routine CCTA interpretation is cost-effective, by refining risk-guided medical management.
Risk of bias in routine mental health outcome data: The case of Health of the Nation Outcome Scales
Background Routine outcome data in secondary mental health services have significant potential for service planning, evaluation and research. Expanding the collection and use of these data is an ongoing priority in the National Health Service (NHS), but inconsistent use threatens their validity and utility. If recording is more likely among certain patient groups or at specific stages of treatment, measured outcomes may be biased and unreliable. Objective The objective is to assess the scale, determinants and implications of incomplete routine outcome measurement in a secondary mental health provider, using the example of the widely collected Health of the Nation Outcome Scores (HoNOS). Methods A retrospective cohort study was conducted using routine HoNOS assessments and episodes of care for patients receiving secondary mental healthcare from an NHS Trust in Southeast England between 2016 and 2022 (n=30 341). Associations among demographic, clinical and service factors, and rates and timings of HoNOS assessments were explored with logistic regressions. Relationships between total HoNOS scores and related mental health outcomes (costs, relapse and improvement between assessments) were estimated after adjusting for the likelihood of assessment. Findings 66% of patients (n=22 288) had a recorded HoNOS assessment. Of the distinct episodes of care for these patients (n=65 439), 43% (n=28 170) were linked to any assessment, 25% (n=16 131) were linked to an initial baseline assessment, while 4.7% (n=3 094) were linked to multiple HoNOS assessments, allowing for evaluation of clinical progress. Likelihood and timing of assessment were significantly associated with a range of factors, including service type, diagnosis, ethnicity, age and gender. After adjusting for observed factors determining the likelihood of assessment, the strength of association between HoNOS scores and overall costs was significantly reduced. Conclusion Most of the activity observed in this study cannot be evaluated with HoNOS. HoNOS assessments are highly unlikely to be missing at random. Without approaches to correct for substantial gaps in routine outcome data, evaluations based on these may be systematically biased, limiting their usefulness for service-level decision-making. Clinical implications Routine outcome collection must increase significantly to successfully implement proposed strategies for outcome assessment in community mental healthcare without inconsistent records undermining the use of resulting data.
Long-term outcomes after stress echocardiography in real-world practice: a 5-year follow-up of the UK EVAREST study
Aims Stress echocardiography is widely used to assess patients with chest pain. The clinical value of a positive or negative test result to inform on likely longer-term outcomes when applied in real-world practice across a healthcare system has not been previously reported. Methods Five thousand five hundred and three patients recruited across 32 UK NHS hospitals between 2018 and 2022, participating and results in the EVAREST/BSE-NSTEP prospective cohort study, with data on medical outcomes up to 2023 available from NHS England were included in the analysis. Stress echocardiography results were related to outcomes, including death, procedures, hospital admissions, and relevant cardiovascular diagnoses, based on Kaplan–Meier analysis and Cox proportional hazard ratios (HRs). Median follow-up was 829 days (interquartile range 224–1434). A positive stress echocardiogram was associated with a greater risk of myocardial infarction [HR 2.71, 95% confidence interval (CI) 1.73–4.24, P < 0.001] and a composite endpoint of cardiac-related mortality and myocardial infarction (HR 2.03, 95% CI 1.41–2.93, P < 0.001). Hazard ratios increased with ischaemic burden. A negative stress echocardiogram identified an event-free ‘warranty period’ of at least 5 years in patients with no prior history of coronary artery disease and 4 years for those with disease. Conclusion In real-world practice, the degree of myocardial ischaemia recorded by clinicians at stress echocardiography correctly categorizes risk of future events over the next 5 years. Reporting a stress echocardiogram as negative correctly identifies patients with no greater than a background risk of cardiovascular events over a similar time period.
Critical components of 'Early Intervention in Psychosis': National retrospective cohort study
Background Psychotic disorders are severe mental health conditions frequently associated with long-term disability, reduced quality of life and premature mortality. Early Intervention in Psychosis (EIP) services aim to provide timely, comprehensive packages of care for people with psychotic disorders. However, it is not clear which components of EIP services contribute most to the improved outcomes they achieve. Aims We aimed to identify associations between specific components of EIP care and clinically significant outcomes for individuals treated for early psychosis in England. Method This national retrospective cohort study of 14 874 EIP individuals examined associations between 12 components of EIP care and outcomes over a 3-year follow-up period, by linking data from the National Clinical Audit of Psychosis (NCAP) to routine health outcome data held by NHS England. The primary outcome was time to relapse, defined as psychiatric inpatient admission or referral to a crisis resolution (home treatment) team. Secondary outcomes included duration of admissions, detention under the Mental Health Act, emergency department and general hospital attendances and mortality. We conducted multilevel regression analyses incorporating demographic and service-level covariates. Results Smaller care coordinator case-loads and the use of clozapine for eligible people were associated with reduced relapse risk. Physical health interventions were associated with reductions in mortality risk. Other components, such as cognitive-behavioural therapy for psychosis (CBTp), showed associations with improvements in secondary outcomes. Conclusions Smaller case-loads should be prioritised and protected in EIP service design and delivery. Initiatives to improve the uptake of clozapine should be integrated into EIP care. Other components, such as CBTp and physical health interventions, may have specific benefits for those eligible. These findings highlight impactful components of care and should guide resource allocation to optimise EIP service delivery.
Value-Based Commissioning of Mental Health Services in England: A Feasibility Study Using Multicriteria Decision Analysis
Objectives: Improving mental health services through value-based investment is high priority in healthcare systems globally. However, there is lack of comprehensive and robust evidence on the value for money of these services that incorporates several value elements and public preferences. This study aims to demonstrate the application of multicriteria decision analysis (MCDA) in the assessment of 2 early intervention in psychosis (EIP) services in England. Methods: An MCDA-based evaluation using patient records was conducted to evaluate the value-for-money of 2 EIP services in South-East England: Oxfordshire (EIP-Oxf) and Buckinghamshire (EIP-Bucks). The assessment considered 5 value elements: years of life, quality of life (time to relapse), patient experience (disengagement rates), health inequality (time-to-relapse disparity), and average annual cost. Performance on each value element was estimated using generalized linear models and propensity score matching on electronic health records of 1127 patients. Total MCDA scores integrated standardized predicted means with relative weights that were derived in a previous study. Robustness was assessed using probabilistic sensitivity analysis and service affordability was illustrated in conditional multiattribute acceptability curves. Results: EIP-Oxf outperformed EIP-Bucks in overall scores (0.563 vs 0.552) and offered higher value per pound spend according to cost-per-value ratios (£10 438 per unit of value vs £12 655). Results were driven by lower annual cost per patient and health inequality in EIP-Oxf. Conclusions: MCDA can facilitate value-for-money assessments of mental health services, addressing gaps in comprehensive rationing frameworks. This approach provides a systematic, evidence-driven method for local decision making, with potential for broader healthcare applications.
Challenges and solutions to system-wide use of precision oncology as the standard of care paradigm.
The personalised oncology paradigm remains challenging to deliver despite technological advances in genomics-based identification of actionable variants combined with the increasing focus of drug development on these specific targets. To ensure we continue to build concerted momentum to improve outcomes across all cancer types, financial, technological and operational barriers need to be addressed. For example, complete integration and certification of the 'molecular tumour board' into 'standard of care' ensures a unified clinical decision pathway that both counteracts fragmentation and is the cornerstone of evidence-based delivery inside and outside of a research setting. Generally, integrated delivery has been restricted to specific (common) cancer types either within major cancer centres or small regional networks. Here, we focus on solutions in real-world integration of genomics, pathology, surgery, oncological treatments, data from clinical source systems and analysis of whole-body imaging as digital data that can facilitate cost-effectiveness analysis, clinical trial recruitment, and outcome assessment. This urgent imperative for cancer also extends across the early diagnosis and adjuvant treatment interventions, individualised cancer vaccines, immune cell therapies, personalised synthetic lethal therapeutics and cancer screening and prevention. Oncology care systems worldwide require proactive step-changes in solutions that include inter-operative digital working that can solve patient centred challenges to ensure inclusive, quality, sustainable, fair and cost-effective adoption and efficient delivery. Here we highlight workforce, technical, clinical, regulatory and economic challenges that prevent the implementation of precision oncology at scale, and offer a systematic roadmap of integrated solutions for standard of care based on minimal essential digital tools. These include unified decision support tools, quality control, data flows within an ethical and legal data framework, training and certification, monitoring and feedback. Bridging the technical, operational, regulatory and economic gaps demands the joint actions from public and industry stakeholders across national and global boundaries.
Incorporating Complexity and System Dynamics into Economic Modelling for Mental Health Policy and Planning
Care as usual has failed to stem the tide of mental health challenges in children and young people. Transformed models of care and prevention are required, including targeting the social determinants of mental health. Robust economic evidence is crucial to guide investment towards prioritised interventions that are effective and cost-effective to optimise health outcomes and ensure value for money. Mental healthcare and prevention exhibit the characteristics of complex dynamic systems, yet dynamic simulation modelling has to date only rarely been used to conduct economic evaluation in this area. This article proposes an integrated decision-making and planning framework for mental health that includes system dynamics modelling, cost-effectiveness analysis, and participatory model-building methods, in a circular process that is constantly reviewed and updated in a ‘living model’ ecosystem. We describe a case study of this approach for mental health system policy and planning that synergises the unique attributes of a system dynamics approach within the context of economic evaluation. This kind of approach can help decision makers make the most of precious, limited resources in healthcare. The application of modelling to organise and enable better responses to the youth mental health crisis offers positive benefits for individuals and their families, as well as for taxpayers.
Unravelling Elements of Value of Healthcare and Assessing their Importance Using Evidence from Two Discrete-Choice Experiments in England
Background: Health systems are moving towards value-based care, implementing new care models that allegedly aim beyond patient outcomes. Therefore, a policy and academic debate is underway regarding the definition of value in healthcare, the inclusion of costs in value metrics, and the importance of each value element. This study aimed to define healthcare value elements and assess their relative importance (RI) to the public in England. Method: Using data from 26 semi-structured interviews and a literature review, and applying decision-theory axioms, we selected a comprehensive and applicable set of value-based elements. Their RI was determined using two discrete choice experiments (DCEs) based on Bayesian D-efficient DCE designs, with one DCE incorporating healthcare costs expressed as income tax rise. Respondent preferences were analysed using mixed logit models. Results: Six value elements were identified: additional life-years, health-related quality of life, patient experience, target population size, equity, and cost. The DCE surveys were completed by 402 participants. All utility coefficients had the expected signs and were statistically significant (p < 0.05). Additional life-years (25.3%; 95% confidence interval [CI] 22.5–28.6%) and patient experience (25.2%; 95% CI 21.6–28.9%) received the highest RI, followed by target population size (22.4%; 95% CI 19.1–25.6%) and quality of life (17.6%; 95% CI 15.0–20.3%). Equity had the lowest RI (9.6%; 95% CI 6.4–12.1%), decreasing by 8.8 percentage points with cost inclusion. A similar reduction was observed in the RI of quality of life when cost was included. Conclusion: The public prioritizes value elements not captured by conventional metrics, such as quality-adjusted life-years. Although cost inclusion did not alter the preference ranking, its inclusion in the value metric warrants careful consideration.
Self-poisoning with paracetamol in England: Short report of characteristics of individuals and their overdoses according to source of tablets
Self-poisoning with paracetamol is the most frequently used overdose method in the UK. Psychosocial assessments were conducted by mental health clinicians with 127 consecutive individuals who presented with pure paracetamol overdoses to a large general hospital over 8 months, including asking about the source of the tablets and scoring the patients' acts on the Beck Suicide Intent scale (BSI). Patients were predominantly female (86%) and young (79% aged 12-24 years). Most had used paracetamol which was available in the home (77%). Those who purchased paracetamol for the act took double the number of tablets compared with those who used paracetamol available in the home (37 v. 18), had higher suicidal intent (mean BSI: 11 v. 7) and more often required treatment with N-acetyl cysteine (71% v. 43%). These results highlight the need for safer home storage of paracetamol and consideration of reducing pack size limits on paracetamol that can be purchased.
The impact of a new approach to family safeguarding in social care: Initial findings from an analysis of routine data
Child safeguarding services intervene when a child is at risk of serious emotional or physical harm. Oxfordshire County Council is implementing a new approach to child safeguarding (Family Solutions Plus [FSP]) with a greater focus on whole family support and reducing the need for foster care. We sampled two cohorts of children closed within 1 year and examined the time spent in services. The sample included 474 children entering services before the new model's implementation and 561 children after. A greater proportion of children receiving FSP required a single care plan before their case was closed (85.9%; 69.4%, p < 0.001) and only experienced the lowest level plan (74.5%; 61.8%, p < 0.001). On average, this group spent less time in services for the period being observed (MD = 17.58, 95% confidence interval = 6.19, 28.96). At this early stage, no significant reduction in the number of children requiring foster care was seen (5.5%; 3.9%, p = 0.23). These initial findings suggest a potential association of FSP with a reduced number and level of care plans as well as length of time. Local authorities in England may investigate further whether FSP is a potentially useful model in improving safeguarding services.
A cloud-based medical device for predicting cardiac risk in suspected coronary artery disease: a rapid review and conceptual economic model
Background: The CaRi-Heart® device estimates risk of 8-year cardiac death, using a prognostic model, which includes perivascular fat attenuation index, atherosclerotic plaque burden and clinical risk factors. Objectives: To provide an Early Value Assessment of the potential of CaRi-Heart Risk to be an effective and cost-effective adjunctive investigation for assessment of cardiac risk, in people with stable chest pain/suspected coronary artery disease, undergoing computed tomography coronary angiography. This assessment includes conceptual modelling which explores the structure and evidence about parameters required for model development, but not development of a full executable cost-effectiveness model. Data sources: Twenty-four databases, including MEDLINE, MEDLINE In-Process and EMBASE, were searched from inception to October 2022. Methods: Review methods followed published guidelines. Study quality was assessed using Prediction model Risk Of Bias ASsessment Tool. Results were summarised by research question: prognostic performance; prevalence of risk categories; clinical effects; costs of CaRi-Heart. Exploratory searches were conducted to inform conceptual cost-effectiveness modelling. Results: The only included study indicated that CaRi-Heart Risk may be predictive of 8 years cardiac death. The hazard ratio, per unit increase in CaRi-Heart Risk, adjusted for smoking, hypercholesterolaemia, hypertension, diabetes mellitus, Duke index, presence of high-risk plaque features and epicardial adipose tissue volume, was 1.04 (95% confidence interval 1.03 to 1.06) in the model validation cohort. Based on Prediction model Risk Of Bias ASsessment Tool, this study was rated as having high risk of bias and high concerns regarding its applicability to the decision problem specified for this Early Value Assessment. We did not identify any studies that reported information about the clinical effects or costs of using CaRi-Heart to assess cardiac risk. Exploratory searches, conducted to inform the conceptual cost-effectiveness modelling, indicated that there is a deficiency with respect to evidence about the effects of changing existing treatments or introducing new treatments, based on assessment of cardiac risk (by any method), or on measures of vascular inflammation (e.g. fat attenuation index). A de novo conceptual decision-analytic model that could be used to inform an early assessment of the cost effectiveness of CaRi-Heart is described. A combination of a short-term diagnostic model component and a long-term model component that evaluates the downstream consequences is anticipated to capture the diagnosis and the progression of coronary artery disease. Limitations: The rapid review methods and pragmatic additional searches used to inform this Early Value Assessment mean that, although areas of potential uncertainty have been described, we cannot definitively state where there are evidence gaps. Conclusions: The evidence about the clinical utility of CaRi-Heart Risk is underdeveloped and has considerable limitations, both in terms of risk of bias and applicability to United Kingdom clinical practice. There is some evidence that CaRi-Heart Risk may be predictive of 8-year risk of cardiac death, for patients undergoing computed tomography coronary angiography for suspected coronary artery disease. However, whether and to what extent CaRi-Heart represents an improvement relative to current standard of care remains uncertain. The evaluation of the CaRi-Heart device is ongoing and currently available data are insufficient to fully inform the cost-effectiveness modelling. Future work: A large (n = 15,000) ongoing study, NCT05169333, the Oxford risk factors and non-invasive imaging study, with an estimated completion date of February 2030, may address some of the uncertainties identified in this Early Value Assessment. Study registration: This study is registered as PROSPERO CRD42022366496. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Evidence Synthesis programme (NIHR award ref: NIHR135672) and is published in full in Health Technology Assessment; Vol. 28, No. 31. See the NIHR Funding and Awards website for further award information.
Inflammatory risk and cardiovascular events in patients without obstructive coronary artery disease: the ORFAN multicentre, longitudinal cohort study
Background: Coronary computed tomography angiography (CCTA) is the first line investigation for chest pain, and it is used to guide revascularisation. However, the widespread adoption of CCTA has revealed a large group of individuals without obstructive coronary artery disease (CAD), with unclear prognosis and management. Measurement of coronary inflammation from CCTA using the perivascular fat attenuation index (FAI) Score could enable cardiovascular risk prediction and guide the management of individuals without obstructive CAD. The Oxford Risk Factors And Non-invasive imaging (ORFAN) study aimed to evaluate the risk profile and event rates among patients undergoing CCTA as part of routine clinical care in the UK National Health Service (NHS); to test the hypothesis that coronary arterial inflammation drives cardiac mortality or major adverse cardiac events (MACE) in patients with or without CAD; and to externally validate the performance of the previously trained artificial intelligence (AI)-Risk prognostic algorithm and the related AI-Risk classification system in a UK population. Methods: This multicentre, longitudinal cohort study included 40 091 consecutive patients undergoing clinically indicated CCTA in eight UK hospitals, who were followed up for MACE (ie, myocardial infarction, new onset heart failure, or cardiac death) for a median of 2·7 years (IQR 1·4–5·3). The prognostic value of FAI Score in the presence and absence of obstructive CAD was evaluated in 3393 consecutive patients from the two hospitals with the longest follow-up (7·7 years [6·4–9·1]). An AI-enhanced cardiac risk prediction algorithm, which integrates FAI Score, coronary plaque metrics, and clinical risk factors, was then evaluated in this population. Findings: In the 2·7 year median follow-up period, patients without obstructive CAD (32 533 [81·1%] of 40 091) accounted for 2857 (66·3%) of the 4307 total MACE and 1118 (63·7%) of the 1754 total cardiac deaths in the whole of Cohort A. Increased FAI Score in all the three coronary arteries had an additive impact on the risk for cardiac mortality (hazard ratio [HR] 29·8 [95% CI 13·9–63·9], p<0·001) or MACE (12·6 [8·5–18·6], p<0·001) comparing three vessels with an FAI Score in the top versus bottom quartile for each artery. FAI Score in any coronary artery predicted cardiac mortality and MACE independently from cardiovascular risk factors and the presence or extent of CAD. The AI-Risk classification was positively associated with cardiac mortality (6·75 [5·17–8·82], p<0·001, for very high risk vs low or medium risk) and MACE (4·68 [3·93–5·57], p<0·001 for very high risk vs low or medium risk). Finally, the AI-Risk model was well calibrated against true events. Interpretation: The FAI Score captures inflammatory risk beyond the current clinical risk stratification and CCTA interpretation, particularly among patients without obstructive CAD. The AI-Risk integrates this information in a prognostic algorithm, which could be used as an alternative to traditional risk factor-based risk calculators. Funding: British Heart Foundation, NHS-AI award, Innovate UK, National Institute for Health and Care Research, and the Oxford Biomedical Research Centre.
Rationing in an Era of Multiple Tight Constraints: Is Cost-Utility Analysis Still Fit for Purpose?
Cost-utility analysis may not be sufficient to support reimbursement decisions when the assessed health intervention requires a large proportion of the healthcare budget or when the monetary healthcare budget is not the only resource constraint. Such cases include joint replacement, coronavirus disease 2019 (COVID-19) interventions and settings where all resources are constrained (e.g. post-COVID-19 or in low/middle-income countries). Using literature on health technology assessment, rationing and reimbursement in healthcare, we identified seven alternative frameworks for simultaneous decisions about (dis)investment and proposed modifications to deal with multiple resource constraints. These frameworks comprised constrained optimisation; cost-effectiveness league table; ‘step-in-the-right-direction’ approach; heuristics based on effective gradients; weighted cost-effectiveness ratios; multicriteria decision analysis (MCDA); and programme budgeting and marginal analysis (PBMA). We used numerical examples to demonstrate how five of these alternative frameworks would operate. The modified frameworks we propose could be used in local commissioning and/or health technology assessment to supplement standard cost-utility analysis for interventions that have large budget impact and/or are subject to additional constraints.
Cost-effectiveness of therapist-assisted internet-delivered psychological therapies for PTSD differing in trauma focus in England: an economic evaluation based on the STOP-PTSD trial
Background: Although there are effective psychological treatments for post-traumatic stress disorder (PTSD), they remain inaccessible for many people. Digitally enabled therapy is a way to overcome this problem; however, there is little evidence on which forms of these therapies are most cost effective in PTSD. We aimed to assess the cost-effectiveness of the STOP-PTSD trial, which evaluated two therapist-assisted, internet-delivered cognitive behavioural therapies: cognitive therapy for PTSD (iCT-PTSD) and a programme focusing on stress management (iStress-PTSD). Methods: In this health economic evaluation, we used data from the STOP-PTSD trial (n=217), a single-blind, randomised controlled trial, to compare iCT-PTSD and iStress-PTSD in terms of resource use and health outcomes. In the trial, participants (aged ≥18 years) who met DSM-5 criteria for PTSD were recruited from primary care therapy services in South East England. The interventions were delivered online with therapist support for the first 12 weeks, and three telephone calls over the next 3 months. Participants completed questionnaires on symptoms, wellbeing, quality of life, and resource use at baseline, 13 weeks, 26 weeks, and 39 weeks after randomisation. We used a cost-effectiveness analysis to assess cost per quality-adjusted life year (QALY) at 39 weeks post-randomisation, from the perspective of the English National Health Service (NHS) and personal social services and on the basis of intention-to-treat for complete cases. Treatment modules and the platform design were developed with extensive input from service users: service users also advised on the trial protocol and methods, including the health economic measures. This is a pre-planned analysis of the STOP-PTSD trial; the trial was registered prospectively on the ISRCTN Registry (ISRCTN16806208). Findings: NHS costs were similar across treatment groups, but clinical outcomes were superior for iCT-PTSD compared with iStress-PTSD. The incremental cost-effectiveness ratio for NHS costs and personal social services was estimated as £1921 per QALY. iCT-PTSD had an estimated 91·6% chance of being cost effective at the £20 000 per QALY threshold. From the societal perspective, iCT-PTSD was cost saving compared with iStress-PTSD. Interpretation: iCT-PTSD is a cost-effective form of therapist-assisted, internet-delivered psychological therapy relative to iStress-PTSD, and it could be considered for clinical implementation. Funding: Wellcome Trust and National Institute of Health Research Oxford Health Biomedical Research Centre.