Our latest research, all in one place. Browse our collection of journal articles, reports and conference proceedings to see how we’re contributing to HEOR research. Remember to:
OBJECTIVES: Healthcare systems are increasingly using 'precision medicine' to ensure that patients receive the most appropriate treatment. Whilst the benefits of precision medicine are widely discussed, there is less discussion around the circumstances where precision medicine is most likely to reap benefits, and even less discussion around the potential downsides of precision medicine. This study aims to address these points.
METHODS: A hypothetical case study was developed that with two available treatments: T1 (with an effectiveness rate of 90%) and T2 (effectiveness = 60%). Different scenarios are run, where the individual patients who would benefit from T2 are (i) entirely 'within' the 90% that would also benefit from T1, (ii) covering the 10% who would not benefit from T1 but also including some would benefit from T1, and (iii) an 'overlapping' case in-between. For each scenario, two options were assessed: 'With precision medicine' (i.e. the decision maker can identify which patients will benefit from each treatment) and 'no precision medicine'.
RESULTS: In all scenarios, total population health increased when precision medicine would be applied. Costs were reduced in all scenarios, although this did not include the cost of implementing the precision medicine approach itself. Decision making was shown to be more complex, because precision medicine would introduce multiple layers of decisions. Data requirements were greatly increased with precision medicine, and decision uncertainty was also greater (due to smaller sample sizes within smaller subgroups). In a health system that uses value-based pricing, value was shown not to increase, since the price of treatments would likely increase in line with the improved effectiveness due to precision medicine methods.
CONCLUSIONS: In the case study presented, precision medicine methods delivered increase population health, but the value for money varied considerably between scenarios. Better understanding of disease areas in which precision medicine will benefit patients is essential.
Health technology assessment (HTA) evaluates the benefits of medical technologies and helps determine the value of a diagnostic or medical intervention and whether it should be made available in a health system. Real World Evidence (RWE) provides insights on how technologies are used and perform in a real world setting and is becoming increasingly important for reimbursement and regulatory decision making.
HTA submissions typically use generic frameworks for assessing medical innovations, which are not specific for diagnostics or medical devices, and may hinder how their value is measured and evaluated. Additionally, these frameworks may not include RWE, which is important to enable a complete evaluation of evidence, particularly for medical devices.
This forum aims to highlight opportunities for improvements to HTA frameworks to more fully capture the value of diagnostics and medical devices. Case studies will be used to illustrate uses of RWE and the importance of including a tailored evidence evaluation framework for diagnostics and medical devices. The forum will also include a state of the art discussion on the methods to evaluate diagnostic tests (Dr. Lavinia Ferrante), a presentation on the current challenges experienced by HTAs for the assessment on these technologies (Mr. David Tamblyn), and a discussion with two medical device companies (representatives: Lindsay Bockstedt and Chiara Capobianco) presenting their approaches in using RWE, and sharing how evidence standards may evolve as RWE becomes more widely accepted. The panel will conclude with questions from the moderator and the audience.
OBJECTIVES: Healthcare's supply chain contributes 62% of the 25 million tonnes of CO2e emissions generated by the UK National Health Services per annum. Changing from single use equipment to reusable equivalent can reduce CO2e up to 56%. The SHTG recognized the need to evaluate the environmental credentials of single use equipment through a parallel assessment alongside a health economic analysis. This novel research is the first UK parallel assessment published the Scottish Health Technologies Group (SHTG). An innovative hybrid approach utilized multidisciplinary methods to overcome data challenges. The findings of the report are in line with research and provides important methods for HTA sustainability globally.
METHODS: Applying environmental management frameworks, a carbon footprint of single use rhinolaryngoscopes was compared with a reusable equivalent. Data collection techniques included questionnaires, interviews and the use of guidance for technological representativeness were used to quantify national GHG emissions and waste volumes. The technologies were categorized using thresholds based on the functional unit, to strengthen support for the HTA decision making process. Sensitivity analyses were performed.
RESULTS: The carbon emissions of a single use flexible rhinolaryngoscope compared to its reusable equivalent was 6.03kgCO2e and 3.26kgCO2e respectively. Data extrapolation reveals the annual environmental impact of this technology, throughout NHS Scotland, to be 13,652kgCO2e and 7,381kgCO2e, for the single use and reusable devices, respectively. Raw material acquisition, the use of personal protective equipment and transportation were carbon hotspots. Use of the single use devices generates 12.58 tonnes of waste per year further burdening healthcare resources. This pilot study recommends the use a reusable equivalent in this setting.
CONCLUSIONS: Aligned with NHS net zero targets, these findings confirm the need to perform a parallel environmental assessment of technologies alongside a health economic analysis. Data constraints can be overcome using hybrid methodologies. This work support policy development in HTA sustainability framework development.
BACKGROUND: Three recent randomized controlled trials demonstrated that, in patients with symptomatic paroxysmal atrial fibrillation (PAF), first-line pulmonary vein isolation with cryoballoon catheter ablation reduces atrial arrhythmia recurrence compared to initial antiarrhythmic drug (AAD) therapy. This study aimed to evaluate the cost-effectiveness of first-line cryoablation compared to first-line AADs from a German healthcare payer perspective.
METHODS: Individual patient-level data from 703 participants with untreated PAF enrolled into three randomized clinical trials (Cryo-FIRST, STOP AF First and EARLY-AF) were used to derive parameters for the cost-effectiveness model (CEM).
The CEM structure consisted of a hybrid decision tree and Markov model. The decision tree (one-year time horizon) informed initial health state allocation in the first cycle of the Markov model (40-year time horizon; three-month cycle length). Health benefits were expressed in quality-adjusted life years (QALYs). Cost inputs were sourced from German diagnosis-related groups and the Institute for the Hospital Remuneration System (InEK). Costs and benefits were discounted at 3% per annum.
RESULTS: Cryoablation was cost-effective, incurring ~ €200 per patient while offering an increase in QALYs (~ 0.18) over a lifetime. This produced an average incremental cost-effectiveness ratio of ~ €1,000 per QALY gained. Individuals were expected to receive ~ 1.2 ablations over a lifetime, regardless of initial treatment. However, those initially treated with cryoablation as opposed to AADs experience 0.9 fewer re-ablations and a 45% reduction in time spent in AF health states.
CONCLUSION: Initial rhythm control with cryoballoon ablation in symptomatic PAF is a cost-effective treatment option in a German healthcare setting.
OBJECTIVES: Poor mental wellbeing is one of the leading causes of long-term sickness absence from work despite conditions, such as stress and anxiety, being treatable and often preventable. The aim of this analysis was to conduct economic modelling and provide data on costs and benefits to employers who are considering implementing a workplace intervention to improve wellbeing. Additionally, the analysis was used to assess any changes in employee outcomes (e.g. productivity and staff turnover).
METHODS: A cost-consequence model with a one-year time horizon was developed to assess the impact of workplace mental wellbeing interventions. Because all workplaces are different, it is not useful to present one single base case. Instead, the model generates a series of hypothetical case studies, with varying levels of absenteeism, presenteeism and staff turnover, as well as different levels of productivity and staff replacement costs. Several mental wellbeing interventions were compared with 'no intervention' (current practice) to calculate the total incremental costs and incremental cost per employee.
RESULTS: In the hypothetical case study with 50 employees and an intervention cost of £100, the intervention had a net cost saving of £3,395 per employee. Savings were due to reductions in absenteeism and presenteeism. Sensitivity analysis assessed the impact of varying each input, to reflect that the inputs will vary substantially for each individual organization and setting. The intervention is more likely to be cost saving when the baseline level of absenteeism and staff turnover are high, and the level of presenteeism and intervention cost are low.
CONCLUSIONS: Mental wellbeing interventions may influence a range of outcomes but outcomes demonstrating a mental wellbeing benefit to employees may be challenging to translate into monetary value. The model can be used by decision makers and employers to understand the potential economic and wellbeing implications of implementing a mental wellbeing intervention in the workplace.
OBJECTIVES: In the UK, the National Institute for Health and Care Excellence (NICE) requires that "relevant" cost-effectiveness studies and health-related quality-of-life (HRQoL) data are identified using "systematic" and "transparent" searches and cost and healthcare resource use (CHRU) data are "identified systematically". Systematic literature reviews (SLRs) can be resource intensive and time consuming and this study aims to help determine whether the SLR approach is an efficient use of limited resources.
METHODS: We reviewed what methods companies submitting to NICE claimed to use (systematic versus other), whether their methodologies reflected this, what effect this had on how Technology Appraisals (TAs) were appraised, and what this may mean for acceptability of future methods. A sample of company submission documents for NICE TAs (1 March to 18 June 2024) were retrieved.
RESULTS: 22 TAs were identified. 20 single TAs (STAs) described using SLRs to identify EEs and HRQoL. 19 of these STAs described using SLRs for CHRU data. 1 STA submission did not describe a CHRU SLR, instead using reference costs and a pragmatic review of similar models. The Evidence Assessment Group (EAG) did not comment on this approach in its critique. 2 TAs were rapid assessments, meaning SLRs were not feasible. Instead, a pragmatic approach used evidence from 2 living reviews.
CONCLUSIONS: Economics reviews in NICE TAs continue to mostly be SLRs despite no explicit requirement for this. We identified no explicit criticism from the EAG where a pragmatic approach was taken. Because SLRs expend large resources, this research suggests that a carefully considered pragmatic approach could be sufficient to identify relevant data using transparent and replicable methods. Advances in reviewing — for example the integration of artificial intelligence in record selection or data extraction — may help to bridge the gap and make companies more comfortable in using pragmatic reviews for highly valuable TA submissions.
OBJECTIVES: Modifying the delivery of healthcare in order to reduce environmental will come at some cost, whether that cost is monetary (i.e. expenditure to reduce harmful effects) or via health (patients switching to less harmful, but less cost-effective treatments). This study aimed to estimate the public's views about such trade-offs.
METHODS: 508 members of the public completed a discrete choice experiment (DCE), which asked them to state their preferences between different health system outcomes, measured by (i) life expectancy, (ii) carbon emissions and (iii) impact on biodiversity. Two alternative sets of questions were presented. The first reported that the environmental effects would be felt within the respondent's own country of residence, and the second reported that the effects would occur elsewhere in the world.
RESULTS: People were willing to lose an average of 0.75 years of life expectancy in order to see a 5% reduction in carbon emissions. They were willing to lose 1.59 years of life expectancy to save 100 species from becoming extinct. Conversely, people would require an increase of 1.55 years of life expectancy to see carbon emissions increase by 5% and would require 2.88 additional years of life expectancy if 100 more species were to become extinct. When the environmental impact was described as occurring outside the respondent's own country, the strength of preference was reduced by approximately 50%
CONCLUSIONS: Whilst this study was exploratory and should not be used for policy making, it demonstrates that it is feasible to elicit opinions from the public around trade-offs between health outcomes and environmental outcomes.
