bluuebunny/crossref_metadata_2025 huggingface dataset:
OP06 Utilizing Health Technology Assessment Outputs To Develop Health Technology Management Protocols In The Irish Setting
Authors: Gorry Claire , Daly Maria , Barrett Rosealeen , Finnigan Karen , Smith Amelia , Doran Stephen , Duggan Bernard , Clarke Sarah , Barry Michael
Published: January 2025

Introduction

Increasingly in Ireland, there are specific criteria attached to reimbursement approval for new medicines. Health technology assessment (HTA) identifies where uncertainty is greatest in relation to clinical and cost-effectiveness evidence and budget impact estimates; our health technology management (HTM) approach uses these outputs from HTA to design protocols to manage these uncertainties in the post-reimbursement phase.

Methods

A bespoke managed access protocol (MAP) is developed for each medicine reimbursed under this approach, informed by uncertainties highlighted in the HTA, directions from the decision-maker, and relevant particulars arising from commercial negotiations. Individual patient reimbursement applications are submitted via an online application system linked directly to the national pharmacy claims system. Pharmacists review the applications and approve reimbursement support where the patient meets the reimbursement criteria. The process is adaptive, allowing expansion of the criteria to include previously excluded patient cohorts, and the addition of new indications. It can also work across differing reimbursement arrangements (hospital/primary care).

Results

The MAP for liraglutide for weight management confines reimbursement to patients with a body mass index greater than or equal to 35 kg/m², prediabetes, and high risk for cardiovascular disease. Phase I reimbursement support lasts for six months; patients not attaining greater than or equal to five percent weight loss are deemed non-responders as per the HTA, and reimbursement support is discontinued. The MAP for dupilumab confined reimbursement support to adults with refractory moderate-to-severe atopic dermatitis, where cost-effectiveness was plausible in the HTA. The MAP for calcitonin-gene-related-peptides monoclonal antibodies confines reimbursement support to patients with chronic migraine, refractory to at least three prophylactic treatments, where cost-effectiveness was plausible in the HTA.

Conclusions

Across these MAPs, over 3,000 patients accessed novel treatments for chronic illnesses in September 2023. HTM provides an effective mechanism to facilitate access to high-cost medicines for targeted patient groups, while providing increased oversight and budgetary certainty. Key to acceptance is utilization of HTA outputs to implement evidence-based HTM measures targeting specific uncertainties as highlighted in the HTA report.
OP08 Health Technology Assessments Of Artificial Intelligence: Special Considerations And Development Of A Checklist
Authors: Batten Leona , Needham-Taylor Antonia , England Clare , Jarrom David
Published: January 2025

Introduction

Artificial intelligence (AI) technologies are becoming more widespread in daily life, including in health and care settings. AI is being developed for use in many areas, including diagnostics, treatment planning, and patient monitoring. There are new challenges and additional considerations when performing a health technology assessment (HTA) for AI use in healthcare.

Methods

Health Technology Wales has developed additional guidance and a checklist of considerations for researchers to use when undertaking an HTA on AI. These documents were created as a result of involvement in discussions with healthcare services around AI; attendance at meetings and training sessions with government, healthcare, and academic institutions; and observations from undertaking our first HTAs investigating AI technologies.

Results

We identified seven main areas to consider: (i) the AI model being used and its training datasets; (ii) clarity on where in the clinical pathway the AI sits and whether this is appropriate for the local healthcare service; (iii) clear identification of the target patient population and whether there are gaps in the evidence base for subgroups; (iv) who uses the AI and the training required; (v) possible barriers and inequities in usage, particularly if the AI is patient facing; (vi) ongoing monitoring of the AI model; and (vii) data security and usability.

Conclusions

HTA assessment of AI presents new challenges for HTA bodies. Additional outcomes for assessment (including user acceptability) may be required, and an awareness of background information that allows for contextualization of the technology and clear indication of its usefulness in the local healthcare setting is key. The development of guidance related to AI technologies may enable rigorous evaluation.
OP13 Improving Case Finding For Celiac Disease In Children And Adults: Evidence Synthesis And Economic Modeling
Authors: Elwenspoek Martha , Thom Howard , Sheppard Athena , Keeney Edna , O’Donnell Rachel , Jackson Joni , Roadevin Cristina , Dawson Sarah , Lane Deborah , Stubbs Jo , Everitt Hazel , Watson Jessica , Peter Gillett Alastair Hay , Robins Gerry , Jones Hayley , Mallett Sue , Whiting Penny
Published: January 2025

Introduction

Celiac disease (CD), an autoimmune disorder triggered by gluten, impacts about one percent of the population. Only one-third receive a diagnosis, leaving the majority unaware of their condition. Untreated CD can lead to gut lining damage, resulting in malnutrition, anemia, and osteoporosis. Our primary goal was to identify at-risk groups and assess the cost-effectiveness of active case finding in primary care.

Methods

Our methodology involved systematic reviews and meta-analyses focusing on the accuracy of CD risk factors (chronic conditions and symptoms) and diagnostic tests (serological and genetic). Prediction models, based on identified risk factors, were developed for identifying individuals who would benefit from CD testing in routine primary care. Additionally, an online survey gauged individuals’ preferences regarding diagnostic certainty before initiating a gluten-free diet. This information informed the development of economic models evaluating the cost-effectiveness of various active case finding strategies.

Results

Individuals with dermatitis herpetiformis, a family history of CD, migraine, anemia, type 1 diabetes, osteoporosis, or chronic liver disease showed one and a half to two times higher risk of having CD. IgA tTG, and EMA demonstrated good diagnostic accuracy. Genetic tests showed high sensitivity but low specificity. Survey results indicated substantial variation in preference for certainty from a blood test before initiating a gluten-free diet. Cost-effectiveness analyses showed that, in adults, IgA tTG at a one percent pre-test probability (equivalent to population screening) was the most cost effective. For non-population screening strategies, IgA EMA plus HLA was most cost effective. There was substantial uncertainty in economic model results.

Conclusions

While population-based screening with IgA tTG appears the most cost effective in adults, decisions for implementation should not solely rely on economic analyses. Future research should explore whether population-based CD screening aligns with UK National Screening Committee criteria and requires a long-term randomized controlled trial of screening strategies.
OP17 Methods To Measure The Environmental Impacts Of Health Technologies And Include Them In Economic Evaluations: A Scoping Review
Authors: Ardito Vittoria , Banks Helen , Cusumano Niccolò , Tarricone Rosanna
Published: January 2025

Introduction

The environmental footprint of the healthcare sector is widely acknowledged and increasingly impacting decision-making in health policy. This study aims to explore what methods and metrics have been proposed to measure environmental impact of health technologies, and to investigate the feasibility and consequences of its inclusion in economic evaluations. This study is part of a larger Horizon Europe project, HI-PRIX.

Methods

We conducted a PRISMA-ScR-guided scoping review of the scientific publications in PubMed, Web of Science, and Scopus between 2013 and November 2023. For the grey literature, the international HTA database and HTA agencies websites were searched to identify ongoing or published HTA dossiers. The search strategy was developed around two concepts: environment and health technology assessment. Any study or report that described a conceptual framework, methodology, or approach used or theorized to integrate environmental impacts of health technologies in an HTA was considered eligible for inclusion.

Results

Starting from 12,336 records, 16 scientific publications and 6 HTA dossiers were included for analysis. One-third of the contributions were published in 2023 and were mostly opinions, editorials, reviews, or economic evaluations. Lifecycle assessment was considered the preferred approach to investigate environmental impacts, yet difficulties exist; for example, methodologies for measuring greenhouse gas emissions are established, while for other dimensions are under development. Nevertheless, methods to incorporate environmental impact into economic models appear viable. About half of the papers analyzed cost–utility analysis, multiple-criteria decision analysis, and cost–benefit analysis as potential approaches. Fewer papers addressed budget impact, cost-effectiveness analysis, or other approaches.

Conclusions

Incorporating the environmental impact of health technologies in economic evaluations is under development, but consensus is still lacking on appropriate, feasible methodologies for its uptake. Before considering it in pricing or reimbursement-related decisions, the preferred method to maximize utility levels of different stakeholders (e.g., HTA agencies, industry) needs clarification.
OP29 Determinants Of The Financial Impact Of Rare Disease Drugs In Italy: Differences Between Expected And Observed Pharmaceutical Expenditure
Authors: Mennini Francesco Saverio , Cicchetti Americo , Sciattella Paolo , Rumi Filippo , Zanuzzi Matteo , Carletto Angelica , Sammarco Annalisa , Romano Federica , Russo Pierluigi
Published: January 2025

Introduction

In Italy, a fixed proportion of health spending is allocated to pharmaceutical expenditure. While the main objective of setting a budget for pharmaceuticals is to control spending, the effectiveness of this ceiling is questionable. This study aims to investigate the determinants of pharmaceutical expenditure for orphan drugs and gather information for effective planning and programming of pharmaceutical spending.

Methods

Data analysis relied on pharmaceutical companies’ pricing and reimbursement (P&R) dossiers submitted to the Italian Medicines Agency (AIFA) for drug-reimbursement approval, along with AIFA’s internal procedural documents. The study encompassed all rare disease drugs reimbursed from January 2013 to January 2019. For each drug, a comparison was made between the expected post-negotiation expenditure and the actual spending observed over the three years following reimbursement approval. Potential determinants of the normalized ratio between observed and expected spending were identified using univariate and multivariate beta regression models. The same methodology was replicated to identify potential determinants of the difference between expected spending before and after negotiation.

Results

Fifty-two rare disease drugs admitted for reimbursement during the study period were analyzed. The median expenditure in the first three commercialization years was 7.6 percent lower than the expected post-negotiation spending. Beta regression analysis indicated a significantly lower reduction for innovative drugs (β 0.736, p-value 0.011 univariate, β 0.585, p-value 0.045 multivariate). Similar effects were observed for P&R procedures (β 0.902, p-value 0.007) and the number of indications presented (β 0.754, p-value 0.021), but only in univariate model. Beta regression analysis for the expected expenditure ratio before/after negotiation revealed a significant effect only for the payment-by-result variable (β 1.485, p-value 0.001).

Conclusions

Observed expenditure for orphan drugs aligns with the expected spending post-negotiation. However, in the subgroup of innovative orphan drugs, the observed pharmaceutical spending was higher than estimated. This could be attributed to prescriber preferences and to a prevalent patient pool awaiting innovative treatment. It appears that the recognition of innovativeness favors orphan drugs that are rewarded with faster market access.
OP31 Monitoring Of The Budget Impact Determinants Of Incorporated Technologies For Rare Diseases In The Brazilian Health System
Authors: Pereira Silva Mariá Gonçalves , Lyrio Amanda Oliveira , Neiva Pantuzza Laís Lessa , Borges Thais Conceição , Ottavio Barbara Pozzi , de Freitas Lopes Ana Carolina , Bonan Luciene
Published: January 2025

Introduction

Budget impact analyses for the treatment of rare diseases are especially important for the sustainability of health systems due to high treatment costs and uncertainties in target population estimates. The objective of this work is to analyze the elements that influence discrepancies between predicted and observed budget impacts for enzyme replacement therapies for rare diseases in Brazil’s public health system.

Methods

All enzyme replacement therapies for rare diseases evaluated by the National Committee for Health Technology Incorporation in the Brazilian Public Health System (Conitec) and with at least one year of use were included. For each technology, the following were identified: number of patients, median patient weight, annual quantity of medication, unit price, and budget impact. The attributes were compared between previous estimates and real-world observation after use. The data sources were publicly accessible administrative databases and Conitec technical reports.

Results

Five technologies were selected: elosulfase alfa, alglucosidase alfa, idursulfase, laronidase, and galsulfase. In the first year, the difference between the estimated and the observed number of patients treated was up to 15 percent lower or higher for four technologies, but with monthly fluctuation throughout the year. The median weight of users was between 23 percent and 468 percent higher for three technologies. The observed price was as expected, with variations between three percent lower and 14 percent higher. The quantity of medicines used was lower (between 39% and 46%) than expected for all technologies. The observed budget impact was 37 percent to 47 percent lower than estimated.

Conclusions

Real-world budget impact was lower than expected for all technologies. The main cause of discrepancies was the estimate of the annual amount of medication, which did not consider gradual adherence and discontinuation of treatment. This highlights the need to review the budget impact methodology for rare diseases, forecasting monthly market share and treatment discontinuation rate.
OP42 A Budget Impact Analysis Of The Introduction Of Noninvasive Prenatal Testing To Korean National Health Insurance
Authors: Seo Hyerin , Ahn Jeonghoon , Jin Doyeon , Lee Hyorim
Published: January 2025

Introduction

This study assessed the budget impact (BI) of introducing noninvasive perinatal testing (NIPT) to the Korean National Health Insurance (KNHI). It aims to provide useful economic evidence on reimbursement decisions on prenatal screening. Since NIPT is widely used in Korea as a noncovered service, BI can be reliably estimated from real-world data (RWD).

Methods

In this BI analysis, we derived the total number of pregnant women from 2017 birth statistics (n=358,000) and its distribution of singleton births (96.1%) and multiples (3.9%). The age distribution of pregnant women was 29.4 percent for 35 and above, and 70.6 percent for below 35, according to the 2017 statistics. For NIPT costs, we considered a price range of KRW357,000 (USD260) to KRW715,000 (USD522) from a 2018 survey. To evaluate the BI of introducing NIPT, we examined eight scenarios based on NIPT cost sharing of 30 percent and 70 percent, NIPT price, and whether to include pregnant women aged less than 35 years old.

Results

BI for KNHI was estimated as KRW6 trillion (USD4 billion) to approximately KRW56 trillion (USD40 billion). Scenario seven, targeting older pregnant women with serum screening high risk with NIPT price at the lower end and payer coverage of 30 percent, shows the lowest annual BI of KRW6,115,813,866 (USD4,469,516); scenario two, covering all older pregnant women and younger high-risk cases with NIPT price at the higher end and payer coverage of 70 percent, exhibits the highest burden at KRW56,240,636,611 (USD41,091,993).

Conclusions

Our BI analysis of introducing NIPT to KNHI can serve as essential data for estimating insurer burdens during the potential transition of NIPT to provisional or selective coverage. In the absence of prenatal diagnostics cost-effectiveness research in Korea, our findings provide crucial evidence for establishing relevant reimbursement criteria, addressing a gap in current research and supporting evidence-based policymaking.
OP57 Comparing Institute For Clinical And Economic Review Comparative Effectiveness Assessments And Federal Joint Committee Added Benefit Assessments
Authors: DiStefano Michael J. , Pearson Steven D. , Rind David M. , Zemplenyi Antal
Published: January 2025

Introduction

We compared the Institute for Clinical and Economic Review’s (ICER) ratings of comparative clinical effectiveness with the German Federal Joint Committee’s (G-BA) added benefit ratings, and explored what factors, including the evidence base, may explain disagreement between the two organizations.

Methods

Drugs were included if they were assessed by ICER under its 2020–2023 Value Assessment Framework and had a corresponding assessment by G-BA as of March 2023 for the same indication, patient population, and comparator drug. To compare assessments, we modified ICER’s proposed crosswalk between G-BA and ICER benefit ratings to account for G-BA’s extent and certainty ratings. We also determined whether each assessment pair was based on similar or dissimilar evidence. Assessment pairs exhibiting disagreement based on the modified crosswalk despite a similar evidence base were qualitatively analyzed to identify reasons for disagreement.

Results

We identified 15 assessment pairs and seven out of fifteen were based on similar evidence. G-BA and ICER assessments disagreed for each of these drugs. For 4/7 drugs, G-BA (but not ICER) determined the evidence was unsuitable for assessment: for 2/4 drugs, G-BA concluded the key trials did not appropriately assess the comparator therapy; for 1/4, G-BA did not accept results of a before-and-after study due to non-comparable study settings; for 1/4, G-BA determined follow-up in the key trial was too short. Among assessment pairs where both organizations assessed the evidence, reasons for disagreement included concerns about long-term safety, generalizability, and study design.

Conclusions

This study underscores the role of value judgments within assessments of clinical effectiveness. These judgments are not always transparently presented in assessment summaries. The lack of clarity regarding these value-based decisions underscores the need for improvements in transparency and communication, which are essential for promoting a more robust health technology assessment process and supporting transferability of assessments across jurisdictions.
OP58 Diagnostics And Treatments For COVID-19: Update From A Living Systematic Review Of Economic Evaluations
Authors: Hopkin Gareth , Elvidge Jamie , Narayanan Nithin , Nicholls David , Dawoud Dalia
Published: January 2025

Introduction

The COVID-19 pandemic put substantial strain on healthcare systems globally. Early decision-making about diagnostic tests and treatments was driven by the need for rapid responses with a focus on reducing clinical burden. As COVID-19 continues its transition into an endemic state, health technology assessment (HTA) agencies will need to consider the clinical- and cost-effectiveness of tests and treatments, as with other conditions.

Methods

We first conducted a systematic literature review in July 2021 and updated the search in July 2023. The review aimed to identify economic evaluations of diagnostics for SARS-CoV-2 and treatments for COVID-19 using predefined search strategy across journal databases and sources of grey literature. In the update, an additional targeted search was completed with terms relating to novel treatments. Search results were screened by title and abstract, and full texts of potentially relevant studies were reviewed against selection criteria. Studies with very serious methodological limitations were excluded. Findings from studies were synthesized narratively due to high levels of heterogeneity.

Results

The database search identified 8,287 unique records, of which 54 full texts were reviewed, 28 were quality assessed, and 15 were included. Three further studies were included through HTA sources and citation checking. Of the 18 studies ultimately included, 16 evaluated pharmacological treatments including corticosteroids, antivirals, and immunotherapies. Two studies in lower-income settings evaluated the cost-effectiveness of rapid antigen tests and critical care provision. In most studies, a healthcare or payer perspective was used, and the comparator was standard care. There were 17 modeling analyses and one trial-based evaluation. Cost–utility analyses using QALYs were the most common analysis type.

Conclusions

This update indicates that there are cost-effective treatments for COVID-19, with repurposed pharmacological treatments like dexamethasone presenting best value. There also appear to be promising options for people with severe disease alongside standard care. Future economic evaluations would benefit from reflecting the changing context around COVID-19 with parameters that reflect current circumstances, and fully incremental analyses comparing different treatment options.
OP69 Are Artificial-Intelligence-Based Literature Reviews Accepted By Health Technology Assessment Bodies?
Authors: Singh-Mangat Gautamjeet , Sharma Sugandh , Bergemann Rito
Published: January 2025

Introduction

Literature reviews (LR) play a crucial role in all health technology assessment (HTA) dossiers, presenting evidence-based value of interventions. There is global exploration of artificial intelligence (AI) to expedite and enhance the efficiency of literature reviews. Our research aimed to identify any existing guidance from HTA bodies regarding the use of AI for conducting literature reviews.

Methods

We conducted a comprehensive search and review of any published guidance from prominent HTA bodies, including the National Institute for Health and Care Excellence (NICE, England), Scottish Medicines Consortium (SMC, Scotland), National Centre for Pharmacoeconomics (NCPE, Ireland), National Authority for Health (HAS, France), Federal Joint Committee (G-BA, Germany), Institute for Quality and Efficiency in Health Care (IQWiG, Germany), Canadian Agency for Drugs and Technologies in Health (CADTH, Canada), and Pharmaceutical Benefits Advisory Committee (PBAC, Australia). This was done to gain insights into their views regarding the utilization of AI in literature reviews. Additionally, we engaged with HTA representatives, such as NICE, to gain a deeper understanding of their perspectives.

Results

We found a lack of clear guidance on the use of AI for conducting LRs. NICE has recommended a priority screening technique using machine learning (ML) for identification of a higher proportion of relevant papers at an earlier stage. NICE is currently in the process of developing guidance and is updating its manual in this area. SMC refers readers to NICE methodologies. In its HRB-CICER report, NCPE only acknowledges the potential of ML algorithms for LRs, with no additional information. IQWiG, in its general methods, recommends the use of ML-validated classifiers for identifying randomized controlled trials (RCTs) within bibliographic searches.

Conclusions

Our research indicates that there is scarce guidance available for the use of AI in LRs for HTA submissions. However, considering the rapidly evolving nature of this field, it is anticipated that guidance documents and manuals will be updated in the near future.
OD19 Future Health And Economic Burden Of Cardiovascular Disease In Type 2 Diabetes In Qatar, From 2023 To 2032
Authors: Abushanab Dina , Al-Badriyeh Daoud , Marquina Clara , Liew Danny , Al-Zaidan Manal , Al-Kuwari Mohammed Ghaith , Abdulmajeed Jazeel , Ademi Zanfina
Published: January 2025

Introduction

The Middle East and North Africa region accounts for the largest prevalence of type 2 diabetes (T2D). Qatar ranks top 10 for global T2D prevalence, with 17 percent in 2022. Also, 50 to 70 percent of the cardiovascular events occurred in T2D. We sought to estimate the future health and economic burden of cardiovascular disease (CVD) in T2D from 2023 to 2032.

Methods

A dynamic multistate model in people with T2D was constructed. The demographic profile of the population was based on Qatari citizens and residents with T2D aged 40 to 90 years in 2022. First CVD events (i.e., myocardial infarction [MI] and stroke) were calculated via the 2013 Pooled Cohort Equation using data from Primary Health Care Corporation. Recurrent CVD events were sourced from the global Reduction of Atherothrombosis for Continued Health (REACH) registry. Outcomes were MI and stroke, years of life lived, quality-adjusted life years (QALYs), total direct and productivity loss costs. Utility and cost model inputs were drawn from published sources. The model adopted a Qatari societal perspective.

Results

The model estimates 123,524 non-fatal MIs (95% uncertainty interval [UI]: 116,923, 130,065), 70,466 non-fatal strokes (95% UI: 67,945, 73,476) and 15,410 CVD deaths (95% UI: 15,217, 15,794), respectively. T2D population accrued 4,834,146 (95% UI: 4,781,235, 4,881,695) total years of life lived and 3,817,246 (95% UI: 3,756,963, 3,870,616) total QALYs. Direct costs accounted for 59.52 percent of the total costs, with a projection of QAR43.59 billion (USD11.98 billion) (95% UI: QAR9.14 billion [USD2.5 billion], QAR134.20 billion [USD36.87 billion]), while the total indirect costs were expected to exceed QAR29.65 billion (USD8.14 billion) (95% UI: QAR2.40 billion [USD659.34 million], QAR113 billion [USD31.04 billion]).

Conclusions

This study highlights that the considerable rising burden of CVD in T2D in Qatar will impact not only the healthcare system but also the society overall. The findings may be used to prioritize strategies targeting T2D to prevent CVD burden.
OD23 Evolving Prostate Cancer Screening Strategies In Germany: A Cost–Utility Analysis Comparing Traditional And Emerging Modalities
Authors: Muchadeyi Muchandifunga T. , Hao Shuang , Hernandez-Villafuerte Karla , Khan Shah , Becker Nikolaus , Krilaviciute Agne , Seibold Petra , Gulati Roman , Albers Peter , Schlander Michael , Clements Mark
Published: January 2025

Introduction

In 2021, approximately 15,000 men in Germany died from prostate cancer (PCa). The national health policy is considering shifting from annual digital rectal examination (DRE)-based screening to an age-related prostate-specific antigen (PSA)-based risk-adapted and organized screening strategy. Our research investigated the cost–utility of the current DRE-based strategy versus organized age-related PSA-based risk-adaptive PCa screening strategies in Germany.

Methods

We adapted the Swedish Prostata model to the German context, recalibrating it with PCa clinical and epidemiological data from the national and state registries. The model includes preclinical and clinical disease health states defined by tumor, nodal, and metastatic stages and Gleason scores, and assumes that the benefits of screening arise from stage shift. We assessed the cost–utility of 14 strategies, ranging from no screening to DRE, and age-related, PSA-based, risk-adapted screening. Health state utility values and test characteristics were sourced from the literature. Inpatient and outpatient care costs were derived from the German diagnostic-related groups and uniform-based valuation systems.

Results

Among all strategies evaluated and compared with no screening, the “DRE only” strategy led to substantial overdiagnosis, the highest incremental cost, and minimal quality-adjusted life years (QALY) gains. PSA testing starting at 50 to 60 years with reflex MRI for PSA greater than 3 ng/mL cases followed by combined systemic and targeted biopsy reduced the number of biopsies and overdiagnosis by 75 percent and 26 percent, albeit for fewer QALYs and higher costs (dominated) than the same strategy without reflex MRI. The PSA-based risk-adaptive strategy, starting at 50 to 60 years without reflex MRI, demonstrated an 85 percent probability of being cost effective within the EUR30,000 (USD32,211) to EUR100,000 (USD107,369)/QALY willingness-to-pay range.

Conclusions

While Germany’s HTA emphasizes clinically added benefits and health-related quality of life, cost-effectiveness analysis substantiates this evidence. As a standalone early detection tool, DRE leads to substantial overdiagnosis, unnecessary biopsies, and increased healthcare costs. Overall, this study demonstrated the importance of age-related PSA risk-adaptive PCa screening. The value of MRI deserves further investigation, considering MRI’s positive effect on screening acceptability.
OD28 Towards Implementing New Payment Models For The Reimbursement Of High-Cost, Curative Therapies: Insights From Semi-Structured Interviews
Authors: Desmet Thomas , Michelsen Sissel , den Brande Elena Van , Dyck Walter Van , Simoens Steven , Huys Isabelle
Published: January 2025

Introduction

In response to the intricate challenges posed by high-cost, one-shot curative therapies, this study explores what hinders the wide implementation of innovative payment schemes across Europe. Drawing insights from the Belgian social healthcare system, this study focused on defining the necessary and sufficient conditions for implementing outcome-based spread payments in the context of market access to advanced medicinal products

Methods

Semi-structured interviews (n=33) were conducted with physicians (n=2), hospital pharmacists (n=4), hospital managers (n=2), patient representatives (n=3), industry representatives (n=5), Belgian policymakers (n=6), sickness fund representatives (n=4), legislative experts (n=2), and accounting experts (n=5) to elicit opinions and insights on stakeholders’ responsibilities and roles, and identify the necessary and sufficient conditions to establish outcome-based spread payments for the reimbursement of innovative therapies. The interviews took place between July 2020 and October 2020. The framework method analysis was performed using NVivo software (version 20.4.1.851). Statements were allocated into six main topics: payment structure, spread payments, outcome-based agreements, governance, transparency, and regulation.

Results

Interviewees across stakeholder groups endorsed the idea of implementing outcome-based spread payments. However, opinions varied on practical and legal feasibility, especially regarding long-term follow-up for patients, data collection burden on physicians, and implications on the financing flow of health technology developers, hospitals, and the government. Concerns were also raised regarding the potential need for new governance structures, enhanced transparency on agreements and pricing mechanisms, as well as defining data requirements to address uncertainties often seen with this type of therapy. All interviewees emphasized the importance of increasing stakeholders’ understanding of these agreements to foster broader acceptance and successful implementation.

Conclusions

The effective implementation of outcome-based spread payments falls behind because consensus on how this reimbursement method can be a sustainable solution is missing. Leveraging the concepts of necessary and sufficient conditions from organizational research, this study provides guidance on resolving challenges and defines stakeholders’ roles for successfully implementing this reimbursement approach.
OD30 Clinician-Driven Health Technology Assessment: National Cancer Medicines Review For Off-Label Uses And On-Label Off-Patent Uses In NHSScotland
Authors: O’Connell Richard , Doherty Louis , Andrews Pamela , Craig Louise , Drinkell James , Dalrymple Heather , Clive Sally
Published: January 2025

Introduction

Publicly funded cancer services face significant financial and capacity challenges. It is estimated that 40 percent of medicines used to treat cancer are outside their marketing authorization or “off-label.” These uses are usually outside the remit of health technology assessment (HTA) groups. Accessing emerging off-label uses is mostly through individual patient requests, which are resource intensive, delay patient treatment, and produce inequity.

Methods

A program providing national HTA review of off-label and off-patent cancer medicine uses has been established by Healthcare Improvement Scotland. Processes include horizon scanning, support for proposing clinicians, and engaging patient groups. Relevant published and unpublished clinical and cost-effectiveness information—identified through systematic literature searches, engagement with pharmaceutical companies, academic and health service data groups—supports independent appraisal and decision-making. Where cost-effectiveness information is unavailable, a value-judgment framework, including magnitude of clinical benefit, uncaptured benefits, and budget and service impact, is utilized to standardize review. The decision-making Council includes public partners, and advice is shared across NHSScotland.

Results

From July 2022 to October 2023, the program has published advice on nine proposals—eight off-label uses and one on-label off-patent use. Health economic models from a pharmaceutical company and an academic group supported decision-making on two proposals, value-judgment frameworks for two proposals, and real-world evidence for one proposal. Eight proposals were supported, and one was not supported. Each supported proposal slowed cancer, prolonged life, or reduced toxicity compared to standard treatment options. Four were cost-saving and three had a low medicines budget impact. Three were service-saving and three had no significant impact on services.

Conclusions

Novel HTA programs can address gaps in medicines governance to improve patient outcomes and support sustainability. Clinical connections, patient group engagement, health economic collaborations and linkage to national cancer data teams and academics have facilitated bespoke approaches to evidence-gathering despite limited resources. Our agile and adaptive approach has enabled robust review and decision-making on varied and impactful proposals.
OD33 Assessment Tool For MHealth Apps To Manage Depression (EvalDepApps Project)
Authors: Carrion Carme , Davins-Riu Meritxell , Duarte-Díaz Andrea , Ferreira-Cavalcanti Janaina , Fuster-Casanovas Aïna , Gelabert Estel , Gómez-Calderón Corpus , Moretó-Melero Sònia , Pérez-Navarro Antoni , Robles Noemí , Vidal-Alaball Josep
Published: January 2025

Introduction

The use of apps represents a revolution in mental health. Fast, versatile, and manageable, mHealth apps allow empowerment of patients and professionals and can even reduce stigmatization. There is not yet a standardized method to assess their effectiveness and safety. The objective of the EvalDepApps project is to develop an assessment tool for apps that have management of depression as the main goal.

Methods

The EvalDepApps project follows several stages:

(i) Systematic review and meta-analysis following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement, to identify evidence about effectiveness and safety of mHealth interventions to manage depressive symptoms among adults, and criteria to be included in the app assessment tools. The primary outcome was the reduction of depressive symptoms, and only randomized controlled trials (RCTs) were included.

(ii) Delphi process with 30 participants (patients and healthcare professionals) to reach consensus about the criteria to be included in the tool.

(iii) Co-creation workshops with 12 healthcare professionals and 12 patients to co-design the EvalDepApps tool.

Results

Twenty-nine RCTs were included. The most common elements were psychoeducation, goal setting, and gamification. Significant effect for mHealth interventions in reducing depressive symptoms compared with non-active control (95% confidence interval: −0.87, −0.37; I2=87%) was identified. Hybrid interventions combining mHealth with face-to-face sessions were the most effective. Any study-related adverse events were reported. Response rate was 59 percent (26/44) in round one and 52 percent (23/44) in round two. Twenty-eight out of 51 criteria (54.9%) were accepted by consensus. Proposals were received about the look and feel of the content, usability aspects, sections, and main features of the EvalDepApps tool.

Conclusions

mHealth interventions, particularly hybrid ones, can be effective in reducing depressive symptoms. There is a need for personalized approaches. It is important to prioritize evidence-based principles and standardized evaluation tools. A set of 25 criteria will be included in the EvalDepApps tool that will be co-created thanks to the input given by healthcare professionals and people diagnosed with depression.
OD34 Consideration Of Medical Device Characteristics In Health Technology Assessment: A Gap In The Methods Guidelines And In Practice
Authors: Basu Rituparna , Eggington Simon , Hallas Natalie , Strachan Liesl
Published: January 2025

Introduction

It is well accepted that medical devices (MDs) and procedures have several unique characteristics compared to pharmaceuticals, such as learning curve (LC), incremental innovation (II), dynamic pricing (DP), and organizational impact (OI). The objective of this study was to determine the extent to which these MD characteristics are routinely assessed by health technology assessment (HTA) agencies and incorporated in their guidelines and reports.

Methods

Three approaches were taken. First, a review of the most recent HTA methods guidelines from 13 selected HTA agencies and five HTA networks was undertaken. Next, HTA reports from these agencies were reviewed for inclusion of MD-specific characteristics for 16 selected MDs, and finally, a narrative literature review on this topic was conducted.

Results

Twelve of thirteen included HTA organizations and some HTA networks (2/5) have either published general or MD-specific method guidelines, while several addressed MD-specific characteristics. The National Institute for Health and Care Excellence (NICE) included all four MD characteristics in their guidelines, but this did not equate to their inclusion in published HTA evaluations. EuNetHTA described the inclusion of LC (within patient safety) and OI within their guidance. The results highlight a lack of consistency among HTA organizations. For the narrative review, 10/149 articles were reviewed. Most provided recommendations on challenges faced by HTAs, proposed steps to address uncertainties around MD characteristics and reported a lack of methodological guidance for evaluating MDs.

Conclusions

A lack of inclusion of MD characteristics in HTA is a complex interplay of several important factors. For these characteristics to become a formal part of HTA of MDs in the future, clear guidance and frameworks are required to enable manufacturers to develop appropriate evidence and for HTA practitioners to assess their impact more broadly.
OD48 Improving Public Understanding Of Health Technology Assessment Decisions
Authors: Russell Kate , McCormack Jackie , Dickson Jennifer , Cairns Daniel
Published: January 2025

Introduction

Since 2018, the Scottish Medicines Consortium (SMC) has published a plain English summary for each health technology assessment (HTA) decision called Decision Explained (DE). This provides clear information to patients, Patient Group Partners (PGPs), and the public about what SMC’s decisions mean for them. The DE document was evaluated and updated in 2023 to ensure it continues to meet this purpose.

Methods

The evaluation consisted of two components. All (186) registered PGPs were invited to complete an online five-question survey focusing on the use of the DE document. This included readership, language, and SMC decision-making transparency. A separate focus group for public representatives took place, discussing design, accessibility, and content. Identical sample DE documents were used for both groups for consistency. Survey responses were collated and analyzed. Focus group responses were analyzed using thematic analysis. The DE document was revised, and the new version was considered for implementation by SMC’s Public Involvement Network Advisory Group.

Results

Survey respondents (n=20) found the DE document helpful or very helpful in improving understanding of SMC advice. Some commented on complex language and information about how the medicine works being irrelevant. The focus group commented on excess information and favored simplified content and structure. Analysis of both sets of research data resulted in several recommended changes. These included the decision statement being moved to the start of the document, the language being simplified, and the section on how a medicine works being removed. Revised documents including these changes were prepared and were reviewed and approved by the SMC’s Public Involvement Network Advisory Group.

Conclusions

Published plain English explanations are helpful for improving patient and public understanding of HTA decisions for new medicines. It is important this information is concise, relevant, and aligned to accessibility good practice. The recent review of the SMC DE documents led to changes that help to ensure they meet the needs of stakeholders.
PP07 One Bad Apple Can Spoil The Barrel: Are We Effectively Evaluating Software As A Medical Device?
Authors: Curtis-Gretton Luc , Malcolm Robert
Published: January 2025

Introduction

There are many differences between medical devices, pharmaceuticals, and Software as a Medical Device (SaMD). This should impact the way SaMDs are evaluated in health technology assessment (HTA). SaMD technologies often target multiple indications, are regularly updated, and often result in non-quantifiable benefits. The objective of this research was to identify problems and potential solutions when evaluating SaMDs in England.

Methods

This research took the perspective of the HTA process in England. We conducted a pragmatic review of publicly available grey literature, such as National Institute for Health and Care Excellence (NICE) guidelines and processes, government schemes, funding mechanisms, and other published reports and opinion pieces, to summarize how SaMDs are currently being evaluated. This included an overview of the current systems and funding structures (inclusive of recent developments), where potential issues may lie, and what is currently being done to address these issues. We concluded by making recommendations to improve the evaluation of these technologies.

Results

Difficulty quantifying outcomes of SaMD technologies, alongside the preference of decision-makers to evaluate technologies for single indications, causes a bottleneck of unevaluated technologies to build. HTA bodies then group many non-identical technologies into single appraisals, resulting in a range of SaMD technologies with varying quality being implemented through managed access agreements. Some schemes and funding mechanisms led by public bodies in England aim to improve efficiency and encourage technological development. However, the HTA process in England remains characterized by long evaluation processes and high clinical evidence requirements, which many SaMD providers find difficult to navigate.

Conclusions

Although progress has been made, there is clear incentive to improve the way in which SaMD technologies are assessed in HTA. We recommend that a more rapid mixed-method approach be implemented. This should draw on quantitative economic analysis supplemented with qualitative clinical, patient, and expert opinion. SaMDs should be evaluated either individually or within smaller groups than current evaluation systems.
PP19 Time And Cost Savings Of Machine Learning And Artificial Intelligence (AI) In Systematic Reviews: A Case Study
Authors: Littlewood Anne , McCool Rachael , Edwards Mary , di Ruffano Lavinia Ferrante
Published: January 2025

Introduction

Conducting a systematic review (SR) of clinical trials is labor-intensive and expensive. However, existing open-source content can be used to develop custom machine learning tools suited to the workflow of individual organizations. This case study details the potential of a bespoke tool developed by York Health Economics Consortium (YHEC) for reducing the time and cost involved in producing an SR.

Methods

RESbot is a flexible, stand-alone machine learning tool created using an extensively tested open-source dataset developed by Cochrane. The tool identifies randomized controlled trials (RCTs) from a large corpus of records. It has a user interface and inputs/outputs to fit into the company’s existing workflow at any stage. RESbot has two settings. The “sensitive” setting identifies a higher number of possible RCTs with a lower risk of missing eligible studies, while the “precise” setting is more focused. For both settings, we estimated the reduction in resources required for record screening in two examples of RCT-only reviews.

Results

Scoping searches in MEDLINE were conducted for SRs of RCTs in femoropopliteal artery diseases (FAD) and postpartum depression (PD). The results were run through RESbot. For the FAD SR, 1,444 references were retrieved, with the sensitive and precise RESbot settings reducing the record set by 38 percent and 64 percent, respectively. For the PD SR, a record set of 2,153 records was reduced by 25 percent and 41 percent, respectively. Resource savings offered by RESbot vary depending on subject but may reduce the time taken to screen records by up to 64 percent, with a subsequent reduction in cost to the organization commissioning the SR.

Conclusions

The use of bespoke machine learning tools in SR production has the potential to reduce the time and staff costs involved in producing a review. This case study tested the effect on a small number of records, but for larger reviews retrieving tens of thousands of records, reductions in time and costs can be very significant.