Single nucleotide polymorphism marker analysis in donor-derived cell-free (dd-cf) DNA for solid organ transplantation is a technique for post-transplantation monitoring, including early detection of injury to the transplanted organ, signs of infection, and treatment decision-making, by measuring dd-cf-DNAs as a percentage of the total cf-DNAs in the patient’s body in donors and recipients of kidney, heart, lung, or liver transplants.

The assessments were performed via a systematic review. Searching five databases (KoreaMed, Ovid MEDLINE, Ovid Embase, and Cochrane) yielded 1,619 related studies. Two reviewers independently assessed the quality of these studies using a Scottish Intercollegiate Guidelines Network checklist, and the assessment results were described based on the results of the quality appraisal and level of evidence.

The population of the included studies was patients who underwent kidney, heart, lung, or liver transplantation. Medical outcomes in kidney transplantation patients were reported in 15 studies. The index test was reported to have an area under curve (AUC) of 0.68 to 0.99 and a sensitivity of 0.24 to 1.00. Four studies reported effectiveness data for the index test for lung transplantation patients. The diagnostic accuracy of the index test for acute cell-mediated rejection was reported have an AUC of 0.72. Sensitivity was reported as 0.44 and specificity as 0.80 for heart transplant patients, and sensitivity as 0.73 to 1.00 and specificity as 0.60 to 0.95 for liver transplant patients.

This is a safe and effective technique for post-transplantation monitoring, including the early detection of injury to the transplanted organ and signs of infection, and for treatment decision-making, by measuring dd-cf-DNA as a percentage of total cf-DNA in the patient’s body in recipients and donors of kidney, heart, lung, or liver transplantation (level of evidence: C).

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.

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.

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.

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.

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.

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.

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.

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.

The diffusion of digital health interventions (DHIs) requires agreement on a minimum information framework to define them. The ISPOR Digital Health (DH) Special Interest Group (SIG) developed the PICOTS-ComTeC framework based upon a systematic review and a Delphi study. It is an enriched version of the traditional PICOTS widely adopted in health technology assessment (HTA). ComTeC stands for communication, technology, and context.

The PICOTS-ComTeC is based upon a review that included the Shannon–Weaver model of communication, AHRQ Quality Measures, technology, geography, and the World Health Organization classification of DHIs followed by a Delphi panel. The development process adhered to the EQUATOR guidelines. The PICOTS-ComTeC aims to be a flexible and versatile tool tested on different DHIs. The results of the testing are discussed from the HTA perspective considering the tool’s additional value, utility for and applicability to HTA. The additional value is strictly linked to the actual need for a dedicated PICOTS for DHIs and its implications for HTA assessments of DHIs.

The PICOTS-ComTeC was tested internally and externally to the ISPOR DH-SIG on four DHIs for breast cancer surgery/management/patient education, one DHI for obesity, and one DHI for patients with heart failure. The testing phase demonstrated the level of detail required to use the tool, hitherto available evidence to cover all domains, and opened up discussion on implications of the PICOTS-ComTeC framework for HTA related activities (i.e., scoping, literature search, comparator selection). It emerged that there is a diffuse lack of homogeneity and details when DHIs are defined in the literature with significant implications for conducting appropriate HTAs.

The diffuse adoption of the PICOTS-ComTeC for patient-facing DHIs will promote a greater level of detail in order to define homogenous DHI groups. The implications for HTA range from the definition of relevant research questions to the selection of the most appropriate comparator so that assessments are geared to fulfill the needs of decision-makers.

Pemetrexed and immunotherapies (e.g., pembrolizumab) are approved for first-line maintenance (1LM) treatment of nonsquamous advanced/metastatic non-small-cell lung cancer (NSCLC), but real-world data on their use are limited. The objective of this study was to assess 1LM clinical outcomes, safety, and treatment patterns of immunotherapy versus immunotherapy+pemetrexed among patients with advanced/metastatic NSCLC from the EU4 (France, Germany, Italy, Spain)+UK.

Data from patients in the US, Canada, and EU4+UK with nonsquamous advanced/metastatic NSCLC without targetable mutations were collected via electronic case report form. Physician-identified patients (≥18 y) in the EU4+UK were eligible for this subgroup analysis if they achieved stable disease or complete or partial response with first-line platinum-based chemotherapy+immunotherapy (January 2019 to March 2021) and received 1LM immunotherapy or immunotherapy+pemetrexed. Patients were followed from index (1LM initiation) until last physician contact or death. Outcomes were overall survival (OS), progression-free survival (PFS), treatment patterns and duration, and adverse events.

Among the selected 367 patients (male, 71.9%; mean±StDev age, 63.4±7.2 y; current/former smokers, 85.8%), 203 (55.3%) received immunotherapies, most commonly pembrolizumab (n=173; 85.2%), and 164 (44.7%) received immunotherapy+pemetrexed. Patients receiving immunotherapy had longer median adjusted OS and PFS compared to those receiving immunotherapy+pemetrexed (OS hazard ratio [HR]: 0.63; 95% confidence interval [CI]: 0.36, 0.90; PFS HR: 0.58; 95% CI: 0.38, 0.79). Patients receiving immunotherapy versus patients receiving immunotherapy+pemetrexed had longer median treatment duration (14.0 vs 10.3 mo; p<0.001) and were less likely to experience anemia (19.7% vs 33.5%; p<0.01). Results were similar in the overall study population.

In this real-world study, among the selected patients with nonsquamous advanced/metastatic NSCLC who achieved stable disease or complete or partial response with first-line therapy, the addition of pemetrexed to immunotherapy in 1LM did not appear to confer a clinical benefit. Identifying treatments that can improve clinical outcomes for these patients remains an area of unmet need.

Reducing environmental impact and ensuring sustainable practices are important to the medical technology (MedTech) industry. However, it is unclear how these factors will be formally addressed by health technology assessment (HTA). The objective of this research was to understand what sustainability measures are required and included in HTA reports on medical technologies in five European countries (France, England, Germany, Italy, and Spain).

HTA guidelines, framework papers, and published HTA reports for devices were searched from January 2022 to November 2023 for inclusion of environmental aspects. Search terms included environmental sustainability, carbon footprint, greenhouse gas, and waste generation. Data were extracted into standardized templates and analyzed both quantitively and qualitatively for the inclusion of sustainability and environmental impact measures.

HTA guidance on inclusion of sustainability and environmental measures is lacking. While some countries request the inclusion of these aspects in the HTA process, there is little detail on evidence requirements and how it will be evaluated. Of the over 450 HTA reports examined, less than 10 percent included environmental aspects, with most sustainability benefit claims made related to the reduction in waste or less resources used. Very few claims were supported by published evidence. This resulted in the exclusion of potential environmental benefits in final HTA recommendations. Costs associated with environmental impact of medical technologies were rarely assessed.

Current inclusion and evaluation of sustainability measures in MedTech HTA in Europe is nascent. While countries like England [National Institute for Health and Care Excellence (NICE)] and France [Haute Autorité de santé (HAS)] have very recently made public statements regarding the importance of environmental impact, there is a growing need for detailed guidance on environmental evidence requirements and how these will be incorporated into the evaluation and decision-making processes.

A consortium of five Spanish health technology assessment (HTA) agencies conducted the European Reference Networks Guidelines Programme for the development, appraisal, and implementation of clinical practice guidelines aiming to support clinical decision-making in the field of rare diseases (RDs). In response to this objective, methodologists and information specialists conducted systematic reviews (SRs). This study aims to explore the barriers/facilitators they encountered.

A survey was designed to elicit HTA agencies’ experience in developing SRs on RDs. Information was collected on the number of SRs conducted and the types of RDs and clinical questions addressed. In addition, they were asked to identify barriers and facilitators for each stage of the review (from the definition of PICO [population, intervention, comparator, outcome] components of the question to the issuing of recommendations). Finally, they were asked for process improvement suggestions. The survey was distributed by email and completed online. A thematic analysis was conducted to identify the issues identified at each stage of SR.

A total of 111 SRs were conducted on 35 RDs. Most clinical questions were about diagnosis and treatment. The main barriers identified were lack of MesH (Medical Subject Headings) terms associated with the conditions, non-representative abstracts and keywords, lack of relevant information in the body of the articles, and reported data not allowing for quantitative syntheses or recommendations to be made. Facilitating aspects included Orphanet’s specific source of RD documents and having expert clinicians in the working groups who were also involved in all steps of the SR.

Conducting SRs in the field of RDs is challenging. Authors of primary studies are encouraged to be more exhaustive in reporting the results. More research focused on the SR methodology in RDs is necessary to address their particular characteristics and obtain robust results. It is crucial to collaborate with reference networks to address RDs, where the evidence is scarce.

The growing burden of chronic kidney disease (CKD) in Brazil is increasingly evident, marked by its significant contributions to mortality rates and healthcare costs. Managing CKD, especially through renal replacement therapy (RRT), demands substantial resources. To enhance healthcare decision-making, a thorough examination of the relationship between the rising prevalence of CKD and its clinical and economic impacts is crucial.

We developed a patient-level simulation model to project the natural history of CKD, defined as the IMPACT CKD. This model integrated factors such as acute kidney injury, cardiovascular events, and comorbidities, and aimed to assess CKD’s clinical, humanistic, and economic impact on the healthcare system. It forecasted the burden of CKD over the next decade (2023 to 2032). This projection is pivotal to derive the burden of CKD for health technology assessment (HTA) evaluations. Validation was conducted against Brazil’s demographic data and cross-validated with the Inside CKD model.

The IMPACT CKD forecast a rapid increase of CKD population in Brazil, outpacing the growth of the general population. Specifically, there is an expected 6.9 percent increase in stages 3 to 5 CKD, leading to a higher demand for dialysis (projected 370,000 cases in 2032) and transplants (projected 115,000 cases in 2032). A significant increase in cardiovascular CKD-related events (+100.6%) and mortality (+67.8%) is expected. In 2032, it is projected 15 million CKD patients will be in stages 1 to 2, and 12.7 million in stages 3 to 5. CKD-related healthcare costs will represent 25.7 percent of Brazil’s healthcare budget, and dialysis will reach USD2.7 billion in annual costs.

IMPACT CKD predicts an increasing CKD prevalence and an alarming rise in stages 3 to 5 and RRT, including thousands of premature deaths, and a substantial economic burden on the Brazilian healthcare system. This data could be informative for healthcare decision-makers when choosing strategy to reduce the impact of CKD in Brazil.

Progress and innovation in artificial intelligence (AI)-based healthcare interventions continue to develop rapidly. However, there are limitations in the published health economic evaluations (HEEs) of AI interventions, including limited reporting on characteristics and development of algorithms. We developed an extension to the existing Consolidated Health Economic Evaluation Reporting Standards (CHEERS) to improve consistency, transparency, and reliability of the reporting of HEEs of AI interventions.

The Delphi method was used, following a prespecified study protocol. A steering group with expert oversight was formed to guide the development process. A long list of potential items was defined based on two recent systematic reviews of HEEs of AI-based interventions. The steering group identified and invited 119 experts to the three-stage survey. Participants were asked to score each item on a nine-point Likert scale, and they were also able to provide free-text comments. The final checklist was piloted on a random sample of nine HEEs of AI-based interventions.

Three stages of the Delphi survey were completed by 58, 42, and 31 multidisciplinary respondents, respectively, including HTA specialists, health economists, AI experts, and patient representatives. The CHEERS-AI extension includes 18 AI-specific reporting items. Ten are entirely new items, including considerations about user autonomy, validation of the AI component, and AI-specific uncertainty. In addition, elaborations on eight existing CHEERS items were added to emphasize important AI-specific nuances. Some participants highlighted that CHEERS-AI can provide key benefits; for example, it could clarify the misconception that the predictive algorithms supporting AI-driven healthcare interventions are available for use without cost.

CHEERS-AI can aid in improved reporting quality for researchers, editors, and reviewers conducting or assessing HEEs of AI interventions.

The reliability of cost–utility analyses depends on the quality of health state utility values (HSUVs). Given the increasing number of studies eliciting HSUVs, systematic reviews (SRs) are vital to economic evaluations. Nevertheless, a universally acceptable quality appraisal (QA) tool specific to the SRs of HSUV studies is lacking—this study aimed to develop one and fill this gap.

We employed a mixed-method approach, starting with a rapid review to identify QA dimensions, QA items, and terminology in the SRs of HSUV-eliciting studies. This informed a modified Delphi process with a seven-member international expert panel, aiming to define key terms, refine the QA tool dimensions, and establish relevant signaling questions. The experts participated in two anonymous online survey rounds interspersed with structured feedback, enabling iterative refinement of their views. Following these surveys, a virtual face-to-face meeting was held to resolve outstanding issues. Consensus was defined a priori at all stages of the modified Delphi process.

The rapid review identified three QA dimensions and 16 initial items, noting the diverse terminologies in defining QA. Response rates to the first- and second-round questionnaires and the virtual consensus meeting were 100, 86, and 71 percent, leading to a consensus on the definitions of scientific quality, QA, the three QA dimensions (reporting, methodological limitation, and risk of bias and relevance), and scope of the QA tool. The number of QA items was refined to 14: all relevant to reporting, six to relevance, and 11 to methodological limitations and bias risk dimensions. The QA tool underscores distinct evaluations for each dimension.

We present the first version of a QA checklist designed to provide SR authors with a tool to appraise the quality of HSUV-eliciting studies comprehensively. The QA tool aims to (i) facilitate QA in SRs of HSUV elicitation studies, (ii) promote consistency in the appraisal process, and (iii) emphasize the importance of differentiating between reporting quality, methodology, and relevance.

Despite dementia being the seventh leading cause of death globally, there is relatively little discussion of the presence and impact of inequalities in this context. We explore ways to quantify the magnitude and variation over time of inequalities related to people living with dementia (PLWD) and their informal carers.

We conducted a targeted literature review to identify inequalities faced by PLWD and their informal carers regarding their access to and experience of health and social care in England, Wales, and Northern Ireland. We selected four of the identified inequalities as case studies (CS) to explore data and methods that can be used to measure and monitor progress to tackle them. The CS considered were: (CS1) timely diagnosis in rural areas; (CS2) financial pressures for informal carers; (CS3) timely diagnosis in deprived areas; and (CS4) diagnosis rates for ethnic minority groups. We use data from 2018 to 2023 in England.

We identified 110 inequalities for PLWD and 28 inequalities for carers. For CS1, we proposed two measures: the “rurality gap” (gap in diagnosis rates between the most and least rural areas) and the “concentration index” (the extent to which diagnosis rates are distributed disproportionately between less or more rural areas). The rurality gap suggests that diagnosis rates are five to eight percent lower in rural areas in England. The concentration index supports this finding. CS2 shows that 41 percent of informal carers experience financial difficulties. Due to insufficient data, it was not possible to construct robust measures for CS3 and CS4.

Many inequalities for PLWD and their informal carers are reported in the literature. Our CS highlight the need to improve methods and data to measure a set of inequalities, including those to calculate dementia prevalence and measure timely diagnosis. Better data is crucial now to inform value assessment of the upcoming Alzheimer’s disease treatments and avoid exacerbating existing inequalities.

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.

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.

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.

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.

Human tissue biobanks provide vital infrastructure to support both basic science and clinical research, but their economic value in terms of attributable population health gains is unclear. We evaluated the population health returns from investment in the Victorian Cancer Biobank (VCB). The VCB comprises five hospital-integrated sample repositories and a central lead agency located in Melbourne, Australia.

This evaluation assigned monetary values to the health gains attributable to VCB-supported public-funded research. These were then compared to the total investment in VCB infrastructure since inception (2006 to 2022) to determine the return on investment (ROI). A time lag of 40 years was incorporated, recognizing the delay from investment to impact in scientific research. Health gains were therefore measured for the years 2046 to 2066, with a three percent discount rate applied. Health gains were measured in terms of disability-adjusted life years (DALYs) attributable to VCB-associated research, with monetary cost assigned via the standardized value of a statistical life year (AUD227,000 [USD149,883]).

The age-standardized DALY rate attributable to cancer was modeled for two standpoints: (i) extrapolating the current decreasing trajectory and (ii) assuming nil future improvement from current rates, with 33 percent of the difference attributed to scientific innovation. The proportion of the aggregate health gain attributable to VCB-supported research was estimated from the number of VCB-credited scientific publications as a proportion of total oncology publications over the same period. The AUD32,628,016 [USD21,554,571] of public funding invested in VCB activities over the years 2006 to 2022 generated AUD84,561,373 [USD55,868,539] total savings. Return on investment was AUD1.59 [USD1.05] for each AUD1 [USD0.66] invested.

The VCB offers a strong return on investment in terms of population health impacts, justifying the use of public funds and supporting the use of biobanks to advance scientific research. Future health technology assessments could capture the total impact of research on the role of the biobanks attributed to research outputs.

Early health technology assessment (eHTA) can help to explore the potential value of a technology in the early stages of development. Care pathway analysis (CPA) is a method to identify and map clinical decisions in the current and new care pathways (including the new intervention). This work provides examples of applying CPA within the context of eHTA for medical interventions.

CPA usually involves a pragmatic review to identify and synthesize national/international guidelines that describe the care pathway for the condition of interest. This is typically followed by a qualitative evaluation that can include semistructured interviews with thematic analysis. Interviews with experts are undertaken to understand where (and why) real-world practices differ from published guidance and to validate the care pathway. They also help to evaluate the strengths/weaknesses of the new technology, potential population and role in the pathway, and barriers/facilitators to adoption. The CPA forms the basis of economic modeling that helps assess the monetary value of the new technology.

The application of CPA from two recent projects will be presented: an innovative diagnostic test for respiratory tract infections and a medical device for treating cataracts. Additionally, the value of CPA in eHTA will be described from the technology developers’ perspective. In both projects, CPA was used to inform the potential value propositions of the new technology and its positioning in the care pathway. It also helped to optimize the structure of the early economic model and to identify evidence generation needs. The early model identified the pathway that was more likely to be cost effective in the future.

CPA is a valuable method within the context of eHTA. Alongside identifying the potential role and positioning of the new technology, test developers found the assessment useful for informing internal strategy decisions and discussions with potential external investors. The developers were able to demonstrate the clinical perspective around the value of the test, elicited through an independent and rigorous methodology.

Rapid advancements in technology are significantly impacting the healthcare system, and decision-making regarding technology adoption occurs at multiple decentralized levels within hospitals. National bodies seek to standardize this process, yet differing visions and strategies hinder centralization. This study explores the relationship between technological innovation and hospital strategies, focusing on scanning and assessment, aiming to assess the feasibility of centralized decision-making.

To do this, we performed a qualitative analysis through 23 semistructured interviews in seven hospitals in the Netherlands, a country characterized by strong healthcare innovation and decentralization. We interviewed different actors involved in technological innovation, on different levels in the organization: CEOs, medical doctors, medical physicists or similar roles, and innovation managers. Ethics approval was obtained, and interviews were conducted, recorded, transcribed, and shared with participants for accuracy confirmation. Thematic analysis via grounded theory methodology and ATLAS.ti software generated insights on technological innovation’s relationship to hospitals’ strategies. Initial codes were refined into themes relevant to the research question.

Hospitals primarily aim to provide optimal patient care, with academic hospitals emphasizing research and education. Some hospitals aspire to be pioneers in adopting new technologies, while patient-centric healthcare is a shared goal. Technological strategies are not precisely designed in hospitals, being shaped by factors like people, financial constraints, or external environments. Hospitals’ scanning of technologies lacks systematization, and evaluations before and after technology adoption are not univocally performed. The need for systematic scanning and assessment practices is recognized by some interviewees, while others emphasize the importance of experimenting without the constraint of evaluation, perceiving it as a hurdle delaying innovation.

Centralization could represent a benefit for hospitals, allowing them more streamlined decision-making, but it could also be perceived as a barrier. Involving hospitals’ stakeholders in centralization would be crucial to achieve it through a joint effort. Suggestions for future research could include focusing on a specific hospital, involving more stakeholders, and exploring other decentralized healthcare systems.

Detailed, precise information on a pharmaceutical’s projected therapeutic use is required for horizon scanning. Inferring an estimated indication from trial protocols is a key skill of horizon scanners. The International Horizon Scanning Initiative (IHSI) database utilizes semi-automated data collection. This pilot aimed to verify that the extraction of relevant word sets to generate an estimated indication could be semi-automated.

Ten drugs approved in Europe in 2021 were selected as the pilot test set. The test set included drugs approved for the treatment of rare diseases (n=4), haemato-oncology (n=3), and non-oncology conditions (n=3). Eight of the drugs were approved based on phase III trials. The assessment comprised a review of the pivotal trial that supported product registration for these drugs. We undertook a comparison between a human curator and a natural language processing (NLP) algorithm in generating granular tags relating to key aspects of the drugs’ estimated indication (stage of disease, patient-specific subgroup, and place in treatment).

In 50 percent of cases, the NLP accurately tagged a word or word set related to stage of disease, patient-specific subgroup, or place in treatment, which was also tagged by human curators. In 50 percent of cases, the NLP did not identify words or word sets tagged by human curators. Where relevant, the NLP successfully tagged the same word sets relating to stage of disease for all drugs in the test set. The same word sets relating to patient-specific subgroup were successfully tagged for three drugs in the set. NLP successfully tagged word sets relating to place in treatment for two drugs.

The NLP algorithm is successful in extracting relevant word sets, which can be used to generate an estimated indication in an automated or semi-automated process. The pilot highlighted that further testing is required to advance the sensitivity of the algorithm. Further piloting exploring both unsupervised and supervised modeling approaches (named entity recognition and deep neural networks, respectively) is planned.

This study investigated the various incentives employed in Organisation for Economic Co-operation and Development (OECD) and European Economic Area (EEA) countries to enhance access to innovative medical technologies. The literature review encompasses real and theoretical models, offering an overview of strategies to bridge the gap between innovation and access. A strengths, weaknesses, opportunities, and threats (SWOT) analysis was conducted to analyze incentives in health system and therapeutic area context.

The review methodically examined peer-reviewed articles, reports, and policy documents published between 2000 and 2023. Databases searched include PubMed, Scopus, Web of Science, and EconLit. Grey literature was searched from international organizations’ websites, including the World Bank, World Health Organization (WHO), OECD, Pan American Health Organization (PAHO), and European Commission. Inclusion criteria focused on relevance of financial and non-financial mechanisms to effective implementation of innovative medical technologies, and their application within OECD and EEA countries. COVID-19 research, vaccines, cost-effectiveness studies, and studies that did not discuss implementation were excluded. A SWOT analysis was utilized to categorize the mechanisms by therapeutic area and health system design.

The review identified diverse mechanisms, including reinsurance, impact bonds, outcomes-based agreements, annuity payments, and risk-sharing agreements. Financial mechanisms, such as outcomes-based agreements, were prominent but highlighted implementation obstacles, including a lack of data infrastructure capable of linking outcomes to payments, which ultimately undermines the effectiveness of these strategies. Non-financial mechanisms, such as population health management, were also identified. The effectiveness varied, with some models showing significant improvement in technology accessibility, while others faced implementation and affordability challenges. Comparative analysis highlighted differences in efficacy dependent on the therapeutic area and type of health system in which the incentive is applied.

The review underscores multifaceted approaches to improve access to innovative medical technologies. While financial incentives play a crucial role, non-financial strategies are also vital. This study provides insights into which incentives are most effective in certain health systems and therapeutic areas. Policymakers can benefit from these insights, leveraging successful models and addressing challenges to ensure equitable access to medical innovations.

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.

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.

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.

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.

Burkitt lymphoma (BL) is a rare and highly aggressive subtype of non-Hodgkin’s lymphoma. Several studies have identified prognostic factors (PFs) for disease progression and mortality among adults with BL. However, there is no consensus on risk stratification based on PFs. This study aims to identify, critically assess, and synthesize the available evidence on PFs for survival in adults with BL.

A systematic review of the literature was conducted. MEDLINE, Embase, and CENTRAL were searched from inception to 22 February 2022. Randomized or non-randomized clinical trials and longitudinal observational studies were eligible for inclusion. Reference screening, data extraction, and risk-of-bias assessment using the Quality in Prognosis Studies (QUIPS) tool for prognostic factor studies were conducted independently and in duplicate. Publication bias was examined by visual inspection of funnel plots. Effect measures and the corresponding 95% confidence intervals were pooled with an indirect variance estimation in meta-analyses using Review Manager 5, and sensitivity analyses were conducted. Certainty of evidence was assessed using GRADE.

The search identified 1,119 references after duplicate removal. Of these, 76 potentially relevant papers were selected for full-text assessment and 36 studies (N=10,882) reported in 39 articles were eligible for inclusion. Older age, higher performance status, and central nervous system involvement were associated with poorer overall survival (OS) and progression-free survival (PFS). Black patients exhibited significantly lower OS and relative survival. Bone marrow involvement and higher albumin levels were associated with poorer OS. Treatment with rituximab and treatment with methotrexate were associated with better OS and PFS. No significant differences in survival were found for HIV status, sex, and risk stratification.

This study, framed within a collaboration with European Reference Network EuroBloodNet, provides a comprehensive and methodologically rigorous evidence review on PFs in adults with BL. Several significant associations of PFs and survival estimates were observed, providing data to inform treatment decisions and to improve patient care.

Extending fecal immunochemical tests for hemoglobin (FITs) to primary care patients with high-risk symptoms suggestive of colorectal cancer (CRC) could reduce colonoscopy waiting lists, enabling earlier treatment. Higher FIT thresholds could decrease referrals but increase missed disease compared with lower thresholds. We aimed to systematically review and synthesize test accuracy data across thresholds for use in a cost-effectiveness analysis.

Searches across ten sources were conducted (December 2022). Included were diagnostic accuracy studies of HM-JACKarc, OC-Sensor, FOB Gold, QuikRead go, NS-Prime, and four Immunodiagnostik (IDK) tests in patients presenting to, or referred from, primary care with symptoms suggestive of CRC using any reference standard. Risk of bias was assessed with QUADAS-2. Syntheses of sensitivity and specificity at all reported thresholds were planned for each test to provide summary estimates at all possible thresholds within the observed range. Sensitivity analyses investigating population type and reference standard, and subgroup analyses by patient characteristics (e.g., anemia, age, sex, ethnicity) were conducted.

HM-JACKarc (n=16 studies) sensitivity ranged from 95.9 percent (95 percent credible interval [95% CrI]: 92.7, 97.9) to 46.3 percent (95% CrI: 37.4, 54.9) and specificity from 65.1 percent (95% CrI: 55.6, 74.8) to 97.7 percent (95% CrI: 94.7, 99.2) (thresholds 2 and 400 μg hemoglobin/g feces [μg/g], respectively). OC-Sensor (n=11) sensitivity ranged from 94.2 percent (95% CrI: 91.2, 96.7) to 54.2 percent (95% CrI: 48.4, 60.2) and specificity from 62.7 percent (95% CrI: 47.4, 77.2) to 97.3 percent (95% CrI: 92.9, 99.3) (thresholds 4 and 200 μg/g, respectively). FOB Gold (n=3) sensitivity ranged from 91.4 percent (95% CrI: 71.6, 99.6) to 73.9 percent (95% CrI: 53.8, 91.2) and specificity from 78.1 percent (95% CrI: 70.0, 86.0) to 96.4 percent (95% CrI: 92.6, 98.9) (thresholds 2 and 150 μg/g, respectively). There were limited or no data on the other tests.

Sensitivity and specificity were synthesized for three tests only, since data for the remaining tests were extremely limited or absent. Even at the lowest threshold, none of the tests had perfect sensitivity. Future studies should further investigate comparative accuracy and the impact of patient characteristics, patient recruitment criteria, and the reference standard on estimates of diagnostic test accuracy.