Artificial intelligence-enhanced patient evaluation: bridging art and science.

The advent of digital health and artificial intelligence (AI) has promised to revolutionize clinical care, but real-world patient evaluation has yet to witness transformative changes. As history taking and physical examination continue to rely on long-established practices, a growing pipeline of AI-enhanced digital tools may soon augment the traditional clinical encounter into a data-driven process. This article presents an evidence-backed vision of how promising AI applications may enhance traditional practices, streamlining tedious tasks while elevating diverse data sources, including AI-enabled stethoscopes, cameras, and wearable sensors, to platforms for personalized medicine and efficient care delivery. Through the lens of traditional patient evaluation, we illustrate how digital technologies may soon be interwoven into routine clinical workflows, introducing a novel paradigm of longitudinal monitoring. Finally, we provide a skeptic's view on the practical, ethical, and regulatory challenges that limit the uptake of such technologies.

Is the price right? Paying for value today to get more value tomorrow.

BACKGROUND: Contemporary debates about drug pricing feature several widely held misconceptions, including the relationship between incentives and innovation, the proportion of total healthcare spending on pharmaceuticals, and whether the economic evaluation of a medicine can be influenced by things other than clinical efficacy. MAIN BODY: All citizens should have access to timely, equitable, and cost-effective care covered by public funds, private insurance, or a combination of both. Better managing the collective burden of diseases borne by today's and future generations depends in part on developing better technologies, including better medicines. As in any innovative industry, the expectation of adequate financial returns incentivizes innovators and their investors to develop new medicines. Estimating expected returns requires that they forecast revenues, based on the future price trajectory and volume of use over time. How market participants decide what price to set or accept can be complicated, and some observers and stakeholders want to confirm whether the net prices society pays for novel medicines, whether as a reward for past innovation or an incentive for future innovation, are commensurate with those medicines' incremental value. But we must also ask "value to whom?"; medicines not only bring immediate clinical benefits to patients treated today, but also can provide a broad spectrum of short- and long-term benefits to patients, their families, and society. Spending across all facets of healthcare has grown over the last 25 years, but both inpatient and outpatient spending has outpaced drug spending growth even as our drug armamentarium is constantly improving with safer and more effective medicines. In large part, this is because, unlike hospitals, drugs typically go generic, thus making room in our budgets for new and better ones, even as they often keep patients out of hospitals, driving further savings. CONCLUSION: A thorough evaluation of drug spending and value can help to promote a better allocation of healthcare resources for both the healthy and the sick, both of whom must pay for healthcare. Taking a holistic approach to assessing drug value makes it clear that a branded drug's value to a patient is often only a small fraction of the drug's total value to society. Societal value merits consideration when determining whether and how to make a medicine affordable and accessible to patients: a drug that is worth its price to society should not be rendered inaccessible to ill patients by imposing high out-of-pocket costs or restricting coverage based on narrow health technology assessments (HTAs). Furthermore, recognizing the total societal cost of un- or undertreated conditions is crucial to gaining a thorough understanding of what guides the biomedical innovation ecosystem to create value for society. It would be unwise to discourage the development of new solutions without first appreciating the cost of leaving the problems unsolved.

Tribulations and future opportunities for artificial intelligence in precision medicine.

Upon a diagnosis, the clinical team faces two main questions: what treatment, and at what dose? Clinical trials' results provide the basis for guidance and support for official protocols that clinicians use to base their decisions. However, individuals do not consistently demonstrate the reported response from relevant clinical trials. The decision complexity increases with combination treatments where drugs administered together can interact with each other, which is often the case. Additionally, the individual's response to the treatment varies with the changes in their condition. In practice, the drug and the dose selection depend significantly on the medical protocol and the medical team's experience. As such, the results are inherently varied and often suboptimal. Big data and Artificial Intelligence (AI) approaches have emerged as excellent decision-making tools, but multiple challenges limit their application. AI is a rapidly evolving and dynamic field with the potential to revolutionize various aspects of human life. AI has become increasingly crucial in drug discovery and development. AI enhances decision-making across different disciplines, such as medicinal chemistry, molecular and cell biology, pharmacology, pathology, and clinical practice. In addition to these, AI contributes to patient population selection and stratification. The need for AI in healthcare is evident as it aids in enhancing data accuracy and ensuring the quality care necessary for effective patient treatment. AI is pivotal in improving success rates in clinical practice. The increasing significance of AI in drug discovery, development, and clinical trials is underscored by many scientific publications. Despite the numerous advantages of AI, such as enhancing and advancing Precision Medicine (PM) and remote patient monitoring, unlocking its full potential in healthcare requires addressing fundamental concerns. These concerns include data quality, the lack of well-annotated large datasets, data privacy and safety issues, biases in AI algorithms, legal and ethical challenges, and obstacles related to cost and implementation. Nevertheless, integrating AI in clinical medicine will improve diagnostic accuracy and treatment outcomes, contribute to more efficient healthcare delivery, reduce costs, and facilitate better patient experiences, making healthcare more sustainable. This article reviews AI applications in drug development and clinical practice, making healthcare more sustainable, and highlights concerns and limitations in applying AI.

Factors Associated with Veteran Self-Reported Use of Digital Health Devices.

BACKGROUND: Digital health devices (DHDs), technologies designed to gather, monitor, and sometimes share data about health-related behaviors or symptoms, can support the prevention or management of chronic conditions. DHDs range in complexity and utility, from tracking lifestyle behaviors (e.g., pedometer) to more sophisticated biometric data collection for disease self-management (e.g., glucometers). Despite these positive health benefits, supporting adoption and sustained use of DHDs remains a challenge. OBJECTIVE: This analysis examined the prevalence of, and factors associated with, DHD use within the Veterans Health Administration (VHA). DESIGN: National survey. PARTICIPANTS: Veterans who receive VHA care and are active secure messaging users. MAIN MEASURES: Demographics, access to technology, perceptions of using health technologies, and use of lifestyle monitoring and self-management DHDs. RESULTS: Among respondents, 87% were current or past users of at least one DHD, and 58% were provided a DHD by VHA. Respondents 65 + years were less likely to use a lifestyle monitoring device (AOR 0.57, 95% CI [0.39, 0.81], P = .002), but more likely to use a self-management device (AOR 1.69, 95% [1.10, 2.59], P = .016). Smartphone owners were more likely to use a lifestyle monitoring device (AOR 2.60, 95% CI [1.42, 4.75], P = .002) and a self-management device (AOR 1.83, 95% CI [1.04, 3.23], P = .037). CONCLUSIONS: The current analysis describes the types of DHDs that are being adopted by Veterans and factors associated with their adoption. Results suggest that various factors influence adoption, including age, access to technology, and health status, and that these relationships may differ based on the functionalities of the device. VHA provision of devices was frequent among device users. Providing Veterans with DHDs and the training needed to use them may be important factors in facilitating device adoption. Taken together, this knowledge can inform future implementation efforts, and next steps to support patient-team decision making about DHD use.

Integrated Devices: A New Regulatory Pathway to Promote Revolutionary Innovation.

Policy Points Current medical device regulatory frameworks date back half a century and are ill suited for the next generation of medical devices that involve a significant software component. Existing Food and Drug Administration efforts are insufficient because of a lack of statutory authority, whereas international examples offer lessons for improving and harmonizing domestic medical device regulatory policy. A voluntary alternative pathway built upon two-stage review with individual component review followed by holistic review for integrated devices would provide regulators with new tools to address a changing medical device marketplace.

Konectom™ cognitive processing speed test enables reliable remote, unsupervised cognitive assessment in people with multiple sclerosis: Exploring the use of substitution time as a novel digital outcome measure.

BACKGROUND: The Konectom™ smartphone-based cognitive processing speed (CPS) test is designed to assess processing speed and account for impact of visuomotor function on performance. OBJECTIVE: Evaluate reliability and validity of Konectom CPS Test, performed in clinic and remotely. METHODS: Data were collected from people with multiple sclerosis (PwMS) aged 18-64 years and healthy control participants (HC) matched for age, sex, and education. Remote test-retest reliability (intraclass correlation coefficients, ICC); correlation with established clinical measures (Spearman correlation coefficients); group analyses between cognitively impaired/unimpaired PwMS; and influence of age, sex, education, and upper limb motor function on CPS Test measures were assessed. RESULTS: Eighty PwMS and 66 HC participated. CPS Test measures from remote tests had good test-retest reliability (ICC of 0.67-0.87) and correlated with symbol digit modalities test (highest |ρ| = 0.80, p < 0.0001). Remote measures were stable (change from baseline < 5%) and correlated with MS disability (highest |ρ| = 0.39, p = 0.0004) measured by Expanded Disability Status Scale. CPS Test measures displayed sensitivity to cognitive impairment (highest d = 1.47). Demographics and motor function had the lowest impact on CPS Test substitution time, a measure accounting for visuomotor function. CONCLUSION: Konectom CPS Test measures provide valid, reliable remote measurements of cognitive processing speed in PwMS.

Real-world smartphone data can trace the behavioural impact of epilepsy: A case study.

BACKGROUND: Neurobehavioural comorbidities have a detrimental effect on the quality of life of people with epilepsy, yet tracking their impact is challenging as behaviour may vary with seizures and anti-seizure medication (ASM) side effects. Smartphones have the potential to monitor day-to-day neurobehavioural patterns objectively. We present the case of a man in his late twenties with drug-resistant focal epilepsy in whom we ascertained the effects of ASM withdrawal and a convulsive seizure on his touchscreen interactions. METHODS: Using a dedicated app, we recorded over 185 days the timestamps of 718,357 interactions. We divided the various smartphone behaviours according to the next-interval dynamics of the interactions by using a joint interval distribution (JID). During two ASM load transitions, namely before versus during tapering and tapering versus restarting medication, we used cluster-based permutation tests to compare the JIDs. We also compared the JID of the seizure day to the average of the previous 3 days. RESULTS: The cluster-based permutation tests revealed significant differences, with accelerated next-interval dynamics during tapering and a reversal upon medication restart. The day of the convulsion exhibited a marked slowing of next-interval dynamics compared to the preceding 3 days. CONCLUSION: Our findings suggest that the temporal dynamics of smartphone touchscreen interactions may help monitor neurobehavioural comorbidities in neurological care.

Treatment Effect Waning Assumptions: A Review of National Institute of Health and Care Excellence Technology Appraisals.

OBJECTIVES: This study aims to review the National Institute of Health and Care Excellence (NICE) technology assessments to gain insights into the implementation of treatment effect (TE) waning, whereby the hazard or survival in an assessed technology converges to that of the comparator. This analysis aims to contribute to inform future guidance in this area. METHODS: Technology appraisals published October 20, 2021 to September 20, 2023 were reviewed and data extracted on TE waning circumstances, methods, and rationale to compile a database based on 3 research questions: When are TE waning assumptions used? What methods are used? Why have the company/Evidence Assessment Group/committee preferred these methods? RESULTS: Both the evidence assessment group/company and the committee included TE waning assumptions in 28 appraisals. There was no pattern of waning assumptions between shorter (<20 years) and longer (>20 years) time horizons. The most prominent time point for applying waning assumptions was at 5 years, with 30 out of 59 (50.8%) of the methods applied used 5 years. Stopping rules were used in 21 out of 30 (70.1%) of the appraisals for which the committee included waning, and waning assumptions were used more in oncology. The most common reason given for including TE waning assumptions was precedent from prior appraisals. CONCLUSIONS: Considerable heterogeneity existed in both the methods used and justifications given for TE waning assumptions. This variability poses a risk of inconsistent decision making. Reliance on past appraisals emphasizes the necessity to advocate for evidence-driven approaches and underscores the demand for guidance on suitable methods for incorporating assumptions.

Multistakeholder Perceptions of Additional Value Elements for United States Value Assessment of Health Interventions.

OBJECTIVES: Limitations in conventional cost-effectiveness methods have led to calls for incorporation of additional value elements in assessments of health technologies. However, gaps remain in how additional value elements may inform decision making. This study aimed to prioritize additional value elements from the perspective of healthy individuals without a specific condition or indicated for a specific treatment in the United States among a multistakeholder panel and compare the importance of perspective-specific value elements. METHODS: Additional value elements were prioritized in 2 phases: (1) we identified and categorized additional value elements in a targeted literature review, and (2) we convened a multistakeholder group-based preference elicitation study (N = 28) to evaluate the description of each value element and rank and generate normalized weights of each value element for its significance in value assessment. The importance of additional value elements was also weighted relative to patient-centric value elements. RESULTS: The rank and weight of contextual value elements among 28 stakeholders were "severity of the disease" (26.2%), "disadvantaged and vulnerable target populations highly represented" (21.8%), "broader economic impact" (17.3%), "risk protection" (13.8%), "rarity of the disease" (11.3%), and "novel mechanism of action" (9.7%). Relative weight of the additional value elements versus patient-centric value elements was 52% and 48%, respectively. CONCLUSIONS: Study findings may inform priority setting for value frameworks and emerging US government assessments. The group-based elicitation method is repeatable and useful for structured deliberative processes in value assessment and may help improve the consistency and predictability of what is important to stakeholders.

Mapping Health Technology Assessment Agency Approaches for Biosimilar Value Assessment: An ISPOR Special Interest Group Report.

OBJECTIVES: A systematic literature review undertaken by the ISPOR Biosimilar Special Interest Group highlighted that limited guidance exists on how to assess biosimilars value and on appropriate economic evaluation techniques. This study described current health technology assessment (HTA) agency approaches for biosimilar value assessment. METHODS: Semi-structured interviews (n = 16) were carried out with HTA experts in Africa, America, Asia, Australia, and Europe to investigate current HTA practices for biosimilars. Data categorization was based on a thematic analysis approach. Findings from the qualitative data analysis were interpreted in view of relevant published literature. RESULTS: Our research suggests that in systems in which frameworks for biosimilar regulatory approval are well established, HTA agencies can accept the regulators' comparability exercise, and reimbursement decisions can generally be based on price comparisons. This approach is accepted in practice and allows streamlining of biosimilars value assessment. Nevertheless, conducting HTAs for biosimilars can be relevant when (1) the originator is not reimbursed, (2) the biosimilar marketing authorization holder seeks reimbursement for indications/populations, pharmaceutical forms, methods and routes of administration that differ with respect to the originator, and (3) a price premium is sought for a biosimilar based on an added-value claim. Further, HTA agencies' role conducting class-review updates following biosimilar availability can support greater patients' access to biologics. CONCLUSIONS: Internationally, there are differences in how national competent authorities on pricing and reimbursement of pharmaceuticals perceive HTA's role for biosimilars. Therefore, HTA agencies are encouraged to issue clear guidance on when and how to conduct HTAs for biosimilars, and on which economic techniques to apply.

Evidence Quality and Health Technology Assessment Outcomes in Reappraisals of Drugs for Rare Diseases in Germany.

OBJECTIVES: Evidence on reappraisals of health technologies in Germany is limited, and for rare disease treatments (RDTs), the Federal Joint Committee follows different processes (limited or regular), depending on whether an annual revenue threshold has been exceeded. Our objective is to better understand (re)appraisal processes and their outcomes for RDTs in Germany. METHODS: We analyzed appraisal documents of 55 RDT indications for which an initial appraisal and a reappraisal were conducted between 2011 and 2023. We extracted information for the type of evidence, the risk of bias, the availability of additional evidence, and the change in the maturity of survival data as proxies for evidence quality. Specifically, we reviewed the reasons for conducting reappraisals, examined how evidence quality and the clinical benefit rating (CBR) differed between initial appraisals and reappraisals, and explored the association between evidence quality and (1) the CBR and (2) the change in the CBR after reappraisal. RESULTS: Most reappraisals were conducted because the annual revenue threshold was exceeded or the initial appraisal resolution was time limited. Almost all initial appraisals used the limited process, whereas the majority of reappraisals used the regular process. The CBR increased in only 9 and decreased in 21 of 55 reappraisals. There was some evidence that reappraisals with an accepted randomized controlled trial were significantly more likely to achieve a higher CBR. CONCLUSIONS: Findings confirmed that reasons and processes for conducting reappraisals of RDTs in Germany differ. Further, high CBRs in reappraisals were not common and evidence quality in initial appraisals and reappraisals was limited.

Utilization, Expenditure, and Treatment Patterns Associated With Calcitonin Gene-Related Peptide Monoclonal Antibodies Reimbursed Subject to a Managed Access Protocol in Ireland.

OBJECTIVES: Calcitonin gene-related peptide monoclonal antibodies (CGRP mAbs) are novel high-cost treatments for the prevention of migraine. This study presents data on utilization, expenditure, and treatment patterns with CGRP mAbs available under a managed access protocol in Ireland, to a cohort of treatment refractory patients (failed 3 or more previous treatments) with chronic migraine. METHODS: Data were extracted from the Primary Care Reimbursement Service High Tech claims database and special drug request online system and analyzed using Microsoft Excel and SAS. Treatment persistence was evaluated by refill patterns, and adherence was evaluated using the proportion of days covered method. Expenditure data were extracted directly from the database. RESULTS: Between September 1, 2021 and April 30, 2023, 1517 applications for reimbursement approval for a CGRP mAb were received; 1458 (96.1%) were approved for reimbursement. Total expenditure on CGRP mAbs in year 1 (September 1, 2021 to August 31, 2022) was €3.2 million. The majority of patients initiated treatment with fremanezumab (60.8%) or erenumab (37.1%). Almost 90% of patients were considered adherent, and treatment persistence was high, with more than 75% of patients receiving more than 12 months of treatment in our 18-month study time frame. CONCLUSIONS: This study demonstrates the importance of active health technology management, after reimbursement, in enabling cost-effective use of high-cost treatments while providing budget certainty for the healthcare payer. High levels of adherence and persistence suggest that treatment is successfully targeted in situations which unmet clinical need is greatest.

A Targeted Review of Worldwide Indirect Treatment Comparison Guidelines and Best Practices.

OBJECTIVES: Controls and governance over the methodology and reporting of indirect treatment comparisons (ITCs) have been introduced to minimize bias and ensure scientific credibility and transparency in healthcare decision making. The objective of this study was to highlight ITC techniques that are key to conducting objective and analytically sound analyses and to ascertain circumstantial suitability of ITCs as a source of comparative evidence for healthcare interventions. METHODS: Ovid MEDLINE was searched from January 2010 through August 2023 to identify publicly available ITC-related documents (ie, guidelines and best practices) in the English language. This was supplemented with hand searches of websites of various international organizations, regulatory agencies, and reimbursement agencies of Europe, North America, and Asia-Pacific. The jurisdiction-specific ITC methodology and reporting recommendations were reviewed. RESULTS: Sixty-eight guidelines from 10 authorities worldwide were included for synthesis. Many of the included guidelines were updated within the last 5 years and commonly cited the absence of direct comparative studies as primary justification for using ITCs. Most jurisdictions favored population-adjusted or anchored ITC techniques opposed to naive comparisons. Recommendations on the reporting and presentation of these ITCs varied across authorities; however, there was some overlap among the key elements. CONCLUSIONS: Given the challenges of conducting head-to-head randomized controlled trials, comparative data from ITCs offer valuable insights into clinical-effectiveness. As such, multiple ITC guidelines have emerged worldwide. According to the most recent versions of the guidelines, the suitability and subsequent acceptability of the ITC technique used depends on the data sources, available evidence, and magnitude of benefit/uncertainty.

Perils of Randomized Controlled Trial Survival Extrapolation Assuming Treatment Effect Waning: Why the Distinction Between Marginal and Conditional Estimates Matters.

OBJECTIVES: A long-term, constant, protective treatment effect is a strong assumption when extrapolating survival beyond clinical trial follow-up; hence, sensitivity to treatment effect waning is commonly assessed for economic evaluations. Forcing a hazard ratio (HR) to 1 does not necessarily estimate loss of individual-level treatment effect accurately because of HR selection bias. A simulation study was designed to explore the behavior of marginal HRs under a waning conditional (individual-level) treatment effect and demonstrate bias in forcing a marginal HR to 1 when the estimand is "survival difference with individual-level waning". METHODS: Data were simulated under 4 parameter combinations (varying prognostic strength of heterogeneity and treatment effect). Time-varying marginal HRs were estimated in scenarios where the true conditional HR attenuated to 1. Restricted mean survival time differences, estimated having constrained the marginal HR to 1, were compared with true values to assess bias induced by marginal constraints. RESULTS: Under loss of conditional treatment effect, the marginal HR took a value >1 because of covariate imbalances. Constraining this value to 1 lead to restricted mean survival time difference bias of up to 0.8 years (57% increase). Inflation of effect size estimates also increased with the magnitude of initial protective treatment effect. CONCLUSIONS: Important differences exist between survival extrapolations assuming marginal versus conditional treatment effect waning. When a marginal HR is constrained to 1 to assess efficacy under individual-level treatment effect waning, the survival benefits associated with the new treatment will be overestimated, and incremental cost-effectiveness ratios will be underestimated.

Assessing the Performance of Alternative Methods for Estimating Long-Term Survival Benefit of Immuno-oncology Therapies.

OBJECTIVES: This study aimed to determine the accuracy and consistency of established methods of extrapolating mean survival for immuno-oncology (IO) therapies, the extent of any systematic biases in estimating long-term clinical benefit, what influences the magnitude of any bias, and the potential implications for health technology assessment. METHODS: A targeted literature search was conducted to identify published long-term follow-up from clinical trials of immune-checkpoint inhibitors. Earlier published results were identified and Kaplan-Meier estimates for short- and long-term follow-up were digitized and converted to pseudo-individual patient data using an established algorithm. Six standard parametric, 5 flexible parametric, and 2 mixture-cure models (MCMs) were used to extrapolate long-term survival. Mean and restricted mean survival time (RMST) were estimated and compared between short- and long-term follow-up. RESULTS: Predicted RMST from extrapolation of early data underestimated observed RMST in long-term follow-up for 184 of 271 extrapolations. All models except the MCMs frequently underestimated observed RMST. Mean survival estimates increased with longer follow-up in 196 of 270 extrapolations. The increase exceeded 20% in 122 extrapolations. Log-logistic and log-normal models showed the smallest change with additional follow-up. MCM performance varied substantially with functional form. CONCLUSIONS: Standard and flexible parametric models frequently underestimate mean survival for IO treatments. Log-logistic and log-normal models may be the most pragmatic and parsimonious solutions for estimating IO mean survival from immature data. Flexible parametric models may be preferred when the data used in health technology assessment are more mature. MCMs fitted to immature data produce unreliable results and are not recommended.

Tackling Challenges in Assessing the Economic Value of Tumor-Agnostic Therapies: A Cost-Effectiveness Analysis of Pembrolizumab as a Case Study.

OBJECTIVES: Assessing the value of tumor-agnostic drugs (TAD) is challenging given the potential variability in treatment effects, trials with small sample sizes, different standards of care (SoC), and lack of comparative data from single-arm basket trials. Our study developed and applied novel methods to assess the value of pembrolizumab compared with SoC to inform coverage decisions. METHODS: We developed a partitioned survival model to evaluate the cost-utility of pembrolizumab for previously treated patients with 8 advanced or metastatic microsatellite instability-high or mismatch repair-deficient cancers from a US commercial payer perspective. Efficacy of pembrolizumab was based on data from trials directly or with adjustment using Bayesian hierarchical models. Eight chemotherapy-based external control arms were constructed from the TriNetX electronic health record databases. Tumor-specific health-state utility values were applied. All costs were adjusted to 2022 US dollars. RESULTS: At a lifetime horizon, pembrolizumab was associated with increased effectiveness compared with chemotherapies in colorectal (quality-adjusted life years [QALYs]: +0.64, life years [LYs]: +0.64), endometrial (QALYs: +3.79, LYs: +5.47), and small intestine cancers (QALYs: +1.73, LYs: +2.48), but not for patients with metastatic gastric, cholangiocarcinoma, pancreatic, ovarian, and brain cancers. Incremental cost-effectiveness ratios varied substantially across tumor types. Pembrolizumab was found to be cost-effective in treating colorectal and endometrial cancers (incremental cost-effectiveness ratios: $121 967 and $139 257, respectively), and not cost-effective for other assessed cancers at a $150 000 willingness-to-pay/QALY threshold, compared with SoC chemotherapies. CONCLUSIONS: The cost-effectiveness of TADs can vary by cancers. Using analytic tools such as external controls and Bayesian hierarchical models can tackle several challenges in assessing the value of TADs and uncertainties from basket trials.

How Do the Institute for Clinical and Economic Review's Assessments of Comparative Effectiveness Compare With the German Federal Joint Committee's Assessments of Added Benefit? A Qualitative Study.

OBJECTIVES: 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 may explain the disagreement between the 2 organizations. METHODS: We included drugs if they were assessed by ICER under its 2020 to 2023 Value Assessment Framework and had a corresponding assessment by G-BA as of January 2024 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 certainty ratings. We also determined whether each pair was based on similar evidence. Assessment pairs exhibiting disagreement based on the modified crosswalk despite a similar evidence base were qualitatively analyzed to identify reasons for disagreement. RESULTS: Out of 15 drug assessment pairs matched on indication, patient subgroup, and comparator, none showed agreement in their assessments when based on similar evidence. Disagreement was attributed to differences in evidence evaluation, including evaluations of safety, generalizability, and study design, as well as G-BA's rejection of the available evidence in 4 cases as unsuitable. CONCLUSIONS: The findings demonstrate that even under conditions where populations and comparators are identical and the evidence base is consistent, different assessors may arrive at divergent conclusions about comparative effectiveness, thus underscoring the presence of value judgments within assessments of clinical effectiveness. To support initiatives that seek to facilitate the exchange of value assessments between countries, these value judgments should always be transparently presented and justified in assessment summaries.

Proposal for a General Outcome-based Value Attribution Framework for Combination Therapies.

OBJECTIVE: Valuing and pricing the components of combination therapies can be difficult due to competition law issues, difficulty implementing different prices for the same product in alternative uses, and attributing value to each component of the combination. We propose a value attribution solution that allows all combination components to be priced according to their relative value in the combination. METHODS: We developed a value attribution solution that is universal, symmetrical, and neutral to each combination constituent, regardless of whether it is the backbone or the add-on; and complete, meaning it will always attribute the full value of the combination between the component parts. Moreover, it can be applied to any number of components in the combination (e.g. triplets or quadruplets). We compared this solution to two other existing approaches. RESULTS: The results of the proposed value attribution solution sit between those of the two other value attribution approaches as it combines elements of each. As the degree of additivity moves further away from one in either direction, then our general approach ratios also move, reflecting the impact of the incremental value. CONCLUSION: The proposed value attribution solution for combination therapies differs from two existing approaches by being universally applicable and allowing for symmetry when neutral to the constituent components of the combination. To optimally contribute to policy debate and practice, various requirements for its implementation need to be well understood including how to overcome (1) partial information, (2) whether its assumptions can be relaxed, and (3) implementation issues.

The Impact of Additive PICOs in a European Joint Clinical Health Technology Assessment.

OBJECTIVES: To assess the potential number of EU PICOs based on EUnetHTA 21 guidance and to explore further evidence-based opportunities to produce more predictable and workable EU PICOs. METHODS: The consolidated EU PICOs of two future hypothetical medicines in first line non small cell lung cancer (1L NSCLC) and third line multiple myeloma (3L MM) were derived using published HTA reports of two recent medicines in similar indications based on EUnetHTA 21 proposed guidance. Sensitivity analysis assessed the impact of additional PICO requests. The number of analyses requested was estimated. RESULTS: In 1L NSCLC and 3L MM, six and nine EU Member States (MS), respectively, had published HTA reports. PICO consolidation resulted in 10 PICOs for 1L NSCLC and 16 PICOs for 3L MM, increasing to 14 and 18 PICOs respectively when England's NICE scope was included to proxy remaining MS. A minimum of 280 and 720 analyses would be requested, exponentially increasing as additional outcome measures and subgroups are requested. CONCLUSIONS: The PICO approach outlined by EUnetHTA 21 results in a significant number of analysis requests and substantial resources. Use of complementary analyses alongside evidence-based methods to derive PICOs and engaging with the health technology developer throughout the process, would create a workable EU PICO that is predictable and most impactful for the EU, resulting in a timely and high-quality assessment report that is more usable at a MS level.

Linking Reimbursement to Patient Benefits for Advanced Therapy Medicinal Products and Other High-Cost Innovations: Policy Recommendations for Outcomes-Based Agreements in Europe.

OBJECTIVES: Health technology assessment (HTA) of advanced therapy medicinal products (ATMPs), such as high-cost and one-time cell and gene therapies, is particularly challenging. Outcomes-based agreements (OBAs) are a potential solution to mitigate the risks while providing access to patients but are not widely used across Europe. This study aimed to develop policy recommendations to support the acceptability and implementation of OBAs in Europe. METHODS: A policy sandbox approach was used to engage with stakeholders and explore how HTA organizations can support reimbursement decisions regarding OBAs for ATMPs. A panel of 38 experts from across the European region was convened in 2 workshops, representing payers, HTA organizations, patients, registries, and an industry trade body. RESULTS: Policy recommendations were developed to support the appropriate consideration of OBAs for reimbursing highly uncertain technologies, such as ATMPs. If a positive HTA recommendation cannot be made at the proposed price, then a simple price discount reflecting the uncertainty is preferred over complex solutions such as OBAs. If an OBA is pursued, it should be designed collaboratively with all stakeholders to understand data collection feasibility and minimize burden to patients and providers. Payers are encouraged to approach OBAs as a tool for informed decision making, including a readiness to make negative reimbursement decisions based on unfavorable evidence. CONCLUSIONS: The study presents a policy framework for using OBAs in reimbursement decisions. OBAs must be carefully designed, focusing on appropriateness and the burden of implementation. The relevant authorities should be committed to making decisions in light of the resulting evidence.