Nusinersen and risdiplam are available in the Brazilian Unified Health System (SUS) for the treatment of spinal muscular atrophy (SMA) type 1. Onasemnogene abeparvovec, a promising gene therapy, was approved in 2020 in Brazil. Given the high cost of this therapy and its promise of a lifetime effect, the objective of this study was to evaluate the cost effectiveness of onasemnogene abeparvovec, compared with nusinersen and risdiplam, in the treatment of SMA type 1 from the perspective of SUS in different scenarios.

A Markov model was adapted from one originally developed for the USA that considers five states of health. Short-term data were obtained from pivotal clinical trials and long-term survival curves were extracted from published reports from the USA. Maintenance of motor function milestones achieved at the end of follow up in clinical trials was considered until death. Costs and quality-adjusted life-years (QALYs) were discounted at five percent per year over a baseline lifetime time horizon. Alternative scenarios were evaluated for horizons of five and ten years, with and without a discount.

Onasemnogene abeparvovec resulted in an incremental cost of BRL742,890 (USD297,156) per QALY and an increase of 3.32 QALYs in relation to the alternatives over a lifetime time horizon. In the same time horizon, but without the discount, onasemnogene abeparvovec resulted in an incremental cost-effectiveness ratio (ICER) of BRL166,539 (USD66,615) per QALY. In a five-year time horizon, considering the discount rate, the therapy resulted in an ICER of BRL12,527,667 (USD5,011,066); in ten years the ICER was BRL3,384,793 (USD1,353,917).

Since the benefits of onasemnogene abeparvovec mainly occur in the long term, decision makers need to consider the uncertainty of assumptions of sustained effectiveness in view of the high initial cost of the technology.

Osteoporosis is characterized by decreased bone mass and density, increasing skeletal fragility, and the risk of fragility fracture. Fragility fractures are associated with a high economic burden. Denosumab (Prolia®) is a pharmacological therapy used to treat osteoporosis and reduce the risk of fragility fracture. This study aimed to assess the cost effectiveness of denosumab, compared with other pharmacological therapies (oral bisphosphonates, intravenous [IV] ibandronate, zoledronate, raloxifene, and bazedoxifene) and no treatment, for treating postmenopausal women with osteoporosis.

A discrete event simulation model was developed using a lifetime time horizon. A Swiss healthcare payer perspective was adopted. Time-to-fracture distributions were derived from Swiss-specific Fracture Risk Assessment Tool (FRAX®) probabilities. Reductions in the risk of vertebral and nonvertebral fractures due to treatment were informed by a Bayesian network meta-analysis. Cost-effectiveness frontier analysis was utilized. Pairwise incremental cost-effectiveness ratios (ICERs) between denosumab and each comparator were also estimated. Sensitivity analyses were conducted to identify key drivers and explore the overall certainty of findings.

At a hypothetical willingness-to-pay (WTP) threshold of CHF100,000 (EUR101,630), IV ibandronate was the most cost-effective therapy in women aged 60 years who had a very high risk of fracture, and in women aged 70 or 80 years of any risk level. In women aged 60 years with a lower risk level, zoledronate was the most cost-effective option. Nevertheless, ICERs from pairwise comparisons between denosumab and some comparators (no treatment, bazedoxifene, raloxifene, and/or zoledronate depending on the cohort’s age and risk profile) were below the hypothetical WTP threshold. Higher intervention costs, smaller reductions in the risk of hip fracture, and shorter duration of residual benefit associated with denosumab contributed to the high ICER values seen in pairwise comparisons with oral bisphosphonates (as a class) and IV ibandronate.

The present evaluation supported the cost effectiveness of denosumab against some, but not all, comparators. Nevertheless, these results should be interpreted cautiously in light of uncertainty in the true effect of treatments on fracture risk.

Approximately 34.8 million people globally are affected by HIV, 34,000 of whom are in Türkiye, and the impact of HIV continues to grow. Not providing the necessary treatment eventually leads to life threatening AIDS-related consequences. In this study, a descriptive analysis of the published official data on HIV/AIDS was undertaken to assess existing statistics and raise social awareness. The aim was to provide data that will help decision makers in future planning by forecasting the possible number of cases and treatment costs to 2030 using available statistics in Türkiye.

The forecast of HIV-infected patients, deaths, and healthcare costs to 2030 were calculated using linear regression based on data published between 1985 and 2022 in the literature or by official authorities. The proportion of past deaths caused by AIDS was used to forecast deaths, and the number of patients living with HIV was estimated indirectly using this forecast. Possible treatment expenditures related to HIV/AIDS in Türkiye were estimated based on published healthcare cost data and the number of living patients obtained by considering the possible increase in HIV/AIDS cases, future inflation predictions from the Turkish Central Bank, existing literature, and information from statista.com.

Estimates suggested that 3,002 new cases of HIV/AIDS in 2021 will become 5,709 among a total of 74,227 living patients in 2030. The 598 deaths reported between 1985 and 2022 are predicted to rise to 1,256 by 2030. Estimation of the total treatment cost of HIV/AIDS was TRY1,051,026,183 (USD118,683,580) in 2021, which was estimated to reach TRY15,432,842,049 (USD296,450,696) by 2030. This consisted of outpatient visits (TRY246,710,838 [USD4,739,088]), laboratory tests (TRY2,072,489,815 [USD39,810,623]), inpatient visits (TRY1,352,192,479 [USD25,974,373]), management of complications (TRY3,371,126,960 [USD64,756,247]), and antiretroviral therapy drugs (TRY8,390,321,957 [USD161,170,365]).

The prevalence of HIV/AIDS is expected to rise by 137 percent by 2030, with the economic burden increasing 14.7 times in TRY (2.5 times in USD) from 2021 to 2030 in Türkiye. This proves the severity of the situation and the need for relevant policy measures for society.

In scenarios of vaccine scarcity or the context of organizational complexity, it is necessary to define prioritization strategies for allocating vaccine in compliance with the criteria of equity and efficiency of health resources. The COVIDIAGNOSTIX project, based on health technology assessment (HTA), assessed the role of SARS-CoV-2 serological tests as a companion diagnostic in the definition of strategies for vaccine administration. To guarantee evidence support for health policy choices, two different strategies were analyzed: one based on administering the vaccine booster dose to the entire population (VACCINE strategy) and the other based on allocation criteria (TEST&VACCINE strategy).

An Italian multidisciplinary team conducted a decision-oriented HTA using a combination of the EUnetHTA Core Model and the multicriteria decision analysis model based on the Analytic Hierarchy Process.

Moreover, the Department of HTA method was integrated with the Susceptible-Exposed-Infectious-Recovered model, appropriate modelling techniques, simulation, and quantification of uncertainty that considered the ability to reduce deaths and to contain the pandemic. After identifying the evaluation elements and the decision-making structure, the weights of the evaluation areas and key performance indicators were calculated. This is a constituent part of the mathematical model of data processing, as the Analytic Hierarchy Process was based on a structured questionnaire that compared the relative importance of the two elements on a qualitative scale (1=equal importance; 9=more important).

The processing of the scores attributed to the key performance indicators concerning all the evaluation domains resulted in a performance of 94 percent for the TEST&VACCINE strategy and 84 percent for the VACCINE strategy. The TEST&VACCINE strategy was the most advantageous in various scenarios due to the greater speed of response from an operational and economic point of view.

The assessment schemes defined by COVIDIAGNOSTIX (i.e., technologies, intended use, and settings), which highlight the characteristics that differentiate the tests from each other and guarantee a timely and appropriate evaluation, can be adapted to respond to similar health policy management situations.

In clinical practice, health outcomes relevant for economic evaluations, such as health-related quality of life (i.e., utilities), are not always available. However, algorithms can be developed to map available outcome measures to utilities. In the Netherlands, the Health of the Nations Outcomes Scores (HoNOS) is a physician-reported, disease-specific outcome measure frequently used for patients with severe mental illness for which no mapping algorithms for utilities currently exist. The aim of this study was to develop an algorithm to map responses on the HoNOS to EQ-5D utilities for use in economic evaluations.

A dataset was obtained from the Pharmacotherapy Monitoring and Outcome Survey cohort study containing data from patients with psychotic disorders. The dataset contains EQ-5D-3L domain and HoNOS scores, the age and sex of patients, and additional demographics. Correlation between the EQ-5D-3L and HoNOS was evaluated. To derive mapping functions, least absolute shrinkage and selection operator (LASSO) regression and random forest algorithms were applied with various predictor variables using a machine learning approach, whereby data were split into separate training and test sets. Cross-validation was then used to compare the performance of different models using R-squared and the root mean square error (RMSE).

A total of 2,111 patients were included in the study. Spearman’s correlation coefficients indicated a weak to moderate negative correlation of -0.31. Based on model performance metrics, LASSO models outperformed random forest models on the training set, where the model including all individual HoNOS items and the age and sex of patients showed the best overall performance with an RMSE of 0.237 and an R-squared of 0.218. When applied to the test set, this resulted in an R-squared of 0.233 and a mean absolute error of 0.177.

The HoNOS can be mapped onto EQ-5D-3L utilities with moderate predictive accuracy. The reported mapping algorithm may be sufficient to predict overall population utility scores for use in health economic evaluations but lacks accuracy for individual patient predictions.

Machine learning (ML) algorithms are computational procedures that use pattern recognition and inference by learning from previously categorized documents to predict the category to which a new document belongs. The role of machine learning within cancer registries remains unclear given the lack of in-depth testing and guidance from health technology assessment (HTA) agencies. We evaluated the effectiveness of coding new cases through machine learning at the Integrated Cancer Registry.

The Integrated Cancer Registry covers the eastern area of Sicily in Italy, which has an annual average incidence of about 10,000 cases of malignant neoplasm. Potential new cancer cases were retrieved from pathology services and processed by pathologists who confirmed the neoplastic nature of supposed cases and specified the morphological type and location of the tumors. The current method involves identification by reading the free-text report when International Classification Diseases for Oncology information was not provided. We used the new Microsoft ML.Net Library, a framework developed in response to the challenge of facilitating machine learning pipeline utilization in large software applications. A total of 1,050,952 free-text pathology reports published from 2003 to 2018 were selected separately from all Sicilian pathology services and uploaded to machine learning software that explored eight binary classification algorithms.

We evaluated each algorithm’s performance by calculating metrics (the number of true positives, true negatives, false positives, and false negatives) from the classification procedure applied to the test dataset. The metrics used were accuracy, F1 score, and area under the receiver operating characteristic curve. With a test set of around 210,000 text diagnoses, each algorithm reached an F1 score of up to 95 percent.

Machine learning algorithms capture relevant information about tumors from free-text pathology reports, optimizing the process and reducing waste. With the help of machine learning systems, cancer registries can provide more timely data for research and evaluation of all types of new cancer technologies (drugs, devices, radiology and radiotherapy equipment, diagnostic devices, robotic surgery, and vaccines).

Over the past decade there have been increasing interactions between health technology assessment (HTA) agencies through international networks at the policy level and European joint actions at the product level. A pilot project is underway to explore collaboration beyond Europe between HTA agencies in Australia, Canada, and the UK. This study the compared HTA recommendations of new active substances (NAS) appraised by Australia’s Pharmaceutical Benefits Advisory Committee (PBAC), Canada’s CADTH, and England’s National Institute for Health and Care Excellence (NICE).

Using publicly available data and established benchmarking methodology, we examined 45 NAS appraised by PBAC, CADTH, and NICE between 2017 and 2021. Analysis was performed to assess rollout time from regulatory to HTA recommendation, and to the first HTA recommendation.

Most products were submitted to the Europe Medicine Agency first (89%). However, 71 percent of NAS in Australia and 69 percent in Canada were submitted to HTA in parallel with regulatory review, which shortened overall rollout time. The median HTA submission gap among the three agencies was 140 days in Australia, 102 days in Canada, and 8 days in England. PBAC had the highest number of negative recommendations (51%), followed by CADTH (18%), and NICE (5%). The congruence of HTA decisions was highest between CADTH and NICE (56%), compared with PBAC and CADTH (11%), and PBAC and NICE (20%)

To achieve a more collaborative HTA process it is necessary to understand the rollout time in these jurisdictions. This study identified submission gaps among the regulatory agencies, but there may be more synergy in the future as regulators in the three jurisdictions work collaboratively through the Access Consortium. Currently, the submission gap for the three HTA agencies was mostly within six months, making collaboration on joint assessment possible. We observed divergences in HTA recommendations due to the methodology and decision criteria applied by each agency. Therefore, collaboration on assessment should build on the clinical aspects, although HTA decisions should be grounded in the local context.

The National Institute For Health And Care Excellence (NICE) is widely acknowledged as a seminal health technology assessment (HTA) body, known for its transparent and accountable approach to decision-making. This research aimed to investigate the impact of NICE methodology and decisions on international HTA bodies. We sought to identify direct and indirect factors that may influence an international HTA body’s methods or outcomes. To the best of our knowledge, this is the first research to use a qualitative approach to understand the influence of NICE on other HTA bodies.

We conducted 13 semi-structured qualitative interviews with HTA and market access experts from industry and academia from nine countries (Brazil, Israel, Italy, Japan, Poland, Saudi Arabia, South Korea, Sweden, and the United Arab Emirates). The interview script was organized into three main sections: comparing NICE methods and processes with other HTA bodies; the impact of specific NICE decisions; and Likert scale questions (to allow for comparability of opinions).

Most interviewees believed their local HTA body would consider NICE’s decision when evaluating a medicine. However, the way and extent to which NICE influences HTA varied across countries. The most common means of considering a NICE decision was as background information or context for an HTA evaluation. Generally, interviewees suggested that negative NICE decisions had more impact on local decision-making than positive decisions. Nine of the 13 interviewees agreed or strongly agreed that their country’s HTA body considers the decisions of other HTA bodies in their decision-making process. Eleven of the 13 interviewees agreed or strongly agreed that the development of their country’s HTA body methods and processes was influenced by NICE.

NICE is perceived to be a seminal HTA body, with continued influence on HTA agencies in other countries. However, the mechanisms and extent of this influence varies considerably between countries. We suggest that implicit factors are likely to contribute more to NICE’s influence than individual decisions. Nevertheless, further research is needed to reveal these factors and increase efficiency in international HTA decision-making processes.

Hospitals play a significant and important role in funding high-cost medicines so patients can access treatments they need. High-cost medicines are often specialty medicines, which contribute to a significant and increasing portion of the hospital budget. It is imperative that these expensive medicines are governed and managed with a fair, standardized evidence-based process. We aim to provide a framework for Drugs and Therapeutics Committees (DTCs).

During 2021, Guiding Principles were developed following a literature review and survey of current practices by DTCs in Australia. An Expert Advisory Group (EAG) was convened, comprising individuals with expertise in quality use of medicines, evidence-based medicine and medicines governance. The guiding principles were drafted by the EAG, in consultation with a range of stakeholders and relevant external organizations. All feedback was collated, reviewed and discussed to refine the content of the final Guiding Principles released in January 2022.

Seven overarching principles provide key recommendations for the governance of high-cost medicines:

1. (i) A definition of high‑cost medicines should be determined and clearly articulated for use by each medicines governance committee.

2. (ii) Review of high-cost medicines requires members with relevant expertize to facilitate good and effective decision-making.

3. (iii) The committee should engage directly with the applicant prior to review to ensure a full understanding of the rationale for the request.

4. (iv) consistent, robust and transparent procedure for the assessment of high-cost medicine applications should be defined and implemented for use by each medicines governance committee to ensure fair process.

5. (v) Ethical considerations fundamentally underpin deliberations around high-cost medicines.

6. (vi) The decisions and outcomes of the decision making should be transparent and appropriately communicated to the various audiences.

7. (vii) The high-quality assessment of high-cost medicines requires appropriate training and resourcing.

These national Guiding Principles promote consistent, evidence-based use of high-cost medicines and provide a framework for DTCs to assess and achieve effective governance for the quality use of high‑cost medicines.

Expert judgement has an important role in health technology assessment (HTA), including as a source of evidence to inform economic modeling when published data are lacking. Quantitative information may be elicited from experts to inform model inputs and associated uncertainty using one of many expert elicitation methodologies. Here, the feasibility and potential benefits of one expert elicitation method, the Sheffield Elicitation Framework (SHELF), to the HTA process is examined.

The SHELF method seeks to express the knowledge of multiple experts in the form of a subjective probability distribution. Eliciting a subjective probability distribution allows the uncertainty of experts to be included in probabilistic sensitivity analysis, which is becoming an increasingly prominent feature of HTAs. The individual knowledge of participating experts is combined through behavioral aggregation, where experts participate in a discussion before being asked to provide judgments from the perspective of a rational impartial observer. The whole process is led by a facilitator who ensures all participants contribute and confirm that the final distribution is a product of consensus, not compromise.

We recently conducted two SHELF elicitations as part of an ongoing project aiming to streamline the assessment of positron emission tomography (PET) in Australia. These elicitations provided insight into the usefulness of SHELF within the HTA setting. Given the constraints imposed by the COVID-19 pandemic, the elicitation sessions were conducted online rather than in the ideal face-to-face manner. In collaboration with one of the developers, we successfully adapted the method by making use of video conferencing technology to provide an online environment that mimicked the face-to-face setup as much as possible.

SHELF provides a rigorous and scientific method by which to elicit the knowledge of multiple experts in the form of a probability distribution. However, the method is resource intensive and may be best reserved for when data on key drivers are lacking.

New statistical methodology, known as progression models for repeated measures (PMRM), can estimate the slowing of progression (percentage slowing or time delay) of Alzheimer’s disease from trial data on disease-modifying therapies. We compared the PMRM methodology with mixed models for repeated measures (MMRM) and Cox time-to-event analysis on simulated trial data with respect to their power and interpretability of estimates.

Two novel models were included: PMRM (estimating slowing of progression and allowing different rates across visits) and proportional-slowing PMRM. Clinical Dementia Rating (CDR) Sum of Boxes score and progression to dementia as assessed by CDR global score were the primary outcomes for MMRM/PMRM and the Cox model, respectively. Subject-level placebo arm trajectories were jointly simulated based on estimated CDR mean trajectories and joint temporal correlation structure of 538 amyloid-positive patients with mild cognitive impairment who met typical disease-modifying trial inclusion criteria from the Alzheimer’s Disease Neuroimaging Initiative study. Active arm trajectories were simulated to show an average 20 percent slowing of disease progression, compared with placebo, at each visit. We conducted 1,000 simulations across multiple scenarios, varying the number of patients per arm (200 to 700) and clinical trial duration (18 to 36 months).

The power of PMRM models was greater than that of MMRM, and much greater than that of the Cox model whose power never exceeded 45 percent. PMRM models accurately estimated the underlying treatment effect (median 20% slowed progression, which translated to a delay in progression of 5 and 7 months at trial durations of 24 and 36 months, respectively), unlike quantifications of the MMRM (median estimated 25% reduction in decline), and the Cox model (median estimated hazard ratio of 0.9).

For disease-modifying therapies, PMRM estimates may have a more intuitive clinical interpretation in terms of delayed progression than MMRM or Cox models and enable a description of the amount of time spent in less severe disease stages. Among all the methods studied, PMRM offered the best combination of interpretability and power.

Few studies have explored the relationship between different venous access devices and health-related quality of life (HRQoL) among patients with breast cancer in China. This study aimed to evaluate the HRQoL of patients with breast cancer in China who underwent different venous access devices and to estimate the association between type of venous access device and HRQoL.

A multicenter cross-sectional study was conducted in three tertiary hospitals from three major geographical regions in China. The final sample consisted of 472 patients aged from 18 to 78 years. The HRQoL was measured with the EQ-5D-5L scale and the EuroQoL Group visual analog scale. The venous access devices were divided into totally implantable venous access devices (TIVAD), peripherally inserted central catheters (PICC), and other devices. The multivariate regression analyses were used to explore the association between type of venous access device and HRQoL.

Of 472 participants, 352 (75%) used the TIVAD device, 89 (19%) used the PICC device, and 31 (7%) used other devices. The TIVAD group had the highest EQ-5D-5L values (mean 0.89, standard deviation [SD] 0.178), while the PICC group had the lowest values (mean 0.85, SD 0.239). The EQ-5D-5L values for the other venous access device group was in between (mean 0.88, SD 0.127). However, the multivariate analysis indicated that the VAS and EQ-5D-5L scale dimension scores among patients were not significantly different (P>0.05) for the various central venous access devices.

This study demonstrates a non-significant association between the type of venous access device used and the HRQoL of patients with breast cancer in China. Although patients with a TIVAD experienced more pain during device insertion and access for chemotherapy, the negative effect on HRQoL scores was smaller than for PICCs.

Limited knowledge of the symptomatology of aortic stenosis (AS) among the general population may delay diagnosis and have a major impact on morbidity and resource use. Training programs have often been advocated by the scientific community. The present study reported the results of an assessment of a training program for the general population.

Patients who attended healthcare centers were asked to answer a questionnaire on their level of knowledge around AS. A cohort of patients without training (n=681) answered the questionnaire and a second cohort answered the questionnaire via phone 24 hours after training (n=197). Propensity score matching by sex and age was used to obtain a balanced sample between the two cohorts, giving a total study sample of 394 individuals (197 without training and 197 with training). A descriptive analysis was performed to compare differences in the level of knowledge between the two cohorts. Predictors of AS symptomatology were identified using multivariate logistic regression.

The trained cohort was more aware of AS disease than the untrained cohort (79% versus 31%, 95% confidence interval [CI]: 0.39, 0.56; p<0.001). They were also better at distinguishing the symptoms associated with AS (80% versus 43%, 95% CI: 0.28, 0.48, p<0.001) and were more aware of its severity (36% versus 12%; 95% CI: 0.16, 0.32, p<0.001). Moreover, the trained cohort were better at identifying symptoms that should make them consider visiting a doctor (76% versus 65%; 95% CI 0.02, 0.20, p<0.02). No differences were observed in level of concern regarding AS (8% versus 4%; 95% CI: -0.0046, 0.09, p=0.08).

The trained people who were aware of AS (p=0.04) correctly classified AS as a valvular disease (p=0.025), would seek medical consultation when AS symptoms occurred (p=0.04), and were more likely to correctly detect AS symptoms.

The training program significantly improved the knowledge and awareness of AS in the general population. This can improve the timeliness of AS diagnosis, reducing the health and economic burden of AS for the healthcare system.

Aortic stenosis is an insidious disease that has a high mortality rate when it becomes symptomatic. Surgical valve replacement is the treatment of choice and has predictable risks. Transcatheter aortic valve replacement (TAVR) is a less invasive alternative to surgery, which is indicated for high-risk patients.

Complications after TAVR include paravalvular leak, cerebrovascular events, and the need for pacemaker implantation. A health technology assessment report carried out by the Health Technology Assessment Unimed-BH group in 2018, two years before it became part of the National Supplementary Health Agency, recommended the introduction of TAVR with the following criteria: indications provided by a group of specialists; forwarding of a report with detailed clinical data; results of imaging exams; and follow-up results for up to one year after the procedure. After the introduction of TAVR with the agreed criteria, it was possible to access TAVR results from the private healthcare system of Unimed-BH.

Administrative data were collected from the Unimed-BH database. All patients who received a TAVR implant from 2013 to 2017 were included by virtue of a court injunction, and after 2018 by operator concession and within agreed criteria.

From July 2013 to June 2019, 83 patients underwent TAVR implantation by Unimed BH. The median age of patients was 83.4 years (interquartile range 66.5 to 97.9), most of whom were women (56%). There was a predominance of patients in New York Heart Association classification III (50%) and IV (29%). There were 36 patients who underwent TAVR before 2018 and 47 patients within the agreed criteria. In the period prior to the agreed criteria, 28 percent needed a pacemaker, compared with 23 percent after 2018. During the follow-up period, 39 patients died: 18 (50%) before 2018 and 11 (23%) after 2018.

The agreement made with the providers, which included the obligation of having a team of specialists responsible for the indication and access to clinical data through the report, improved patient outcomes. This may be due to having a better indication for the procedure or to the greater experience of the professionals involved in its delivery.

The hospital-based Health Technology Assessment (HB-HTA) Unit in the Hospital of the President’s Affairs Administration has been operating since 2015 and is the first example of the implementation of the HB-HTA system in Kazakhstani hospitals. In addition to assessing the feasibility of implementing new health technologies (HTs) into the hospital’s practice, the Unit also interacts with the National Regulatory Authority (NRA) to transfer new technologies into the National Reimbursement System (NRS). We report on the transformation of the HB-HTA Unit from a stand-alone entity to an integrated, specialized agency.

Data were drawn from reports of the HB-HTA Unit and internal NRA documents. Inclusion of new HTs into the NRS consists of the following sequential stages: (i) implementing the technology in at least one hospital; (ii) filing an application with the Ministry of Health Care (MoH) in the field of HTA to resolve the issue of reimbursement at the national level; (iii) in case of a positive decision, approval at the national level of the clinical protocol for using the medical intervention; (iv) agreement on the reimbursement price of the technology.

Based on positive recommendations from the HB-HTA report in 2015, the hospital implemented 19 new nuclear medicine technologies. In 2016, the hospital initiated an application to the MoH to include these technologies in the NRS (previously, these technologies were carried out only for a fee or with private insurance). From 2016 to 2020, a positive decision from the MoH was received, protocols for medical interventions were published at the national level, and cost estimates were formulated. In 2021, 19 new medical services in nuclear imaging and scintigraphy were included in the NRS.

Despite the long and bureaucratic process of including new HTs in the NRS, the HB-HTA Unit managed to speed up this process. One of the main priorities of the integrated HB-HTA Unit is to promote the transfer of HTs into the health system at the national level.

Health technology assessment (HTA) agencies in Spain have an important role in informing decisions about the introduction and use of health technologies in the Spanish National Health System. However, although different approaches have been taken to measure and improve their impact, no study to date has explored the perceived impact of HTA products at the national level. The aim of this study was to explore the perspectives of macro-, meso-, and micro-level decision makers on how to improve the impact of HTA.

Three online focus groups were conducted with policy makers, healthcare managers, clinicians, and patients. The transcripts were evaluated using a deductive thematic analysis based on a multidimensional framework to explore mechanisms of impact.

Four key themes were identified:

1. (i) Timeliness and use of HTA assessments: Although the quality of the reports was recognized, the time taken for the elaboration and extension of reports negatively affected their use. Participants considered that reports should be tailored to the needs of end users (e.g., briefer versions available for meso-and micro-level use);

2. (ii) Effective engagement and external communications: The engagement of multiple stakeholders (policy makers, manufacturers, clinicians, and patients) in the elaboration process was considered crucial to improve HTA impact and ensure adequate communication of results;

3. (iii) Good institutional reputation and fit within the healthcare and policy making system: Stakeholders agreed on the need to strengthen collaboration at the national level and increase public understanding of the value of HTA and its use in healthcare decision-making; and

4. (iv) Effective implementation of policy change regarding health technologies: Stakeholders were very receptive to the results and recommendations of HTA reports when new technologies are demanded, but the identification and selection process should be improved to guarantee that these reports are available on time.

This study has identified different proposals and mechanisms that could improve the impact of HTA in Spain.

Healthcare reform through appropriate care is a current focus for many jurisdictions. A variety of policy options, or “levers,” are available to decision makers to influence appropriate care. However, these levers are not always identified in advance of developing policy recommendations, and few direct, empirical analyses are available to support their selection. An appropriate care policy lever inventory was developed for health technology assessment (HTA) users in Alberta, Canada, to support HTA scoping and policy development.

Relevant information was identified by a single reviewer through a scoping search of MEDLINE, forward and backward searching, and targeted gray literature searches. An Excel-based inventory was populated with a list of policy levers and their descriptions, policy effectiveness, and implementation considerations. Filters were developed to identify levers based on key characteristics. The inventory was iteratively refined through presentations to and feedback from key user groups.

The inventory contained 53 policy levers aiming to influence service provision, clinician behavior, fiscal policies, populations or organizations, and patient behavior. The levers varied in how they restrict decision-making. Few levers were considered high impact (>5% change to behavior, utilization, or cost) or well-supported (>10 studies reporting effectiveness). Stakeholders found the inventory information useful, particularly for considering potential levers not frequently utilized within their respective programs. A user guide and case examples were also developed to help users learn to navigate the inventory.

An inventory of policy levers, which can be tailored to specific clinical areas and topics, can be of assistance to healthcare decision makers developing and utilizing HTAs to improve appropriateness of care. With limited indication-specific evidence, policy makers must utilize the broader evidence base on appropriate care policy levers to select and implement strategies that are applicable and transferable to their context. Challenges remain in systematically identifying all relevant literature given the inventory’s breadth, and in updating the inventory to reflect new evidence.

The Swiss Health Technology Assessment (HTA) program is a unique, innovative program that connects research with policy making. In 2017, a HTA unit was established within the Federal Office of Public Health following a decision by the Federal Council in 2015 to intensify efforts in HTA.

The legal basis of the HTA program is Article 32 of the Federal Health Insurance Act, which specifies that health technologies (i.e., all preventive, diagnostic, and therapeutic interventions in health care) covered by the compulsory health insurance must be effective (E), appropriate (A), and economically efficient (E).

Health technologies that do not meet the EAE criteria are not eligible for coverage. For health technologies that are already reimbursed, re-evaluation of the criteria can result in the removal of technologies from the catalog of benefits or limitations being placed on their reimbursement.

The initial focus of the HTA program was the re-evaluation of controversial health technologies. This focus was later expanded to evaluating new and upcoming technologies through horizon scanning. Challenges encountered since the start of the program include:

• • aligning the classic HTA domains with the EAE criteria;

• • identifying suitable re-evaluation topics;

• • tailoring HTA processes to regulation options and decision-making processes; and

• • involving stakeholders in the HTA process without jeopardizing the quality and objectivity of the research.

Despite various initial challenges, the HTA program has become an acknowledged and appreciated actor within the Swiss reimbursement policy landscape. An outlook on the program’s future will also be shared.

In Brazil, the incorporation or disinvestment of health technologies into the Unified Health System (SUS) are advised by the National Committee for Health Technology Incorporation (Conitec). Despite the thorough evaluation carried out by Conitec, the results measured after implementation do not always reflect the economic and clinical impact expected from the incorporation. Thus, real-world evidence (RWE) is essential for monitoring health technologies. The aim of this study was to report how Brazil is using the RWE to obtain additional information about the incorporated technologies.

Actions related to the use of RWE for monitoring of technologies incorporated into the SUS were described. The period evaluated was between 2012 and 2022.

The first Conitec recommendation in which the use of real-life data in the decision-making process was evidenced occurred in 2016. Administrative data from a cohort of patients identified that beta-interferons for Multiple Sclerosis were less effective than the other drugs used in the Brazilian public system. A further eight reports have been published assessing the performance of technologies using administrative data.

Another strategy for RWE generation was through the funding of primary studies, highlighting a study with 21 rare diseases and another one to evaluate Zolgensma gene therapy, acquired through court for Spinal Muscular Atrophy. Both studies are ongoing and aim to evaluate the effectiveness, safety, adherence, and cost of medications in the evaluated diseases. Conitec is also following studies in RWE financed by pharmaceutical companies to evaluate effectiveness for incorporated technologies subject to reassessment. Additionally, managed access arrangements have been promoted for generating RWE when there is uncertainty about outcomes.

Real-world evidence from administrative data and clinical research allows monitoring after the implementation of technologies in the Unified Health System in Brazil. This makes it possible to reallocate resources in health and contribute for the system sustainability, in addition to generating data that reduce the uncertainties assumed at the time of incorporation.

Real-world data (RWD) is an important source of evidence for health technology assessment (HTA). It is widely used to fill clinical trial data gaps and to inform risk-sharing agreements. HTA is mandatory in many jurisdictions as it is used for price negotiation between a manufacturer and a payer. HTA practitioners have so far had limited involvement in the debate surrounding access to RWD as regulators have primarily focused on scientific research and market authorization. This study examined the challenges of obtaining RWD for HTA decision-making that is beneficial at the population level when data sources are restricted to maintain the data integrity and rights of the public.

Types of RWD and processes for obtaining data were assessed for two jurisdictions (Australia and Denmark). Types of data considered were national registries, ongoing or completed cohorts, surveys at various universities, archived historical data, and medical claims data. The assessment was performed by analyzing a series of cases.

There were similarities and differences between the two jurisdictions. In both jurisdictions the process for obtaining data included an ethics application as well as data handling fees. Patients and clinicians had little to no say in what their data are used for. It can take up to six months to obtain data. Person identification numbers enable linking of different datasets. Population wide data are accessible in Denmark only through secure servers, whereas full data sets, such as prescription data, can be released for research in Australia. Public hospital data, such as electronic health records, are not easily obtained in Denmark. In Australia, public hospitals are run by individual states and, therefore, additional effort is required to access nationwide data.

Access to RWD for HTA is challenging in both Australia and Denmark. Improvements in the process of applying for data and linking different data sources for HTA purposes are still needed.