The COVID-19 pandemic significantly affected healthcare systems. The most immediate effect was the increased demand for healthcare resources. This study aimed to conduct a case-mix analysis at one of the teaching hospitals in Malaysia to understand the economic implications of the pandemic.

Admissions related to COVID-19, either as a primary or secondary diagnosis, were extracted and given ICD-10 codes for diagnosis and ICD9-CM codes for procedures. The combined ICD-10 and ICD9-CM codes were imported into a case-mix grouper to generate the case-mix codes. The codes used for COVID-19 were A-4-13-I, A-4-13-II, and A-4-13-III for mild, moderate, and severe disease, respectively. Clinical pathways were collected and healthcare resource utilization was estimated by combining top-down and bottom-up costing approaches. Discounting and inflation were based on guidelines and official rates. The cost data were reported in US dollars (price year 2021).

A total of 4,889 patients with a COVID-19 diagnosis were admitted to the hospital in 2021. Of these, 4,813 patients (98%) had a primary diagnosis of COVID-19. The remaining 76 patients (2%) were admitted for other medical reasons but were found to be positive for SARS-Cov-2 during admission. Therefore, for these patients, infection with the virus was considered a secondary diagnosis during the treatment episode.

Among the 4,813 patients, 3,909 (81%) were admitted with mild COVID-19 (A-4-13-I), 630 (13%) had moderate COVID-19 (A-4-13-II), and 274 (6%) had severe disease (A-4-13-III). More than half (56%) of the patients with a secondary diagnosis of COVID-19 were admitted for elective procedures. The average length of hospital stay (LOS) for mild disease was 9 days, with cumulative hospital costs of USD1,543. The average LOS for both moderate and severe disease was 21 days, and the cumulative hospital costs were USD23,527 and USD26,731 respectively. The total costs incurred for COVID-19 were estimated at USD19,259,153.

COVID-19 has considerable economic implications. This study provided information as part of a health technology assessment in the hospital to inform evidence-based healthcare decisions.

Gaucher disease is a lysosomal storage disease of autosomal recessive inheritance that is caused by a deficiency of the enzyme glucocerebrosidase. This deficiency results in accumulation of the enzyme’s main substrate in the lysosomes of macrophages, mainly in the spleen, liver, and bone marrow. In more severe cases it can affect the lung, kidneys, and central nervous system. There are two main treatments available for patients with Gaucher disease: enzyme replacement therapy and inhibition of substrate synthesis. The main enzyme replacement therapy used in Brazil is imiglucerase, an analog of the human β-glucocerebrosidase enzyme. Imiglucerase is produced by recombinant DNA technology using a cell culture derived from the Chinese hamster ovary. It has 497 amino acids and differs from the endogenous enzyme by an amino acid at position 495, where histidine is replaced by arginine. The objective of the study was to analyze the survival of patients treated for Gaucher disease with imiglucerase in Brazil from 2000 to 2015.

We constructed a retrospective cohort study of patients with Gaucher disease who received imiglucerase through the Brazilian National Health System from 2000 to 2015 using a national database created from the linkage of administrative databases.

A total of 1,241 patients who received imiglucerase were included. The overall survival rates at one, ten, and 15 years were 98.7 percent (95% confidence interval [CI]: 98.1, 99.4), 92.3 percent (95% CI: 90.2, 94.4), and 89.4 percent (95% CI: 85.6, 93.3), respectively.

Our findings advance the understanding of the profile, survival, and risk factors of people with Gaucher disease, adding new data to the discussion regarding pharmaceutical therapies and patient care, and providing data for the development of new public health policies for the use of advanced, high-cost drugs for rare diseases.

Psoriasis is an immune-mediated chronic inflammatory disease that can affect the skin, joints, and nails. The treatment of the disease is offered by the Brazilian Public Health System (SUS) in accordance with the guidelines of the Ministry of Health. The aim of this study was to analyze real-world data (RWD) on the implementation and use of monoclonal antibodies (mAbs) for the treatment of psoriasis in the SUS.

This is a descriptive study that used national administrative data on drug dispensing from the Open Room for Health Intelligence Situation (SABEIS-SUS) from October 2019 to December 2021. Adult individuals (≥18 years) with vulgar (L40.0), generalized pustular (L40.1), gutata (L40.4) and other (L40.8) psoriasis who used the mAbs adalimumab, etanercept, risankizumab, secukinumab and ustekinumab were included.

The year of implementation of mAbs for the treatment of psoriasis in the SUS was October 2019 (adalimumab, etanercept and secukinumab) and May 2020 (ustekinumab). Risankizumab was implemented in April 2022. The number of individuals using mAb grew from 366 in 2019 to 10,146 in 2021. In 2019, 2020 and 2021, the proportion of individuals using each mAbs was 62.3 percent, 46.2 percent and 35.4 percent (adalimumab), 7.9 percent, 3.3 percent and 2.7 percent (etanercept), 29.8 percent, 33.8 percent and 30.5 percent (secukinumab), 0 percent, 16.7 percent and 31.4 percent (ustekinumab), respectively.

The number of mAbs users has greatly increased from 2019 to 2021, which may indicate a successful implementation of the psoriasis treatment in SUS. Most individuals used adalimumab in the year of the first implementation. However, the proportion of users of this mAb has greatly decreased after the implementation of ustekinumab. This reduction should not be so expressive since adalimumab and ustekinumab are recommended in different lines of treatment. The low proportion of etanercept use may be due the fact the medication is indicated for individuals up 18 years of age. This study provides important real-word evidence for monitoring the implementation of mAbs for psoriasis treatment in Brazil.

During COVID-19 pandemic Follow-up Centers were established by Turkish Ministry of Health (MoH) to detect possible complications in recovered COVID-19 patients at an early stage and make necessary interventions on time. It was aimed to reveal the short, medium and long-term effects of the disease by monitoring regularly. The Follow-up Center algorithms were designed by 10 clinicians of different branches with the support from United Nations Development Programme (UNDP). The follow-ups were made for one year in two pilot centers by using the health information systems infrastructure. In the dissemination process, Follow-Up centers were established initially in 24 and subsequently in 81 provinces.

In this study, the establishment, dissemination, operation and patient follow-up process of the COVID-19 Follow-up Centers were examined. The one-year (between 1 December 2021 and 1 December 2022) data obtained were analyzed. The patient follow-up;

• • was made at 0, 1, 3, 6 and 12 months for the first year,

• • planned to be made twice in the second year and the following years if needed.

In the first year, people who received 3 follow-ups by using the forms and scales in the integrated information system modules were assumed to be followed up regularly.

Among the one-year data obtained from the COVID-19 follow-up centers, the total number of follow-ups, the distribution of follow-ups by date, gender and age groups and symptoms according to time were examined. In the first year; 11,288 people were included in the follow-ups and 18,328 follow-ups were made; 2,462 people were followed-up regularly. The followed up people consisted of 51.8% women; 48.3% of them were men. The incidence of symptoms decreased from 1,198 people in the first follow-up and to 180 people in the third follow-up.

The establishment of Follow-up Centers is considered to be an important initiative to generate systematic data on the long-term effects of COVID-19. It was concluded that conducting studies using two-year data obtained from the follow-up centers, especially for complications, would be beneficial for management of the COVID-19 pandemic and in preparation for similar pandemics.

Assessing, funding, and implementing cell and gene therapies are usually based on limited evidence. This requires health technology assessment (HTA) agencies to develop new methodologies; payers to accept risk-based funding; industry to consider the right evidence and price; hospitals to consider if they have the necessary requirements; patients to consider their risk appetite for gene therapies; and health departments to consider all the above. Ensuring timely patient access to these therapies is challenging in Australia’s federated health system. To ensure stakeholders are aligned, all must come to the table and share their respective insights, experiences, and expertise to support planning, decision-making, funding, and commissioning of these therapies. It is time to develop a new consultative and decision-making paradigm to expedite HTAs, funding, commissioning, and timely patient access for cell and gene therapies.

Australian federal, state, and territory government representatives agreed to develop a framework that clarifies processes around information sharing, HTA, funding, commissioning, and monitoring of highly specialized therapies and services (including cell and gene therapies). A draft national framework was developed that addresses assessment, funding, and implementation of high cost, highly specialized therapies and services (e.g., bone marrow transplants). However, it is unclear whether non-government stakeholders have been consulted.

The framework for assessing, funding, and implementing high cost, highly specialized therapies and services across Australia’s public hospital system is pending endorsement by each of the jurisdictional governments. High-level in nature, the framework’s primary audiences are industry and public hospitals. While not all processes are in place, the framework is forward-looking. A detailed implementation plan is warranted to better inform the roles and requirements of each stakeholder.

The framework allows stakeholders to better understand government processes regarding assessment, funding, and implementation of high-cost therapies and services, thereby fostering a collaborative environment that supports timely patient access. Articulating process details in a follow-up implementation plan is essential to gain the trust of, and input from, industry, clinicians, and patient representatives.

Outcome-based commissioning – a set of arrangements to define and pay for a service based on pre-agreed outcomes – has been operationalized in some regional care settings (e.g., adult social care). However, it remains largely aspirational due to operational considerations and challenges. Outcomes-based commissioning shares a common goal with economic evaluation alongside health technology appraisal (HTA): to achieve value for money for outcomes from a finite budget.

We explored the considerations, implications, and challenges regarding the practical role of relevant outcomes in economic evaluation, relative to care commissioning, using England as a case study. Our exploration bridges a gap between economic evaluation evidence and practical resource allocation decision-making, focusing on conceptual (e.g., what are ‘relevant’ outcomes), practical considerations (e.g., quantifying and using relevant endpoints or surrogate outcomes alongside costs), and pertinent issues when linking these to commissioning based payment mechanisms.

Firstly, there is a disconnect between existing economic evaluation approaches and commissioning processes. For example, using a single quality-adjusted life-year (QALY) maximum and limited consideration of affordability relative to cost effectiveness. Secondly, service-focused outcomes (e.g., seeing a specialist team) rather than person-focused outcomes (e.g., QALYs) are often desirable from a practical commissioning and service provider perspective as they make it easier to measure key performance indicators. Thirdly, both person- and service-focused payment structures could lead to market inefficiencies when activity is focused on only people for whom a prespecified outcome can be achieved or service delivered; these approaches require additional efficiency-equity tradeoff considerations (e.g., using distributional cost-effectiveness analyses).

We highlight payment structures as a major and complex consideration for commissioning, for which economic evaluation provides little to no consideration. Service-related outcomes and payments can be used as surrogate outcomes within economic modeling frameworks, while monitoring and evaluation can still be based on economic outcomes (e.g., QALYs and aggregated costs). Accounting for and explaining direct links from payment structures to economic outcomes is a major step to bridging a gap between economic evaluation evidence and practical resource allocation.

Gender medicine responds to the need for a reassessment of the medical-scientific approach in a gender perspective, to increase knowledge of the different aspects underlying gender differences and the appropriateness/ effectiveness of health interventions.

A policy review of documents prepared by the Italian Ministry of Health on gender medicine was carried out, to investigate the possible areas of intervention of health technology assessment in the development of this interdisciplinary dimension. The areas of highest priority for action have been identified.

In Italy, the Ministry of Health, with the support of the National Institute of Health, issued a Plan for Application and Dissemination of Gender Medicine in June 2019. Our review shows that for the development of research on the mechanisms of pathogenesis the Italian Plan gives indications on the identification of diagnostic markers, prognostic and predictive response in a gender perspective, but there are no formalized rules that constitute a constraint or an obligation to do so. In Horizon Europe calls, for example, “Pragmatic trials on minimally invasive diagnostics” (HORIZON-MISS-2023-CANCER-01-03) on the other hand, it is required that gender and gender issues should be taken into account in all projects and all data should be disaggregated by gender, socio-economic status and ethnicity. Separating subjects into two groups in the analysis leads to greater complexity. This is even more true when considering the different types of gender. The total number of subjects to be included must likely increase to maintain statistical power in evaluating effects in subgroups. This increase leads to an increase in time and cost, if one needs to provide separate data by sex and even more so by gender. Different statistical tests to be used, according to the type of variables of the primary endpoint, should be considered in the study protocols.

It seems appropriate to suggest reviewing upcoming health technology assessments with an eye to gender medicine. Gender medicine should become a strategic goal of prevention in public health and will strengthen the concept of the patient centrality until the personalization of therapies is achieved.

During public health crises such as the COVID-19 pandemic, decision-makers have relied on infectious disease models to predict and estimate the impact of various health technologies. The difficulties associated with capturing and representing uncertainty using infectious disease models leads to a high risk of making decisions that are misaligned to policy objectives. Even when uncertainty is adequately captured in the analysis, the tools for communicating the risks and harms of making wrong decisions have proved inadequate, which can lead to the suboptimal adoption of critical health technologies including vaccines and antivirals. We aim to adapt and extend health economic methods for the characterization, estimation, and communication of uncertainty to infectious disease modeling.

Economic and infectious disease models share many features, including the comparison of policy alternatives on outcomes important to decision-makers (such as hospital census, total infections), but each takes a different approach to analysis of uncertainty. We extend best practices from health economics to infectious disease modeling and develop a suite of tools and visualization techniques which represent parameter uncertainty and the risk these unknowns present to decision-makers.

In consultation with decision-makers and infectious disease modeling experts we developed the ‘Decision Uncertainty Toolkit’ of model outputs and visuals. Visual tools for uncertainty are developed to: (i) accurately capture uncertainty in key infectious disease model outputs, and (ii) support intuitive and direct interpretation by infectious disease modelers and decision-makers. We also developed quantitative measures for the downside risk of policy alternatives, specified to capture both the probability and magnitude of losses relative to policy targets for a range of infectious disease model outputs. Together, these outputs can support decision-making by quantifying outcome uncertainty and the risks associated with policy alternatives.

We developed the toolkit visuals and risk measures alongside infectious disease modelers and decision makers. The toolkit is designed to improve decision-maker understanding of decision risk in order to improve outcomes during future public health crises.

Decision makers often use value-based decision rules to determine whether technologies offer good value for money and should therefore be adopted, comparing cost-effectiveness analysis results with a threshold value. This assumes that decision makers are indifferent to interventions with the same expected value but different levels of underlying uncertainty. Such indifference is unlikely to hold in practice. We propose a risk-based price and accompanying decision rules to address this limitation.

We characterized risk using the per-patient expected value of perfect independent information (EVPII), a modification of a standard output from value of information analysis. The EVPII estimates the expected value of net benefit losses caused by uncertainty related to a technology, independent of the uncertainty related to alternative treatments. ‘Payer risk tolerance’ is then defined as the maximum per-patient risk of making wrong decisions that payers are willing to accept, expressed in monetary terms. The risk-based price is the price at which the EVPII is equal to the payer risk tolerance.

The risk-based pricing decision rules are as follows: (i) a technology is acceptable for adoption at the submitted price if the incremental net benefit of the technology is greater than or equal to zero and the EVPII is less than or equal to the payer risk tolerance; and (ii) the optimal technology has the greatest expected net benefit at the lowest of the sponsor submitted, value-based, or risk-based price at a given cost-effectiveness threshold value.

The risk-based price incorporates uncertainty and risk attitudes into decision-making. We demonstrate that both risk-averse and risk-neutral payers prefer the outcomes of risk-based pricing. Risk-based decision rules incentivize sponsors to develop evidence. Implementation of the risk-based price improves outcomes for patients by increasing health system net benefits under constrained resources, with better alignment to decision maker risk attitudes.

In health technology assessment (HTA), economic evaluations assessing biologic drugs for rheumatoid arthritis (RA) involve modeling patients’ responses to multiple treatments given sequentially over a lifetime horizon. When data from randomized controlled trials (RCTs) are scarce, data from non-randomized studies (e.g., single-arm trials [SATs] and disease registries) can be used to supplement the evidence base. This research aimed to demonstrate meta-analytic methods for combining effectiveness data from randomized and non-randomized studies and their corresponding impact on cost-effectiveness estimates.

Data comparing patients receiving second-line rituximab with continued background non-biologic treatment were extracted from one RCT and six SATs identified in an HTA assessing second-line rituximab for RA, and from the British Society for Rheumatology Biologics Register-Rheumatoid Arthritis, by applying a target trial emulation approach. A binomial meta-analysis model was used to estimate the probabilities of achieving the European League against Rheumatism (EULAR) response criteria by pooling data from the RCT, SATs, and the registry. The probabilities were entered into a decision model from a previous HTA to derive incremental cost-effectiveness ratio (ICER) estimates for treatment strategies with and without biologic drugs.

Compared with the original analysis, the estimated probability of at least a moderate EULAR response on rituximab from combined sources was substantially lower. For example, the probability obtained from an RCT was 0.68 (95% credible interval [CrI]: 0.345, 0.907), but only 0.29 (95% [CrI]: 0.242, 0.333) when using RCT plus registry data and 0.29 (95% CrI: 0.244, 0.336) for combined RCT, registry, and SAT data. In the cost-effectiveness analysis, the median ICERs were higher when including real-world data.

Synthesis of all relevant data, including RWD, provides additional information regarding the variability in cost-effectiveness estimates and can be considered in sensitivity analyses for HTA decision-making.

It is estimated that osteoporosis affects over 200 million people globally. Postmenopausal women (PMW) have an increased risk of developing osteoporosis due to low estrogen levels. This study assessed the safety and effectiveness of denosumab (Prolia®) relative to placebo, selective estrogen receptor modulators (SERMs) (bazedoxifene and raloxifene), and bisphosphonates (alendronate, ibandronate, risedronate, and zoledronate) for the treatment of osteoporosis in PMW.

Systematic searches were conducted in three biomedical databases (PubMed, the Cochrane Library, and Embase) to identify randomized controlled trials (RCTs) of PMW with osteoporosis allocated to denosumab, placebo, bisphosphonates, or SERMs. The Cochrane Risk of Bias 2.0 tool was used to critically appraise included RCTs. Pairwise and Bayesian network meta-analyses were performed on the following predetermined outcomes: fractures (vertebral and nonvertebral); adverse events (AEs); mortality; serious AEs (SAEs); withdrawals due to AEs; bone mineral density (BMD); and AEs caused by denosumab discontinuation.

The analyses included 12 RCTs (22 publications, 25,879 participants). Denosumab, ibandronate, alendronate, zoledronate, and risedronate produced a statistically significant improvement in total hip (TH) and lumbar-spine (LS) BMD, compared with placebo. Similarly, ibandronate, risedronate, and alendronate showed a statistically significant improvement in femoral neck (FN) BMD. Risedronate produced a statistically significant decrease in nonvertebral fractures (risk ratio 0.20, 95% confidence interval: 0.00, 0.97) relative to placebo. However, there were no significant differences between any of the interventions for rates of vertebral fractures, AEs, SAEs, withdrawals due to AEs, or mortality, compared with placebo.

None of the included trials reported evidence on AEs caused by denosumab discontinuation.

Denosumab was associated with significant improvements in both LS and TH BMD relative to placebo. Similarly, compared with placebo, denosumab was not associated with significant changes in nonvertebral or vertebral fractures. Denosumab was not associated with significant changes in safety outcomes relative to placebo. Given that some of the analyses suffered from statistical imprecision, these findings should be interpreted with caution. Regarding policy, continued funding of denosumab needs to be reviewed.

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that affects quality of life and sometimes requires the use of multiple drugs. Therefore, it is relevant to address the experiences of patients, family members, and caregivers in relation to out-of-hospital SLE drug treatment. This paper presents the results of a pilot project of a Qualitative Evidence Synthesis (QES) conducted by the National Committee for Health Technology Incorporation (Conitec) in the Brazilian public health system.

For this thematic synthesis, a structured search was conducted in the MEDLINE, CINAHL, and LILACS databases. Seventeen articles were included, and their quality was evaluated using the Critical Appraisal Skills Program criteria. Article content, which was extracted into a spreadsheet adapted from JBI SUMARI, underwent thematic content analysis. Confidence in the findings was evaluated using the GRADE Confidence in the Evidence from Reviews of Qualitative Research tool.

Fifteen findings related to three central themes: self-image and appearance; SLE as a chronic disease (disease oscillation, recurrence of symptoms, fear of organ damage, expectation of cure or modification of the disease course, and frequency of medical appointments); and experience with drug therapy (belief in the need for drugs, skepticism, chronicity of treatment, financial difficulty, adverse effects as obstacles to adherence and a source of suffering, efficacy/effectiveness, large quantity and frequency of drugs, and multiple therapeutic attempts).

The findings suggest that patients, family members, and caregivers have an ambivalent relationship with drug treatment. Even though they believe in the effectiveness of the drugs, they also distrust the need to keep using them, especially when SLE is controlled. The improvement of cosmetic manifestations and adverse effects also seem to be important outcomes. Furthermore, the high occurrence of adverse effects and the daily use of many drugs can make treatment adherence harder. In any case, there is an expectation of cure or more significant impact on the course of the disease through pharmacotherapy.

While the impact of health technology assessments (HTAs) is often not evaluated, some HTA bodies measure the impact of patient involvement in their processes. Evaluating how patient involvement is perceived by all stakeholders may help to improve practices and avoid activities that unduly burden patient and HTA communities. Frameworks and tools have been designed to analyze the impact of patient engagement along the healthcare development lifecycle. Reporting on the impact of patient involvement in HTA-specific activities, however, continues to be infrequent, unstandardized, and not comprehensive.

Having a common framework to characterize and report on the impact of patient involvement may enable this practice to be optimized and harmonized across HTA contexts.

The Patient and Citizen Involvement Interest Group (PCIG) within Health Technology Assessment International set out to contextualize this impact and support reporting. A questionnaire was developed, piloted, and rolled out to collect multistakeholder personal perceptions of the impact of patient involvement in individual HTAs. Questions included: “What difference did you feel patient involvement made in the HTA activity?” and “What would have been missed without patient involvement?”. From January 2019 to September 2021, 24 responses (including one joint submission) were collected through the PCIG’s network from HTA bodies (11), patient representatives (12), and industry representatives (2) from North America (5), South America (3), Europe (13), and Australia (3).

Common themes were extracted from these experiences to characterize the impact of patient participation in HTA processes. Based on these commonalities, a harmonized framework consisting of three “domains” is proposed: impact on the decision-making process; impact on patient stakeholders; and impact on the HTA body. The framework includes a set of items under each domain to support reporting.

By having common language and measures, the HTA community can harmonize processes across jurisdictions to evaluate and communicate the value of patient involvement in HTA. Improving consistent reporting may facilitate more efficient process improvement for meaningful integration of patient stakeholders into HTA decision-making.

Australian health technology assessment (HTA) committees and processes at the national level have needed to consider an increasing focus on patient involvement and interactions within their scope. As various approaches have been explored, the visibility and impacts of patient involvement and consumer representation has evolved markedly over the most recent five years.

Program activities were developed from review of contemporary HTA models of practice across various HTA sectors internationally alongside input from individual patients and patient groups. Practical application of program pilots was influenced by specific requirements of the Office of HTA, the coordination of HTA Committee procedures and timelines, and involvement of HTA Committee consumer members.

The development of capacity building programs for HTA consumer committee members, the growth of external activity and communications targeting patient groups and networks, and the establishment of an expert position to develop the HTA Consumer Evidence and Engagement Unit within the Department’s Office of HTA, are all examples of the work delivered in this period to better integrate patient evidence and inputs into HTA processes and decision-making. Activities over the next period will seek to establish formal frameworks for meaningful involvement that can demonstrate these contributions to evaluations and decision-making.

Various examples of patient involvement and participation in processes have evolved over time. The scope and impacts of these experiences have illustrated important participatory demands and resourcing needs, as well potential benefits for deliberations. The Australian Government and Departmental frameworks for HTA currently seek to enhance the development of patient evidence inputs and participation. These developments will be informed by the Australian context and comprehensive consultation with Australian patient groups and their networks. Strategies for improvements are anticipated to be relevant across all HTA processes and Committees within HTA areas.

Fabry disease is a rare, inherited X-linked lysosomal storage disease characterized by a wide spectrum of heterogeneously progressive clinical phenotypes, and which results in progressive kidney disease, cardiomyopathy, cerebrovascular disease, and reduced life expectancy. Disease-specific therapy aims to improve symptoms, stabilize current disease and delay progression. In Australia treatment access requires that patients meet pre-specified criteria, which have been in place for more than 15 years. Patient questions prompted the patient organization, Fabry Australia, to investigate why these criteria had remained unchanged despite significant progress in the understanding and management of Fabry disease.

A panel comprising two members of Fabry Australia and its Medical Advisory Committee conducted a review of the literature. The aim of this was to inform the clinical quality of the Australian treatment access criteria with reference to international guidelines and contemporary data. The findings from the literature were applied to develop consensus recommendations for classification and Fabry-specific treatment initiation criteria in diagnosed patients.

Evidence supports earlier treatment with reduced barriers to access in some circumstances. Australian access criteria are misaligned with this. They do not distinguish between classical and non-classical Fabry phenotypes, neglect the impact of quality of life and gastrointestinal symptoms, and impose symptom-severity related criteria, which may lead to unnecessary treatment initiation delay. An updated framework is presented. It differentiates phenotypes, facilitates more timely access to Fabry-specific treatment for classical males, and supports relevant organ involvement criteria in classical females and patients with non-classical disease.

A well-performing health technology assessment system facilitates patient access to cost-effective treatments that improve health outcomes. Timely treatment initiation is important to avoid irreversible organ damage in Fabry patients. Patients’ questions about out-dated access criteria has prompted research and uncovered barriers that are no longer clinically valid. The perspectives of the patient as a stakeholder in their disease management should not be overlooked when assessing the value of health technologies in the rare disease setting.

Umbrella digital health term (DHT) (digital health, eHealth, mHealth, telehealth, and telemedicine) definitions contain insufficient information about patient value for health economics and outcomes research and health technology assessment (HTA) purposes. Qualitative content analysis of secondary DHT (e.g., telesurgery and teleradiology) definitions was performed by the ISPOR Digital Health Special Interest Group to determine if they were more useful for health economics and outcomes research purposes.

Secondary DHT definitions were extracted from a previous scoping review and consolidated by reviewer pairs using uniform rules. Definitions were analyzed for explicit (directly stated) or implicit (inferred) information on 24 categories: Patient, Intervention, Comparator, Outcome, Timing, Setting (PICOTS); the Shannon-Weaver communication model (SWE) (sender, message, encoder, channel, decoder, and receiver, extended with mode of information exchange); the quality domains of Agency for Healthcare Research and Quality (AHRQ) (safe, effective, patient-centered, timely, efficient, and equitable); information related to applied technology or geographic scope; and the World Health Organization (WHO) classification of digital health interventions v1.0 (digital health interventions category, health system challenges, and system categories).

Across 107 unique definitions of 73 secondary DHTs, the number of explicitly or implicitly addressed categories across the frameworks ranged from zero to 15, with references to elements of PICOTS (79.4%), SWE (90.7%), AHRQ (30.8%), applied technology (52.3%), geographic scope (0%), and WHO frameworks (86.9%). PICOTS information was found for Patients in 35 percent of definitions, Intervention in 59 percent, Comparator in 20 percent, and Outcomes in 18 percent.

Secondary DHT definitions do not adequately specify PICOTS or other characteristics of interest for HTA. An online Delphi survey has been launched among a wider group of ISPOR members to identify the minimum information set to define patient facing DHTs for evidence summaries and value assessments. The results of this research should be shared for discussion with other digital health stakeholder groups.

Allocating government resources for drug treatments continues to be a challenge in health care, particularly given the increasing number of high-cost personalized drug treatments, finite resources, and aging population. Since taxpayers fund government health budgets, it is important to understand how they think funding should be distributed, considering attributes such as cost of drug treatments, risk of dying, commonality of medical conditions, and quality of life changes with drug treatments. The aim of this study was to understand what attributes of a medical condition and treatment determine a community’s willingness to fund new drug treatments. Two decision-making contexts were explored: the allocation of funds from a health budget and a willingness-to-pay (WTP) perspective.

A representative sample of 500 Australian adults completed an online survey. The survey comprised two discrete choice experiments (DCEs) with different framing: an allocation of government funds and a WTP for drug treatments. The government allocation DCE allowed a choice between two hypothetical alternatives, each describing the medical condition and the drug treatment, while the WTP for funding showed one hypothetical alternative with an option to not fund the drug treatment. Seven DCE attributes, informed by a literature review, were displayed in each choice set relating to the medical condition (risk of dying, prevalence, and ages affected) and to the drug treatment (change in quality of life, additional life-years, availability of other drug treatments, and cost to the government and the taxpayer).

The resulting DCE model will establish the funding prioritization choices made by the general community. We expect changes in quality of life and risk of dying to be very important attributes. Of key interest for this study is how the difference in the decision-making context impacts preferences. We expect taxpayers to employ a stricter rule set in funding decisions when paying out of pocket (WTP exercise).

The findings from this research have implications for decision makers when aligning funding decisions with community preferences and values.

In recent years, most countries have struggled to meet the annual demand for increases in healthcare resources. This scenario poses a significant challenge for those who pay for or manage healthcare services, namely the clinicians and hospital managers Thus, value-based implementation for resource allocation may include disinvestment initiatives to maximize benefits to patients and the population. The purpose of this study was to explore the feasibility of incorporating a systematic and explicit value assessment in hospital-based decision-making for the prioritization of resource allocation.

An evidence-informed stakeholder engagement workshop was held with approximately 50 hospital directors and utilized a scenario analysis of making decisions for hospital procurement. The key question discussed was what should be considered when making decisions about resource allocation and disinvestment in health services at the hospital level. The participants were divided into five groups with a mix of multilevel institutional categories. Each group was given a similar resource allocation scenario, a wish list, and a shift list. The participants were involved in a facilitated discussion on the process, criteria for prioritization, and the justification of their final selections. Subsequently, a deliberative discussion was held at the end of the workshop to explore the feasibility of this prioritization method.

Prioritization criteria that were identified and unanimously agreed upon included effectiveness, safety, burden of disease, suitability of services, human resources and facilities, and economic considerations. The deliberative discussion also highlighted the impact of the disinvestment of services, managing the expectation of patients and clinicians, and monitoring and audit mechanisms.

The value of disinvestment should not compromise access to services and quality of care. There is a huge potential for implementing a systematic and explicit value assessment in hospital-based decision-making for prioritization of resource allocation. Further refinement of the process and mitigation of challenges will enable its use.

National health insurance (NHI) Taiwan has provided additional markups on dental service fees for people with specific disabilities, and the expenditure has increased significantly from TWD473 million (USD15 million) in 2016 to TWD722 million (USD24 million) in 2022. The purpose of this study was to determine oral health risk and to develop a risk assessment model for capitation outpatient dental payments in children with Autism.

Based on the literature and expert opinion, we developed a level of oral health risk model from the claim records of 2019. The model uses oral outpatient claim data to analyze: (i) the degree of caries disease; (ii) the level of dental fear or cooperation; and (iii) the level of tooth structure. Each factor was given a score from zero to four and a total score was calculated. Low-, medium-, and high-risk groups were formed based on the total points. The oral health risk capitation models are estimated by ordinary least squares using an individual’s annual outpatient dental expenditure in 2019 as the dependent variable. For subgroups based on age group and level of disability, expenditures predicted by the models are compared with actual outpatient dental expenditures. Predictive R-squared and predictive ratios were used to evaluate the model’s predictability.

The demographic variables, level of oral health risk, preventive dental care, and the type of dental health care predicted 30 percent of subsequent outpatient dental expenditure in children with autism. For subgroups (age group and disability level) of high-risk patients, the model substantially overpredicted the expenditure, whereas underprediction occurred in the low-risk group.

The risk-adjusted model based on principal oral health was more accurate in predicting an individual’s future expenditure than the relevant study in Taiwan. The finding provides insight into the important risk factor in the outpatient dental expenditure of children with autism and the fund planning of dental services for people with specific disabilities.

New methodologies such as machine learning are becoming widely available and are increasingly used. However, more guidance on their role in the context of economic evaluations would be beneficial.

We developed a machine learning model to predict recurrent depressive episodes and incorporated the model outcomes in a health economic model to assess the cost effectiveness of offering targeted prevention of recurrent depression. We considered the impact on cost effectiveness (defined as cost per quality-adjusted life-year) for machine learning models with different thresholds for classifying a patient as being at risk, resulting in different precision-recall pairs.

Targeted prevention of recurrent depression could enhance the cost effectiveness of depression treatment by preventing a small number of recurrent depressive episodes in patients where the estimated risk of recurrence is relatively high. More depressive episodes could be prevented with the trade-off of less cost effectiveness for the healthcare system.

Health economic modeling approaches can be augmented with machine learning methods, which broadens the areas in which evidence can be generated for policy makers to base their budget allocation. The precision of such predictive machine learning models must be high enough to be able to improve a care-as-usual healthcare system. Machine learning models generally let you set the level of precision acquired, at the cost of a possibly low recall, thereby limiting the impact on the healthcare system as a whole. More and better data for training these machine learning models will allow developed models to better distinguish patients who will and won’t develop a recurrent depressive episode, and for higher recall given a desired precision threshold. This will translate into a more substantial improvement in the treatment of depressive disorders in the healthcare system.