Cost-Effectiveness Analysis of the High-Dose Trivalent Influenza Vaccine in the Elderly Population in Italy

Introduction

Globally, the influenza virus causes an estimated one billion infections annually, with 3–5 million severe cases particularly among vulnerable populations such as the elderly and individuals with chronic conditions.^1,2 The burden of disease is considerable, with respiratory complications accounting for an estimated 290,000 to 650,000 deaths each year.²

In Italy, influenza remains a critical public health issue. Annually, approximately 9% of the population contracts influenza, leading to between 8,000 and 17,000 deaths, 84% of which occur among individuals ≥65 years of age.^3–5 In the elderly, aging is associated with a gradual and physiological decline in immune function, a phenomenon referred to as “immunosenescence”. This process leads to diminished immunological responsiveness, whereby immune cells exhibit reduced capacity to recognize and respond to pathogens unless strongly stimulated.⁶ Immunosenescence has been identified as a key factor contributing to increased susceptibility to infectious diseases such as influenza, and is strongly associated with a heightened risk of severe complications—particularly those of a cardiorespiratory nature.^3–5 In addition, elderly have more comorbidities than the general population, making them more susceptible to influenza-related complications.⁷

Influenza vaccination, aimed at preventing seasonal flu epidemics, is one of the most widely implemented and significant public health interventions. Given the reduced immunogenicity of standard influenza vaccines in older adults, enhanced vaccine approaches have been developed over the years.⁸ These include the MF59-adjuvanted vaccine, the recombinant vaccine, and the high-dose vaccine.⁸ In Italy, MF59-adjuvanted and high-dose vaccines are preferentially recommended for individuals ≥65 years of age.⁹

Beyond the direct health threat posed by influenza, the virus also carries a significant economic burden on healthcare systems and national economies. Consequently, vaccination campaigns must be meticulously planned, weighing both the clinical benefits of the vaccines and the economic sustainability of these interventions.¹

To ensure efficient allocation of healthcare resources and maximize health benefits for the population, it is essential to use vaccine-specific evaluation frameworks. The evaluation of vaccines should be conducted on the basis of solid, robust, and high-quality evidence. In line with the evolving European HTA framework,^10,11 which emphasizes robust comparative effectiveness evidence to inform healthcare decision-making, this analysis prioritized high-quality randomized controlled trials (RCTs) for relative vaccine efficacy estimates, complemented by meta-analyses and observational data where appropriate.

Several studies have evaluated the clinical and economic value of the high-dose vaccine in various healthcare settings, highlighting important advantages over standard-dose vaccines, including superior protection against influenza and a marked reduction in influenza-related hospitalizations, cardiorespiratory complications, and mortality.^12–20

Building upon this evidence, the present study aims to further assess the cost-effectiveness and cost-utility of the high-dose trivalent influenza vaccine—TIV-HD (Efluelda^®, Sanofi Winthrop Industrie, Gentilly, France) in comparison with the standard-dose trivalent vaccine (TIV-SD) in the Italian elderly population (≥65 years of age) The analysis is intended to provide additional insights to support evidence-based healthcare policy and optimize resource allocation strategies.

Materials and Methods

A cost-effectiveness analysis was conducted to evaluate different influenza vaccination strategies in the Italian elderly population (≥65 years of age). The analysis compared two alternative scenarios, assuming the same proportion of the elderly population—reflecting the average seasonal vaccination coverage—would receive either the TIV-SD (SD vaccination strategy) or the TIV-HD (HD vaccination strategy). Clinical and economic outcomes were estimated for the entire national elderly cohort to assess the overall impact at the population level.

Study Design

A static decision-analytic model (Figure 1) was developed to simulate the clinical course of influenza and estimate both clinical outcomes and healthcare costs associated with vaccination strategies in the target population (≥65 years of age).

Figure 1 Model structure. Abbreviations: ED, Emergency Department; GP, General Practitioner; HD, high-dose; SD, standard dose; yo, years old.

The model captured three distinct influenza-related clinical pathways, which were not mutually exclusive, reflecting the possibility that an individual could experience multiple influenza-related events. The first pathway estimated the number of influenza cases, as well as the associated healthcare resource use, including General Practitioner (GP) consultations and Emergency Department (ED) visits among symptomatic individuals. The second pathway focused on complications possibly associated with influenza and estimated the number of hospitalizations across the entire target population, including those due to respiratory and cardiovascular events. This approach allowed for the independent assessment of influenza cases and hospitalizations. The third pathway estimated influenza-attributable mortality, applying a conditional probability to influenza cases. This framework enabled influenza-related mortality to be modeled as a function of influenza cases, while remaining independent from the occurrence of other clinical events.

Time Horizon and Perspective

The analysis was conducted from the perspective of the Italian National Health Service (SSN), taking into account only direct medical costs, considering vaccine acquisition and administration, outpatient visits, ED consultations, and hospitalizations. A one-year time horizon was adopted to capture the clinical and economic outcomes related to influenza and corresponds to a single influenza season. However, to account for the long-term health impact of influenza-related premature mortality, the model estimated life years (LYs) lost beyond the specified time horizon. These estimates were adjusted for health-related quality of life to derive quality-adjusted life years (QALYs). LYs, QALYs, and costs constituted the basis for calculating the incremental cost-effectiveness ratio (ICER).

A 3% annual discount rate was applied to calculate the present value of future costs and outcomes.²¹

Epidemiological Inputs

Table 1 presents the input data of the model. The modeled cohort included all individuals ≥65 years of age residing in Italy as of January 1, 2025, according to official demographic data from the Italian National Institute of Statistics (ISTAT)²² (Table 1).

Table 1 Demographic, Vaccination Coverage, and Influenza-Related Outcome Data for the Italian Elderly Population Used in the Model

The distribution of underlying comorbidities within this population was assumed to reflect that observed in the general elderly Italian population, as reported by the most recent epidemiological data and national health sources. In particular, in the age groups 65–74 and ≥75, 34.2% and 52.2% of subjects, respectively, have at least 1 chronic condition²³ (Table 1). The presence of ≥1 comorbidities defines the abovementioned subsets as high-risk population.

The vaccine coverage rate, applied identically across both vaccination strategies (TIV-HD and TIV-SD), was set at 53.3%, based on national data from the 2023/2024 influenza season for the elderly population (≥65 years of age)²⁴ (Table 1). Additionally, coverage was stratified according to risk groups, using data from the Passi d’Argento surveillance system for the 2022/2023 season.²⁵ Specifically, the observed coverage ratio between high-risk and low-risk groups in the 2022/2023 season was assumed to remain constant for the 2023/2024 season (Table 1).

The expected number of influenza cases in the target population was estimated by applying a seasonal attack rate of 7.2%²⁶ (Table 1), derived from published literature representative of the unvaccinated population. For vaccinated individuals, infection risk was adjusted according to the vaccine-specific effectiveness of TIV-HD and TIV-SD (see the “Efficacy and Effectiveness Inputs” section). Consequently, the overall incidence of influenza was modeled as a function of both the vaccination coverage rate and the differential effectiveness of the two vaccines.

All-cause mortality (background mortality) was applied to both the influenza-free population and individuals who survived an influenza episode during the modeled influenza season.³⁰ Age-stratified mortality rates (ie, 1.13% and 4.44% in the 65–74 and ≥75 age groups, respectively) were used to project residual life expectancy and survival in the absence of influenza-related events.³⁰

Influenza-Related Healthcare Events

As previously described, the model simulated different clinical pathways to estimate influenza-related healthcare events, including outpatient care, ED visits, possibly influenza-related hospitalizations, and influenza-attributable mortality.

Outpatient GP visits and ED presentations were modeled as conditional events upon the development of symptomatic influenza. The probability of a GP visit was set at 38.6%, applied uniformly across all age and risk groups²⁸ (Table 1). In contrast, ED access was modeled according to age and risk group distributions.²⁷ The total number of ED accesses was calculated by applying these probabilities to the estimated number of influenza cases for each vaccination strategy (Table 1).

Possibly influenza-related hospitalizations, associated with respiratory or cardiovascular complications, were estimated using an annual hospitalization rate of 7,839.7 per 100,000 individuals,²⁹ applied uniformly across the target population (Table 1). In the absence of Italy-specific seasonal data, it was assumed—based on observed winter patterns—that 60% of these hospitalizations occurred during the influenza season. Among all cardiorespiratory hospitalizations, 49.7% were attributed to respiratory infections,³¹ and 83.0% of total hospital admissions were considered to involve complications.^32,33 These rates were used to define the baseline risk of hospitalization due to influenza-related cardiorespiratory complications for a hypothetical unvaccinated cohort and subsequently adjusted according to the vaccine-specific effectiveness of TIV-SD and TIV-HD in preventing severe outcomes.

To account for the probability of death conditional on influenza, an excess mortality rate of 108.14 deaths per 100,000 individuals⁵ was applied uniformly across both age groups (Table 1). This rate reflects the elevated risk of death among older adults, particularly those with comorbidities or frailty, when exposed to influenza infection.

Efficacy and Effectiveness Inputs

In adults ≥65 years of age, the absolute effectiveness of TIV-SD in reducing the risk of symptomatic influenza compared to no vaccination was estimated at 46%.^32,33 This effect was modeled to produce a proportional decrease in influenza cases and related healthcare utilization, including GP visits and ED access. The incremental relative efficacy of TIV-HD to TIV-SD in preventing symptomatic influenza was estimated at 24.2%, according to the phase IIIb-IV RCT by DiazGranados et al.³⁴

For influenza-related hospitalizations due to respiratory and cardiovascular complications, the absolute effectiveness of TIV-SD was assumed to be 28.0%,^35,36 applied uniformly across all age and risk categories. According to a systematic review and meta-analysis of randomized and observational studies conducted over 12 influenza seasons, including over 45 million individuals ≥65 years of age,¹² the incremental effectiveness of TIV-HD over TIV-SD in reducing these hospitalizations was 16.7%. This rate was applied consistently across all modeled strata in the present analysis (ages 65–74 and ≥75 years; high- and low-risk groups).

Cost Inputs

Direct medical costs for each vaccination strategy were estimated by quantifying healthcare resource utilization associated with clinical events along each modeled pathway. These included theoretical vaccine procurement and administration, as well as the costs associated with the management of influenza-related events (Table 2).

Table 2 Unit Costs (€) Associated with Vaccination Strategies and Healthcare Resource Utilization for Influenza-Related Events in the Elderly Population

Influenza vaccines are not reimbursed as standard pharmaceutical products in Italy; however, their cost is fully covered by regional health authorities for defined target populations. Doses are procured annually through public tenders based on estimated coverage needs. The base-case analysis was structured into three distinct scenarios, each reflecting a different assumed premium price per dose of TIV-HD relative to the TIV-SD. The analyses considered three theoretical scenarios: a minimum gap of €15, an intermediate gap of €17, and a maximum gap of €22 between the two vaccines. These values were selected to represent theoretical differences in acquisition costs.

Utility Inputs

Utility inputs were derived from age-specific health-related quality of life estimates reported in the literature.⁴² In cases of symptomatic influenza, baseline utility was temporarily reduced to reflect the disutility associated with acute illness, assumed to last an average of six days. As a consequence, by applying the utility per day with influenza of 0.2947,⁴³ the utility loss due to influenza case for 65–74 and ≥75 age groups were estimated to be 0.0099 and 0.0091, respectively. For patients hospitalized due to cardiorespiratory complications, an additional disutility was applied per episode (0.018), as documented in the literature.³² Disutility values per episode (including hospital length of stay) were specific to each clinical event (eg, uncomplicated influenza, hospitalization, complications) and were used to quantify the associated loss in QALYs within the model. QALY losses due to premature mortality were also considered, as per standard cost-effectiveness modelling practice, ie, calculated by multiplying the remaining life expectancy at time of death by age-specific quality of life scores from population norms and applying a 3% discount rate.

Sensitivity Analyses

Deterministic sensitivity analysis (DSA) and probabilistic sensitivity analysis (PSA) were conducted to assess the uncertainties associated with the base-case inputs.

To assess the robustness of the model outcomes to variations in individual input parameters, the DSA was performed and presented as a tornado diagram. The Incremental Net Monetary Benefit (INMB) was selected as the central outcome. For each input, the INMB was recalculated by varying the parameter within a plausible range or, where appropriate, by applying at least an arbitrary ±20% deviation from the mean value. Supplementary Table 1 reports the range of the parameters varied in the deterministic sensitivity analysis. The resulting scenario-specific INMBs were then compared to the base-case estimate, allowing for the identification of parameters with the greatest influence on decision uncertainty.

The PSA was conducted with 1,000 iterations to capture the uncertainty surrounding the ICER in the base-case scenario. The results are represented on the incremental cost-effectiveness (CE) plane, displaying the dispersion of the 1,000 ICER estimates as the ratio of incremental costs to incremental benefits between TIV-HD and TIV-SD.

Results

The differences in total clinical outcomes and healthcare expenditure between the HD vaccination strategy (with TIV-HD) and the SD vaccination strategy (with TIV-SD) across the three base-case price gap scenarios are reported in Tables 3–6.

Table 3 Comparison of Specific (Ie, with Positive Swab) Influenza Outcomes, Ie, Influenza Cases, Outpatient Visits for Influenza, and ED Visits for Influenza Between the HD Vaccination Strategy and the SD Vaccination Strategy in the Elderly Italian Population Results are Presented at Population Level

Table 4 Comparison of Less Specific (Without Swab Confirmation) Influenza Outcomes, Ie, Hospitalizations for Cardiorespiratory Events Between the HD Vaccination Strategy and the SD Vaccination Strategy in the Elderly Italian Population. Results are Presented at Population Level

Table 5 Comparison of Mortality, Life years, and QALYs Between the HD Vaccination Strategy and the SD Vaccination Strategy in the Elderly Italian Population. Results are Presented at Population Level

Table 6 Comparison of Healthcare Costs Between the HD Vaccination Strategy and the SD Vaccination Strategy in the Elderly Italian Population. Differences are Presented at Population Level

From a clinical standpoint, the TIV-HD strategy was associated with a meaningful reduction in the burden of disease. Compared to TIV-SD, the use of TIV-HD resulted in fewer influenza cases, outpatient consultations, ED visits, hospitalizations for cardiorespiratory complications, and influenza-related deaths (Tables 3–5). The use of TIV-HD lead to 13,678 additional QALYs and 14,070 life-years gained at the cohort level, compared to TIV-SD (Table 5).

Across all base-case scenarios, TIV-HD was associated with substantial cost savings for the Italian National Health Service, with projected reductions ranging from €135 million (minimum price gap between the two vaccines) to €82 million (maximum price gap between the two vaccines) over a one-year time horizon (Table 7).

Table 7 Base Case Cost-Effectiveness Results Comparing High-Dose Trivalent Influenza Vaccine with Standard-Dose Trivalent Influenza Vaccine in the Elderly Italian Population

Although the vaccination cost for TIV-HD was higher than for TIV-SD, this was largely offset by reductions in downstream healthcare costs, particularly those associated with the treatment of influenza-related complications (Table 6). Significant cost savings were observed in the management of hospitalizations for cardiorespiratory events, as well as in prescription drug use, outpatient visits, and ED accesses.

In conclusion, TIV-HD was a dominant strategy in all scenarios considered compared to TIV-SD (Table 7).

A threshold analysis was conducted to identify the maximum unit price at which TIV-HD would remain the dominant strategy over TIV-SD, under the current base-case assumptions. Results showed that TIV-HD maintained its dominance—being both more effective and less costly—up to a gap price of €32.92.

Most simulations across all three pricing scenarios confirmed the base-case findings in the probabilistic sensitivity analysis. As shown in Figure 2, the incremental cost-effectiveness pairs are predominantly distributed in the southeast quadrant, indicating that TIV-HD remains more effective and less costly than TIV-SD. The dispersion around each base-case point increases with the assumed per-dose price gap, though most simulations consistently confirm dominance.

Figure 2 (A) Probabilistic sensitivity analysis (PSA): scatterplot of 1,000 simulations for the price gap scenario with incremental cost per dose €15, comparing TIV-HD vs. TIV-SD. Each point represents an ICER estimate based on randomly sampled input parameters; (B) Probabilistic sensitivity analysis (PSA): scatterplot of 1,000 simulations for the price gap scenario with incremental cost per dose €17, comparing TIV-HD vs. TIV-SD. Each point represents an ICER estimate based on randomly sampled input parameters; (C) Probabilistic sensitivity analysis (PSA): scatterplot of 1,000 simulations for the price gap scenario with incremental cost per dose €22, comparing TIV-HD vs. TIV-SD. Each point represents an ICER estimate based on randomly sampled input parameters. Abbreviations: CI, confidence interval; ICER, incremental cost-effectiveness ratio; QALY, quality-adjusted life-years; TIV-HD, high-dose trivalent influenza vaccine; TIV-SD, standard-dose trivalent influenza vaccine; WTP, willingness-to-pay.

The key drivers influencing the INMB of vaccination with TIV-HD versus TIV-SD across the three price gap scenarios are illustrated in the tornado diagram (Figure 3). The parameter with the greatest impact on INMB variation is the TIV-HD vaccination coverage.

Figure 3 (A) Deterministic sensitivity analysis (DSA) for incremental cost per dose scenario €15. The adjustment factor is the proportion of hospitalizations for cardiovascular events that occur during the influenza season; (B) Deterministic sensitivity analysis (DSA) for incremental cost per dose scenarios €17. The adjustment factor is the proportion of hospitalizations for cardiovascular events that occur during the influenza season. (C) Deterministic sensitivity analysis (DSA) for incremental cost per dose scenario €22. The adjustment factor is the proportion of hospitalizations for cardiovascular events that occur during the influenza season. Abbreviations: HD, high-dose trivalent influenza vaccine; INMB, incremental net monetary benefit; SD, standard-dose trivalent influenza vaccine.

An additional scenario analysis was conducted to assess the impact of increased vaccine coverage on clinical and economic outcomes. In this analysis, a 10% increase in vaccination coverage was associated with a further reduction in influenza-related clinical events, along with an approximately 9% increase in cost savings across all three evaluated price gap scenarios relative to the base cases (Table 8).

Table 8 Scenario Analysis Assuming a 10% Increase in Vaccine Coverage

Discussion

According to this model, TIV-HD represents a dominant strategy compared to the TIV-SD for the prevention of seasonal influenza in the Italian elderly population. By combining greater clinical effectiveness with overall cost savings, the use of TIV-HD was estimated to improve individual health outcomes while contributing to the more sustainable management of healthcare resources within the SSN.

Although the acquisition cost of TIV-HD was higher than that of TIV-SD, the alternative strategy was estimated to result in substantial cost offsets, particularly through the prevention of hospitalizations for cardiorespiratory complications, which represent a major component of influenza-related healthcare burden in older adults. These findings were consistent with previous economic evaluations conducted in Italy, such as the model-based analysis by Rumi et al and the real-world data assessment by Cicchetti et al, both of which highlighted the favorable cost-effectiveness profile of TIV-HD when considering direct and indirect influenza-related complications.^44,45

The clinical superiority of TIV-HD over TIV-SD has been robustly demonstrated across multiple settings In a large-scale RCT, DiazGranados et al reported a 24.2% higher efficacy of TIV-HD in preventing laboratory-confirmed influenza in people aged 65 and over.³⁴ Complementing these results, a systematic review and meta-analysis of both randomized and observational studies conducted in the United States by Lee et al confirmed the sustained effectiveness of TIV-HD across various age groups (≥65, ≥75, and ≥85) and circulating viral strains.¹² Furthermore, by capturing not only respiratory but also cardiovascular complications triggered by influenza infection, this analysis aims at offering a more comprehensive estimate of the disease burden. This approach is aligned with findings from a retrospective Italian study by Bertolani et al, who emphasized the frequent underestimation of influenza-related hospitalizations in routine reporting.³¹ The risk of acute myocardial infarction within 7 days after detection of influenza B and influenza A was calculated as 10- and 5-fold higher than without influenza infection. This is the reason why cardiovascular societies such as the European Society of Cardiology (ESC)⁴⁶ and the American College of Cardiology (ACC)⁴⁷ recommend influenza vaccination to cardiovascular patients. The results of Bertolani et al were also consistent with clinical trial data, such as the RCT by Fröbert et al conducted in Sweden,³⁶ which demonstrated that influenza vaccination can significantly reduce major adverse cardiovascular events in high-risk populations.

Importantly, while this analysis is limited to the direct comparison between TIV-HD and TIV-SD, a broader public health priority is the urgent need to expand influenza vaccination coverage among the elderly.⁴⁸ Despite the availability of more effective vaccines, vaccination uptake in this high-risk population remains suboptimal in Italy,²⁴ limiting the potential clinical and economic benefits achievable through preventive strategies. Increasing coverage in the elderly would not only reduce preventable morbidity, mortality, and healthcare costs but also contribute to the resilience and sustainability of the healthcare system.⁴⁸ In Italy, influenza vaccination strategies for adults aged ≥65 years also include other enhanced vaccine formulations, such as MF59-adjuvanted influenza vaccines.⁴⁹ The present analysis focused on the comparison between high-dose and standard-dose trivalent vaccines in order to evaluate the incremental value associated with the increased antigen content of the high-dose formulation. Direct comparisons with other enhanced vaccines, including MF59-adjuvanted formulations, were beyond the scope of the present model and would require dedicated analyses incorporating vaccine-specific effectiveness data and comparative evidence.

Furthermore, the regulatory landscape for healthcare technologies in Europe is undergoing a major transformation. Regulation (EU) 2021/2282 on HTA will progressively harmonize the evaluation of new drugs and vaccines across EU member states.¹⁰ In this evolving framework, generating robust, locally contextualized evidence—such as cost-effectiveness analyses tailored to national healthcare systems—becomes increasingly critical. The present study, by providing a comprehensive economic and clinical evaluation of TIV-HD, based on robust effectiveness data coming from RCTs, within the Italian healthcare setting, anticipates these regulatory requirements, thus supporting future decision-making processes aligned with European standards.

This study presented several strengths. The model was grounded on Italian-specific epidemiological, demographic, and healthcare cost data, ensuring high contextual relevance for national decision-making. Additionally, the model comprehensively captured both specific and less specific influenza-related outcomes, including cardiorespiratory complications, which are often underrepresented in traditional burden assessments. In fact, influenza proved to worsen any underlying cardiorespiratory condition.³ We deem that if swabs were performed to every patient presenting with cardiorespiratory disease worsening, an important increase in the number of influenza cases would emerge. To be precise, swabs in these cases are recommended,⁵⁰ but in clinical practice, they are often omitted due to cost reasons. Therefore, the inclusion of cardiorespiratory exacerbations may offer a better overview of the true impact of influenza. In fact, the clinical trials on high-dose influenza vaccines by Gravenstein et al⁵¹ and Palmu et al¹³ considered both specific and less specific outcomes for influenza. Data on vaccine effectiveness were based on clinical trial findings and updated real-world evidence, further reinforcing the credibility of the results. In fact, the best available evidence level was chosen, whether coming from clinical trials, observational studies, or meta-analyses including both randomized and observational studies. In our opinion, the latter source is the most reliable, as it combines both the strongest evidence in experimental conditions and real-world data, which best represent the general population.

This study has also some limitations. In particular, the inclusion of hospitalizations for cardiorespiratory complications which were not necessarily stemming from laboratory-confirmed influenza cases. Because influenza testing is not routinely performed for all patients presenting with respiratory or cardiovascular complications, some of the hospitalizations included in the model may not have been directly attributable to influenza infection. This approach may therefore lead to an overestimation of the influenza-attributable burden and, consequently, of the potential benefits associated with vaccination. At the same time, data about the influenza-related hospitalizations tend to underestimate the disease burden, as several studies have shown that influenza-related complications are often underdiagnosed in routine clinical practice. Furthermore, the data on the probability of GP visits were applied uniformly across the population, without accounting for differences between age or risk groups, potentially resulting in both under- and over-estimations. In addition, while the model evaluates TIV-HD, some effectiveness estimates—particularly those related to hospitalization outcomes—were informed by meta-analyses including both trivalent and quadrivalent high-dose influenza vaccines. These vaccines share the same high-dose antigen content per strain, and the inclusion of QIV-HD data reflects the broader evidence base of the high-dose platform rather than a shift in the evaluated intervention. However, the quadrivalent formulation maintains the same antigen dose for shared strains as the trivalent high-dose vaccine, with the addition of a second B lineage, supporting the clinical continuity of the high-dose platform. Notably, WHO has recently indicated that inclusion of the B/Yamagata lineage in quadrivalent vaccines is no longer warranted due to its apparent absence since 2020,⁵² further reducing potential differences between trivalent and quadrivalent formulations in current epidemiological contexts.

Conclusion

In conclusion, this analysis indicates that TIV-HD was associated with improved outcomes and lower overall costs compared with TIV-SD under the modelled assumptions. Broader adoption of TIV-HD, combined with strategies to enhance vaccination coverage among older adults, may improve public health outcomes and generate economic benefits, thus possibly contributing to a more effective and sustainable healthcare system.