Applying a Constrained Optimization Portfolio Model to Aid Prioritization of Public Health Interventions in Malaysia

The Knowledge and Application of Economics in Healthcare in a High-Income Country Today: The Case of Belgium

Healthcare is a huge business sector in many countries, focusing on the social function of delivering quality health when people develop illness. The system is essentially financed by public funds based on the solidarity principle. With a large financial outlay, the sector must use economic evaluation methods to achieve better efficiency. The objective of our study was to evaluate and to understand how health economics is used today, taking Belgium as an example of a high-income country. The evaluation started with a historical view of healthcare development and ended with potential projections for its future. A literature review focused on country-specific evaluation reports to identify the health economic methods used, with a search for potential gaps. The first results indicated that Belgium in 2021 devoted 11% of its GDP, 17% of its total tax revenue, and 30% of the national Social Security Fund to health-related activities, totalizing EUR 55.5 billion spending. The main health economic method used was a cost-effectiveness analysis linked to budget impact, assigning reimbursable monetary values to new products becoming available. However, these evaluation methods only impacted at most 20% of the money circulating in healthcare. The remaining 80% was subject to financial regulations (70%) and budgeting (10%), which could use many other techniques of an economic analysis. The evaluation indicated two potentially important changes in health economic use in Belgium. One was an increased focus on budgeting with plans, time frames, and quantified treatment objectives on specific disease problems. Economic models with simulations are very supportive in those settings. The other was the application of constrained optimization methods, which may become the new standard of practice when switching from fee-for-service to pay-per-performance as promoted by value-based healthcare and value-based health management. This economic refocusing to a more constrained approach may help to keep the healthcare system sustainable and affordable in the face of the many future challenges including ageing, climate change, migration, pandemics, logistical limitations, and financial instability.

Supporting the revision of the health benefits package in Uganda: A constrained optimisation approach

This study demonstrates how the linear constrained optimization approach can be used to design a health benefits package (HBP) which maximises the net disability adjusted life years (DALYs) averted given the health system constraints faced by a country, and how the approach can help assess the marginal value of relaxing health system constraints. In the analysis performed for Uganda, 45 interventions were included in the HBP in the base scenario, resulting in a total of 26.7 million net DALYs averted. When task shifting of pharmacists' and nutrition officers' tasks to nurses is allowed, 73 interventions were included in the HBP resulting in a total of 32 million net DALYs averted (a 20% increase). Further, investing only $58 towards hiring additional nutrition officers' time could avert one net DALY; this increased to $60 and $64 for pharmacists and nurses respectively, and $100,000 for expanding the consumable budget, since human resources present the main constraint to the system.

Identification of an Optimal COVID-19 Booster Allocation Strategy to Minimize Hospital Bed-Days with a Fixed Healthcare Budget

Healthcare decision-makers face difficult decisions regarding COVID-19 booster selection given limited budgets and the need to maximize healthcare gain. A constrained optimization (CO) model was developed to identify booster allocation strategies that minimize bed-days by varying the proportion of the eligible population receiving different boosters, stratified by age, and given limited healthcare expenditure. Three booster options were included: B₁, costing US $1 per dose, B₂, costing US $2, and no booster (NB), costing US $0. B₁ and B₂ were assumed to be 55%/75% effective against mild/moderate COVID-19, respectively, and 90% effective against severe/critical COVID-19. Healthcare expenditure was limited to US$2.10 per person; the minimum expected expense using B_1, B_2, or NB for all. Brazil was the base-case country. The model demonstrated that B₁ for those aged <70 years and B₂ for those ≥70 years were optimal for minimizing bed-days. Compared with NB, bed-days were reduced by 75%, hospital admissions by 68%, and intensive care unit admissions by 90%. Total costs were reduced by 60% with medical resource use reduced by 81%. This illustrates that the CO model can be used by healthcare decision-makers to implement vaccine booster allocation strategies that provide the best healthcare outcomes in a broad range of contexts.

Economic Evaluation of Vaccination Programs: A Guide for Selecting Modeling Approaches

OBJECTIVES

Illustrate 3 economic evaluation methods whose value measures may be useful to decision makers considering vaccination programs.

METHODS

Keyword searches identified example publications of cost-effectiveness analysis (CEA), fiscal health modeling (FHM), and constrained optimization (CO) for economic evaluation of a vaccination program in countries where at least 2 of the methods had been used. We examined the extent to which different value measures may be useful for decision makers considering adoption of a new vaccination program. With these findings, we created a guide for selecting modeling approaches illustrating the decision-maker contexts and policy objectives for which each method may be useful.

RESULTS

We identified 8 countries with published evaluations for vaccination programs using >1 method for 4 infections: influenza, human papilloma virus, rotavirus, and malaria. CEA studies targeted health system decision makers using a threshold to determine the efficiency of a new vaccination program. FHM studies targeted public sector spending decision makers estimating lifetime changes in government tax revenue net of transfer payments. CO studies targeted decision makers selecting from a mix of options for preventing an infectious disease within budget and feasibility constraints. Cost and utility inputs, epidemiologic models, comparators, and constraints varied by modeling method.

CONCLUSIONS

Although CEAs measures of incremental cost-effectiveness ratios are critical for understanding vaccination program efficiency for all decision makers determining access and reimbursement, FHMs provide measures of the program's impact on public spending for government officials, and COs provide measures of the optimal mix of all prevention interventions for public health officials.

Pneumococcal conjugate vaccines in Taiwan: optimizing health gains in children and older adults through constrained optimization modeling: Pneumococcal conjugate vaccines optimization in Taiwan

OBJECTIVES

Budgetary constraints force healthcare authorities to set priorities for optimal vaccine interventions. A comprehensive decision-making tool would help inform the best combination and sequence of introduction of vaccines within constrained budgets.

METHODS

Looking at available vaccines against pneumococcal infections in Taiwan (10/13-valent pneumococcal conjugate vaccines [PCV10, PCV13] and 23-valent pneumococcal polysaccharide vaccine [PPV23]), a constrained optimization (CO) model was used to assess the optimal combination of vaccines in children and older adults that would maximize the quality-adjusted life years under predefined budget constraints. Scenario analyses were carried out to evaluate the impact of vaccine efficacy (VE) on the optimized solution.

RESULTS

The CO model demonstrated that the optimal sequence of vaccine introduction was PPV23 in older adults and PCV10 in children. The optimal solution was mostly driven by the potential to reduce disease burden in the older adult population. The VE of PPV23 in older adults and the VE of PCV vaccines against serotype 19A invasive pneumococcal disease had little impact on the optimal solution.

CONCLUSIONS

The CO approach can be used to set priorities for introducing new vaccines while maximizing health gains per age group within the constrained National Vaccine Fund for the prevention of pneumococcal disease in Taiwan.

Informing decision makers seeking to improve vaccination programs: case-study Serbia

Background:The optimisation of vaccine policies before their implementation is beholden upon public health decision makers, seeking to maximise population health. In this case study in Serbia, the childhood vaccines under consideration included pneumococcal conjugate vaccination (PCV), rotavirus (RV) vaccination and varicella zoster virus (VZV) vaccination. Objective: The objective of this study is to define the optimal order of introduction of vaccines to minimise deaths, quality adjusted life years (QALYs) lost, or hospitalisation days, under budget and vaccine coverage constraints. Methods: A constrained optimisation model was developed including a static multi-cohort decision-tree model for the three infectious diseases. Budget and vaccine coverage were constrained, and to rank the vaccines, the optimal solution to the linear programming problem was based upon the ratio of the outcome (deaths, QALYs or hospitalisation days) per unit of budget. A probabilistic decision analysis Monte Carlo simulation technique was used to test the robustness of the rankings. Results: PCV was the vaccine ranked first to minimise deaths, VZV vaccination for QALY loss minimisation and RV vaccination for hospitalisation day reduction. Sensitivity analysis demonstrated the most robust ranking was that for PCV minimizing deaths. Conclusion: Constrained optimisation modelling, whilst considering all potential interventions currently, provided a comprehensive and rational approach to decision making.