1
|
Standaert B, Vandenberghe D, Connolly MP, Hellings J. The Knowledge and Application of Economics in Healthcare in a High-Income Country Today: The Case of Belgium. JOURNAL OF MARKET ACCESS & HEALTH POLICY 2024; 12:264-279. [PMID: 39315121 PMCID: PMC11417786 DOI: 10.3390/jmahp12030021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/01/2024] [Revised: 08/07/2024] [Accepted: 08/26/2024] [Indexed: 09/25/2024]
Abstract
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.
Collapse
Affiliation(s)
- Baudouin Standaert
- Department of Care & Ethics, Faculty of Medicine & Life Sciences, University of Hasselt, 3590 Diepenbeek, Belgium; (D.V.); (J.H.)
| | - Désirée Vandenberghe
- Department of Care & Ethics, Faculty of Medicine & Life Sciences, University of Hasselt, 3590 Diepenbeek, Belgium; (D.V.); (J.H.)
| | - Mark P Connolly
- Global Market Access Solutions (GMAS), Charlotte, NC 28202, USA;
- Department of Pharmacoepidemiology and Pharmacoeconomics, Public University of Groningen, 9700 AB Groningen, The Netherlands
| | - Johan Hellings
- Department of Care & Ethics, Faculty of Medicine & Life Sciences, University of Hasselt, 3590 Diepenbeek, Belgium; (D.V.); (J.H.)
| |
Collapse
|
2
|
Pike J, Leidner AJ, Chesson H, Stoecker C, Grosse SD. Data-Related Challenges in Cost-Effectiveness Analyses of Vaccines. APPLIED HEALTH ECONOMICS AND HEALTH POLICY 2022; 20:457-465. [PMID: 35138601 PMCID: PMC9233035 DOI: 10.1007/s40258-022-00718-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 01/16/2022] [Indexed: 05/13/2023]
Abstract
Cost-effectiveness analyses (CEAs) are often prepared to quantify the expected economic value of potential vaccination strategies. Estimated outcomes and costs of vaccination strategies depend on numerous data inputs or assumptions, including estimates of vaccine efficacy and disease incidence in the absence of vaccination. Limitations in epidemiologic data can meaningfully affect both CEA estimates and the interpretation of those results by groups involved in vaccination policy decisions. Developers of CEAs should be transparent with regard to the ambiguity and uncertainty associated with epidemiologic information that is incorporated into their models. We describe selected data-related challenges to conducting CEAs for vaccination strategies, including generalizability of estimates of vaccine effectiveness, duration and functional form of vaccine protection that can change over time, indirect (herd) protection, and serotype replacement. We illustrate how CEA estimates can be sensitive to variations in specific epidemiologic assumptions, with examples from CEAs conducted for the USA that assessed vaccinations against human papillomavirus and pneumococcal disease. These challenges are certainly not limited to these two case studies and may be relevant to other vaccines.
Collapse
Affiliation(s)
- Jamison Pike
- Centers for Disease Control and Prevention, National Center for Immunization and Respiratory Diseases, 1600 Clifton Road NE, Atlanta, GA, 30329, USA.
| | - Andrew J Leidner
- Centers for Disease Control and Prevention, National Center for Immunization and Respiratory Diseases, 1600 Clifton Road NE, Atlanta, GA, 30329, USA
| | - Harrell Chesson
- Centers for Disease Control and Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, Atlanta, GA, USA
| | - Charles Stoecker
- School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Scott D Grosse
- Centers for Disease Control and Prevention, National Center on Birth Defects and Developmental Disabilities, Atlanta, GA, USA
| |
Collapse
|
3
|
Lu CY, Tang CH, Fu T, Pwu RF, Ho YF. Pneumococcal conjugate vaccines in Taiwan: optimizing health gains in children and older adults through constrained optimization modeling: Pneumococcal conjugate vaccines optimization in Taiwan. Int J Infect Dis 2021; 114:155-164. [PMID: 34749009 DOI: 10.1016/j.ijid.2021.10.058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 10/27/2021] [Accepted: 10/30/2021] [Indexed: 11/28/2022] Open
Abstract
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.
Collapse
Affiliation(s)
- Chun-Yi Lu
- National Taiwan University, No. 1, Section 4, Roosevelt Rd, Da'an District, Taipei City, Taïwan 10617.
| | - Chao Hsiun Tang
- Taipei Medical University, No. 250, Wuxing St, Xinyi District, Taipei City, Taïwan 110.
| | - Tiffany Fu
- GSK, Rochester Park 23, 139234 Singapore, Singapore.
| | - Raoh-Fang Pwu
- Taipei Medical University, No. 250, Wuxing St, Xinyi District, Taipei City, Taïwan 110.
| | - Yu-Fan Ho
- GSK, Rochester Park 23, 139234 Singapore, Singapore.
| |
Collapse
|
4
|
Sauboin C, Mihajlović J, Postma MJ, Geets R, Antic D, Standaert B. Informing decision makers seeking to improve vaccination programs: case-study Serbia. JOURNAL OF MARKET ACCESS & HEALTH POLICY 2021; 9:1938894. [PMID: 34367530 PMCID: PMC8317957 DOI: 10.1080/20016689.2021.1938894] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 05/27/2021] [Accepted: 06/01/2021] [Indexed: 06/13/2023]
Abstract
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.
Collapse
Affiliation(s)
- Christophe Sauboin
- Health Economics Department, GSK, Wavre, Belgium
- Department of Health Sciences, University of Groningen, University Medical Centre Groningen, Groningen, Netherlands
- Department of Economics, Econometrics & Finance, Faculty of Economics & Business, University of Groningen, Groningen, The Netherlands
| | - Jovan Mihajlović
- Department of Health Sciences, University of Groningen, University Medical Centre Groningen, Groningen, Netherlands
- Mihajlović Health Analytics (Miha), Novi Sad, Serbia
| | - Maarten Jacobus Postma
- Department of Health Sciences, University of Groningen, University Medical Centre Groningen, Groningen, Netherlands
- Department of Economics, Econometrics & Finance, Faculty of Economics & Business, University of Groningen, Groningen, The Netherlands
| | - Regine Geets
- Health Economics Department, GSK, Wavre, Belgium
| | | | | |
Collapse
|
5
|
Standaert B, Van Vlaenderen I, Van Bellinghen LA, Talbird S, Hicks K, Carrico J, Buck PO. Constrained Optimization for the Selection of Influenza Vaccines to Maximize the Population Benefit: A Demonstration Project. APPLIED HEALTH ECONOMICS AND HEALTH POLICY 2020; 18:519-531. [PMID: 31755016 PMCID: PMC7347519 DOI: 10.1007/s40258-019-00534-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
BACKGROUND Influenza is an infectious disease causing a high annual economic and public health burden. The most efficient management of the disease is through prevention with vaccination. Many influenza vaccines are available, with varying efficacy and cost, targeting different age groups. Therefore, strategic decision-making about which vaccine to deliver to whom is warranted to improve efficiency. OBJECTIVE We present the use of a constrained optimization (CO) model to evaluate targeted strategies for providing influenza vaccines in three adult age groups in the USA. METHODS CO was considered for identifying an influenza vaccine provision strategy that maximizes the benefits at constrained annual budgets, by prioritizing vaccines based on return on investment. The approach optimizes a set of predefined outcome measures over several years resulting from an increasing investment using the best combination of influenza vaccines. RESULTS Results indicate the importance of understanding the relative differences in benefits for each vaccine type within and across age groups. Scenario and threshold analyses demonstrate the impact of changing budget distribution over time, price setting per vaccine type, and selection of outcome measure to optimize. CONCLUSION Significant gains in cost efficiency can be realized for a decision maker using a CO model, especially for a disease like influenza with many vaccine options. Testing the model under different scenarios offers powerful insights into maximum achievable benefit overall and per age group within the predefined constraints of a vaccine budget.
Collapse
|
6
|
Varghese L, Ezat Wan Puteh S, Schecroun N, Jahis R, Van Vlaenderen I, Standaert BA. Applying a Constrained Optimization Portfolio Model to Aid Prioritization of Public Health Interventions in Malaysia. Value Health Reg Issues 2020; 21:172-180. [PMID: 32044690 DOI: 10.1016/j.vhri.2019.11.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Accepted: 11/17/2019] [Indexed: 11/18/2022]
Abstract
OBJECTIVES Countries have constrained healthcare budgets and must prioritize new interventions depending on health goals and time frame. This situation is relevant in the sphere of national immunization programs, for which many different vaccines are proposed, budgets are limited, and efficient choices must be made in the order of vaccine introduction. METHODS A constrained optimization (CO) model for infectious diseases was developed in which different intervention types (prophylaxis and treatment) were combined for consideration in Malaysia. Local experts defined their priority public health issues: pneumococcal disease, dengue, hepatitis B and C, rotavirus, neonatal pertussis, and cholera. Epidemiological, cost, and effectiveness data were informed from local or regionally published literature. The model aimed to maximize quality-adjusted life-year (QALY) gain through the reduction of events in each of the different diseases, under budget and intervention coverage constraints. The QALY impact of the interventions was assessed over 2 periods: lifetime and 20 years. The period of investment was limited to 15 years. RESULTS The assessment time horizon influenced the prioritization of interventions maximizing QALY gain. The incremental health gains compared with a uninformed prioritization were large for the first 8 years and declined thereafter. Rotaviral and pneumococcal vaccines were identified as key priorities irrespective of time horizon, hepatitis B immune prophylaxis and hepatitis C treatment were priorities with the lifetime horizon, and dengue vaccination replaced these with the 20-year horizon. CONCLUSIONS CO modeling is a useful tool for making economically efficient decisions within public health programs for the control of infectious diseases by helping prioritize the selection of interventions to maximize health gain under annual budget constraints.
Collapse
Affiliation(s)
| | | | - Nadia Schecroun
- Keyrus Biopharma c/o GSK, Health Economics Department, Wavre, Belgium
| | - Rohani Jahis
- Ministry of Health, Disease Control Division, Putrajaya, Malaysia
| | | | | |
Collapse
|
7
|
Standaert B, Sauboin C, DeAntonio R, Marijam A, Gomez J, Varghese L, Zhang S. How to assess for the full economic value of vaccines? From past to present, drawing lessons for the future. JOURNAL OF MARKET ACCESS & HEALTH POLICY 2020; 8:1719588. [PMID: 32128075 PMCID: PMC7034472 DOI: 10.1080/20016689.2020.1719588] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Revised: 12/20/2019] [Accepted: 01/15/2020] [Indexed: 06/10/2023]
Abstract
Background:Cost-effectiveness analysis (CEA) is the economic analysis method most commonly applied today in the context of replacing one treatment with a new one in a developed healthcare system to improve efficiency. CEA is often requested by local healthcare decision-makers to grant reimbursement. New preventative interventions, such as new vaccines, may however have much wider benefits inside and outside healthcare, when compared with treatment. These additional benefits include externalities on indirect clinical impact, reallocation of specific healthcare resources, improved quality of care, better productivity, better disease control, better fiscal revenues, and others. But these effects are sometimes difficult to integrate into a meaningful CEA result. They may appear as specific benefits for specific stakeholders, other than the stakeholders in healthcare. Objective: Based on a historical view about the application of economic assessments for vaccines our objective has been to make the inventory of who was/is interested in knowing the economic value of vaccines, in what those different stakeholders are likely to see the benefit from their perspective and how were/are we able to measure those benefits and to report them well. Results: The historical view disclosed a limited interest in the economic assessment of vaccines at start, more than 50 years ago, that was comparable to the assessment of looking for more efficiency in new industries through optimization exercises. Today, we are exposed to a very rich panoply of different stakeholders (n= 16). They have their specific interest in many different facets of the vaccine benefit of which some are well known in the conventional economic analysis (n=9), but most outcomes are hidden and not enough evaluated and reported (n=26). Meanwhile we discovered that many different methods of evaluation have been explored to facilitate the measurement and reporting of the benefits (n=18). Conclusion: Our recommendation for future economic evaluations of new vaccines is therefore to find the right combination among the three entities of stakeholder type selection, outcome measure of interest for each stakeholder, and the right method to apply. We present at the end examples that illustrate how successful this approach can be.
Collapse
Affiliation(s)
| | | | | | - Alen Marijam
- Value Evidence and Outcome, GSK, Collegeville, PA, USA
| | - Jorge Gomez
- R&D Health Outcomes, GSK, Buenos Aires, Argentina
| | | | - Sharon Zhang
- Regional Health Outcomes, GSK, Singapore, Singapore
| |
Collapse
|
8
|
Mauskopf J, Standaert B, Connolly MP, Culyer AJ, Garrison LP, Hutubessy R, Jit M, Pitman R, Revill P, Severens JL. Economic Analysis of Vaccination Programs: An ISPOR Good Practices for Outcomes Research Task Force Report. VALUE IN HEALTH : THE JOURNAL OF THE INTERNATIONAL SOCIETY FOR PHARMACOECONOMICS AND OUTCOMES RESEARCH 2018; 21:1133-1149. [PMID: 30314613 DOI: 10.1016/j.jval.2018.08.005] [Citation(s) in RCA: 85] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2018] [Accepted: 08/16/2018] [Indexed: 05/21/2023]
Abstract
This report provides recommendations for budget holders and decision makers in high-, middle, and low-income countries requiring economic analyses of new vaccination programs to allocate scarce resources given budget constraints. ISPOR's Economic Evaluation of Vaccines Designed to Prevent Infectious Disease: Good Practices Task Force wrote guidelines for three analytic methods and solicited comments on them from external reviewers. Cost-effectiveness analyses use decision-analytic models to estimate cumulative changes in resource use, costs, and changes in quality- or disability-adjusted life-years attributable to changes in disease outcomes. Constrained optimization modeling uses a mathematical objective function to be optimized (e.g. disease cases avoided) for a target population for a set of interventions including vaccination programs within established constraints. Fiscal health modeling estimates changes in net present value of government revenues and expenditures attributable to changes in disease outcomes. The task force recommends that those designing economic analyses for new vaccination programs take into account the decision maker's policy objectives and country-specific decision context when estimating: uptake rate in the target population; vaccination program's impact on disease cases in the population over time using a dynamic transmission epidemiologic model; vaccination program implementation and operating costs; and the changes in costs and health outcomes of the target disease(s). The three approaches to economic analysis are complementary and can be used alone or together to estimate a vaccination program's economic value for national, regional, or subregional decision makers in high-, middle-, and low-income countries.
Collapse
Affiliation(s)
| | | | - Mark P Connolly
- University of Groningen, Groningen, The Netherlands; Global Market Access Solutions LLC, Geneva, Switzerland
| | | | - Louis P Garrison
- Department of Pharmacy, The Comparative Health Outcomes, Policy, and Economics (CHOICE) Institute, University of Washington, Seattle, WA, USA
| | | | - Mark Jit
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine and Public Health, London, UK
| | | | - Paul Revill
- Centre for Health Economics, University of York, York, UK
| | - Johan L Severens
- Erasmus School of Health Policy & Management, Erasmus University Rotterdam, Rotterdam, The Netherlands; Institute of Medical Technology Assessment, Erasmus University Rotterdam, Rotterdam, The Netherlands
| |
Collapse
|