Targeted versus universal prevention. A resource allocation model to prioritize cardiovascular prevention

被引:5
|
作者
Feenstra T.L. [1 ,2 ]
van Baal P.M. [1 ,3 ]
Jacobs-van der Bruggen M.O. [1 ]
Hoogenveen R.T. [4 ]
Kommer G.-J. [5 ]
Baan C.A. [1 ,6 ]
机构
[1] Centre for Prevention and Health Services Research, National Institute for Public Health and the Environment (RIVM), Bilthoven
[2] Department of Epidemiology, University Medical Centre Groningen, Groningen
[3] Institute for Medical Technology Assessment, Erasmus University Rotterdam, Rotterdam
[4] Expertise Centre for Methodology and Information Services, RIVM, Bilthoven
[5] Centre for Public Health Forecasting, RIVM, Bilthoven
[6] EMGO Institute for Health and Care Research, VU University Amsterdam, Amsterdam
关键词
Diabetes Patient; Optimal Allocation; Capacity Constraint; Efficiency Frontier; Mathematical Programming Model;
D O I
10.1186/1478-7547-9-14
中图分类号
学科分类号
摘要
Background: Diabetes mellitus brings an increased risk for cardiovascular complications and patients profit from prevention. This prevention also suits the general population. The question arises what is a better strategy: target the general population or diabetes patients.Methods: A mathematical programming model was developed to calculate optimal allocations for the Dutch population of the following interventions: smoking cessation support, diet and exercise to reduce overweight, statins, and medication to reduce blood pressure. Outcomes were total lifetime health care costs and QALYs. Budget sizes were varied and the division of resources between the general population and diabetes patients was assessed.Results: Full implementation of all interventions resulted in a gain of 560,000 QALY at a cost of €640 per capita, about €12,900 per QALY on average. The large majority of these QALY gains could be obtained at incremental costs below €20,000 per QALY. Low or high budgets (below €9 or above €100 per capita) were predominantly spent in the general population. Moderate budgets were mostly spent in diabetes patients.Conclusions: Major health gains can be realized efficiently by offering prevention to both the general and the diabetic population. However, a priori setting a specific distribution of resources is suboptimal. Resource allocation models allow accounting for capacity constraints and program size in addition to efficiency. © 2011 Feenstra et al; licensee BioMed Central Ltd.
引用
收藏
相关论文
共 50 条
  • [41] A Synchronized Model for Crash Prediction and Resource Allocation to Prioritize Highway Safety Improvement Projects
    Mishra, Sabyasachee
    [J]. 2ND CONFERENCE OF TRANSPORTATION RESEARCH GROUP OF INDIA (2ND CTRG), 2013, 104 : 992 - 1001
  • [42] Targeted proteomics improves cardiovascular risk prediction in secondary prevention
    Nurmohamed, Nick S.
    Pereira, Joao P. Belo
    Hoogeveen, Renate M.
    Kroon, Jeffrey
    Kraaijenhof, Jordan M.
    Waissi, Farahnaz
    Timmerman, Nathalie
    Bom, Michiel J.
    Hoefer, Imo E.
    Knaapen, Paul
    Catapano, Alberico L.
    Koenig, Wolfgang
    de Kleijn, Dominique
    Visseren, Frank L. J.
    Levin, Evgeni
    Stroes, Erik S. G.
    [J]. EUROPEAN HEART JOURNAL, 2022, 43 (16) : 1569 - +
  • [43] Modifiable cardiovascular risk factors and genetics for targeted prevention of dementia
    Rasmussen, Ida Juul
    Frikke-Schmidt, Ruth
    [J]. EUROPEAN HEART JOURNAL, 2023, 44 (28) : 2526 - 2543
  • [44] Usefulness of Empagliflozin Versus Liraglutide for Prevention of Cardiovascular Mortality
    Arbel, Ronen
    Hammerman, Ariel
    Azuri, Joseph
    [J]. AMERICAN JOURNAL OF CARDIOLOGY, 2018, 122 (06): : 981 - 984
  • [45] PCSK9 inhibitors: Ratification of the role of LDL cholesterol in cardiovascular prevention. Towards a convergence of European and North American prevention guidelines?
    Guijarro, C.
    Camafort, M.
    [J]. REVISTA CLINICA ESPANOLA, 2020, 220 (06): : 374 - 382
  • [46] Accident prevention. Presentation of a model placing emphasis on human, structural and cultural factors
    Lund, J
    Aaro, LE
    [J]. SAFETY SCIENCE, 2004, 42 (04) : 271 - 324
  • [47] Application of the revised universal soil loss equation model on landslide prevention. An example from N. Euboea (Evia) Island, Greece
    Dimitrios Rozos
    Hariklia D. Skilodimou
    Constantinos Loupasakis
    George D. Bathrellos
    [J]. Environmental Earth Sciences, 2013, 70 : 3255 - 3266
  • [48] Genetic susceptibility and oxidative stress in prostate cancer: An integrated model with implications for prevention.
    Klein, E
    Silverman, R
    Casey, G
    [J]. CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION, 2005, 14 (11) : 2784S - 2784S
  • [49] Primary prevention of cardiovascular events and type 2 diabetes - Should we prioritize our interventions?
    Sultan, A.
    Thuan, J. F.
    Avignon, A.
    [J]. DIABETES & METABOLISM, 2006, 32 (06) : 559 - 567
  • [50] Application of the revised universal soil loss equation model on landslide prevention. An example from N. Euboea (Evia) Island, Greece
    Rozos, Dimitrios
    Skilodimou, Hariklia D.
    Loupasakis, Constantinos
    Bathrellos, George D.
    [J]. ENVIRONMENTAL EARTH SCIENCES, 2013, 70 (07) : 3255 - 3266