Sue J Goldie1, Norman Daniels. 1. Department of Health Policy and Management, Center for Health Decision Science, Harvard School of Public Health, Harvard Global Health Institute, Harvard University, 718 Huntington Ave, 2nd floor, Boston, MA 02115, USA. sue_goldie@harvard.edu
Abstract
BACKGROUND: Disease simulation models of the health and economic consequences of different prevention and treatment strategies can guide policy decisions about cancer control. However, models that also consider health disparities can identify strategies that improve both population health and its equitable distribution. METHODS: We devised a typology of cancer disparities that considers types of inequalities among black, white, and Hispanic populations across different cancers and characteristics important for near-term policy discussions. We illustrated the typology in the specific example of cervical cancer using an existing disease simulation model calibrated to clinical, epidemiological, and cost data for the United States. We calculated average reduction in cancer incidence overall and for black, white, and Hispanic women under five different prevention strategies (Strategies A1, A2, A3, B, and C) and estimated average costs and life expectancy per woman, and the cost-effectiveness ratio for each strategy. RESULTS: Strategies that may provide greater aggregate health benefit than existing options may also exacerbate disparities. Combining human papillomavirus vaccination (Strategy A2) with current cervical cancer screening patterns (Strategy A1) resulted in an average reduction of 69% in cancer incidence overall but a 71.6% reduction for white women, 68.3% for black women, and 63.9% for Hispanic women. Other strategies targeting risk-based screening to racial and ethnic minorities reduced disparities among racial subgroups and resulted in more equitable distribution of benefits among subgroups (reduction in cervical cancer incidence, white vs. Hispanic women, 69.7% vs. 70.1%). Strategies that employ targeted risk-based screening and new screening algorithms, with or without vaccination (Strategies B and C), provide excellent value. The most effective strategy (Strategy C) had a cost-effectiveness ratio of $28,200 per year of life saved when compared with the same strategy without vaccination. CONCLUSIONS: We identify screening strategies for cervical cancer that provide greater aggregate health benefit than existing options, offer excellent cost-effectiveness, and have the biggest positive impact in worst-off groups. The typology proposed here may also be useful in research and policy decisions when trade-offs between fairness and cost-effectiveness are unavoidable.
BACKGROUND: Disease simulation models of the health and economic consequences of different prevention and treatment strategies can guide policy decisions about cancer control. However, models that also consider health disparities can identify strategies that improve both population health and its equitable distribution. METHODS: We devised a typology of cancer disparities that considers types of inequalities among black, white, and Hispanic populations across different cancers and characteristics important for near-term policy discussions. We illustrated the typology in the specific example of cervical cancer using an existing disease simulation model calibrated to clinical, epidemiological, and cost data for the United States. We calculated average reduction in cancer incidence overall and for black, white, and Hispanic women under five different prevention strategies (Strategies A1, A2, A3, B, and C) and estimated average costs and life expectancy per woman, and the cost-effectiveness ratio for each strategy. RESULTS: Strategies that may provide greater aggregate health benefit than existing options may also exacerbate disparities. Combining human papillomavirus vaccination (Strategy A2) with current cervical cancer screening patterns (Strategy A1) resulted in an average reduction of 69% in cancer incidence overall but a 71.6% reduction for white women, 68.3% for black women, and 63.9% for Hispanic women. Other strategies targeting risk-based screening to racial and ethnic minorities reduced disparities among racial subgroups and resulted in more equitable distribution of benefits among subgroups (reduction in cervical cancer incidence, white vs. Hispanic women, 69.7% vs. 70.1%). Strategies that employ targeted risk-based screening and new screening algorithms, with or without vaccination (Strategies B and C), provide excellent value. The most effective strategy (Strategy C) had a cost-effectiveness ratio of $28,200 per year of life saved when compared with the same strategy without vaccination. CONCLUSIONS: We identify screening strategies for cervical cancer that provide greater aggregate health benefit than existing options, offer excellent cost-effectiveness, and have the biggest positive impact in worst-off groups. The typology proposed here may also be useful in research and policy decisions when trade-offs between fairness and cost-effectiveness are unavoidable.
Authors: Jeremy D Goldhaber-Fiebert; Natasha K Stout; Joshua A Salomon; Karen M Kuntz; Sue J Goldie Journal: J Natl Cancer Inst Date: 2008-02-26 Impact factor: 13.506
Authors: Niko Speybroeck; Carine Van Malderen; Sam Harper; Birgit Müller; Brecht Devleesschauwer Journal: Int J Environ Res Public Health Date: 2013-11-04 Impact factor: 3.390