Literature review of data-based models for identification of factors associated with racial disparities in breast cancer mortality
| Autor: | Maggie Atwood, Brian C Hill, Rindy Tija, Lorena Peña, Diana Prieto, Ethan Maltz, Lisa Miller, Jafar Haghsenas, Earl M Norman, Leandra H Burke, Milton Soto-Ferrari, Kelsey Berndt, Evan J. White |
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| Rok vydání: | 2016 |
| Předmět: |
Research literature
021103 operations research business.industry 030503 health policy & services Health Policy Breast cancer mortality 0211 other engineering and technologies Early detection Health Informatics 02 engineering and technology Review Article medicine.disease 03 medical and health sciences Identification (information) Breast cancer Quantitative analysis (finance) Environmental health Health care parasitic diseases medicine 0305 other medical science business Psychology Statistical hypothesis testing |
| Zdroj: | Health systems (Basingstoke, England). 8(2) |
| ISSN: | 2047-6965 |
| Popis: | In the United States, early detection methods have contributed to the reduction of overall breast cancer mortality but this pattern has not been observed uniformly across all racial groups. A vast body of research literature shows a set of health care, socio-economic, biological, physical, and behavioural factors influencing the mortality disparity. In this paper, we review the modelling frameworks, statistical tests, and databases used in understanding influential factors, and we discuss the factors documented in the modelling literature. Our findings suggest that disparities research relies on conventional modelling and statistical tools for quantitative analysis, and there exist opportunities to implement data-based modelling frameworks for (1) exploring mechanisms triggering disparities, (2) increasing the collection of behavioural data, and (3) monitoring factors associated with the mortality disparity across time. |
| Databáze: | OpenAIRE |
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