Big Data Analytics and the Struggle for Equity in Health Care: The Promise and Perils
| Autor: | Mary E. Charlson, Daniel B. Neill, Said A. Ibrahim |
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| Rok vydání: | 2020 |
| Předmět: |
Potential impact
Health (social science) Equity (economics) Computer science business.industry algorithmic decision-making Health Policy health care innovation Big data Public Health Environmental and Occupational Health health care disparities big data analytics Data science inequities Transformative learning Health Information Management Health care Perspective biases business |
| Zdroj: | Health Equity |
| ISSN: | 2473-1242 |
| Popis: | Big data is both a product and a function of technology and the ever-growing analytic and computational power. The potential impact of big data in health care innovation cannot be ignored. The technology-mediated transformative potential of big data is taking place within the context of historical inequities in health and health care. Although big data analytics, properly applied, hold great potential to target inequities and reduce disparities, we believe that the realization of this potential requires us to explicitly address concerns of fairness, equity, and transparency in the development of big data tools. To mitigate potential sources of bias and inequity in algorithmic decision-making, a multipronged and interdisciplinary approach is required, combining insights from data scientists and domain experts to design algorithmic decision-making approaches that explicitly account and correct for these issues. |
| Databáze: | OpenAIRE |
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