' Kimberly Parry | MTTLR

Big Data: Transitioning Away From the White Male Norm

As the capacity to generate and use digital information increases, the use of big data has permeated many industries. Its usage in medicine is poised to make major impacts on clinical practice. There are many benefits to the quality and efficiency of healthcare that can be achieved through the utilization of big health data. But there is a need for an understanding of how big data will affect populations that face disparities and inequalities in medicine – women and people of color. In medicine, the white male is generally the default. This default often affects how women and people of color are diagnosed and treated. Women may go undiagnosed and untreated due to having “exclusively female disease” or diseases that occur more frequently in women than men. Or they are misdiagnosed because their symptoms don’t manifest in the same way they do in men. For people of color, differences in race may affect the efficacy of drugs and medical devices. For both populations, they may ultimately have to be sicker or wait longer to qualify for the same treatment as a white man. Big data may help overcome these disparities through recognition of patterns in the treatment of women and people of color. Data generated during the course of care can be used to measure quality, develop hypotheses, and compare effectiveness of different treatments. Artificial intelligence (AI) technology provides the ability to take massive data sets and find patterns. These identified patterns may reveal gender and racial differences that affect diagnosis and treatment. Through the use of big data in precision medicine, for example, the identification of “biological variation...