BACKGROUND: Most research on identifying and understanding health disparities focused on measurement strategies and analytics design over administrative and survey data. What has received less attention, however, is the complex interplay between privacy concerns and the needs of health disparity research. OBJECTIVES: The main objective of the paper is to illustrate the fundamental challenges facing the reconciliation of privacy needs and health disparity research. RESEARCH DESIGN: We investigated whether privacy disparity exists over raw, unprocessed, public health data, and then examined the effect of a state-of-the-practice data anonymization process and a state-of-the-art privacy-preserving data sharing technique on both privacy disparity and the efficacy of health disparity research. RESULTS: We demonstrate that the essential elements for health disparity research, for example, the integration of demographics attributes such as race in public health datasets, could indeed lead to privacy disparity if not carefully treated. DISCUSSIONS AND POLICY IMPLICATIONS: The findings in this paper indicate that regulators must carefully study the privacy implications before mandating the inclusion of certain attributes like race and geolocation in a released dataset. For example, the Affordable Care Act requires all federally supported public health programs to collect data on race, ethnicity, sex, geographic location, etc., to the extent feasible. Although doing so could help identify health disparities, if the collected data are directly released without proper sanitization, the released data may introduce privacy disparities, causing further harm to underserved populations.
BACKGROUND: Most research on identifying and understanding health disparities focused on measurement strategies and analytics design over administrative and survey data. What has received less attention, however, is the complex interplay between privacy concerns and the needs of health disparity research. OBJECTIVES: The main objective of the paper is to illustrate the fundamental challenges facing the reconciliation of privacy needs and health disparity research. RESEARCH DESIGN: We investigated whether privacy disparity exists over raw, unprocessed, public health data, and then examined the effect of a state-of-the-practice data anonymization process and a state-of-the-art privacy-preserving data sharing technique on both privacy disparity and the efficacy of health disparity research. RESULTS: We demonstrate that the essential elements for health disparity research, for example, the integration of demographics attributes such as race in public health datasets, could indeed lead to privacy disparity if not carefully treated. DISCUSSIONS AND POLICY IMPLICATIONS: The findings in this paper indicate that regulators must carefully study the privacy implications before mandating the inclusion of certain attributes like race and geolocation in a released dataset. For example, the Affordable Care Act requires all federally supported public health programs to collect data on race, ethnicity, sex, geographic location, etc., to the extent feasible. Although doing so could help identify health disparities, if the collected data are directly released without proper sanitization, the released data may introduce privacy disparities, causing further harm to underserved populations.
Authors: Karriem S Watson; Elizabeth G Cohn; Alecia Fair; Usha Menon; Laura A Szalacha; Selena M Carpenter; Consuelo H Wilkins Journal: Health Expect Date: 2022-03-30 Impact factor: 3.318