An Ethical Framework for the Use of Consumer-Generated Data in Health Care

July 2019
Topics: Social and Behavioral Sciences, Health, Data Analytics, Data Management, Information Privacy, Social Behavior
Dr. Eldesia L. Granger, The MITRE Corporation
Dr. Jessica S. Skopac, The MITRE Corporation
Susan U. Mbawuike, The MITRE Corporation
Anna T. Levin, The MITRE Corporation
Dr. Susan J. Dwyer, University of Maryland
Dr. Arnon S. Rosenthal, The MITRE Corporation
Jillian A. Humphreys, The MITRE Corporation
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The Ethical Framework for the Use of Consumer-Generated Data in Health Care profiled in this document establishes ethical values, principles, and guidelines to guide the use of Consumer-Generated Data for health care purposes (i.e., diagnosis, prevention, treatment, payment, care operations, population management, health monitoring, and/or the delivery of essential public health services).

Consumers are largely unaware that organizations are acquiring and using their personal lifestyle data for health care purposes. Organizations may have benevolent intentions—such data can be used in productive ways that ultimately benefit consumers’ health—but consumers can potentially be harmed if this data is used inappropriately or unethically.

Consumer-generated data (CGD) refers to individual lifestyle or behavior data generated by an individual’s engagement in a non-clinical commercial, participatory, or social activity (e.g., an individual’s online search history, social media activity, purchase transaction history, etc.). CGD is an undeniably valuable commodity for organizations. Whether analyzed alone or integrated with clinical data, CGD offers a tantalizingly rich trove of information from which organizations can glean critical insights about how lifestyle factors affect health outcomes, disease risk, and health services utilization. Organizations also may use CGD to develop more personalized and efficient health care experiences for their consumers.

However, CGD use also has the potential to harm individuals or populations. Use of CGD may result in erroneous inferences about a consumer’s health, exacerbate health disparities by perpetuating historical biases (e.g., structural inequities), or render certain populations invisible. Consumer segmentation and personalization of services based on CGD can restrict consumer choice or limit opportunities by making assumptions about consumer preferences or group classifications. Additionally, without certain protections, CGD use may negatively impact health insurance access by influencing plan pricing.

Though access to CGD offers unprecedented opportunities to organizations, serious ethical concerns exist surrounding privacy, consent, trust, data security, and data control. Moreover, to harness analytic insights from CGD and other data, organizations are increasingly crossing into the technological territory of increasingly complex algorithms and machine learning, which raises additional ethical concerns related to fairness, transparency, accountability, and autonomy.

Consumers expect organizations working in health to have sound ethical values and to invest in and promote their best health. Organizations have a responsibility to proactively evaluate and address ethical concerns surrounding the use of CGD for health care purposes to reduce potential harms to individuals and populations. By voluntarily adopting a consistent ethical decision-making approach whenever they use CGD, organizations can guard against reputational harm and prevent erosion of consumer trust and confidence stemming from perceived misuse of CGD.

The purpose of the Ethical Framework for the Use of Consumer-Generated Data in Health Care is twofold:

  1. To guide organizations seeking to establish policies that promote the ethical use of CGD for health care purposes, including CGD acquisition, storage, disclosure/distribution, processing, analysis, and application
  2. To motivate organizations to discuss the ethical implications of machine learning and develop appropriate governance processes to facilitate the ethical use of machine learning for analysis of CGD and other data

A wide range of health care stakeholders— providers, payers, health systems, population management vendors, and other industry organizations (e.g., technology, social media, or e-commerce companies)— providing products or services for health care can employ this Framework to ensure that they use CGD in an ethically defensible way.

By adopting this Framework, organizations can feel confident that they are handling CGD ethically and taking actions that will actively preserve and foster the trust of their consumers.

Download PDF (19.14 MB)

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