Dr. Jessica Skopac


Jessica Skopac is a Principal Health Policy Analyst at the MITRE corporation with over 12 years of experience in healthcare and public health. At MITRE, her work includes serving as a project leader within the Care, Cost, Quality and Innovation department to provide policy support for the Center for Medicare & Medicaid Services’ Center for Clinical Standards and Quality and Co-Principal Investigator for the development of an ethical and policy framework to guide the use of consumer-generated data for healthcare providers, systems, and payers. Prior to joining MITRE, Skopac served as a health policy analyst at the Hilltop Institute, a non-partisan policy research organization within the University of Maryland, Baltimore County, where she provided ongoing strategic evaluation of the Maryland Asthma Control Program in accordance with CDC issued guidelines, conducted a needs assessment for the Maryland state public health system in preparation for national public health department accreditation, helped compile an environmental scan of Hospital Community Benefits Program requirements in each of the 50 states, and authored the final report submitted on behalf of the Advisory Committee on Operating Model and Insurance Rules for the Maryland Health Benefit Exchange (MHBE), which was subsequently presented to the Maryland General Assembly. She also served as a program evaluation specialist at the Institute for Community Health and Public Policy Liaison for the Maryland Chapter of the American Academy of Pediatrics. Skopac received a Bachelor of Arts degree in Interdisciplinary Studies, a Master of Arts degree in Applied and Professional Ethics, a doctorate in Health Policy, and a juris doctor from the University of Maryland.


Day 2: September 12, 2019 | Session 3 | 4:20 PM - 4:40 PM

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

Jessica Skopac, PhD, Health Technical Center, Mitre Corporation, McLean, VA, USA

Problem: Consumer-generated data (CGD) (e.g., social media use, internet searches, buying behaviors, memberships, etc.) increasingly is being used to forecast health outcomes, risks, and utilization. The absence of ethical standards to guide CGD use in health care analytics may result in harms to patient privacy and autonomy, disruption of trust in the patient-provider relationship, or marginalization of individuals/populations.

Design: The research team employed a modified Delphi method, beginning with literature reviews focused on U.S. and international CGD policies; health care ethics; and ethical concerns for analytics, algorithms, and machine learning.

The literature reviews led to development of a preliminary set of ethical values, principles, and guidelines for the framework. The team conducted consensus workshops, focus groups, and key informant interviews with multidisciplinary teams in different settings and incorporated feedback into the final framework.

Findings: The team developed a conceptual model to explain how the five values, eight principles, and 39 user-specific guidelines work in tandem to support ethical decision-making. The five non-hierarchical values of the framework are: Individual Self-determination, Health, Distributive Justice, Trustworthiness, and Privacy. The eight non-hierarchal principles are: Respect Autonomy, Consider Fairness, Ensure Accountability, Empower Individuals and Communities, Preserve Data Security, Promote Data Protection, Promote Transparency, and Consider Individual and Population Health. External expert reviewers found the framework to be comprehensive and that its implementation would improve consumer protections.

Conclusions: Providing an actionable, user-specific ethical framework for CGD use in health care will help organizations use CGD in a manner that safeguards persons and populations from negative impact.