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COVID-19COVID-19 and Health EquityCOVID-19: Health Data Sharing and PrivacyMechanisms for Advancing Public HealthHealth Information and Data Sharing

Q&A on Racial Equity Throughout Data Integration

October 15, 2020

Overview

The Network has partnered with All In Data for Community Health on a series of webinars focused on racial equity and data integration. In this excerpt of a webinar Q&A, Sallie Milam, Deputy Director of the Network’s Mid-States Region, shares her perspective on why racial equity matters and where trust-building can occur in the data life cycle, including her work with Tribal communities.

Q: What are some strategies to center racial equity with Tribal Nations and their peoples?

It is essential to begin with honoring and respecting Tribal data sovereignty. Tribal nations are separate and sovereign jurisdictions. As sovereign nations, Tribes have inherent authority to protect their Tribal citizens’ health and wellness and provide public health services as they determine best. Read more about Tribal public health law and Tribal self-determination. To govern public health service delivery to their people, Tribal nations have the authority to administer the collection, ownership, and application of their own data, which is known as indigenous data sovereignty.

Where Tribes do not have the capacity to collect data on Tribal citizens themselves, they may partner with other jurisdictions, such as state governments. Data sharing between state governments, Tribal Epidemiology Centers, and Tribes should be grounded in a strong data governance program. Data Governance Strategies for States and Tribal Nations. A first step in establishing a data governance program is the adoption of a principle-based framework that aligns with the organization’s mission, vision, and values.

State governments and Tribes might evaluate starting with the NCVHS Stewardship Framework which identifies eight elements:

  1. Openness, transparency, and choice – what information is being collected and why, consent options
  2. Purpose specification – the initial purpose of the data collection and its downstream uses are defined and made explicit at the point of collection
  3. Community engagement and participation – whether and how communities should be involved in decision-making about data
  4. Data integrity and security – evaluation of confidentiality, integrity and availability risks to the data and a plan to address those risks
  5. Accountability – identification of a person or entity responsible for data governance at each stage of the data lifecycle
  6. Protecting de-identified data – ensuring that data are de-identified, as appropriate, and have administrative safeguards, as needed
  7. Attending to the risks of “enhanced” data sets – ensuring that re-identification risks are appropriately managed when data sets are merged
  8. Stigma and discrimination – ensuring that data uses don’t stigmatize or result in negative attitudes towards communities

This Fact Sheet provides considerations for state governments and Tribes’ evaluation of a data governance framework, meaningful Tribal partnership and consultation in data sharing, and best practices for data sharing between Tribes and state governments. All In’s Lessons from the First Wave offers real-world examples of successes in Tribal, Tribal Epidemiology Center and state government collaboration and communication around data sharing. Honoring and respecting Tribal data sovereignty is critical for Tribes to protect the health and wellness of their citizens and to achieve health equity.

Q: Could you talk about how you see the role of public health law in promoting racial equity in data sharing?

Law and policies define all aspects of the data life cycle, including collection, use, sharing, and destruction. Data owners may not be able to share data needed to address racial disparities due to restrictions or ambiguities within law or policy. The Network for Public Health Law offers an equity assessment framework for public health laws and policies. This framework assists in identifying issues in the drafting, design, or implementation of a law or policy that could have a disproportionate impact on different population groups. The framework is meant to guide a discussion around how equity is considered in both process and outcomes and can help identify opportunities for improvement. This equity assessment tool is a critical tool at a critical time.

Law may also protect racial equity by prohibiting data sharing in certain situations. Concern over immigration enforcement can prevent immigrants from obtaining needed health care. Many immigrants worry that health workers will share their undocumented status with immigration authorities. Removing barriers to immigrants’ utilization of preventive and other health care services is important for public health. This Network for Public Health Law issue brief explores relevant federal and state health privacy laws and how they apply to undocumented immigrants and provides information on health care providers’ rights and responsibilities when providing health care to immigrants.

Emerging frameworks to enable data sharing across the social determinants of health hold promise to improve racial equity. In this report, SIREN illuminates where health care organizations share personal information outside of healthcare with other sectors – such as housing programs, school health programs, and social service programs – while protecting individual privacy in compliance with federal and state law. De-identification is also a data sharing strategy that advances health equity where it is useful for a community and population where individual-level data are not

Read the Q&A in its entirety here.

The Network for Public Health Law provides information and technical assistance on issues related to public health. The legal information and assistance provided in this post do not constitute legal advice or legal representation. For legal advice, readers should consult a lawyer in their state.

Support for the Network is provided by the Robert Wood Johnson Foundation (RWJF). The views expressed in this post do not represent the views of (and should not be attributed to) RWJF.