Commonwealth of Virginia Entity Resolution for Enterprise Data (CoVERED)
The Office of Data Governance and Analytics within the Secretary of Administration has developed a solution to securely and appropriately consolidate data from multiple systems across the state. The Commonwealth of Virginia Entity Resolution for Enterprise Data (CoVERED) ingests two data streams separating the attributes that identify individuals (PII) from those that characterize the government services they receive by leveraging partnerships with executive branch agencies and other organizations through the Commonwealth Data Trust, a safe, secure, and legally compliant information sharing environment that establishes consistent requirements for trust members through a standardized data sharing agreement process.
As mentioned above, the first data stream is limited to the attributes that uniquely identify an individual. These attributes include a personal identifier that is unique to the source data system along with the individual’s first name, middle name, last name, date of birth, race, ethnicity, gender, and may also include other attributes such as social security number and driver’s license number. This data is maintained on secure, isolated, internal systems managed by the Office of Data Governance and Analytics. Personally identifiable information (PII) is only used to match individuals across systems without any attributes associated with the government services they receive. A crosswalk table known as the Universal Entity Index contains a universal identifier for each unique individual linking records across multiple systems via their personal identifier instead of PII.
The second data stream contains the same personal identifier (not PII) that is unique to the source system as well as additional attributes that characterize the government services the individual has received. Some examples include, but are not limited to, whether the individual has received SNAP or TANF benefits, is enrolled in Medicaid, or has received a COVID vaccination. Using the crosswalk table, we are able to identify which individual records match across multiple systems by searching across the row of a specific universal identifier for the presence of a personal identifier associated with the desired systems. Using the previous example, we could identify how many vaccinated individuals also receive SNAP benefits. In this case, we would use the Universal Entity Index to determine how many records have personal identifiers in the vaccine administration system and the SNAP benefits system. We will then query each system for only the service attribute data (not PII) associated with each personal identifier then join the results using the universal identifier from the crosswalk table.
The result is a de-identified table showing the vaccine administration information along with the SNAP benefits information. This table can now be used for further analysis, aggregation, and reporting. The insights generated from the analysis can be used to improve government services, better engage with stakeholders, and promote better outcomes for our constituents. By maximizing the value of Commonwealth data through this secure and appropriate data sharing solution and enterprise analytics services we are driving impact through insight, not identification.