Cross-Jurisdictional Data Exchange Impact on the Estimation of the HIV Population Living in the District of Columbia: Evaluation Study

Abstract

BackgroundAccurate HIV surveillance data are essential to monitor trends to help end the HIV epidemic. Owing to strict policies around data security and confidentiality, HIV surveillance data have not been routinely shared across jurisdictions except a biannual case-by-case review process to identify and remove duplicate cases (Routine Interstate Duplicate Review, RIDR). HIV surveillance estimates for the District of Columbia (DC) are complicated by migration and care seeking throughout the metropolitan area, which includes Maryland and Virginia. To address gaps in HIV surveillance data, health departments of DC, Maryland, and Virginia have established HIV surveillance data sharing agreements. Although the Black Box (a privacy data integration tool external to the health departments) facilitates the secure exchange of data between DC, Maryland, and Virginia, its previous iterations were limited by the frequency and scope of information exchanged. The health departments of DC, Maryland, and Virginia engaged in data sharing to further improve HIV surveillance estimates.ObjectiveThis study assessed the impact of cross-jurisdictional data sharing on the estimation of people living with HIV in DC and reduction of cases in the RIDR process.MethodsData sharing agreements established in 2014 allowed for the exchange of HIV case information (eg, current residential address) and laboratory information (eg, test types, result dates, and results) from the enhanced HIV/AIDS Reporting System (eHARS). Regular data exchanges began in 2017. The participating jurisdictions transferred data (via secure file transfer protocol) for individuals having a residential address in a partnering jurisdiction at the time of HIV diagnosis or evidence of receiving HIV-related services at a facility located in a partnering jurisdiction. The DC Department of Health compared the data received to DC eHARS and imported updated data that matched existing cases. Evaluation of changes in current residential address and HIV prevalence was conducted by comparing data before and after HIV surveillance data exchanges.ResultsAfter the HIV surveillance data exchange, an average of 396 fewer cases were estimated to be living in DC each year from 2012 to 2016. Among cases with a residential status change, 66.4% (1316/1982) had relocated to Maryland and 19.8% (392/1982) to Virginia; majority of these had relocated to counties bordering DC. Relocation in and out of DC differed by mode of transmission, race and ethnicity, age group, and gender. After data exchange, the volume of HIV cases needing RIDR decreased by 74% for DC-Maryland and 81% for DC-Virginia.ConclusionsHIV surveillance data exchange between the public health departments of DC, Maryland, and Virginia reduced the number of cases misclassified as DC residents and reduced the number of cases needing RIDR. Continued data exchanges will enhance the ability of DC Department of Health to monitor the local HIV epidemic.

Common and Unique Barriers to the Exchange of Administrative Healthcare Data in Environmental Public Health Tracking Program

“…The State and Territorial Exchange of Vital Events (STEVE) system, for example, quickly provides vital records data to other jurisdictions and authorized public health and administrative programs, while also ensuring the security and privacy of the data during transmission [ 31 ]. Surveillance data exchange between the public health departments of the District of Columbia, Maryland, and Virginia reduced the number of cases misclassified as District of Columbia residents and reduced the number of cases with duplicates [ 32 ]. CDC’s tracking program and NAHDO can help state health departments communicate with each other and develop an internal data user agreement process to enable data exchange with bordering states.…”

Comparison of Clinical Outcomes of Persons Living With HIV by Enrollment Status in Washington, DC: Evaluation of a Large Longitudinal HIV Cohort Study

“…DC Cohort study and DCDOH HAHSTA surveillance data are matched every 6 months as part of the study protocol. DC Cohort study data were matched based on an 11-key algorithm linking first name, last name, date of birth, and social security number [18][19][20][21]. Linkage keys range from including social security number or full first name, last name, and date birth to only including the first 3 letters of the first name, last name, and the date of birth year.…”

“…Linkage keys range from including social security number or full first name, last name, and date birth to only including the first 3 letters of the first name, last name, and the date of birth year. Matches made through keys 7-11, which all consist of only partial first and last names and dates of birth, were manually reviewed and checked for accuracy (Table 1) [21]. Of the initial 275 patients who matched through keys 7-11, after deduplication nearly 30% (79/275) were not true matches and were eliminated from the dataset.…”

“…Any of these explanations is possible. In an analysis evaluating a local HIV lab data exchange, DC residents diagnosed with HIV and with a current address found nearly 2000 people living with HIV residents were no longer living in DC between 2012 and 2016, with over 80% relocating to surrounding areas [21]. Further, this analysis found differences in relocation by race/ethnicity, gender identity, and mode of transmission, and those who moved out of DC were more likely to be male, black, between the ages of 30 and 39 years, and have a mode of HIV transmission of MSM [21].…”

Enhancing the ATra Black Box Matching Algorithm: Use of All Names for Deduplication Across Jurisdictions

“…The movement of people across jurisdictional boundaries poses challenges for a system designed to follow and support access to care for PWDH. [8][9][10] Several efforts have been deployed to assist in the deduplication of HIV cases across the NHSS, including regional data exchange exemplified in the metropolitan District of Columbia region, Maryland, and Virginia and the use of technology tools such as the ATra Black Box by these and other jurisdictions to deduplicate their eHARS case records and enhance the data quality of their case surveillance records.…”