Page 1 Page 2 Page 3 Page 4 Page 5 Page 6 Page 7 Page 8 Page 9 Page 10 Page 11 Page 12DATA POINTS: A Health Department Roadmap for Enhancing Data to Care Programs 10 Epidemiologists (CSTE), was designed to ensure that all cases are report- ed, but does not function well to track PLWH over time or to report all instances of HIV care. The existing na- tional de-duplication process, the Rou- tine Interstate Duplicate Review (RIDR), is time- and resource-intensive, oper- ates with a significant delay between case report and duplicate resolution, and most importantly is only invoked when there is a disagreement between jurisdictions on residence at initial diagnosis. RIDR therefore does not adequately serve as an effective tool to notify jurisdictions of migration or the existence of out-of- jurisdiction care. Georgetown University, working in partnership with the HIV surveillance programs in the District of Columbia, Maryland, and Virginia developed and piloted a novel and privacy-sensitive method to identify HIV cases across the cross-jurisdictional Washington, D.C. metropolitan area that can be used to better measure the continuum of care and cross-jurisdiction migra- tion, and provide health departments with up-to-date data for public health action. For the pilot, this collabora- tive team developed a deterministic ~1,000-lines algorithm, including a person-matching system with Enhanced HIV/AIDS Reporting System (eHARS) variables. The HIV surveillance programs had not previously identified approximately half of the “Black Box” matches and over 99% of those matches were deemed acceptable during validation. These results demonstrate the large amount of information missing to any one jurisdiction on cross-jurisdictional cases and care. These matches have already made direct and positive impacts on public health practices within each HIV sur- veillance division, including: • Provided justification for detailed data exchanges • Provided opportunity to update vital HIV surveillance data • Provided an expanded opportunity to link HIV surveillance data to out- reach and care efforts within public health departments • Provided updates to addresses for PLWH so they can be classified into jurisdictions where they are cur- rently residing Data sharing and security agreements among the jurisdictions were estab- lished for this project. Examples of these are provided in the resources section. Virginia Resources: Article on Black Box Pilot Please go to NASTAD’s Online Technical Assis- tance Platform (OnTAP) for examples of data sharing agreements. DoesD2CWork? Because many health departments have found low rates of persons not in care after investigating the NIC list that they produce from their surveillance registry, it is important to build evalua- tion of the D2C process and outcomes into the D2C program so that NIC lists increasingly improve. Keep in mind the goal: producing increasingly accu- rate and useful NIC lists that can be prioritized for follow-up. When health departments use a data source, for example, to identify or locate persons not in care, they should evaluate its usefulness early on to improve upon it, eliminate it, or continue to use it without making changes. Studies on the effectiveness of D2C are limited at this point. Seattle con- cluded that the D2C strategy in their jurisdiction may not be more effective than no intervention for people to return to care. Their analysis was quite preliminary but underscores the need to evaluate the process as it is being implemented. Both process and out- come evaluation are useful and there is a discussion of D2C evaluation in the CDC’s D2C toolkit. CDC emphasizes that D2C is only one HIV prevention tool that should be one part of a health department’s comprehensive strategy for linkage and re-engagement in care activities. D2C is a time-intensive strategy that requires adequate staffing to be effec- tive. When evaluating D2C activities it is also important to keep in mind that although the HIV surveillance system is a critical source of data, the system must have complete laboratory re- porting in place (> 95% lab reporting) and consistently maintain high-quality surveillance data in order for D2C to work. Along with the materials in the CDC toolkit consider including relevant process and outcome measures that are directly relevant to improving your specific D2C process and improving the outcome. Health departments need to continually observe and mea- sure whether the processes they are using are yielding information they can actually use and that they are adjust- ing their processes as they implement their program. Health departments need not invest in a process that is traditionally done if it doesn’t efficient- ly provide information they can use for real-time public health action. When selecting outcome indicators, keep in mind the overall goal of the program and which outcomes will lead to reach- ing that goal. Overall, the goal of D2C is to increase the number of PLWH who are diagnosed, in care and, most importantly, have undetectable levels of HIV. A useful way to measure that is by producing an HIV care continuum and recalculating it annually and by different demographic and behavioral groups to measure where they need to focus their efforts. For examples of state-specific HIV care continuums please see Michigan, Tennessee, and Texas. Before using process and outcome indicators, discuss specifically how to measure them. Two important ques- tions are (1) what specific measure makes sense for the health department and (2) do they have the data to mea- sure that outcome. For example, how do they measure retention in care? What time period do they use and do they have the data to answer the questions. Health departments should not be afraid to change these defini- tions as they work with them if they don’t make sense or aren’t giving them information they need to improve their D2C program.