1. Developmental Work Toward Implementation of a Master Patient Index Technical Perspectives and Lessons Learned from North Carolina “Working for a healthier and safer North Carolina” Delbert Williams & Tara Riley-Williams

2. Integration of Surveillance and Public Health Programmatic Activities Delbert Williams Communicable Disease Surveillance Unit North Carolina Division of Public Health

3.  Previous presentations in this series have outlined how surveillance activities are already or may be integrated  Highlight what NC has tried to do as a result integration to improve public health practice(s) Purpose

4. Timeline

5. NC Data availability  All reportable disease surveillance activities are in one administrative unit HIV and other STDs Hepatitis B & C Vaccine Preventable Diseases Rabies Foodborne, vectorborne & waterborne diseases Zoonotics TB Syndromic surveillance (Biosense)

6. I’ve got this data, now what?  Use of HIV/AIDS surveillance data for descriptive purposes at a state or local level  Use of surveillance data for HIV Prevention Planning (Community Planning)  Integration of HIV Prevention Community Planning and Ryan White CARE Planning  HIV surveillance data for CDC funding  HIV surveillance data for HRSA funding  HIV surveillance data to assist in case management

7. Partner Services (PN)  NC approach to using HIV reporting to surveillance to link to partner services previously described  Multifaceted implementation of services includes more than traditional partner notification or contact tracing  DIS also offer “value added” in feeding information back to the surveillance office

8. Laboratory  Close partnership with our State Public Health Laboratory Both SLPH and CD are agencies within the Epidemiology Section of NC DPH Surveillance and Field staff assist with priority contacts for repeat specimen collections  Surveillance office is primary contact point for the acute HIV program linking laboratory notification directly to DIS for patient follow-up and medical evaluation for persons who are likely to be in the acute HIV infection stage

9. HRSA  Linkage with the Ryan White Program Evaluation of unmet need ADAP database Medicaid database CAREWARE  Assisted in discussions with NC Legislature to fund ADAP at 250% of FPL and now at 300%

10. HIV Prevention  CTS/PEMS  Additional special projects that can provide substantial information related to special populations Jail screening Targeted testing

11. Current Status of NC EDSS  The North Carolina Electronic Disease Surveillance System is in the final stages of design and implementation (development of the enhanced system started in January 2006)  Twenty-three counties are currently using NC EDSS for TB surveillance, monitoring DOT and TST (skin tests). An additional 11 counties have trainings planned for TB implementation  The first pilot for general communicable disease and bacterial STD reporting was in March of 2008  Seventy counties are using NC EDSS for CD and bacterial STD reporting

12. Implementation Progress

13. NC EDSS MPI Conversion, Implementation, Maintenance, & Lessons Learned Tara Riley-Williams Communicable Disease Surveillance Unit North Carolina Division of Public Health

14. MPI Scope Overview

15. MPI Scope Details 1.TIMS, NETSS, STD*MIS, eHARS data converted (excluding unnamed data) 2.LTBI : Point forward data only 3.Phased Implementation = Phased MPI Development 4.Event based data was de-duplicated within each converted system 5.Converted data de-duplicated against NC EDSS data in each phase.

16. MPI Development Rules and Approach 1.Person duplicates evaluated within each converted source system first. 2.Person duplicate clean up done in source system prior to conversion (to extent possible) 3.Phased Implementation = Phased MPI Development 4.Persons de-duplicated within each converted system 5.Converted data de-duplicated against NC EDSS data in each phase.

17. MPI Development Rules and Approach 6.Core team assigned to person de-duplication 7.Team evaluated suspect duplicated persons in test converted data 8.Team established consistent rules for determining if persons were the same or different 9.Team evaluated system person match results - suspect versus exact match 10.Team evaluated electronic laboratory result suspect and exact match results separately 11.Note: Converted events were not de-duplicated

18. MPI Match Rules Name - First & Last used, full and soundex versions, two last names matched exactly and inverted SSN – Used if present, exact only DOB – Exact, inversions, and year “off” Address – Exact, partial, and numerical portions only matching levels Sex and race are not currently included Configurable weights are assigned to each match criteria and level to determine a score for exact and suspect matches ELR match rules – redistribute address match weights if address is completely missing

19. MPI Maintenance Converted data de-duplicated before local roll out by special team Person de-duplication of ELR suspects performed by those with security to see all events De-duplication workflows addressed each a.m. Local users alerted to suspect duplicate people upon disease entry but can only see events for which they have permission Events pending de-duplication clearly marked that this action is pending resolution Phased implementation requires iterative conversion de-duplication activites

20. MPI Development Lessons Learned 1.De-duplication within each source system key to overall conversion success 2.Consistent rules for de-duplication are critical 3.Better to keep persons separate when in doubt 4.Essential to evaluate person match success for each ELR laboratory with real data before implementing 5.Different match rules are needed for ELR data than manually entered data 6.Essential to automatically resubmit persons to match rules when any demographic data changes 7.Essential to present to the user as much data as possible when making the match decision