October 2–5, 2007  Lusaka, Zambia

1. STRATEGIES FOR BUILDING NATIONAL-SCALE LONGITUDINAL ELECTRONIC PATIENT MONITORING SYSTEMS FOR HIV TREATMENT AND CARE IN PEPFAR COUNTRIES October 2–5, 2007 Lusaka, Zambia

2. Unique Patient Identifiers – 2 Suzanne Cloutier, MSPH Informatics Consultant – BOTUSA 2

3. Overview Unique Patient ID Guidelines Site Specific ID National ID Data Quality Issues Matching Records 3

4. Unique Patient ID Guidelines • ASTM Conceptual Characteristics • Functional Characteristics • Accessible, Assignable, Identifiable, Verifiable, Mergeable, Splittable • Linkage of Lifelong Health Record • Linkable, Mappable • Patient Confidentiality and Security • Content Free, Controllable, Healthcare Focused, Secure, Disidentifiable, Public 4

5. Unique Patient ID Guidelines • ASTM Conceptual Characteristics • Compatibility with Standards and Technology • Based on Industry Standards, Deployable, Usable • Design Characteristics • Unique, Repository-based, Atomic, Concise, Unambiguous, Permanent, Centrally Governed, Networked, Longevity, Retroactive, Universal, Incremental Implementation • Reduction of Cost and Enhanced Health Status • Cost-effectiveness 5

6. Unique Patient ID Guidelines • HHS Report – Analysis of Unique Patient Identifier Options • Basic functional requirements • Identification of individuals • Identification of information • Support the protection of privacy, confidentiality, and security • Improve health status and help reduce cost through enhanced access to information and care 6

7. Unique Patient ID Guidelines • HHS Report – Analysis of Unique Patient Identifier Options • Components of unique patient identifiers • Identifier • Patient identification (demographic) information • Index • Protection of patient identity (encryption) • Technology infrastructure to search, identify, match, etc. • Administrative infrastructure 7

8. Site Specific ID • Characteristics • Patient ID is issued and maintained by the site • Generally sites are not linked • Different numbering systems may be used by different programs • Consecutive sequence # assigned at point of service • Assign sequence # within a range, e.g. 1000-1999, etc. • Composite ID that includes existing codes • district code + facility code + year + sequence # 8

9. Site Specific IDs • Botswana Situation • IPMS assign a CM # • Sequential # • PIMS assigns a Masa # • Sequential # per facility • TB systems use a composite ID • VCT also uses a composite ID 9

10. Site Specific ID • Disadvantages • Patient ID may be unique only at the issuing site • Patients may have more than 1 ID per program • Patients may have more than 1 ID per site • Very difficult to link patient records • Only opportunity to identify and fix duplicate records is at a higher level • Need to include other identification information to match patients 10

11. National ID • Characteristics • ID is issued and maintained centrally • Generally, only 1 ID per person • Ideally assigned at birth, i.e. cradle to grave • Uniquely identifies a person across multiple organizations, programs, sites, etc. • Allows linkage of information for a lifelong view of a person’s history • Protects privacy and confidentiality 11

12. Data Quality • Data integrity problems with Omang # • Incorrect data entry • Nonexistent Omang #s • Duplicate Omang #s • Misuse of Omang # • Sharing • Using a dead person’s Omang # • Nonuse of Omang # 12

13. Gender Errors in Omang #

14. Data Quality Patients who initiated ART after death

15. Matching Records • National ID not the silver bullet • Must include whatever patient identification information is available • Deterministic vs. Probabilistic Matching • Deterministic – smaller data sets, fewer attributes, and less complex rules • Probabilistic matching – large data sets, large number of variables, real-time, higher accuracy 15

16. Matching Challenges

17. Probabilistic Matching • Requirements • Utilize proven probabilistic algorithms that score and match data across data elements using likelihood statistical theory for accuracy • Support multiple matching score thresholds to allow for customization • Function as an independent portable module, i.e. it must not require programming code to be embedded in source systems or source data to be modified 17

18. Probabilistic Matching Schumacher Scott, Probabilistic Versus Deterministic Data Matching: Making an Accurate Decision. Available at http://www.dmreview.com/article_sub.cfm?articleID=1071712. Accessed June 2007. • Requirements • Use source data in original form and maintain complete historical versioning • Support prioritization and resolution of data errors and ambiguous linkages • Offer role-based security access down to attribute level 18

19. Matching Records • Proof of Concept of Bateleur Software • Evaluate Identity Search Server (ISS) • Prepare sample data with known linkages • Install product on SQL Server and run against existing data • Evaluate the results • Purchase the software 19

20. Thank You! Thank You! Thank You! Thank You! Thank You! 20