Data De-Duplication in DATIM

Transcription

1 Data De-Duplication in Concept and Implementation

2 De-Duplication Overview Background De-Duplication in PEPFAR De-Duplication in De-Duplication Logic Standardizing De-Duplication Efforts 2

3 A Brief History of Duplication The numbers don t add up PEPFAR totals vs. National results Same Things, Same Place, Same Time I did this vs. We did this Partners report individual accomplishments Programs report aggregate, unique results Double-counting vs. Service Overlaps Sometimes it s simple (2 partners, exact same clients) Sometimes it s complex (overlapping community interventions across populations, geographic areas) Program Accountability 3

4 De-Duplication in PEPFAR I & II PEPFAR To Date: De-Duplicate Results at Technical Area Level Only Map Partners, Services, Indicators Add up results Compare to other data sources (MOH national results, Global Fund reporting, etc.) Exclude, extrapolate, estimate Report single, OU-level results by indicator with narrative description of any de-duplication efforts 4

5 De-Duplication in Going Forward: De-Duplicate Results at Site Level Receive site-level data from IPs Review, Approve, Submit data to Interagency Interagency (SI, PCO) use Data De-Duplication App to review duplicates by site/indicator Select standard de-duplication logic where applicable Address unique/contextual duplication or overlap issues at site level case by case Review and address DSD-TA crosswalk overlaps Submit to HQ 5

6 Defining De-Duplication Terms Pure/Normal/Simple De-Duplication: All DSD- DSD or TA-TA duplicate (or differing) valuesto be addressed within DSD-TA Crosswalk/Complex De-Duplication: When multiple partners report DSD and TA results at the same site, which double-counts patients/beneficiaries across DSD and TA results; revise TA value within 6

7 Standard De-Duplication Logic SUM: Add all IM results together at site level (No Duplication of clients by IMs) MAX: Across all IMs, report the highest reported value of each indicator/disaggregation at the site level (Full or Broad Duplication of clients by IMs) CUSTOM: Across all IMs, report a custom value at the site level based on contextual or known programmatic factors (Partial Duplication of clients by IMs) 7

8 Site-Level Simple Duplication Scenarios: Community Partners 8

9 OVC_SERV Community De-Duplication Scenario 1: No Duplication (SUM) DISTRICT X VILLAGE B (Intervention Point) Total OVC_SERV Active Beneficiaries PARTNER 2: 30 (Case Management) VILLAGE A (Intervention Point) VILLAGE C (Intervention Point) PARTNER 1: 30 (Case Management) PARTNER 3: 30 (Case Management)

10 OVC_SERV Community De-Duplication Scenario 2: Broad Duplication (MAX) DISTRICT X PARTNER 2: 60 (Psychosocial Support) VILLAGE B (Intervention Point) Total OVC_SERV Active Beneficiaries VILLAGE A (Intervention Point) VILLAGE C (Intervention Point) PARTNER 1: 30 (IGA Partner) PARTNER 3: 90 (Case Management)

11 OVC_SERV Community De-Duplication Scenario 3: Full Duplication (MAX) DISTRICT X PARTNER 2: 90 (Psychosocial Support) VILLAGE B (Intervention Point) Total OVC_SERV Active Beneficiaries VILLAGE A (Intervention Point) VILLAGE C (Intervention Point) PARTNER 1: 90 (IGA Partner) PARTNER 3: 90 (Case Management)

12 OVC_SERV Community De-Duplication Scenario 4: Partial Duplication (CUSTOM) DISTRICT X PARTNER 2: 60 (Psychosocial Support) VILLAGE B (Intervention Point) Total OVC_SERV Active Beneficiaries 50% Overlap 90 VILLAGE A (Intervention Point) VILLAGE C (Intervention Point) PARTNER 1: 60 (IGA Partner) PARTNER 3: 60 (Education, Child Protection)

13 Site-Level Simple Duplication Scenarios: Clinical Facility Partners 13

14 TX_CURR Facility De-Duplication Scenario 1: Full Duplication (MAX) SITE X TOTAL NUMBER OF ART CLIENTS N = 90 Total TX_CURR_DSD Current on Treatment PARTNER 1: 90 Clients PARTNER 2: 90 Clients

15 TX_CURR Facility De-Duplication Scenario 2: Broad Duplication (MAX) SITE X TOTAL NUMBER OF ART CLIENTS N = 90 Total TX_CURR_DSD Current on Treatment PARTNER 1: 90 Clients PARTNER 2: 50 Clients

16 TX_CURR Facility De-Duplication Scenario 3: Partial Duplication (CUSTOM) SITE X PARTNER 1: 60 Clients TOTAL NUMBER OF ART CLIENTS N = 90 Total TX_CURR_DSD Current on Treatment 25% Assumed Overlap 90 PARTNER 2: 60 Clients

17 TX_CURR Facility De-Duplication Scenario 4: No Duplication (SUM) SITE X PARTNER 1: 45 Clients TOTAL NUMBER OF ART CLIENTS N = 90 Total TX_CURR_DSD Current on Treatment PARTNER 2: 45 Clients

18 DSD-TA Crosswalk Duplication Scenarios: Some Illustrations 18

19 General Principles: 1. De-duplicated MER DSD + TA results = Total unique patients/beneficiaries in country 2. DSD results prioritized over duplicateta results for partners reporting the same results 3. In these duplication cases, TA value must be determined by user (zero? non-zero?) 19

20 TX_CURR_DSD vs. TX_CURR_TA Scenario 1: Full Duplication (TA=0) SITE X TOTAL NUMBER OF ART CLIENTS N = 90 TX_CURR_DSD & TX_CURR_TA Current on Treatment 90 DSD cancels out 90 TA 90 DSD 0 TA (90 total) PARTNER 1: Service Delivery 90 DSD Clients Quarterly Monitoring + HCW Salary PARTNER 2: QI for Retention 90 TA Clients Quarterly Monitoring Only

21 TX_CURR_DSD vs. TX_CURR_TA Scenario 2: Duplication, DSD > TA (TA=0) SITE X TOTAL NUMBER OF ART CLIENTS N = 90 TX_CURR_DSD & TX_CURR_TA Current on Treatment 90 DSD cancels 50 TA 90 DSD 0 TA (90 total) PARTNER 1: Service Delivery 90 DSD Clients Quarterly Monitoring & ARVs PARTNER 2: QI for Retention 50 TA Clients Quarterly Monitoring Only

22 TX_CURR_DSD vs. TX_CURR_TA Scenario 3: Duplication, TA > DSD (CUSTOM) SITE X PARTNER 1: Service Delivery 50 DSD Clients Quarterly Monitoring & ARVs TOTAL NUMBER OF ART CLIENTS N = 90 PARTNER 2: QI Partner 90 TA Clients Quarterly Monitoring Only TX_CURR_DSD & TX_CURR_TA Current on Treatment 50 DSD, (90 TA 50 DSD) = 40 TA 50 DSD 40 TA (90 total)

23 Simple De-Duplication Logic SUM: MAX: CUSTOM: 23

24 DSD-TA Crosswalk De-Duplication Enter TA value that appropriately de-duplicates the DSD-TA Crosswalk Indicator total 24

25 Why Standardize De-Duplication? Allows PEPFAR to simplify and normalize duplication handling globally Enforces accountability and auditability for de-duplication logic/decision-making Preservespartner-level data without source modifications requires standard rules & logic 25

26 What happens inside/outside? Identify pure duplicates in across IMs and agencies Review and confer with Activity Managers, TWGs, Partners Choose de-duplication approach by policy and/or case by case Remediate pure duplicates in Review, confer,& remediate crosswalk duplicates in De-Duplication App 26

27 Data De-Duplication App Live Demonstration 27

28 Questions? 28