OVC_HIVSTAT and Linkages to Care for Strengthened Collection, Analysis, and Use of Routine Health Data

MEASURE Evaluation
MEASURE EvaluationMEASURE Evaluation works to improve collection, analysis and presentation of data to promote better use of data in planning, policymaking, managing, monitoring and evaluating population, health and nutrition programs.
OVC_HIVSTAT and
Linkages to Care
for Strengthened Collection, Analysis,
and Use of Routine Health Data
Jenny Mwanza, MPH
Kristen Brugh, PhD
Lisa Parker, PhD
MEASURE Evaluation
Erin Schelar, MPH, RN
Amy Aberra, MPH
USAID Washington
March 14, 2018
Global Webinar for PEPFAR OVC
Programs
Global, five-year, $232M cooperative agreement
6 partners, led by the University of North Carolina at Chapel Hill
Strategic objective:
Strengthen capacity in developing countries to gather, interpret, and
use data to improve health
MEASURE Evaluation Overview
2
2
Local Partners and Capacity
Building Are Key
 Prime: UNC-CH and partners:
 ICF
 John Snow, Inc.
 Management Sciences for Health
 Palladium
 Tulane University
 MEASURE Evaluation works with more than 72
smaller sub-awardees in over 27 countries
 Over 26 percent of project funding goes back
to minor sub-awardees
3
Global Footprint (more than 40 countries)
4
4
Outline of the Webinar
1. Introduction
2. HIV risk assessment
3. Data analysis and use
4. Recommendations
5
Introduction
6
Activity Objectives
1. Strengthen data collection and management for
reporting on OVC_HIVSTAT
2. Improve tracking of the OVC platform’s
contributions to 95-95-95
7
Activity Deliverables
1. Webinar for all global OVC programs to improve reporting of
OVC_HIVSTAT data for FY18 Q2
2. Study Report to expand upon webinar and will include examples
of best practices
3. Technical assistance for implementing partners who participated in
the study to strengthen their M&E systems in order to improve
collection, analysis and use of OVC_HIVSTAT
4. HIV Risk Assessment Prototype to provide a structure for the
data collection tool that enables high-quality data
collection on risk behaviors for children and adolescents*
*Theprototypewillnotprovideguidance on thetypesofquestionstoinclude
8
Webinar Objectives
1. Clarify rationale for collecting OVC_HIVSTAT data
2. Explain the HIV Risk Assessment cascade and how it is
related to OVC_HIVSTAT disaggregates
3. Demonstrate how OVC_HIVSTAT data can be
analyzed to enhance program outcomes
4. Provide recommendations on how to revise and
implement HIV Risk Assessment
9
Background
• OVC_HIVSTAT data was requested by PEPFAR in FY2017 Quarter 2
with the aim of strengthening the role of OVC programs to identify
children at risk for HIV infection, ensure they are tested, and link
them to care and treatment.
• Performance, data quality, and contextual factors were considered
to select three countries (South Africa, Côte d’Ivoire, and
Zimbabwe) for in-depth study.
• A total of six implementing partners across three countries were
visited between November 2017 and February 2018; 32
qualitative interviews were conducted and over 60 community
volunteers participated in workshops.
• HIV risk assessments, indicator reference sheets, and standard
operating procedures were collected from each implementing
partner.
10
Rationale for OVC_HIVSTAT
1. Implementing partners should assess the HIV risk of OVC
enrolled in their programs in order to focus HIV
counseling and testing services on those OVC determined
to be most at risk for HIV infection.
2. Implementing partners should track whether OVC who
report to be HIV positive are successfully linked to and
retained in treatment and care.
11
HIV risk assessment
12
DATIM
DSD: OVC_HIVSTAT: Total
Auto-calculated
Number of OVC with HIV status reported to implementing partner
(including status not reported).
Numerator will auto-calculate from Status Type Disaggregate.
Numerator
Required Disaggregated by Status Type
Reported HIV positive to IP (includes tested in
the reporting period and known positive)
Of those positive: Currently receiving ART
Of those positive: Not Currently receiving ART
Reported HIV Negative to IP
No HIV status reported to the implementing
partner
Of those not reported: Test not indicated
Of those not reported: Other Reasons
13
Assessment Cascade
2. Conduct
HIV Risk
Assessment
1. Register
OVC & elicit
HIV status
3. Refer at-risk
children to
testing
4. Elicit test
result &
document
14
HIV Unknown – Other Reasons
At Risk
Not at
Risk
Refuse
assess
2. Conduct
HIV Risk
Assessment
1. Register
OVC & elicit
HIV status
HIV +
not on
ART
HIV +
on
ART
HIV
Un-
known
HIV
Neg
HIV +
HIV
Referral
Referral
com-
plete
3. Refer at-risk
children to
testing
4. Elicit test
result &
document
HIV +
not on
ART
HIV +
on
ART
Refuse
Report
HIV
Neg
HIV +
At the end of a reporting period,
any OVC recorded in one of the red boxes (A + B + C+ D +E +F)
in the MIS database, should be reported in DATIM as
“HIV Unknown – Other Reasons”
A
B
C
D
E
F
Stop
StopStop
Stop
Stop
StopStop
15
MIS Database Fields
HIV
Assessment
1. HIV positive
2. HIV positive on ART
3. HIV positive not on ART
4. HIV negative
5. HIV unknown
6. HIV unknown – test not indicated
7. HIV unknown – other reasons
1. At risk
2. Not at risk
HIV Test
Referral
1. Referral made
2. Referral completed
3. Refuse self-report
HIV status
16
Required Suggested
Challenges
Data collection tool
• Risk assessment questions can be confusing
• Outcomes of “At Risk” and “Not at Risk” are not clearly labeled
• Next steps related to HIV test referral are often missing
Record of new test results
• Community workers often hesitate to record HIV-positive test results
• HIV-negative test results are often not recorded at all
• Inconsistent linkage between the paper forms and MIS database
Update of HIV treatment status
• Despite strong documentation of ART treatment status at enrollment, there
was weak documentation of HIV treatment status at 6-month intervals
17
Data Quality Controls
Data entry clerks record
• HIV Unknown – At Risk
• HIV Unknown – Test Not
Indicated
Community volunteers apply HIV
Risk Assessment with guardians to
determine if child displays HIV risk
factors
These risk factors are
recorded on a paper
data collection tool; the
results should be clearly
documented
In a data quality audit,
we must be able to
observe these
outcomes on the
individual child’s form
In a contact trace and verify
exercise, the guardian may be re-
interviewed to determine if the
child displays the same risk factors
1.
2.
3.
4.
5.
18
Data analysis and use
19
Sample performance feedback
on process indicators
20
OVC_HIVSTAT Logic Model
Input Outcome Impact
High-quality
collection forms
Robust
database
Technical
capacity
Standard
Operating
Procedures
95% of all
people living
with HIV will
know their HIV
status
Process
% of unknown
who have been
assessed
% of “at risk”
who have been
referred
% of referrals
completed 95% of all HIV
positive people
on ART (2)
% of HIV
positive with
updated Tx
% of HIV
positive OVC
currently on
ART (1)
% of OVC for
whom HIV
status is known
or test is not
indicated
(1) OVC programs measure self-reported ART treatment status
(2) Point of care data measures actual ART adherence
21
Assessment Cascade
Overview
*These de-aggregates are not reported via DATIM;
these “dummy” data are presented to demonstrate how MIS data can be used to strengthen internal performance
management of IPs and narrative sections of reporting to USAID
22
Assessment Cascade
How to identify high performers?
23
HIV Risk Assessment
% of unknown who were assessed
24
Pre-test Counseling
% of at risk who were referred
25
Support for Testing
% of referrals completed
26
ART Treatment Support
% of HIV positive w/ updated Tx
27
Process Indicators
• We notice that children are “lost” at each stage of the
assessment cascade.
• Therefore, we recommend that all MIS databases collect
these information for internal performance monitoring to
target supervision and conduct ongoing training.
• Although process indicator data will not be reported via
DATIM, we suggest that there is a direct link between
process indicators and outcome indicators.
• IPs should share feedback on process indicators to both
sub-recipients in the field as well Mission focal points/HQ
in the narrative sections of their bi-annual reports.
28
Sample performance feedback
on outcome indicators
29
HIV Status
We seek to diminish
HIV Unknown – Other Reasons
through HIV assessment and testing
30
HIV Status by District
31
Outcome Indicator
% of OVC with Known HIV Status or TNI
HIV Positive + HIV Negative + Test Not Indicated
OVC_SERV <18
32
Global OVC Programs
61% of OVC with Known HIV Status
or Test Not Indicated (FY17Q4)
33
Global OVC Programs
HIV Positive, HIV Negative, HIV Unknown – Test
Not Indicated & OVC_SERV
34
Global OVC Programs
Close-up of Kenya and Zimbabwe
• Kenya has strong
performance because
they have tested a
large proportion of
their OVC_SERV
population.
• On the other hand,
Zimbabwe shows large
numbers of children
who have been
assessed and
determined “test not
indicated.”
35
Global OVC Programs
89% HIV-positive OVC on ART (FY17Q4)*
*These data probably best measure linkage to treatment
and exclude self-reported adherence
36
Recommendations for
implementing partners
37
Recommendations (1)
1. Include risk factors which require testing; if any one risk factor is
met then the child would be referred for HIV testing.
2. Track the outcomes of “At Risk” and “Not at Risk” on the form
3. Track testing referral and completion for “At Risk” on the form
4. Track new HIV test results on the form (or elsewhere)
5. Ensure new HIV test results are entered into the MIS database
6. Ensure ART treatment status is collected regularly on the form (or
elsewhere)
to revise HIV Risk Assessment
(MEASURE Evaluation will be publishing HIV Risk Assessment Prototype
to strengthen M&E aspects of data collection)
38
Recommendations (2)
1. Integrate HIV Risk Assessment within household visits to
ensure sustainability
2. Use paper data collection tool during interview to
improve reliability of the data
3. Organize a training specifically on how to conduct the
HIV Risk Assessment
• Discuss each of the HIV risk factors
• Identify probing questions that are culturally
appropriate
• Do role-plays to explore different scenarios
to implement HIV Risk Assessment
39
Recommendations (3)
1. Implementing partners to provide regular
feedback on process indicators to sub-
recipients.
2. Implementing partners to establish internal
targets for outcome indicators
to use OVC_HIVSTAT data
Process Indicators
• % assessed of unknown
• % referred of at risk
• % referrals completed
• % HIV Tx status updated
Outcome Indicators
• % of OVC with known status
or Test Not Indicated
• % of HIV positive OVC
currently on ART
3. Sub-recipients to organize quarterly data analysis meetings to review progress
4. Sub-recipients to identify districts with weak performance and provide
supportive supervision and enhanced training.
5. Through regular analysis of data,
improve the linkage between risk
assessment, testing, and treatment.
40
Thank you!
To the tireless community
volunteers, M&E officers,
and leaders of
implementing partners
who continually strive to
improve linkages among
OVC populations and HIV
testing and treatment
from HIVSA, PACT, REVE,
MAVAMBO, HOSPAZ,
and FACT.
43
Acknowledgments
MEASURE Evaluation would like to thank Christine Fu, Amy
Aberra, and Erin Schelar of USAID/Washington, for their
continued support and insights into improving HIV Risk
Assessment of Orphans and Vulnerable children in PEPFAR
priority countries.
USAID Health Teams in South Africa, Côte d’Ivoire, and
Zimbabwe—Ambereen Jaffer, Anita Sampson, Brilliant
Nkomo, Collen Marawanyika, David Chikoka, Kathryn
Reichert, Lauren Murphy, Lucie Dagri, Mavis Boateng,
Naletsana Masango, Natalie Kruse-Levy, Samson Chidiya —
and Brenda Yamba from the Regional Office, provided
invaluable guidance and access to local implementing
partners.
44
This presentation was produced with the support of the United States Agency for
International Development (USAID) under the terms of MEASURE Evaluation
cooperative agreement AID-OAA-L-14-00004. MEASURE Evaluation is
implemented by the Carolina Population Center, University of North Carolina at
Chapel Hill in partnership with ICF International; John Snow, Inc.; Management
Sciences for Health; Palladium; and Tulane University. Views expressed are not
necessarily those of USAID or the United States government.
www.measureevaluation.org
1 of 43

Recommended

Sphere standards health response by
Sphere standards   health responseSphere standards   health response
Sphere standards health responsePrabir Chatterjee
1.5K views12 slides
Data management tools for monitoring, evaluation and learning—Options and ideas by
Data management tools for monitoring, evaluation and learning—Options and ideasData management tools for monitoring, evaluation and learning—Options and ideas
Data management tools for monitoring, evaluation and learning—Options and ideasILRI
2K views14 slides
Infosec Audit Lecture_4 by
Infosec Audit Lecture_4Infosec Audit Lecture_4
Infosec Audit Lecture_4Obrina Candra, CISA, ISMS-LA
4K views50 slides
Verbal autopsy by
Verbal autopsyVerbal autopsy
Verbal autopsyAmanBansal134
641 views62 slides
Honors Thesis Proposal by
Honors Thesis ProposalHonors Thesis Proposal
Honors Thesis Proposalbwetzell
3K views31 slides
Most sought after courses in nigeria by
Most sought after courses in nigeriaMost sought after courses in nigeria
Most sought after courses in nigeriastatisense
6.8K views33 slides

More Related Content

What's hot

national aids control program phase IV by
national aids control program phase IVnational aids control program phase IV
national aids control program phase IVArkadeb Kar
3.1K views74 slides
Data Demand and Use Workshop by
Data Demand and Use WorkshopData Demand and Use Workshop
Data Demand and Use WorkshopMEASURE Evaluation
1.3K views92 slides
Introduction to research data management; Lecture 01 for GRAD521 by
Introduction to research data management; Lecture 01 for GRAD521Introduction to research data management; Lecture 01 for GRAD521
Introduction to research data management; Lecture 01 for GRAD521Amanda Whitmire
1.9K views33 slides
Lessons learned in using process tracing for evaluation by
Lessons learned in using process tracing for evaluationLessons learned in using process tracing for evaluation
Lessons learned in using process tracing for evaluationMEASURE Evaluation
1.7K views54 slides
NIST presentation on RMF 2.0 / SP 800-37 rev. 2 by
NIST presentation on RMF 2.0 / SP 800-37 rev. 2NIST presentation on RMF 2.0 / SP 800-37 rev. 2
NIST presentation on RMF 2.0 / SP 800-37 rev. 2NetLockSmith
1.9K views38 slides
105 Common information security threats by
105 Common information security threats105 Common information security threats
105 Common information security threatsSsendiSamuel
267 views31 slides

What's hot(20)

national aids control program phase IV by Arkadeb Kar
national aids control program phase IVnational aids control program phase IV
national aids control program phase IV
Arkadeb Kar3.1K views
Introduction to research data management; Lecture 01 for GRAD521 by Amanda Whitmire
Introduction to research data management; Lecture 01 for GRAD521Introduction to research data management; Lecture 01 for GRAD521
Introduction to research data management; Lecture 01 for GRAD521
Amanda Whitmire1.9K views
Lessons learned in using process tracing for evaluation by MEASURE Evaluation
Lessons learned in using process tracing for evaluationLessons learned in using process tracing for evaluation
Lessons learned in using process tracing for evaluation
MEASURE Evaluation1.7K views
NIST presentation on RMF 2.0 / SP 800-37 rev. 2 by NetLockSmith
NIST presentation on RMF 2.0 / SP 800-37 rev. 2NIST presentation on RMF 2.0 / SP 800-37 rev. 2
NIST presentation on RMF 2.0 / SP 800-37 rev. 2
NetLockSmith 1.9K views
105 Common information security threats by SsendiSamuel
105 Common information security threats105 Common information security threats
105 Common information security threats
SsendiSamuel267 views
MEASURE Evaluation Data Quality Assessment Methodology and Tools by MEASURE Evaluation
MEASURE Evaluation Data Quality Assessment Methodology and ToolsMEASURE Evaluation Data Quality Assessment Methodology and Tools
MEASURE Evaluation Data Quality Assessment Methodology and Tools
MEASURE Evaluation9.6K views
Materi Prof. DR. Hinky Hindra Irawan Satari, dr., Sp.A(K), M.Trop.Paed (1).pdf by dewifebriananursari
Materi Prof. DR. Hinky Hindra Irawan Satari, dr., Sp.A(K), M.Trop.Paed (1).pdfMateri Prof. DR. Hinky Hindra Irawan Satari, dr., Sp.A(K), M.Trop.Paed (1).pdf
Materi Prof. DR. Hinky Hindra Irawan Satari, dr., Sp.A(K), M.Trop.Paed (1).pdf
Systematic Reviews: the process, quantitative, qualitative and mixed methods ... by healthlibaust2012
Systematic Reviews: the process, quantitative, qualitative and mixed methods ...Systematic Reviews: the process, quantitative, qualitative and mixed methods ...
Systematic Reviews: the process, quantitative, qualitative and mixed methods ...
healthlibaust201229.2K views
CDM_Process_Overview_Katalyst HLS by Katalyst HLS
CDM_Process_Overview_Katalyst HLSCDM_Process_Overview_Katalyst HLS
CDM_Process_Overview_Katalyst HLS
Katalyst HLS815 views
SOC 2 Compliance and Certification by ControlCase
SOC 2 Compliance and CertificationSOC 2 Compliance and Certification
SOC 2 Compliance and Certification
ControlCase3.4K views
community-needs-assessment-presentation.ppt by SoumyadipPradhan2
community-needs-assessment-presentation.pptcommunity-needs-assessment-presentation.ppt
community-needs-assessment-presentation.ppt
SoumyadipPradhan2341 views
INCLUSION AND EXCLUSION CRITERIA session ACRM.pptx by ACSRM
INCLUSION AND EXCLUSION CRITERIA session ACRM.pptxINCLUSION AND EXCLUSION CRITERIA session ACRM.pptx
INCLUSION AND EXCLUSION CRITERIA session ACRM.pptx
ACSRM369 views

Similar to OVC_HIVSTAT and Linkages to Care for Strengthened Collection, Analysis, and Use of Routine Health Data

JC2763_PopulationBasedSurveys_en by
JC2763_PopulationBasedSurveys_enJC2763_PopulationBasedSurveys_en
JC2763_PopulationBasedSurveys_enVelma Lopez
253 views110 slides
HIV Index Testing: The USAID DISCOVER-Health Project Experience in Zambia by
HIV Index Testing:  The USAID DISCOVER-Health Project Experience in Zambia HIV Index Testing:  The USAID DISCOVER-Health Project Experience in Zambia
HIV Index Testing: The USAID DISCOVER-Health Project Experience in Zambia JSI
944 views14 slides
Lessons Learned for Strengthening Early Infant Diagnosis of HIV Programs by
Lessons Learned for Strengthening Early Infant Diagnosis of HIV ProgramsLessons Learned for Strengthening Early Infant Diagnosis of HIV Programs
Lessons Learned for Strengthening Early Infant Diagnosis of HIV ProgramsHFG Project
1.1K views38 slides
Overview of HIV self-testing by
Overview of HIV self-testingOverview of HIV self-testing
Overview of HIV self-testingCarmen Figueroa
2K views47 slides
Overview Neel Reilley by
Overview Neel Reilley Overview Neel Reilley
Overview Neel Reilley HIV_STD_Partners_Meeting
193 views27 slides
2016 indicator reference guide at-risk infants tested for hiv by
2016 indicator reference guide   at-risk infants tested for hiv2016 indicator reference guide   at-risk infants tested for hiv
2016 indicator reference guide at-risk infants tested for hiv#GOMOJO, INC.
18 views3 slides

Similar to OVC_HIVSTAT and Linkages to Care for Strengthened Collection, Analysis, and Use of Routine Health Data(20)

JC2763_PopulationBasedSurveys_en by Velma Lopez
JC2763_PopulationBasedSurveys_enJC2763_PopulationBasedSurveys_en
JC2763_PopulationBasedSurveys_en
Velma Lopez253 views
HIV Index Testing: The USAID DISCOVER-Health Project Experience in Zambia by JSI
HIV Index Testing:  The USAID DISCOVER-Health Project Experience in Zambia HIV Index Testing:  The USAID DISCOVER-Health Project Experience in Zambia
HIV Index Testing: The USAID DISCOVER-Health Project Experience in Zambia
JSI 944 views
Lessons Learned for Strengthening Early Infant Diagnosis of HIV Programs by HFG Project
Lessons Learned for Strengthening Early Infant Diagnosis of HIV ProgramsLessons Learned for Strengthening Early Infant Diagnosis of HIV Programs
Lessons Learned for Strengthening Early Infant Diagnosis of HIV Programs
HFG Project1.1K views
2016 indicator reference guide at-risk infants tested for hiv by #GOMOJO, INC.
2016 indicator reference guide   at-risk infants tested for hiv2016 indicator reference guide   at-risk infants tested for hiv
2016 indicator reference guide at-risk infants tested for hiv
#GOMOJO, INC.18 views
8_2-Intro-to-IndicatorsFMEF.pdf by ssusere0ee1d
8_2-Intro-to-IndicatorsFMEF.pdf8_2-Intro-to-IndicatorsFMEF.pdf
8_2-Intro-to-IndicatorsFMEF.pdf
ssusere0ee1d3 views
resource-index-testing-epic-day1.pptx by WilsonKabwita1
resource-index-testing-epic-day1.pptxresource-index-testing-epic-day1.pptx
resource-index-testing-epic-day1.pptx
WilsonKabwita123 views
Where are we on HIV testing services - the achievements and the gaps by Cheryl Johnson
Where are we on HIV testing services - the achievements and the gapsWhere are we on HIV testing services - the achievements and the gaps
Where are we on HIV testing services - the achievements and the gaps
Cheryl Johnson564 views
M01 Introduction to EID and POC EID Testing.pptx by DagneBodena1
M01 Introduction to EID and POC EID Testing.pptxM01 Introduction to EID and POC EID Testing.pptx
M01 Introduction to EID and POC EID Testing.pptx
DagneBodena11 view
Health Education/Risk Reduction referrals to HIV testing in non-clinical sett... by CDC NPIN
Health Education/Risk Reduction referrals to HIV testing in non-clinical sett...Health Education/Risk Reduction referrals to HIV testing in non-clinical sett...
Health Education/Risk Reduction referrals to HIV testing in non-clinical sett...
CDC NPIN 295 views
JRM_2014_Report_Final by Asrade Abate
JRM_2014_Report_FinalJRM_2014_Report_Final
JRM_2014_Report_Final
Asrade Abate176 views
2016 indicator reference guide Prevention Services by #GOMOJO, INC.
2016 indicator reference guide Prevention Services2016 indicator reference guide Prevention Services
2016 indicator reference guide Prevention Services
#GOMOJO, INC.32 views
Cadth 2015 c4 symp 13 april 2015_vooght by CADTH Symposium
Cadth 2015 c4 symp 13 april 2015_vooghtCadth 2015 c4 symp 13 april 2015_vooght
Cadth 2015 c4 symp 13 april 2015_vooght
CADTH Symposium157 views

More from MEASURE Evaluation

Managing missing values in routinely reported data: One approach from the Dem... by
Managing missing values in routinely reported data: One approach from the Dem...Managing missing values in routinely reported data: One approach from the Dem...
Managing missing values in routinely reported data: One approach from the Dem...MEASURE Evaluation
1.6K views52 slides
Use of Routine Data for Economic Evaluations by
Use of Routine Data for Economic EvaluationsUse of Routine Data for Economic Evaluations
Use of Routine Data for Economic EvaluationsMEASURE Evaluation
1.1K views26 slides
Routine data use in evaluation: practical guidance by
Routine data use in evaluation: practical guidanceRoutine data use in evaluation: practical guidance
Routine data use in evaluation: practical guidanceMEASURE Evaluation
2.3K views40 slides
Tuberculosis/HIV Mobility Study: Objectives and Background by
Tuberculosis/HIV Mobility Study: Objectives and BackgroundTuberculosis/HIV Mobility Study: Objectives and Background
Tuberculosis/HIV Mobility Study: Objectives and BackgroundMEASURE Evaluation
779 views78 slides
How to improve the capabilities of health information systems to address emer... by
How to improve the capabilities of health information systems to address emer...How to improve the capabilities of health information systems to address emer...
How to improve the capabilities of health information systems to address emer...MEASURE Evaluation
906 views19 slides
LCI Evaluation Uganda Organizational Network Analysis by
LCI Evaluation Uganda Organizational Network AnalysisLCI Evaluation Uganda Organizational Network Analysis
LCI Evaluation Uganda Organizational Network AnalysisMEASURE Evaluation
625 views24 slides

More from MEASURE Evaluation(20)

Managing missing values in routinely reported data: One approach from the Dem... by MEASURE Evaluation
Managing missing values in routinely reported data: One approach from the Dem...Managing missing values in routinely reported data: One approach from the Dem...
Managing missing values in routinely reported data: One approach from the Dem...
MEASURE Evaluation1.6K views
Use of Routine Data for Economic Evaluations by MEASURE Evaluation
Use of Routine Data for Economic EvaluationsUse of Routine Data for Economic Evaluations
Use of Routine Data for Economic Evaluations
MEASURE Evaluation1.1K views
Routine data use in evaluation: practical guidance by MEASURE Evaluation
Routine data use in evaluation: practical guidanceRoutine data use in evaluation: practical guidance
Routine data use in evaluation: practical guidance
MEASURE Evaluation2.3K views
Tuberculosis/HIV Mobility Study: Objectives and Background by MEASURE Evaluation
Tuberculosis/HIV Mobility Study: Objectives and BackgroundTuberculosis/HIV Mobility Study: Objectives and Background
Tuberculosis/HIV Mobility Study: Objectives and Background
MEASURE Evaluation779 views
How to improve the capabilities of health information systems to address emer... by MEASURE Evaluation
How to improve the capabilities of health information systems to address emer...How to improve the capabilities of health information systems to address emer...
How to improve the capabilities of health information systems to address emer...
MEASURE Evaluation906 views
LCI Evaluation Uganda Organizational Network Analysis by MEASURE Evaluation
LCI Evaluation Uganda Organizational Network AnalysisLCI Evaluation Uganda Organizational Network Analysis
LCI Evaluation Uganda Organizational Network Analysis
MEASURE Evaluation625 views
Using Organizational Network Analysis to Plan and Evaluate Global Health Prog... by MEASURE Evaluation
Using Organizational Network Analysis to Plan and Evaluate Global Health Prog...Using Organizational Network Analysis to Plan and Evaluate Global Health Prog...
Using Organizational Network Analysis to Plan and Evaluate Global Health Prog...
MEASURE Evaluation633 views
Understanding Referral Networks for Adolescent Girls and Young Women by MEASURE Evaluation
Understanding Referral Networks for Adolescent Girls and Young WomenUnderstanding Referral Networks for Adolescent Girls and Young Women
Understanding Referral Networks for Adolescent Girls and Young Women
MEASURE Evaluation606 views
Data for Impact: Lessons Learned in Using the Ripple Effects Mapping Method by MEASURE Evaluation
Data for Impact: Lessons Learned in Using the Ripple Effects Mapping MethodData for Impact: Lessons Learned in Using the Ripple Effects Mapping Method
Data for Impact: Lessons Learned in Using the Ripple Effects Mapping Method
MEASURE Evaluation1.1K views
Development and Validation of a Reproductive Empowerment Scale by MEASURE Evaluation
Development and Validation of a Reproductive Empowerment ScaleDevelopment and Validation of a Reproductive Empowerment Scale
Development and Validation of a Reproductive Empowerment Scale
MEASURE Evaluation409 views
Sustaining the Impact: MEASURE Evaluation Conversation on Maternal and Child ... by MEASURE Evaluation
Sustaining the Impact: MEASURE Evaluation Conversation on Maternal and Child ...Sustaining the Impact: MEASURE Evaluation Conversation on Maternal and Child ...
Sustaining the Impact: MEASURE Evaluation Conversation on Maternal and Child ...
MEASURE Evaluation344 views
Using Most Significant Change in a Mixed-Methods Evaluation in Uganda by MEASURE Evaluation
Using Most Significant Change in a Mixed-Methods Evaluation in UgandaUsing Most Significant Change in a Mixed-Methods Evaluation in Uganda
Using Most Significant Change in a Mixed-Methods Evaluation in Uganda
MEASURE Evaluation491 views
Lessons Learned In Using the Most Significant Change Technique in Evaluation by MEASURE Evaluation
Lessons Learned In Using the Most Significant Change Technique in EvaluationLessons Learned In Using the Most Significant Change Technique in Evaluation
Lessons Learned In Using the Most Significant Change Technique in Evaluation
MEASURE Evaluation794 views
Malaria Data Quality and Use in Selected Centers of Excellence in Madagascar:... by MEASURE Evaluation
Malaria Data Quality and Use in Selected Centers of Excellence in Madagascar:...Malaria Data Quality and Use in Selected Centers of Excellence in Madagascar:...
Malaria Data Quality and Use in Selected Centers of Excellence in Madagascar:...
MEASURE Evaluation269 views
Evaluating National Malaria Programs’ Impact in Moderate- and Low-Transmissio... by MEASURE Evaluation
Evaluating National Malaria Programs’ Impact in Moderate- and Low-Transmissio...Evaluating National Malaria Programs’ Impact in Moderate- and Low-Transmissio...
Evaluating National Malaria Programs’ Impact in Moderate- and Low-Transmissio...
MEASURE Evaluation166 views
Improved Performance of the Malaria Surveillance, Monitoring, and Evaluation ... by MEASURE Evaluation
Improved Performance of the Malaria Surveillance, Monitoring, and Evaluation ...Improved Performance of the Malaria Surveillance, Monitoring, and Evaluation ...
Improved Performance of the Malaria Surveillance, Monitoring, and Evaluation ...
MEASURE Evaluation206 views
Use of Qualitative Comparative Analysis in the Assessment of the Actionable D... by MEASURE Evaluation
Use of Qualitative Comparative Analysis in the Assessment of the Actionable D...Use of Qualitative Comparative Analysis in the Assessment of the Actionable D...
Use of Qualitative Comparative Analysis in the Assessment of the Actionable D...
MEASURE Evaluation658 views
Sustaining the Impact: MEASURE Evaluation Conversation on Health Informatics by MEASURE Evaluation
Sustaining the Impact: MEASURE Evaluation Conversation on Health InformaticsSustaining the Impact: MEASURE Evaluation Conversation on Health Informatics
Sustaining the Impact: MEASURE Evaluation Conversation on Health Informatics
MEASURE Evaluation503 views
7 Steps to EnGendering Evaluations of HIV programs with Adolescent Girls and ... by MEASURE Evaluation
7 Steps to EnGendering Evaluations of HIV programs with Adolescent Girls and ...7 Steps to EnGendering Evaluations of HIV programs with Adolescent Girls and ...
7 Steps to EnGendering Evaluations of HIV programs with Adolescent Girls and ...
MEASURE Evaluation630 views

Recently uploaded

TQM ASSIGMENT 3.pdf by
TQM ASSIGMENT 3.pdfTQM ASSIGMENT 3.pdf
TQM ASSIGMENT 3.pdfد حاتم البيطار
8 views11 slides
Basic Life support (BLS) workshop presentation. by
Basic Life support (BLS) workshop presentation.Basic Life support (BLS) workshop presentation.
Basic Life support (BLS) workshop presentation.Dr Sanket Nandekar
33 views39 slides
Relationships Between Service Providers and Families by
Relationships Between Service Providers and FamiliesRelationships Between Service Providers and Families
Relationships Between Service Providers and FamiliesOlaf Kraus de Camargo
93 views22 slides
Taking Action to Improve the Patient Journey With Transthyretin Amyloidosis (... by
Taking Action to Improve the Patient Journey With Transthyretin Amyloidosis (...Taking Action to Improve the Patient Journey With Transthyretin Amyloidosis (...
Taking Action to Improve the Patient Journey With Transthyretin Amyloidosis (...PeerVoice
7 views23 slides
Top 10 Pharma Companies in Mumbai | Medibyte by
Top 10 Pharma Companies in Mumbai | MedibyteTop 10 Pharma Companies in Mumbai | Medibyte
Top 10 Pharma Companies in Mumbai | MedibyteMedibyte Pharma
17 views1 slide
Cholera Romy W. (3).pptx by
Cholera Romy W. (3).pptxCholera Romy W. (3).pptx
Cholera Romy W. (3).pptxrweth613
38 views11 slides

Recently uploaded(20)

Basic Life support (BLS) workshop presentation. by Dr Sanket Nandekar
Basic Life support (BLS) workshop presentation.Basic Life support (BLS) workshop presentation.
Basic Life support (BLS) workshop presentation.
Taking Action to Improve the Patient Journey With Transthyretin Amyloidosis (... by PeerVoice
Taking Action to Improve the Patient Journey With Transthyretin Amyloidosis (...Taking Action to Improve the Patient Journey With Transthyretin Amyloidosis (...
Taking Action to Improve the Patient Journey With Transthyretin Amyloidosis (...
PeerVoice7 views
Top 10 Pharma Companies in Mumbai | Medibyte by Medibyte Pharma
Top 10 Pharma Companies in Mumbai | MedibyteTop 10 Pharma Companies in Mumbai | Medibyte
Top 10 Pharma Companies in Mumbai | Medibyte
Medibyte Pharma17 views
Cholera Romy W. (3).pptx by rweth613
Cholera Romy W. (3).pptxCholera Romy W. (3).pptx
Cholera Romy W. (3).pptx
rweth61338 views
Pharma Franchise For Critical Care Medicine | Saphnix Lifesciences by Saphnix Lifesciences
Pharma Franchise For Critical Care Medicine | Saphnix LifesciencesPharma Franchise For Critical Care Medicine | Saphnix Lifesciences
Pharma Franchise For Critical Care Medicine | Saphnix Lifesciences
Taking Action to Improve the Patient Journey With Transthyretin Amyloidosis (... by PeerVoice
Taking Action to Improve the Patient Journey With Transthyretin Amyloidosis (...Taking Action to Improve the Patient Journey With Transthyretin Amyloidosis (...
Taking Action to Improve the Patient Journey With Transthyretin Amyloidosis (...
PeerVoice8 views
Top PCD Pharma Franchise Companies in India | Saphnix Lifesciences by Saphnix Lifesciences
Top PCD Pharma Franchise Companies in India | Saphnix LifesciencesTop PCD Pharma Franchise Companies in India | Saphnix Lifesciences
Top PCD Pharma Franchise Companies in India | Saphnix Lifesciences
Pregnancy tips.pptx by reachout7
Pregnancy tips.pptxPregnancy tips.pptx
Pregnancy tips.pptx
reachout740 views
CMC(CHEMISTRY,MANUFACTURING AND CONTROL).pptx by JubinNath2
CMC(CHEMISTRY,MANUFACTURING AND CONTROL).pptxCMC(CHEMISTRY,MANUFACTURING AND CONTROL).pptx
CMC(CHEMISTRY,MANUFACTURING AND CONTROL).pptx
JubinNath27 views
PATIENTCOUNSELLING in.pptx by skShashi1
PATIENTCOUNSELLING  in.pptxPATIENTCOUNSELLING  in.pptx
PATIENTCOUNSELLING in.pptx
skShashi116 views
melani glossophobia.pdf by Paygeon
melani glossophobia.pdfmelani glossophobia.pdf
melani glossophobia.pdf
Paygeon9 views
eTEP -RS Dr.TVR.pptx by Varunraju9
eTEP -RS Dr.TVR.pptxeTEP -RS Dr.TVR.pptx
eTEP -RS Dr.TVR.pptx
Varunraju9131 views
Blockchain based automatic diagnosis of the 12-lead ECG using a deep neural n... by RajaulKarim20
Blockchain based automatic diagnosis of the 12-lead ECG using a deep neural n...Blockchain based automatic diagnosis of the 12-lead ECG using a deep neural n...
Blockchain based automatic diagnosis of the 12-lead ECG using a deep neural n...
RajaulKarim2099 views
DEBATE IN CA BLADDER TMT VS CYSTECTOMY by Kanhu Charan
DEBATE IN CA BLADDER TMT VS CYSTECTOMYDEBATE IN CA BLADDER TMT VS CYSTECTOMY
DEBATE IN CA BLADDER TMT VS CYSTECTOMY
Kanhu Charan36 views
Complications & Solutions in Laparoscopic Hernia Surgery.pptx by Varunraju9
Complications & Solutions in Laparoscopic Hernia Surgery.pptxComplications & Solutions in Laparoscopic Hernia Surgery.pptx
Complications & Solutions in Laparoscopic Hernia Surgery.pptx
Varunraju9106 views

OVC_HIVSTAT and Linkages to Care for Strengthened Collection, Analysis, and Use of Routine Health Data

  • 1. OVC_HIVSTAT and Linkages to Care for Strengthened Collection, Analysis, and Use of Routine Health Data Jenny Mwanza, MPH Kristen Brugh, PhD Lisa Parker, PhD MEASURE Evaluation Erin Schelar, MPH, RN Amy Aberra, MPH USAID Washington March 14, 2018 Global Webinar for PEPFAR OVC Programs
  • 2. Global, five-year, $232M cooperative agreement 6 partners, led by the University of North Carolina at Chapel Hill Strategic objective: Strengthen capacity in developing countries to gather, interpret, and use data to improve health MEASURE Evaluation Overview 2 2
  • 3. Local Partners and Capacity Building Are Key  Prime: UNC-CH and partners:  ICF  John Snow, Inc.  Management Sciences for Health  Palladium  Tulane University  MEASURE Evaluation works with more than 72 smaller sub-awardees in over 27 countries  Over 26 percent of project funding goes back to minor sub-awardees 3
  • 4. Global Footprint (more than 40 countries) 4 4
  • 5. Outline of the Webinar 1. Introduction 2. HIV risk assessment 3. Data analysis and use 4. Recommendations 5
  • 7. Activity Objectives 1. Strengthen data collection and management for reporting on OVC_HIVSTAT 2. Improve tracking of the OVC platform’s contributions to 95-95-95 7
  • 8. Activity Deliverables 1. Webinar for all global OVC programs to improve reporting of OVC_HIVSTAT data for FY18 Q2 2. Study Report to expand upon webinar and will include examples of best practices 3. Technical assistance for implementing partners who participated in the study to strengthen their M&E systems in order to improve collection, analysis and use of OVC_HIVSTAT 4. HIV Risk Assessment Prototype to provide a structure for the data collection tool that enables high-quality data collection on risk behaviors for children and adolescents* *Theprototypewillnotprovideguidance on thetypesofquestionstoinclude 8
  • 9. Webinar Objectives 1. Clarify rationale for collecting OVC_HIVSTAT data 2. Explain the HIV Risk Assessment cascade and how it is related to OVC_HIVSTAT disaggregates 3. Demonstrate how OVC_HIVSTAT data can be analyzed to enhance program outcomes 4. Provide recommendations on how to revise and implement HIV Risk Assessment 9
  • 10. Background • OVC_HIVSTAT data was requested by PEPFAR in FY2017 Quarter 2 with the aim of strengthening the role of OVC programs to identify children at risk for HIV infection, ensure they are tested, and link them to care and treatment. • Performance, data quality, and contextual factors were considered to select three countries (South Africa, Côte d’Ivoire, and Zimbabwe) for in-depth study. • A total of six implementing partners across three countries were visited between November 2017 and February 2018; 32 qualitative interviews were conducted and over 60 community volunteers participated in workshops. • HIV risk assessments, indicator reference sheets, and standard operating procedures were collected from each implementing partner. 10
  • 11. Rationale for OVC_HIVSTAT 1. Implementing partners should assess the HIV risk of OVC enrolled in their programs in order to focus HIV counseling and testing services on those OVC determined to be most at risk for HIV infection. 2. Implementing partners should track whether OVC who report to be HIV positive are successfully linked to and retained in treatment and care. 11
  • 13. DATIM DSD: OVC_HIVSTAT: Total Auto-calculated Number of OVC with HIV status reported to implementing partner (including status not reported). Numerator will auto-calculate from Status Type Disaggregate. Numerator Required Disaggregated by Status Type Reported HIV positive to IP (includes tested in the reporting period and known positive) Of those positive: Currently receiving ART Of those positive: Not Currently receiving ART Reported HIV Negative to IP No HIV status reported to the implementing partner Of those not reported: Test not indicated Of those not reported: Other Reasons 13
  • 14. Assessment Cascade 2. Conduct HIV Risk Assessment 1. Register OVC & elicit HIV status 3. Refer at-risk children to testing 4. Elicit test result & document 14
  • 15. HIV Unknown – Other Reasons At Risk Not at Risk Refuse assess 2. Conduct HIV Risk Assessment 1. Register OVC & elicit HIV status HIV + not on ART HIV + on ART HIV Un- known HIV Neg HIV + HIV Referral Referral com- plete 3. Refer at-risk children to testing 4. Elicit test result & document HIV + not on ART HIV + on ART Refuse Report HIV Neg HIV + At the end of a reporting period, any OVC recorded in one of the red boxes (A + B + C+ D +E +F) in the MIS database, should be reported in DATIM as “HIV Unknown – Other Reasons” A B C D E F Stop StopStop Stop Stop StopStop 15
  • 16. MIS Database Fields HIV Assessment 1. HIV positive 2. HIV positive on ART 3. HIV positive not on ART 4. HIV negative 5. HIV unknown 6. HIV unknown – test not indicated 7. HIV unknown – other reasons 1. At risk 2. Not at risk HIV Test Referral 1. Referral made 2. Referral completed 3. Refuse self-report HIV status 16 Required Suggested
  • 17. Challenges Data collection tool • Risk assessment questions can be confusing • Outcomes of “At Risk” and “Not at Risk” are not clearly labeled • Next steps related to HIV test referral are often missing Record of new test results • Community workers often hesitate to record HIV-positive test results • HIV-negative test results are often not recorded at all • Inconsistent linkage between the paper forms and MIS database Update of HIV treatment status • Despite strong documentation of ART treatment status at enrollment, there was weak documentation of HIV treatment status at 6-month intervals 17
  • 18. Data Quality Controls Data entry clerks record • HIV Unknown – At Risk • HIV Unknown – Test Not Indicated Community volunteers apply HIV Risk Assessment with guardians to determine if child displays HIV risk factors These risk factors are recorded on a paper data collection tool; the results should be clearly documented In a data quality audit, we must be able to observe these outcomes on the individual child’s form In a contact trace and verify exercise, the guardian may be re- interviewed to determine if the child displays the same risk factors 1. 2. 3. 4. 5. 18
  • 20. Sample performance feedback on process indicators 20
  • 21. OVC_HIVSTAT Logic Model Input Outcome Impact High-quality collection forms Robust database Technical capacity Standard Operating Procedures 95% of all people living with HIV will know their HIV status Process % of unknown who have been assessed % of “at risk” who have been referred % of referrals completed 95% of all HIV positive people on ART (2) % of HIV positive with updated Tx % of HIV positive OVC currently on ART (1) % of OVC for whom HIV status is known or test is not indicated (1) OVC programs measure self-reported ART treatment status (2) Point of care data measures actual ART adherence 21
  • 22. Assessment Cascade Overview *These de-aggregates are not reported via DATIM; these “dummy” data are presented to demonstrate how MIS data can be used to strengthen internal performance management of IPs and narrative sections of reporting to USAID 22
  • 23. Assessment Cascade How to identify high performers? 23
  • 24. HIV Risk Assessment % of unknown who were assessed 24
  • 25. Pre-test Counseling % of at risk who were referred 25
  • 26. Support for Testing % of referrals completed 26
  • 27. ART Treatment Support % of HIV positive w/ updated Tx 27
  • 28. Process Indicators • We notice that children are “lost” at each stage of the assessment cascade. • Therefore, we recommend that all MIS databases collect these information for internal performance monitoring to target supervision and conduct ongoing training. • Although process indicator data will not be reported via DATIM, we suggest that there is a direct link between process indicators and outcome indicators. • IPs should share feedback on process indicators to both sub-recipients in the field as well Mission focal points/HQ in the narrative sections of their bi-annual reports. 28
  • 29. Sample performance feedback on outcome indicators 29
  • 30. HIV Status We seek to diminish HIV Unknown – Other Reasons through HIV assessment and testing 30
  • 31. HIV Status by District 31
  • 32. Outcome Indicator % of OVC with Known HIV Status or TNI HIV Positive + HIV Negative + Test Not Indicated OVC_SERV <18 32
  • 33. Global OVC Programs 61% of OVC with Known HIV Status or Test Not Indicated (FY17Q4) 33
  • 34. Global OVC Programs HIV Positive, HIV Negative, HIV Unknown – Test Not Indicated & OVC_SERV 34
  • 35. Global OVC Programs Close-up of Kenya and Zimbabwe • Kenya has strong performance because they have tested a large proportion of their OVC_SERV population. • On the other hand, Zimbabwe shows large numbers of children who have been assessed and determined “test not indicated.” 35
  • 36. Global OVC Programs 89% HIV-positive OVC on ART (FY17Q4)* *These data probably best measure linkage to treatment and exclude self-reported adherence 36
  • 38. Recommendations (1) 1. Include risk factors which require testing; if any one risk factor is met then the child would be referred for HIV testing. 2. Track the outcomes of “At Risk” and “Not at Risk” on the form 3. Track testing referral and completion for “At Risk” on the form 4. Track new HIV test results on the form (or elsewhere) 5. Ensure new HIV test results are entered into the MIS database 6. Ensure ART treatment status is collected regularly on the form (or elsewhere) to revise HIV Risk Assessment (MEASURE Evaluation will be publishing HIV Risk Assessment Prototype to strengthen M&E aspects of data collection) 38
  • 39. Recommendations (2) 1. Integrate HIV Risk Assessment within household visits to ensure sustainability 2. Use paper data collection tool during interview to improve reliability of the data 3. Organize a training specifically on how to conduct the HIV Risk Assessment • Discuss each of the HIV risk factors • Identify probing questions that are culturally appropriate • Do role-plays to explore different scenarios to implement HIV Risk Assessment 39
  • 40. Recommendations (3) 1. Implementing partners to provide regular feedback on process indicators to sub- recipients. 2. Implementing partners to establish internal targets for outcome indicators to use OVC_HIVSTAT data Process Indicators • % assessed of unknown • % referred of at risk • % referrals completed • % HIV Tx status updated Outcome Indicators • % of OVC with known status or Test Not Indicated • % of HIV positive OVC currently on ART 3. Sub-recipients to organize quarterly data analysis meetings to review progress 4. Sub-recipients to identify districts with weak performance and provide supportive supervision and enhanced training. 5. Through regular analysis of data, improve the linkage between risk assessment, testing, and treatment. 40
  • 41. Thank you! To the tireless community volunteers, M&E officers, and leaders of implementing partners who continually strive to improve linkages among OVC populations and HIV testing and treatment from HIVSA, PACT, REVE, MAVAMBO, HOSPAZ, and FACT. 43
  • 42. Acknowledgments MEASURE Evaluation would like to thank Christine Fu, Amy Aberra, and Erin Schelar of USAID/Washington, for their continued support and insights into improving HIV Risk Assessment of Orphans and Vulnerable children in PEPFAR priority countries. USAID Health Teams in South Africa, Côte d’Ivoire, and Zimbabwe—Ambereen Jaffer, Anita Sampson, Brilliant Nkomo, Collen Marawanyika, David Chikoka, Kathryn Reichert, Lauren Murphy, Lucie Dagri, Mavis Boateng, Naletsana Masango, Natalie Kruse-Levy, Samson Chidiya — and Brenda Yamba from the Regional Office, provided invaluable guidance and access to local implementing partners. 44
  • 43. This presentation was produced with the support of the United States Agency for International Development (USAID) under the terms of MEASURE Evaluation cooperative agreement AID-OAA-L-14-00004. MEASURE Evaluation is implemented by the Carolina Population Center, University of North Carolina at Chapel Hill in partnership with ICF International; John Snow, Inc.; Management Sciences for Health; Palladium; and Tulane University. Views expressed are not necessarily those of USAID or the United States government. www.measureevaluation.org