How are programmes specifically designed using collected data?

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Presentation transcript:

How are programmes specifically designed using collected data? Osamu Kunii, MD, MPH, PhD Head, Strategy, Investment and Impact Division The Global Fund to fight AIDS, Tuberculosis and Malaria

Outline Data Use for Action and Improvement Framework (DUFAI) Data Use for fund allocation Data Use for across the grant lifecycle Data and Analytics (DnA) for grant management Data Use for policy change and implementation adjustment

Data Use for Action and Improvement (DUFAI) Framework To strengthen data availability, quality and use of data for program improvement and maximized impact 20 indicators/targets

DUFAI: Integration and Alignment across the metrics Data Use for action and Improvement (DUFAI) Risk management GF Strategy and Strategic Priorities Key metrics and sources of funding (OPEX, Grants) KPI framework This framework consolidates all reporting requirements, including KPI, Strategic Implementation plan, risk tracer indicators, and key metrics

Strategic Performance Framework (KPI 2017-22) Impact / Results Implementation Program Design Funding GF accountability Lower Higher How is global effort performing? 1 KPI 1: Impact KPI 2: Service delivery KPI 9c: Human Rights & Key Pops in UMICs KPI 4: Investment efficiency KPI 5: KPs srvc. coverage KPI 6: RSSH (a, b, c, d, e) How are countries we are supporting performing? 2 KPI 11: Domestic investments KPI 6f: NSP Alignment KPI 8: Gender & age equality KPI 9a: HRts barriers KPI 9b: Human Rights & Key Pop in MICs KPI 7b: Absorptive capacity How are our grants performing? 3 KPI 10: Resource mobilization KPI 3: Alignment of investment & need KPI 7a: Allocation utilization How are GF grant operations performing? 4 KPI 12: Availability of affordable health tech How are internal Secretariat operations performing? 5 Data sources Grant reporting Country info (from CCM) Technical partners Assessments. evaluations Secretariat internal data

Financial Performance Data and Analytics (DnA): Central interactive portal for grant management data Global Region Country Grant General Information Health Financing Financial Performance Risk Disease Process Key Insights Programmatic Performance Launched Future Release Country Coordinating Mechanism

HIV data used for fund allocation Allocation Formula Qualitative Adjustments Stage 1 Stage 2 Disease burden Number of people living with HIV Economic Capacity Based on GNI per capita Max / Min Shares - Max: 10% funding of each disease component; 7.5% of all countries - Min: $500,000 per component Other External Financing Projections of other external financing Populations disproportionately affected by HIV Parameters Key Populations (HIV incidence, prevalence, size, etc.) Absorption and impact Other considerations Potential for impact and absorption Cost of essential programming Coverage gaps Risk of malaria resurgence

Data collection and use at various stages of grant lifecycle Country dialogue Grant making Year 2 Year 1 Year 3 Funding request Assessment of Quality of Data and Programs Progress updates & Annual Funding Decision Epi-analysis ; National program reviews M&E systems assessment National strategic plan Identify gaps Invest Implement, track performance & adjust Investment cases Prioritization models Performance framework M&E plan Risk assessment Strengthen national M&E systems

Grant ratings and determining annual funding amount Step 3 Step 1 Step 2 90-100% 60-89% 30-59% TBD Analysis of Program Performance Indicator Rating b2 b1 C a2 a1 Indicative Funding Range c Financial Performance Grant Management Performance Meets expectations Adequate Inadequate Unacceptable Exceeding expectations Final Grant Rating Annual Funding Disburse. Decision

Lesotho : Use data to drive policy change - High volume of tests - High rate of repeated tests - Declining yield - Increasing cost of implementation -Targeted groups - Differentiated service delivery - Focused on high yield modalities with yield targets - Regular data analysis and adjustment

Community-based monitoring Advantage: bottom-up, demand side, community engagement & buy-in, shorter, local feedback loops Example: Community Tx Observatory in 11 countries, West Africa €3.6 million to International Treatment Preparedness Coalition Findings: stock-out, reasons for not accessing ART, quality of care, out-of-pocket payment Actions: advocacy and improvement for differentiated service delivery, non-facility based HIV testing, communication to prevent stock-outs, funding to viral load testing machines/lab supplies

Way forwards Smarter investment in in-country data systems GF replenishment and domestic resource mobilization Strategic partnership for acceleration toward SDGs

Acknowledgment HIV Team Monitoring, Evaluation and Country Analysis Team Lesotho Country Team Jinkou Zhao, Lee Abdelfadil, Michelle Monroe Gavin Reid,