Introduction to Laboratory Quantification Lab TWG Jason Williams, Principal Laboratory Advisor, SCMS February 20-21, 2013.

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Presentation transcript:

Introduction to Laboratory Quantification Lab TWG Jason Williams, Principal Laboratory Advisor, SCMS February 20-21, 2013

PEPFAR Implementing Partner Overview Introduction to logistics Quantification Forecasting approaches Data use Take aways ForLAB (demonstration) 2

PEPFAR Implementing Partner Logistics system design 3

PEPFAR Implementing Partner Central Warehouse Logistic data flow and aggregation 4 District Laboratories Health Centers Regional Laboratories MOH LMU National Reference Laboratories LIMS Opportunity to integrate

PEPFAR Implementing Partner Laboratory logistics data Date types: Issues, losses/adjustments, stock on hand Test numbers by instrument type Instrument downtime Can be used to: Identify commodity distribution challenges Inform national laboratory quantifications Can also measure: Service delivery performance/capacity Impact of instrument downtime Programmatic performance 5

PEPFAR Implementing Partner Logistics system design 6

PEPFAR Implementing Partner Advocacy Quantifications serve as the core tool for monetary advocacy Forecast output can guide programmatic scale up and define service delivery challenges Forecast process (assumptions) can define data gaps – need for LMIS and M&E strengthening Assist with donor coordination and defined roles and responsibilities Guide programmatic and laboratory coordination 7

PEPFAR Implementing Partner 8 Quantification Activities: Forecasting: estimating the quantities of the products required for a specific health program (or service), and Supply planning: determining cost and when the products should be delivered to ensure an uninterrupted supply for the program Source: USAID | DELIVER PROJECT

PEPFAR Implementing Partner 9 Step 1 Step 2 Step 3 Source: USAID | DELIVER PROJECT Quantification

PEPFAR Implementing Partner Forecasting approaches Forecast methodologies: Consumption (issues) Demographic/Morbidity Service statistics SCMS Approach Comparative review Determine appropriateness – capacity/costs/growth Final forecast established –mixed components 10

PEPFAR Implementing Partner 11 Comparative review

PEPFAR Implementing Partner Quantification: data for decision-making Data Points required for optimization Inventory of instruments Demand (quantification) Instrument utilization, diagnostic contribution and capacity Instrument down time Impact of maintenance agreements and vendor performance 12

PEPFAR Implementing Partner Understanding Instrument Diagnostic Contribution (service data)

PEPFAR Implementing Partner Take aways Focus on ensuring data availability and quality Multi/mixed method forecasting provides transparency, context, and overall confidence in estimates Transform quantification data to monitor programmatic and supply chain performance Use quantification data to make evidence based decisions, optimize procurement decisions Monitor utilization to ensure capacity, scale up strategies 14

PEPFAR Implementing Partner Take aways Forecast process defines data gaps – need for LMIS and M&E strengthening Forecasting guides donor, programmatic and laboratory coordination and advocacy to address funding gaps 15

PEPFAR Implementing Partner Solution: ForLAB Multi-method tool Can be linked to LMIS Flexible Standardized specifications Laboratory network coverage Ability to inform optimization efforts 16