1. 11 Validating AFP’s Theory of Change Michelle J Hindin, MHS PhD AFP Partners Meeting, Kenya Scientist, hindinm@who.inthindinm@who.int

2. 22 AFP’s Theory of Change  At each stage: – Use AFP-SMART to identify barrier and quick win(s) – Use cascade analysis to document quick win – Use decision tree to track progress towards impact (stage 4) – Provide additional documentation that barrier is addressed – Consider feasibility of going to next stage Filename Stage 1: FP Regulation Change or budget allocated Stage 2: Resources allocated to increase FP services Stage 3: Change in provision of FP services Stage 4: Change in FP uptake or service quality

3. 33 Stage 1: FP policy change or FP resources allocated  What additional documentation could be provided?  Is it feasible to go to Stage 2? If not, why? Filename Stage 1: FP Regulation Change or budget allocated Stage 2: Resources allocated to increase FP services Stage 3: Change in provision of FP services Stage 4: Change in FP uptake or service quality  Kenya Quick Win: Siaya, Kakamega, Tharaka Nithi and Kitui counties allocate a combined total of $246,279 to FP Fiscal Year 2015/2016  Documentation: Country budget documents, annual reports

4. 44 Stage 2: Resources allocated for improved FP services  DRC Quick Win: After DRC’s commitment to FP2020, the government purchases S$300,000 worth of contraceptives  Documentation Programme National de Santé de la Reproduction (PNSR)  What additional documentation could be provided?  Is it feasible to go to Stage 3? If not, why? Filename Stage 1: FP Regulation Change or budget allocated Stage 2: Resources allocated to increase FP services Stage 3: Change in provision of FP services Stage 4: Change in FP uptake or service quality

5. 55 Stage 3: Change in provision of FP services  Zanzibar Quick Win: After refresher trainings for forecasting FP commodities for key staff in 10 districts, reduced stock outs and increased availability and access to FP commodities  Documentation Tanzania health management information systems reports.  What additional documentation could be provided?  Is it feasible to go to Stage 4? If not, why? Filename Stage 1: FP Regulation Change or budget allocated Stage 2: Resources allocated to increase FP services Stage 3: Change in provision of FP services Stage 4: Change in FP uptake or service quality

6. 66 Stage 4: Increase of FP use  Indonesia: In Karanganyar district Indonesia, after releasing funds, increase in LAPM services, enhanced data collection, LAPM users increased (32.4%-34.2%)  Documentation: FP village team recording and reporting form, District BKKBN service statistics  What additional documentation could be provided?  Can this be scaled up? Why or why not? Filename Stage 1: FP Regulation Change or budget allocated Stage 2: Resources allocated to increase FP services Stage 3: Change in provision of FP services Stage 4: Change in FP uptake or service quality

7. 77 How can we measure impact in Stage 4?

8. 88 Limitations of data sources: Household Surveys  Infrequent (DHS, MICS every 5 years) though PMA2020 is more frequent. Other national surveys  Disaggregation (often cannot get reliable estimates at the subnational level)  Measures of appropriate use are limited, especially for many short-term methods Are they really taking OCs every day? Using condoms for every sex act? Getting new injections at the appropriate time?

9. 99 Limitations of measuring mCPR with Facility Data  Limited electronic record keeping in many facilities  No guarantee that short-term contraceptive commodities are used. Using condoms for every sex act? Taking OCs every day  Commodity stock fluctuations  Geography – Women make seek sources outside their communities – Short-term methods can be obtained from other sources that are not tracked with the public facilities Pharmacies Other private sector Community health workers

10. 10 Don’t give up--  Triangulate Data! Filename

11. 11 Filename Thank You

12. 12 What can we do to get better estimates?  Household survey: – Link source data with household survey data – Present data with confidence intervals  Facility data: – Move to electronic log books  Combined household and facility – Aggregate month-to-month or quarterly data in facilities to annual or semi-annual data – Aggregate PMA2020 to annual or every two years  Triangulate – Use more data sources Commodity tracking data (e.g. JSI) Community health worker data