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Malaria Intervention Assessment in Four States of Nigeria: An Innovative, Comprehensive, Mixed-Methods Evaluation

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Presented at the 2016 ASTMH conference

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Malaria Intervention Assessment in Four States of Nigeria: An Innovative, Comprehensive, Mixed-Methods Evaluation

  1. 1. Yazoume Ye MEASURE Evaluation/ICF November 17, 2016 ASTMH, Atlanta Malaria Implementation Assessment in Four States of Nigeria: An Innovative, Comprehensive, Mixed- Methods Evaluation
  2. 2.  Background  Objectives of the assessment  Methodology  Results  Summary Outline of Presentation
  3. 3. Background Source: WMR 2015 Epidemiological profile Financing Source: WMR 2015  The President’s Malaria Initiative (PMI) support to Nigeria started in 2010  Initial focus of PMI support was in Cross River, Zamfara, and Nasarawa, then expanded to 11 states, including Sokoto  PMI works with the states to support selected health facilities in malaria service delivery and information systems  Out of a population of 192 million, PMI targets 54 million
  4. 4. To document progress in malaria control interventions 2008 – 2016 in four PMI-supported states — Cross River, Ebonyi, Nassarawa, and Sokoto Objectives of Assessment 1. Describe state-level malaria interventions 2. Document trends in malaria prevention and treatment indicators 3. Compare quality of care between PMI and non-PMI- supported primary public health care facilities 4. Document trends in malaria morbidity and mortality at the hospital level 5. Assess the quality of monthly malaria data at health facilities Main objectives Specific objectives
  5. 5. Methodology Assessment Sites Note: PfPR = Plasmodium falciparum parasitemia rate
  6. 6. Methods Design  Combination of designs o Non-experimental (pre- and post-assessment) o Quasi-experimental design (PMI vs. non-PMI supported health facilities) – Quality of care and quality of data  Trends in key malaria outcome and impact indicators  Period: between 2008 and 2016  Each state treated as independent case study o no comparison conducted across states
  7. 7. Methods Data sources  Secondary data collation o Routine data from primary health centre (PHC) facilities o Document review: Program documents and data, and contextual factors o Household surveys (Demographic and Health Surveys [DHS] and Malaria Indicator Surveys [MIS])  Primary data collection at PHC facilities o Client exit interviews o Key informant interviews o Observation of malaria commodities
  8. 8. Methods  Health facilities o List of all PHC facilities in each state o Stratified random sample using probability proportional to size: Selected 140 facilities in each state (70 PMI and 70 non-PMI-supported) = 560 o Referral hospitals of the selected PHC facilities were included in the sample (= 20 per state) = 80  Clients for exit interviews o Five clients per PHC = 2,800 o Targeted pregnant women attending antenatal care and clients with fever (all ages) Sampling Design
  9. 9. Methods Data collection and analysis  Field work period: February to June 2016  Field team in each state: o Data collection: 1 supervisor, 3 data collators, 1 exit interviewer o Quality assurance: 1 oversight consultant, 2 quality control officers, 1 field manager, 1 backup exit interviewer  State level: Trend of household survey data (DHS 2008, 2013, and MIS 2015)  PHC level (PMI vs. non-PMI- supported facilities) o Trend of malaria diagnostic, treatment and morbidity indicators o Chi-square test: Quality of care malaria indicators o Data quality: accuracy, completeness, consistency, and availability Data collection and collation Data collection Analysis
  10. 10. Results Sample achievement  Facility: 100% in all states  Exit interview: o Ebonyi: 82% o Cross River: 86% o Nassarawa: 98% o Sokoto: 84%
  11. 11. Malaria Prevention and Treatment (State) At least one ITN At least one ITN/2 people Vector control coverage: Household insecticide-treated net (ITN) ownership 0 10 20 30 40 50 60 70 80 90 100 Cross River Ebonyi Nassarawa Sokoto %ofhouseholds DHS 2008 DHS 2013 MIS 2015 0 10 20 30 40 50 60 70 80 90 100 Cross River Ebonyi Nassarawa Sokoto DHS 2008 DHS 2013 MIS 2015
  12. 12. Under five children Pregnant women Vector control coverage: ITN use Malaria Prevention and Treatment (State) 0 10 20 30 40 50 60 70 80 90 100 Cross River Ebonyi Nassarawa Sokoto %ofchildrenunder5yearsold DHS 2008 DHS 2013 MIS 2015 0 10 20 30 40 50 60 70 80 90 100 Cross River Ebonyi Nassarawa Sokoto %ofpregnantwomen DHS 2008 DHS 2013 MIS 2015
  13. 13. Women who received 2+ doses of sulfadoxine-pyrimethamine (SP) during antenatal care visits Women who received 3+ doses of sulfadoxine-pyrimethamine (SP) during antenatal care visits Intermittent preventive treatment in pregnancy (IPTp) coverage Malaria Prevention and Treatment (State) 0 10 20 30 40 50 60 70 80 90 100 Cross River Ebonyi Nassarawa Sokoto %ofpregnantwomen DHS 2008 DHS 2013 MIS 2015 0 10 20 30 40 50 60 70 80 90 100 Cross River Ebonyi Nassarawa Sokoto %ofpregnantwomen DHS 2008 DHS 2013 MIS 2015
  14. 14. Children who received any antimalarial treatment Children who received artemisinin combination therapies (ACTs), out of those that received any antimalarial treatment Case management coverage Malaria Prevention and Treatment (State) 0 10 20 30 40 50 60 70 80 90 100 Cross River Ebonyi Nassarawa Sokoto %ofchildrenunder5yearsold DHS 2008 DHS 2013 MIS 2015 0 10 20 30 40 50 60 70 80 90 100 Cross River Ebonyi Nassarawa Sokoto %ofchildrenunder5yearsold DHS 2008 DHS 2013 MIS 2015
  15. 15. Quality of Care in PHC Facility Proportion of PHC facilities that experienced a stockout of ACTs (register data) Cross River Ebonyi Nasarawa Sokoto 0% 20% 40% 60% 80% 100% 2008 2009 2010 2011 2012 2013 2014 2015 2016 PMI Non-PMI 0% 20% 40% 60% 80% 100% 2008 2009 2010 2011 2012 2013 2014 2015 2016 PMI Non-PMI 0% 20% 40% 60% 80% 100% 2008 2009 2010 2011 2012 2013 2014 2015 2016 PMI Non-PMI 0% 20% 40% 60% 80% 100% 2008 2009 2010 2011 2012 2013 2014 2015 2016 PMI Non-PMI
  16. 16. 0% 20% 40% 60% 80% 100% 120% 2008 2009 2010 2011 2012 2013 2014 2015 2016 Nasarawa PMI Non-PMI Proportion of children under five (U5) that presented at PHC facility with fever and were tested by RDT (register data) 0% 20% 40% 60% 80% 100% 120% 2008 2009 2010 2011 2012 2013 2014 2015 2016 Ebonyi PMI Non-PMI Data completeness was too low (<50%) for Sokoto to compute indicators. 0% 20% 40% 60% 80% 100% 2008 2009 2010 2011 2012 2013 2014 2015 2016 Cross River PMI Non-PMI Quality of Care in PHC Facility
  17. 17. Proportion of U5s with confirmed malaria receiving ACT (register data) Data completeness was too low (<50%) for Sokoto to compute indicators. 0% 20% 40% 60% 80% 100% 120% 2008 2009 2010 2011 2012 2013 2014 2015 2016 Cross River PMI Non-PMI 0% 20% 40% 60% 80% 100% 120% 2008 2009 2010 2011 2012 2013 2014 2015 2016 Ebonyi PMI Non-PMI 0% 20% 40% 60% 80% 100% 120% 2008 2009 2010 2011 2012 2013 2014 2015 2016 Nasarawa PMI Non-PMI Quality of Care in PHC Facility
  18. 18. Malaria case management (exit interviews) 0 10 20 30 40 50 60 70 80 90 100 Cross River Ebonyi Nasarawa Sokoto %ofclientswithfever % of clients with fever who had a test done PMI Non-PMI * Significant differences between PMI and non-PMI facilities in Cross River 0 10 20 30 40 50 60 70 80 90 100 Cross River Ebonyi Nasarawa Sokoto %ofclientswithfever % of clients with fever that tested positive for malaria, who were given ACTs PMI Non-PMI Quality of Care in PHC Facility * Significant differences between PMI and non-PMI facilities in Ebonyi
  19. 19. 0 20 40 60 80 100 Cross River Ebonyi Nasarawa Sokoto %ofpregnantwomen % of pregnant women who were given SP during visit PMI Non-PMI 0 20 40 60 80 100 Cross River Ebonyi Nasarawa Sokoto Among pregnant women who were given SP, % asked to swallow tablets in presence of health worker PMI Non-PMI * No significant differences between PMI and non-PMI facilities were observed in any of the states for either indicator Malaria in pregnancy (exit interviews) Quality of Care in PHC Facility %ofpregnantwomen
  20. 20. Quality of Data in PHC Facility 0 20 40 60 80 100 2008 2009 2010 2011 2012 2013 2014 2015 2016 Cross River PMI Non-PMI 0 20 40 60 80 100 2008 2009 2010 2011 2012 2013 2014 2015 2016 Ebonyi PMI Non-PMI 0 20 40 60 80 100 2008 2009 2010 2011 2012 2013 2014 2015 2016 Nasarawa PMI Non-PMI 0 20 40 60 80 100 2008 2009 2010 2011 2012 2013 2014 2015 2016 Sokoto PMI Non-PMI Availability: Proportion of monthly summary forms (MSFs) available for review at PHC out of the total number of MSFs that should be available to review.
  21. 21. 0 20 40 60 80 100 2008 2009 2010 2011 2012 2013 2014 2015 2016 Cross River PMI Non-PMI 0 20 40 60 80 100 2008 2010 2012 2014 2016 Ebonyi PMI Non-PMI 0 20 40 60 80 100 2008 2009 2010 2011 2012 2013 2014 2015 2016 Nasarawa PMI Non-PMI 0 20 40 60 80 100 2008 2010 2012 2014 2016 Sokoto PMI Non-PMI Completeness: Proportion of MSF data fields completed (filled in) out of the total number of MSF data fields reviewed. Quality of Data in PHC Facility
  22. 22. 0.00 0.50 1.00 1.50 Ebonyi Cross River Nasawara Sokoto # of children under five presenting with fever and tested by rapid diagnostic test (RDT) PMI Non-PMI 0.00 0.50 1.00 1.50 Ebonyi Cross River Nasawara Sokoto # of children under five tested positive for malaria by RDT PMI Non-PMI 0.00 0.50 1.00 1.50 2.00 Ebonyi Cross River Nasawara Sokoto # of children under five with confirmed malaria PMI Non-PMI 0.00 0.50 1.00 1.50 2.00 Ebonyi Cross River Nasawara Sokoto # children under five with confirmed malaria receiving ACT PMI Non-PMI Consistency: Verification ratio — Count in PHC register vs. value reported in the MSF. Quality of Data in PHC Facility
  23. 23. Summary  Coverage of malaria interventions at the state level improved since 2008, but overall remains below set national targets  Availability of malaria commodities at PHCs improved in latter years of the assessment period in both PMI and non-PMI- supported facilities, with greater increases in PMI-supported facilities  Quality of malaria case management was good across all states and slightly higher in PMI-supported PHCs; quality of malaria in pregnancy care varied across all states, however, was generally higher in PMI-supported PHCs  Availability and completeness of routine data at PHC improved in both PMI and non-PMI-supported facilities; consistency results show discrepancies in data transfer
  24. 24. Acknowledgments National Malaria Elimination Programme: Festus Okoh, Taiwo Orimogunje, Nnenna Ezeigwe, Perpetua Uhomoibhi, Timothy Obot, Olufemi Ajumobi PMI/Nigeria: Uwem Inyang, Jessica Kafuko, Richard Niska, Abidemi Okechukwu Nielson Nigeria: Greg Nzuk, Uwem Ndah, Ochiedike Chijioke, Joshua Bamigbode, Pradipta Mitra, Seun Olonade MEASURE Evaluation: Ana Claudia Franca-Koh, Tajrina Hai, Samantha Herrera, Lanre Adesoye, Balarabe Ibrahim, Abimbola Olayemi, Mariam Adio Wahad
  25. 25. This presentation has been supported by the President’s Malaria Initiative (PMI) through the United States Agency for International Development (USAID) under the terms of MEASURE Evaluation cooperative agreement AIDOAA-L-14-00004. MEASURE Evaluation is implemented by the Carolina Population Center at the 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 PMI, USAID, or the United States government. www.measureevaluation.org

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