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Zimbabwe: Results-Based Financing Improves Coverage, Quality and Financial Protection


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A presentation by Dr. Gwinji, Permanent Secretary, Ministry of Health, Zimbabwe and Dr. Tafadzwa Goverwa- Sibanda, delivered during "Transforming Health Systems Through Results-Based Financing," an event held during the Third Global Symposium on Health Systems Research in Cape Town on September 30, 2014. This event was hosted by the Health Results Innovation Trust Fund at The World Bank, in partnership with the PBF Community of Practice in Africa.

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Zimbabwe: Results-Based Financing Improves Coverage, Quality and Financial Protection

  1. 1. 1
  2. 2. • Key messages, strategic context and overview of RBF program • Brigadier General Dr. Gwinji, MOHCC • Preliminary results from impact evaluation and process evaluation • Dr. Sibanda, MOHCC
  3. 3. • RBF is a health systems management tool intended to improve the efficiency of utilization of system inputs • RBF in Zimbabwe piloted in 2 front runner districts in July 2011, then scaled up to 16 additional districts in March 2012 • Contextual background: Dramatic improvements in MCH indicators witnessed throughout the country (MICS 2014) • Yet faster rates of improvement in RBF districts for key indicators • 13 percentage point improvement in the in-facility delivery rate • 12 percentage point improvement in post-natal care coverage • Significant improvement in the quality of ANC services • Not all indicators show relative improvement under RBF • No differential gain in coverage of ANC services • Small gain in use of modern contraceptives
  4. 4. • Improvements in part due to • Team based incentives facilitating teamwork • Regular and structured supervision visits yielding feedback to improve performance • Enhanced community participation • Challenges to be addressed include • Facilities in remote areas or with small catchment populations • Capacity to fully operationalize the quality of care components • Demand side barriers related to religious and socio-economic factors
  5. 5. Country & Project Context During Design Phase [2010-2011] • Population: 13 million (2002 Census estimates) • Decline in public sector financing • Effect on management • supportive supervision • Increase in household out-of-pocket expenditures due to various forms of user-fees • Decline in outcomes & slow progress on some key health MDGs [MDGs 4 & 5]
  6. 6.  RBF aligned with and supports National Health Strategy and policy– equity in access to health services; ◦ User fee removal (package of high impact services) ◦ Rebuild the quality of care standards ◦ Increase access to priority maternal, family planning and child health services ◦ Strengthen the referral system (promotes appropriate care seeking at appropriate levels) ◦ Decentralized service delivery and revitalized primary health care  Prioritized package of services directly linked to burden of disease for mothers, newborns and children under 5  RBF used to operationalize GoZ Results-Based Management Strategy and Results-Based Budgeting Pilot
  7. 7. • Fee-for-services : for both quality and quantity – partial replacement of user fees • Functions separated: purchaser, provider, regulator & external verifier • Key role for community –Health Center Committees 1. Results-Based Contracting • Strengthening planning and RBF management capacity: RBF national management team • Purchasing, verification, strategic management 2. Management and Capacity Building • Capture effect on health outcomes and various aspects of the health system • Accountability through community tracer surveys (CBOs) 3. Monitoring and Documentation
  8. 8. Package of RBF Services Rural Health Centers District Hospital 9. Tetanus TT2+ 10. ARVs to HIV+ preg. Women (PMTCT) 11. Family planning short and long term methods 12. High risk perinatal referrals 13. Vitamin A supplementation 14. Children fully immunized 15. Growth monitoring, children < 5yrs 16. Cure discharged acute malnutrition children < 5yrs (October 2012) 1. OPD new consultations 2. First ANC visit during the first 16 weeks of pregnancy (October 2012) 3. Ante natal care 4 visits completed 4. Post natal care 2 or more 5. Normal deliveries 6. HIV VCT in ANC 7. Syphilis RPR test 8. IPT (x2 doses) 1. Normal deliveries in district hospital 2. Deliveries with complications (caesareans excluded) and post partum complications 3. Caesareans performed 4. Family planning: Tuba Ligations 5. Counter referral note arrives at RHC (October 2012)
  9. 9.  Verified data from health facility registers collected by Local Purchasing Units (LPUs) and entered in the RBF database is utilized for payments  Data flow integrated within national HMIS, no parallel system used  Quantity verification by the LPU undertaken every month  Quality verification by the DHE (for RHCs) and by PHE (for DH) undertaken every quarter  Client satisfaction performed by the CBOs every month and by the counter-verifier every quarter 10/1/2014 9
  10. 10. HMIS - DHIS 2 Entry and Submission into DHIS2 Routine Reporting - T-Series District Facility Programme Database HFO s Data Accessible in Programme System: Same Platform RBF Indicators Downloaded Verified Data Entered Into System Updating HMIS with Verified Data Verificati on
  11. 11. 10/1/2014 11  RBF Funding  DFID and Government of Norway (US$35m)  Ministry of Finance: US$5 million per year from 2014  US$ 28 million disbursed (including $5 million Government counterpart funding)  Population Coverage : 4,1 million  Geographic coverage : 18 rural and 2 low-income urban and peri-urban districts (Harare and Bulawayo)  July, 2011 to October, 2015
  12. 12. Governance & Institutional Arrangements Contract Contract District Health Executive Tracing clients and client satisfaction Policy and Supervision Policy and Supervision Policy and Supervision MoHCW Provincial Health Executive Health Facilities and HCC (415) National Steering Committee District Steering Committee CORDAID Private Purchasing Agency (NPA) Contract + Payment Payment Community Based Clients Organisations CORDAID Local Purchasing Unit Payment Contract + Verification External verification 10/1/2014 12
  13. 13. 13 Baseline (2011) Midline Impact Evaluation (Mar-Sept 2014) Program Inception Endline IE (TBD) Process Monitoring and Evaluation (PME) (November 2013) Technical Review (June 2012) Routine Performance Review (Quarterly) – Operational Data Mid-Term Review (January 2013) Technical Adjustments: Prices and Services Technical Modifications –clinical quality, streamlining verification, equity monitoring 2nd PME Round Planned for October 2014
  14. 14. The IE seeks to determine the causal impact of RBF on priority service utilization and related health indicators ◦ Treatment: Facilities and patients residing in districts that introduce the RBF program ◦ Comparison: Facilities and households in matched “business as usual” districts ◦ Districts matched on various characteristics including:  Average catchment size of facility  Proportion of staff positions filled  Population rates over 2008 – 2010 of ANC coverage, in-facility delivery rates, immunization coverage 14
  15. 15. Participating Districts
  16. 16. Given the purposive selection of study districts, the evaluation must be quasi-experimental. Specifically, ◦ A difference-in-difference (“diff-n-diff”) estimator between matched districts in treatment and control (16 in each arm) estimates program impact ◦ To estimate actual impact: two years of program exposure (2012-2014) is contrasted with a two year period immediately (2008-2010) before the program 16
  17. 17. Household information –  Population representative surveys of health behavior, • including utilization, recall of procedures  health outcomes, • including anthropometry, satisfaction with care, knowledge  and mediating variables • socio-demographics  Baseline data for community and household utilized the 2011 DHS  Follow up data at community, household structured to replicate and supplement the earlier DHS  Yields a sample of ~2800 recent pregnancies/births 17
  18. 18. Facility survey – a comprehensive review of the structure, provision, and quality of care at clinic level  Instruments ◦ Facility checklist ◦ Health worker tool ◦ Exit interview tool (ANC, child illness) ◦ Direct observation (ANC, labor and delivery and child illness) ◦ Chart audit* of routine and complicated delivery • Only in the follow up 180 facilities in 2011 baseline (the NIHFA) and 231 in follow up Technical support from USAID and UNICEF was critical in this undertaking 18
  19. 19. • Data has just been collected and still being processed • However the preliminary results from both population and facility data are now available… • Overall it is a story of strong gains in select health indicators for the entire nation (consistent with the MICS results), with yet more rapid improvement in RBF districts • RBF gains in both the quantity and quality of care, but not for all prioritized indicators 19
  20. 20. • RBF led to gains in both the quantity and quality of care • A 13 percentage point increase in the in-facility delivery rate • A 12 percentage point increase in post-natal care coverage • More women receiving full package of ANC services including urine tests, blood tests, tetanus shots • But not for all prioritized indicators • Little change in ANC coverage and contraceptive use– baseline rates already high 20
  21. 21. RBF pre-trend RBF trend comparison pre-trend comparison trend Start of RBF 0.65 0.6 0.55 0.5 0.45 0.4 2008 2009 2010 2011 2012 2013 2014
  22. 22. Outcome Impact Level of significance Any modern contraception 0.05 0.21 Receipt of any antenatal care (ANC) 0.02 0.43 Time of first ANC -0.19 0.22 Number of ANC visits 0.40 0.15 Blood pressure checked during ANC 0.03 0.55 Urine sample collected during ANC 0.16 0.02 Blood sample collected during ANC 0.08 0.14 Receipt of tetanus vaccine during pregnancy 0.08 0.05 Number of tetanus vaccine 0.33 0.05 Any iron supplements received during pregnancy 0.00 0.99 Receipt of any postpartum care (PPC) 0.12 0.05 A PPC within 2 months of delivery 0.12 0.06 PPC by a skilled provider 0.14 0.02 Facility delivery 0.13 0.00 Skilled delivery 0.14 0.00 22 Most impacts measured in proportional terms. Statistically significant results with in red.
  23. 23. 23 Patient exit interviews ◦ ANC interviews (n=1105) indicate significant improvements in care processes such as measured abdomen and urine sample ◦ Child health interviews (n=1612) indicate significant improvement in measurement and growth monitoring ◦ Client satisfaction is also higher (although at marginal significance, p=.128) Facility measures ◦ Improvements in select facility conditions after RBF:  8 percentage point increase in availability of bio-med waste disposal ◦ Increases in supervision and community involvement after RBF:  Increase in number of HCC meetings (2.7 more per year)  Increase in external assessments of staff (2.4 more per year)  34 percentage point increase in presence of facility work plan
  24. 24. RBF Investments Program Outcomes
  25. 25.  Need to go beyond numbers ◦ Capture rich experiences and lessons from frontlines of PBF implementation & context  Community engagement and support (HCC)  Geographic influences (supervision aspect, cross-catchment area patient movement)  Health facility management skills and dynamism  Extent of mentorship and clinical supervision by district/province  Explain contextual factors that matter the most & account for variation in provider performance  Supporting impact evaluation and not substituting it –better understanding of the our intervention 25
  26. 26. Providers at high performing health facilities (HPF) were reported to be highly motivated.  Regular and well structured supportive supervision improved the capacity to earn more subsidies e.g one (HPF) had an increase in subsidies of 53% to 94% between the first and second quarters.  Team work improved communication ...we are now working as a team to ensure that the T5 (data compilation form) is correct and accurate and we are able to send it to the district in time. We are motivated to work as we get paid for our effort. --( HF Staff Member)  Higher client satisfaction attracted more patients (patient choice)
  27. 27. When low performance is found, facilities attribute reasons to:  Smaller catchment populations & at times geographic remoteness  Irregular supportive supervision Socio-economic and religious factors in the population
  28. 28.  Revisit the remoteness criteria & facility catchment issue  RBF performance payment calculation formula being reviewed (higher remoteness bonus)  Content & structure of quality supervision checklists  Written feedback by district managers mandatory  Modified supervision checklist – more process measures of clinical care introduced  District Health Executive supervision contract revisited – ensure incentive to regularly supervise remote facilities  Integrate RBF into HR management 28
  29. 29. Thank You! 29
  30. 30. Extra slides 30
  31. 31.  What is the impact of RBF on maternal and child health services utilization and outcomes?  What is the impact of RBF (counter verification) on health management information system (HMIS) and on supportive supervision?  What is the effect of RBF on community participation and social determinants of health?  What is the effect of RBF on health workers’ attitude, job satisfaction, retention and attrition, etc?  What is the effect of RBF on patient/client satisfaction and in health seeking behavior? 31
  32. 32. Given the purposive selection of study districts, the evaluation must be quasi-experimental. Specifically, ◦ A difference-in-difference (“diff-n-diff”) estimator between matched districts in treatment and control (16 in each arm) estimates program impact  In a diff-n-diff estimator, the observed trends in outcomes for the comparison districts stand for what would have happened in the RBF districts if not for the RBF program  The validity of this approach can be assessed by comparing pre-RBF trends of same outcomes in RBF and comparison districts before RBF program  To estimate actual impact: two years of program exposure (2012-2014) will be contrasted with a two year period immediately (2008-2010) before the program 32
  33. 33. Start of RBF 0.95 0.9 0.85 0.8 0.75 0.7 0.65 0.6 0.55 0.5 RBF pre-trend RBF trend comparison pre-trend comparison trend 2008 2009 2010 2011 2012 2013 2014
  34. 34. After introduction of RBF 1 0.98 0.96 0.94 0.92 0.9 0.88 RBF pre-trend RBF post-trend comparison pre-trend comparison post-trend 2007 2008 2009 2010 2011 2012 2013
  35. 35.  Key areas PME assessed • Factors affecting health provider performance • Factors influencing changes on the demand (community) side • Compliance of the RBF stakeholders to the project’s implementation guidelines. 35
  36. 36. Binga, Chipinge, Kariba, Mazowe and Zvishavane.
  37. 37.  Selected three facilities in each of five districts  Sequential mixed method deployed  Participants selected included mothers of reproductive age, male community members, influential leaders, health center committee members, district management team, as well as clinic health staff
  38. 38.  RBF: ◦ Strengthens relationships between health care providers & communities and improves access to services at community level (e.g. community ambulance) ◦ Fosters innovations and entrepreneurship among health workers ◦ Improves district managers supportive supervision ◦ Improves health facility infrastructure (service delivery environment) ◦ Improves staff morale and promotes team work 38
  39. 39.  Staff shortage “When one of us attends a workshop only one person is left to deal with registers and the workload is huge and most of the mistakes we make are due to fatigue. We are now losing patients to other institutions…”HF staff “There are a number of clinics surrounding therefore there is competition for example X clinic is GVT owned and well equipped, has drugs and well-staffed so patients prefer going there than spending more time in long queues here where there is staff shortage”. -- HF Staff Member  Shortage of drugs e.g. vaccines  Inadequate infrastructure