Routine Measurement of Quality of Care

1. Routine Measurement of Quality of Care Barbara Rawlins Senior Monitoring and Evaluation Manager, MCHIP/Jhpiego Maryjane Lacoste Tanzania Country Director/MAISHA Program Director, Jhpiego

2. Presentation Overview • Review existing routine quality of care measurement methods • Describe gaps in routine quality of care data for maternal and newborn health services • Present a case study from Tanzania • Discuss future measurement plans

3. Measuring the Quality of Maternal and Newborn Care is… • Multi-faceted and complex • Especially measurement of quality of intra-partum care (as it includes both routine care and management of complications) • Usually conducted through both periodic surveys and routine measurement mechanisms

4. Why measure the quality of maternal and newborn care routinely? • Program managers and policy makers need regular and reliable data for decision making: • Need to understand how the health system is performing at multiple levels • Need to know if “skilled birth attendants” are really skilled • Need to determine if facilities are “ready” to provide services with respect to infrastructure, supplies, drugs and equipment

5. Key Methods for Measuring MNH Quality of Care Routinely • Structured clinical observation of provider-client interactions • Data sources: clinical checklists applied by peers and/or external assessors (e.g., checklists used for quality improvement initiatives, supervision checklists) • Data captured: compliance with clinical guidelines and standards • Inventory of facility infrastructure/supplies/equipment • Data sources: facility audit checklists, supervision reports • Data captured: Stockouts of key medicines, broken and absent equipment, organization of services

6. Key Methods for Measuring MNH Quality of Care Routinely (2) • Record review • Data sources: Health management information system (HMIS) reports; facility registers; patient charts; criterion-based audits; near miss audits; maternal and perinatal death audits; sentinel site surveillance systems, logistics management information systems • Data captured: service utilization; frequency of provision of evidence-based components of care (e.g., for ANC– iron, TT, IPTp); management of complications; numbers of deaths and complications

7. Many Gaps in Routine MNH Quality of Care Data • Observational assessments of client-provider interactions are not widely conducted on a routine basis • Logistics management information systems and supervision reports only include a limited set of facility readiness indicators, such as stockouts • Many MNH service indicators of interest are not captured in national HMIS, especially those related to intrapartum care (e.g., active management of the third stage of labor)

8. Adapting Sentinel Site Surveillance for MNH Quality of Care Monitoring • MCHIP/Malawi and the MAISHA Program in Tanzania are in the process of applying a sentinel site surveillance approach for the continuous quality monitoring of MNH services • The MNH SSS systems are intended to: • Complement MNH data available from national HMIS reports • Test the feasibility of collecting additional MNH quality indicators at facilities on a routine basis • Generate national support for routine collection of facility-based quality indicators that prove feasible

9. What is sentinel site surveillance? • Sentinel sites are health facilities selected (using specific criteria) for monitoring of key indicators that are generally not reported up through the national health management information system • Sentinel site surveillance (SSS) traditionally has been used to track disease-related indicators: • National Malaria Control Programs and the U.S. President’s Malaria Initiative (PMI) use SSS to monitor trends in inpatient and outpatient malaria cases, inpatients deaths, uptake of intermittent preventive treatment of malaria by antenatal care clients

10. Tanzania Case Study: MNH Quality Monitoring by the MAISHA Program • The ACCESS/Tanzania program initiated a SSS system for FANC in 2006/7 • A total of 30 facilities across 16 regions were selected: 10 midwifery preservice clinical sites (hospitals) and 20 facilities that received FANC inservice training (hospitals, health centers and dispensaries) • The SSS System was expanded under MAISHA in 2009 to include monitoring of essential and emergency obstetric and newborn indicators • Now have 40 facilities across 21 regions plus Zanzibar: 19 hospitals, 12 health centers, 9 dispensaries

11. Tanzania Case Study: SSS Indicators FANC Indicators EONC/EmONC Indicators Number of women with obstetric complications (by type of complication) and number referred Number of maternal deaths by cause Number of newborn deaths (<24 hours, 24hours+) Number of stillbirths Number of days oxytocin, ergometrine, misoprostol and MgSO4 out of stock • % of ANC clients receiving IPTp1 and IPT2 • % of ANC clients tested for syphilis • % of ANC clients treated for hookworm • Number of ANC clients with Hb < 8.5g/dl • Number of functional BP machines with stethoscope • Number of days SP, RPR kits and iron out of stock

12. Tanzania Case Study: FANC Trends

13. Tanzania Case Study: EMOC Drug Stockout Trends

14. On the Horizon for MCHIP and MAISHA • MAISHA in Tanzania plans to expand data collection to 200+ facilities from all districts • MCHIP/Malawi is testing a routine MNH Quality sentinel surveillance system in the coming months • MCHIP plans to explore how an abbreviated version of the MNH Quality of Care facility survey can be applied on a routine basis

15. A discussion question for you… • Are there aspects of MNH quality of care we could be monitoring but we are not?

16. Thank you! Follow MCHIP on: www.mchip.net MNH Quality of Care Measurement Resources: http://www.who.int/reproductivehealth/publications/monitoring/9789241547734/en/index.htm http://www.rollbackmalaria.org/partnership/wg/wg_pregnancy/docs/MIPMEFramework.pdf