Presentation outline

Transcription

1 Inter-district differences in correlates of health worker absenteeism Wayan Suriastini (SurveyMETER) Jeffrey Sine (RTI International) Firman Witoelar(SurveyMETER) Dani Alfah (SurveyMETER) Presentation outline Study context Sample & methods Findings Uses & implications

2 Study context USAID-Kinerja/Papua Project Improve local services through governance innovation. Absenteeism identified as a barrier to quality health service delivery. Need to identify roots before considering interventions 4 districts how similar, how different? Findings intended to drive operational policy barriers analysis a analytic policy dialogue method for evaluating feasibility of possible solutions. Survey conducted May/June Study Objectives Measure health provider absenteeism. Doctors, nurses, midwives Understand absenteeism from health workers perspectives and the perspective of health center heads. Obtain the perspective of community members and leaders on services and absenteeism. Provide evidence for intervention/operational policy design to reduce absenteeism.

3 Conceptual framework for absenteeism Individual characteristics Institutional/ policy environment Health Worker Absenteeism Environment factors Facility characteristics Sample frames Health Facilities 57 health centers in 3 districts + 1 city Health Workers Begin with district health office staffing lists Verbal update at health centers, first survey visit Communities 50 male, 50 female FGDs community members In-depth Interviews community leaders

4 50 Health Centers: Health worker sample Nurses Doctors Present Absent Non-present: serving at subfacility or different shift Midwives Population Sample type Census 2 per HC 2 per HC Census Census Target Sample Interviewed % Interviewed 93% 98% 87% 88% 97% Instruments Health center level Unannounced attendance roster am Health center head interview Health facility assessment Health worker level Workers present during unannounced visit Workers not present Community level FGD guidelines In-depth interview instrument

5 Measured 2 kinds of absenteeism Cross-sectional at the time of the unannounced visit All health workers Self-re-ported historical (past 4 weeks) Providers interviewed in-depth Segregated by those present/absent on cross-sectional measure Logistic regression model Dependent variable Health worker present/absent Independent variables Individual Environment = characteristics + + characteristics Health center characteristics Gender Profession Marital status Age Kids < 6 yrs Yrs experience Ethnic group/ place of birth Fare to HC Housing Lives with family Private practice Wants to transfer Work satisfaction Geography of community Ethnic composition of community EmOcfacility, Overnight capacity Opening schedule Villages/sub-facilities in catchment area Facility condition Internet, phone signal HC head characteristics Absenteeism interventions DHO supervision

6 Topline findings 50 Large inter-district differences in absenteeism rates Pe ercent Absent Kota Jayapura Kab. Jayapura Jayawijaya Mimika

7 Multivariate Analysis Results: Inter-district differences Worker characteristics Kota Jayapura Significant odds ratios Kab Jayapura Jayawijaya Mimika Gender.... Profession Age Married Has children < 6 yrsold Wants to transfer.. +. Ethnicity/place of birth... ++

8 Environment characteristics Kota Jayapura Significant odds ratios Kab Jayapura Jayawijaya Mimika Fare home to health ctr Topographicof community Ethnicity of community No. villages in coverage area Lives with family.... Lives in government housing Health center characteristics Significant odds ratios Kota Kab Jayapura Jayapura Jayawijaya Mimika No. of sub-facilities EmOC-capable facility Overnight bed capacity Open 7 days/week Health center condition Internet connected +... Mobile phone signal

9 Health center characteristics Healthctrhead profession Significant odds ratios Kota Kab Jayapura Jayapura Jayawijaya Mimika Head wants transfer.... Head was absent HC has nodoctor.... HC has no lab tech HC has no pharmacist.... Last DHOsupervision visit.... Using findings: Operational policy barriers analysis

10 Operational policy barriers Source: Cross, et. al. Reforming Operational Policies. POLICY Occasional Papers #7; Participatory solution building Driver Poor job performance of health center head Operational barrier Operational policy solution Lack of clear performance standards. Poor leadership capacity Poorly administered rewards/sanctions systems Codified fit &proper standards; pre-appointment assessment requirement. Post-appointment periodic evaluation. Define leadership excellence. Shift to new participatory, transparent management methods. Offerregular refresher training; regularize in DHO budget. Standardize, codify and clearly communicate rewards/sanctions. StrengthenDHO staff supervision skills;ensure system consistently appliedacross time and PKM.

11 Participatory solution building Driver High fare for healthworker transport to the health center Operational barrier Operational policy solution Subsidiesnot targeted Health workers not living in assigned PKM housing DHO-provided transportationfor workers in remote PKM poorly managed and maintained Identify strategic need PKM and focus subsidies on them. Establish and regularly update a database on PKM housing condition and needs; finance maintenance & construction. Issue regulations requiring staff assigned housing to live there; monitor regularly. Shift responsibility and resources fortransportation management to PKM. Participatory solution building Driver Poor health center facility condition Operational barrier Operational policy solution Poorly coordinated planning Poor guidanceand support from DHO Develop an improved mechanism to coordinate drug supply planning between DHO and each PKM. Issuea formal decree to establish a Tim Pembina PKM; integrate with Monevtim; regularly evaluate team effectiveness.

12 Observations & Implications Measuring health worker absenteeism is not straightforward Time of day measured greatly affects rate. Need to verify those working at sub-facilities. Perspective on meetings, trainings, seminars matters. Heads not always truthful about who s in, who s not. How to count long term absent providers? How to accommodate special arrangements? Discrepancy between DHO and PKM worker rosters.

13 Observations Rates were not a surprise to district health officials. welcomed confirmation/evidence. Our methods UNDER estimate extent of the problem. Compensated for late arrival, early departure. Communities have good instincts on absenteeism drivers. opportunity for community-involved abatement? Disagreement over acceptable vs. unacceptable reasons need for better guidance to workers. Operational policy barriers dialogue can lead consensus on solutions and follow-through commitment. Future research Evaluation of interventions adopted. Additional secondary analysis of dataset: Does past absenteeism predict future absenteeism? What facility condition aspects most need attention? How adequate (volume, condition) is housing supply for health workers? What is the relationship between worker satisfaction and health facility condition, housing? National picture of health worker absenteeism; regional differences in drivers.

14 Terima kasih