Determinants of Population Coverage Measurement for Key Health Indicators in Haïti
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Introduction
Health system strengthening is a prerequisite to achieving continuous and impactful improvements in population health outcomes and the sustainable development goals 3 (SDGs 3) in low and middle-income countries. This study aimed to characterize and estimate the association of health facilities’ determinants with their performance levels in measuring population coverage for key health indicators in Haïti.
Methods
The 2017-2018 Haïti DHS service provision assessment (SPA) data were used to conduct this study. A sample of 993 primary health care facilities was dichotomized into the institutions that measured population coverage for key health indicators and the institutions that did not measure population coverage for key health indicators. These institutions were profiled according to specific characteristics, health management information system infrastructure, and funding sources. A multivariable logistic regression model provided estimates of the association between these determinants and institutional performance level in measuring population coverage for key health indicators.
Results
Most primary health care facilities were health centers without bed (36.4%) and community health centers (35.4%), under the managing authority of the government (33.4%) or the private for-profit sector (30.3%), located in rural areas (63.3%), operating a health services data collection system (93.7%), reporting data at least once per month (85.5%), staffed with health services data management personnel (in-house designated 18.9%, in-house non-designated 22.8%, and outsourced 23.8%), and funded by out-of-pocket payment (79.8%) and the Ministry of Health (53.4%). However, health services data technology was only available and functioning in less than half of all health facilities. Further analysis revealed that Institutions that measured population health coverage were predominantly community health centers (43.6%, UOR = 3.21, 95% CI [2.09, 4.96], p < 0.001) and health centers without bed (32.0%, UOR = 1.41, 95% CI [0.92, 2.15], p = 0.11), managed by the government (46.7%) and mixed entities (22.4%, UOR = 0.54, 95% CI [0.36, 0.81], p = 0.003), had a data collection system in place (98.2%, UOR = 7.68, 95% CI [3.86, 15.31], p < 0.001), reported data frequently at least once per month (98.0%, UOR = 35.57%, 95% CI [15.45, 81.89], p < 0.001) and had complete data on non-communicable diseases (99.3%, UOR = 6.00, 95% CI [2.01, 17.89], p = 0.001) and antenatal care services (97.1%, UOR = 6.24, 95% CI [3.56, 10.95], p < 0.001). Data management personnel was either formal, informal or contracted in more than 70% of these institutions located primarily in rural areas. In contrast, merely.one-third of these institutions were equipped with health services data technology (UOR = 0.55, 95% CI [0.43, 0.72], p < 0.001). Top funding sources were mostly out-of-pocket or individual direct payments (81.6%), UOR = 1.29, 95% CI [0.95, 1.76], p = 0.106) and from the Ministry of Health (68.7%, UOR = 4.37, 95% CI [3.34, 5.71], p < 0.001). Comparatively and within group, differences were noted among institutions that did not measure population coverage for key health indicators in Haïti.
Conclusion
Measuring population coverage for key health indicators is vital for strengthening the health system in Haïti. Continued reinforcement of the national public health policy, incremental and long-term increase in government funding in health care, sustained health management information system capacity-building; and political will, commitment, and stability are warranted.
