What predicts health facility delivery among women? analysis from the 2021 Madagascar Demographic and Health Survey.

BACKGROUND: One of the pivotal determinants of maternal and neonatal health outcomes hinges on the choice of place of delivery. However, the decision to give birth within the confines of a health facility is shaped by a complex interplay of sociodemographic, economic, cultural, and healthcare system-related factors. This study examined the predictors of health facility delivery among women in Madagascar. METHODS: We used data from the 2021 Madagascar Demographic and Health Survey. A total of 9,315 women who had a health facility delivery or delivered elsewhere for the most recent live birth preceding the survey were considered in this analysis. Descriptive analysis, and multilevel regression were carried out to determine the prevalence and factors associated with health facility delivery. The results were presented as frequencies, percentages, crude odds ratios and adjusted odds ratios (aORs) with corresponding 95% confidence intervals (CIs), and a p-value < 0.05 was used to declare statistical significance. RESULTS: The prevalence of health facility delivery was 41.2% [95% CI: 38.9-43.5%]. In the multilevel analysis, women aged 45-49 [aOR = 2.14, 95% CI = 1.34-3.43], those with secondary/higher education [aOR = 1.62, 95% CI = 1.30-2.01], widowed [aOR = 2.25, 95% CI = 1.43-3.58], and those exposed to mass media [aOR = 1.18, 95% CI = 1.00-1.39] had higher odds of delivering in health facilities compared to those aged 15-49, those with no formal education, women who had never been in union and not exposed to mass media respectively. Women with at least an antenatal care visit [aOR = 6.95, 95% CI = 4.95-9.77], those in the richest wealth index [aOR = 2.74, 95% CI = 1.99-3.77], and women who considered distance to health facility as not a big problem [aOR = 1.28, 95% CI = 1.09-1.50] were more likely to deliver in health facilities compared to those who had no antenatal care visit. Women who lived in communities with high literacy levels [aOR = 1.54, 95% CI = 1.15-2.08], and women who lived in communities with high socioeconomic status [aOR = 1.72, 95% CI = 1.28-2.31] had increased odds of health facility delivery compared to those with low literacy levels and in communities with low socioeconomic status respectively. CONCLUSION: The prevalence of health facility delivery among women in Madagascar is low in this study. The findings of this study call on stakeholders and the government to strengthen the healthcare system of Madagascar using the framework for universal health coverage. There is also the need to implement programmes and interventions geared towards increasing health facility delivery among adolescent girls and young women, women with no formal education, and those not exposed to media. Also, consideration should be made to provide free maternal health care and a health insurance scheme that can be accessed by women in the poorest wealth index. Health facilities should be provided at places where women have challenges with distance to other health facilities. Education on the importance of antenatal care visits should also be encouraged, especially among women with low literacy levels and in communities with low socioeconomic status.

Model for building quality resilient health facility.

The AfIHQSA Model is the model for building quality resilient health systems. It is proposed as a compliment to and in many instances as an alternative to the many other existing in ensuring a systematic and a sustained approach to improving outcomes in African health systems. It seeks to bring the necessary transformation to healthcare quality and patient safety and facilitate the attainment of desired outcomes. The model is unique in its iterative nature and how it places premium on sustaining the gains of improvement. The authors are concerned about the lack of sustainability of the many quality improvement efforts on the continent and how they all fade out into obscurity upon the exit of the proponents. Six iterative steps are proposed in the use of the model and these are: leadership commitment and buy-in; situational analysis of quality management capacity; systems strengthening for quality management; quality improvement interventions for care outcomes; standardization/accreditation/certification; and iterative monitoring, evaluation of performance of interventions and learning. Most of the quality interventions and efforts on the continent have failed because the steps in this model have not been sufficiently followed and addressed. The required strengthening of the various components of the health system necessary to sufficiently bear the weight of any quality intervention and guarantee sustainability of the gains is often ignored. As authors, we have therefore formally adopted the use of this model and plan to further continue evaluating and monitoring its utility and its generalizability in different institutions and countries.