A guide to Primary Health Care Facility Supervision
DHS Working Papers No. 114
Demographic and Health Surveys, Working Paper
Levels and Inequities
DHS Further Analysis Reports No. 110
This study shows large variations in maternal health indicators across high-priority counties in Kenya. Nairobi exceeds the national average on all maternal health indicators in this study, while other highpriority counties consist
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ently are disadvantaged compared with Kenya as a whole in most maternal health indicators. Kisumu exceeds the national average in use of antenatal care, delivery in a health facility, and postnatal care, but not other indicators. Nakuru has fewer women with fertility risk and fewer women who report that the distance they must travel to reach a health facility is a problem.
This study identifies a number of inequities in maternal health indicators across socio-demographic characteristics in the high-priority counties—most in the distribution of delivery care and least in antenatal care. Inequities are also observed in fertility risk and postnatal care.
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DHS Further Analysis Reports No. 111
This study is a theory-driven analysis of the socio-demographic determinants of maternal care seeking in Kenya. Specifically, it examines predisposing, enabling, and need factors potentially associated with use of antenatal care (ANC), health
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facility delivery, and timely postnatal care (PNC).
This study uses data from the 2014 Kenya Demographic and Health Survey (KDHS) conducted among women age 15-49 with a live birth in the five years preceding the survey. It includes data from all 47 counties of Kenya, grouped contiguously into 12 regions. We apply Andersen’s Behavioral Model of Health Services Use to examine socio-demographic predictors of health service use. We estimate logistic regression models for adequate use of ANC (defined as attending at least four ANC visits, starting in the first three months of pregnancy), delivery in a health facility, and PNC within 48 hours of delivery.
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A nationwide survey of a representative sample of health facilities across public health services in all states and regions of Myanmar has been undertaken since 2014 to track Reproductive Health Commodity Security (RHCS) indicators, such as the availability of reproductive health (RH) commodities; t
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he supply chain (including cold chain systems); staff training and supervision; availability of guidelines and protocols; information and communication technologies; methods of waste disposal; and user fees. The surveys have also obtained the views of clients about the quality and cost of services through exit interviews. This is the third report for Myanmar, which is an assessment of the situation in 2016.
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A cross-sectional descriptive study design covering all states and regions was undertaken to:
1) To assess availability, utilization and supply chain management system for RH commodities at different levels of health facilities,
2) To assess quality of RH services with emphasis on family
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planning in terms of training, supervision, use of guidelines and ICT, and
3) To determine clients’ accessibility to RH services provided at different level of facilities.
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In 2014, the Ministry of Health (MOH) in Malawi conducted a nationwide assessment of emergency obstetric and newborn care (EmONC) services. This cross-sectional facility-based survey used 10 data collection modules. Data collection began on 23rd Sep
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tember 2014 and concluded on 17th October 2014, in all 28 districts. Facilities in both the public and private sector (for-profit and not-for-profit) were included. Since the focus of the assessment was obstetric and newborn care, health facilities that did not offer maternal and newborn health (MNH) services were not selected. In all districts, a census of all hospitals and a 60 percent random sample of health centres that ought to have performed deliveries in the previous year yielded a total of 365 facilities: 87 hospitals and 278 health centres. All these facilities were visited during the assessment. During analysis, weighting procedures were applied to extrapolate results to the district and national level, representing all 87 hospitals and 464 health centres. Such weighting was necessary as a stratified random sample of health centres was taken and weighting applied to all indicators and presentations that have health facility as a unit of measurement. Case reviews and provider’s interviews, on the other hand, are not weighted as their sampling strategy is based on convenience.
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The report is based on comprehensive information collected at representative sample health facilities all over the country by well-organized and trained teams during May and August 2015. This is a continuation of 2014 Assessment activities and findings also reflect comparison between two consecutive
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years.
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The GFF needs an additional US$2.5 billion from 2021 to 2025 to enable countries to protect health gains and accelerate progress toward the 2030 Goals. Of this amount, the GFF urgently needs to secure new pledges of US$1.2 billion by the end of 2021 to help its current 36 partner countries protect
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and maintain essential health services and implement time-sensitive service delivery and health system improvements to enable a sharp bend of the curve back to a positive trajectory to close the gap to the SDGs.
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This study is a theory-driven analysis of the socio-demographic determinants of maternal care seeking in Kenya. Specifically, it examines predisposing, enabling, and need factors potentially associated with use of antenatal care (ANC), health facility
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delivery, and timely postnatal care (PNC).This study uses data from the 2014 Kenya Demographic and Health Survey (KDHS) conducted among women age 15-49 with a live birth in the five years preceding the survey. It includes data from all 47 counties of Kenya, grouped contiguously into 12regions.We apply Andersen’s Behavioral Model of Health Services Use to examine socio-demographic predictors of health service use.We estimate logistic regression models for adequate use of ANC (defined as attending at least four ANC visits, starting in the first three months of pregnancy), delivery in a health facility, and PNC within 48 hours of delivery.
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The Newborn Situational Analysis reports of 2009 and 2011, as well as the “Bottleneck analysis on neonatal health” of 2013, culminated in the Nigeria launch of “Call to action on Newborn health” at the first National Newborn Health Conference in 2014. This call to action provided the framewo
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rk for the development of the Nigeria Every Newborn Action
Plan (NiENAP). The NiENAP lays out a vision to end preventable stillbirths and newborn deaths by accelerating progress and scaling up evidence- based high-impact and cost effective interventions. The plan is guided by the principles of country-leadership, integration, accountability, equity, human rights, innovation and research. This blue print outlines our commitment as government and stakeholders to repositioning newborn health as we implement approaches that impact on the lives of newborns for improved health outcome.
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DHS Working Papers No. 86
This report presents further analysis of the 2015 Nepal Health Facility Survey. Data analysis is based on the Donabedian framework for assessing quality of care in health services, which divides the indicators into three groups: structure, process,
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and outcome. The World Health Organization Service Availability and Readiness Assessment (SARA) indicator guideline was used to assess facility service readiness, service quality and client satisfaction with maternal health services. The study performed both bivariate and multivariate regression analysis to examine the association of maternal health service readiness and quality indicators with client satisfaction.
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