Interim emergency guidelines
Johnson CC et al. Journal of the International AIDS Society 2017, 20:21594 http://www.jiasociety.org/index.php/jias/article/view/21594 | https://doi.org/10.7448/IAS.20.1.21594
The TB section of the toolkit presents selected (a) programmatic output and (b) outcome and impact indicators for TB. In addition to recommended monitoring programs and measuring the outcomes and impact of TB programs, indicators for the strengthening of health systems, strengthening of community sy...stems and some indicators that measure quality of services are also included.
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Downloaded from https://aidsinfo.nih.gov/guidelines on 10/19/2019
Developed by the HHS Panel on Antiretroviral Therapy and Medical Management of Children Living with HIV—A Working Group of the Office
of AIDS Research Advisory Council (OARAC)
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, 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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Submitted to the US Agency for International Development by the Systems for Improved Access to Pharmaceuticals and Services (SIAPS) Program.
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 facility delive...ry, 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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Case Study on Improving HIV Testing and Services for Children Orphaned or made Vulnerable by HIV (OVC)
Towards the Peoples Health Assembly Book - 4
J Nepal Health Res Counc 2012 May;10(21):82-87
Barriers to HIV Services and Treatment for Persons with Disabilities in Zambia
The 80-page report documents the obstacles faced by people with disabilities in both the community and healthcare settings. These include pervasive stigma and discrimination, lack of access to inclusive HIV prevention ed...ucation, obstacles to accessing voluntary testing and HIV treatment, and lack of appropriate support for adherence to antiretroviral treatment. The report also describes the sexual and intimate partner violence women and girls with disabilities face, and the need for the government and international donors to do more to ensure inclusive and accessible HIV services.
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DHS Methodological Report No. 20
This study used Service Provision Assessment (SPA) and Demographic and Health Survey (DHS) data from Haiti, Malawi, and Tanzania to compare traditionally used additive methods with a data reduction method—principal component analysis (PCA).
We scored ...the quality of health facilities with three approaches (simple additive, weighted additive, and PCA) for two constructs: quality of services, with only facilities-level data, and quality of care, which incorporates observation and client data. We ranked facilities as high, medium, or low quality based on their scores. Our results indicated that the rankings change with the scoring methodology. There was more consistency in the rankings of facilities by the simple additive and PCA methods than the weighted additive and PCA-based rankings. This may be due to the low factor loadings and little variance explained by the first component in the PCA. We aggregated facility scores to their respective DHS clusters (Haiti, Malawi) or regions (Tanzania) and geographically linked them to women interviewed in DHS surveys to test associations between the use of family planning services and the quality environment, as measured with each index.
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