TY - JOUR
T1 - Disparities in Availability of Essential Medicines to Treat Non-communicable Diseases in Uganda: A Cross-sectional Poisson Analysis Using the 2013 Service Availability and Readiness Assessment
AU - Armstrong-Hough, M.
AU - Kishore, S.
AU - Schwartz, Jeremy
PY - 2017/4/7
Y1 - 2017/4/7
N2 - Background: The most widely endorsed methodology used to collect data on health system readiness is the Service Availability and Readiness Assessment (SARA), a comprehensive survey of health facility preparedness, developed by the World Health Organization. SARA data have not previously been used to model and analyze the predictors of readiness indicators measured in the survey. We sought to demonstrate that SARA data can be used in this way by modeling the availability of essential medicines for treating non-communicable diseases (EM-NCD). Methods: We built a Poisson regression model using data collected at 196 Ugandan health facilities in the 2013 SARA survey. Our outcome of interest was the number of different EM-NCD available in each facility. Basic amenities, basic equipment, region, health facility type, managing authority, capacity for diagnosing NCDs, and range of HIV services were used as predictor variables. Findings: Adjusting for basic amenities, basic equipment, and capacity for diagnosing NCDs, our final model indicates significant associations between EM-NCD availability and geographic region, health facility type, managing authority, and range of HIV services. Adjusting for other variables such as facility type and amenities, private for-profit facilities' number of EM-NCD is 124% higher on average than public facilities (p
AB - Background: The most widely endorsed methodology used to collect data on health system readiness is the Service Availability and Readiness Assessment (SARA), a comprehensive survey of health facility preparedness, developed by the World Health Organization. SARA data have not previously been used to model and analyze the predictors of readiness indicators measured in the survey. We sought to demonstrate that SARA data can be used in this way by modeling the availability of essential medicines for treating non-communicable diseases (EM-NCD). Methods: We built a Poisson regression model using data collected at 196 Ugandan health facilities in the 2013 SARA survey. Our outcome of interest was the number of different EM-NCD available in each facility. Basic amenities, basic equipment, region, health facility type, managing authority, capacity for diagnosing NCDs, and range of HIV services were used as predictor variables. Findings: Adjusting for basic amenities, basic equipment, and capacity for diagnosing NCDs, our final model indicates significant associations between EM-NCD availability and geographic region, health facility type, managing authority, and range of HIV services. Adjusting for other variables such as facility type and amenities, private for-profit facilities' number of EM-NCD is 124% higher on average than public facilities (p
UR - https://www.mendeley.com/catalogue/154551c0-4a1e-307b-a1df-72fc8248224b/
U2 - 10.1016/j.aogh.2017.03.309
DO - 10.1016/j.aogh.2017.03.309
M3 - Article
SN - 0027-2507
VL - 83
SP - 138
JO - Annals of Global Health
JF - Annals of Global Health
IS - 1
ER -