Armstrong-Hough Mari, Kishore Sandeep P, Byakika Sarah, Mutungi Gerald, Nunez-Smith Marcella, Schwartz Jeremy I
Epidemiology of Microbial Diseases Department, Yale School of Public Health, New Haven, Connecticut, United States of America.
Arnhold Institute for Global Health, Mt. Sinai School of Medicine, New York, New York, United States of America.
PLoS One. 2018 Feb 8;13(2):e0192332. doi: 10.1371/journal.pone.0192332. eCollection 2018.
Although the WHO-developed Service Availability and Readiness Assessment (SARA) tool is a comprehensive and widely applied survey of health facility preparedness, SARA data have not previously been used to model predictors of readiness. We sought to demonstrate that SARA data can be used to model availability of essential medicines for treating non-communicable diseases (EM-NCD).
We fit a Poisson regression model using 2013 SARA data from 196 Ugandan health facilities. The outcome was total number of different EM-NCD available. Basic amenities, equipment, region, health facility type, managing authority, NCD diagnostic capacity, and range of HIV services were tested as predictor variables.
In multivariate models, we found significant associations between EM-NCD availability and region, managing authority, facility type, and range of HIV services. For-profit facilities' EM-NCD counts were 98% higher than public facilities (p < .001). General hospitals and referral health centers had 98% (p = .004) and 105% (p = .002) higher counts compared to primary health centers. Facilities in the North and East had significantly lower counts than those in the capital region (p = 0.015; p = 0.003). Offering HIV care was associated with 35% lower EM-NCD counts (p = 0.006). Offering HIV counseling and testing was associated with 57% higher counts (p = 0.048).
We identified multiple within-country disparities in availability of EM-NCD in Uganda. Our findings can be used to identify gaps and guide distribution of limited resources. While the primary purpose of SARA is to assess and monitor health services readiness, we show that it can also be an important resource for answering complex research and policy questions requiring multivariate analysis.
虽然世界卫生组织开发的服务可用性和准备情况评估(SARA)工具是一项全面且广泛应用的卫生设施准备情况调查,但SARA数据此前未被用于构建准备情况的预测模型。我们试图证明SARA数据可用于构建治疗非传染性疾病基本药物(EM-NCD)的可用性模型。
我们使用来自乌干达196家卫生设施的2013年SARA数据拟合了一个泊松回归模型。结果变量是可用的不同EM-NCD的总数。将基本便利设施、设备、地区、卫生设施类型、管理机构、非传染性疾病诊断能力以及艾滋病毒服务范围作为预测变量进行测试。
在多变量模型中,我们发现EM-NCD可用性与地区、管理机构、设施类型以及艾滋病毒服务范围之间存在显著关联。营利性设施的EM-NCD数量比公共设施高98%(p < 0.001)。与初级卫生中心相比,综合医院和转诊卫生中心的数量分别高98%(p = 0.004)和105%(p = 0.002)。北部和东部的设施数量明显低于首都地区的设施(p = 0.015;p = 0.003)。提供艾滋病毒护理与EM-NCD数量降低35%相关(p = 0.006)。提供艾滋病毒咨询和检测与数量增加57%相关(p = 0.048)。
我们发现乌干达国内在EM-NCD可用性方面存在多种差异。我们的研究结果可用于识别差距并指导有限资源的分配。虽然SARA的主要目的是评估和监测卫生服务准备情况,但我们表明它也可以成为回答需要多变量分析的复杂研究和政策问题的重要资源。