Dasgupta Sharoda, Kramer Michael R, Rosenberg Eli S, Sanchez Travis H, Sullivan Patrick S
Laney Graduate School, Emory University, Mailstop 1000-001-1AF, 209 Administration Building, 201 Dowman Drive, Atlanta, GA 30322 USA ; Department of Epidemiology, Rollins School of Public Health, Emory University, 1518 Clifton Road NE, Atlanta, GA 30329 USA.
Springerplus. 2016 Jul 4;5(1):984. doi: 10.1186/s40064-016-2515-8. eCollection 2016.
No existing measures of HIV care access consider both spatial proximity to services and provider-related characteristics in a single measure. We developed and applied a tool to: (1) quantify spatial access to HIV care services (supply) and (2) identify underserved areas with respect to HIV cases (demand), by travel mode, in Atlanta.
Building on a study of HIV care engagement, data from an HIV care provider database, and HIV case counts by zip code tabulation area (ZCTA) from AIDSVu.org, we fit a discrete choice model to estimate practice characteristics most salient in defining patient care access. Modified spatial gravity modeling quantified supply access based on discrete choice model results separately for travel by car and by public transportation. Relative access scores were calculated by ZCTA, and underserved areas (defined as having low supply access and high HIV case count) were identified for each travel mode.
Characteristics retained in the final model included: travel distance, available provider-hours, availability of ancillary services, and whether Ryan White patients were accepted. HIV provider supply was higher in urban versus suburban/rural areas for both travel modes, with lower supply access if traveling by public transportation. Underserved areas were concentrated in south and east Atlanta if traveling by public transportation, overlapping with many areas of high poverty. Approximately 7.7 %, if traveling by car, and 64.3 %, if traveling by public transportation, of Atlanta-based persons with diagnosed HIV infection resided in underserved areas.
These findings highlight underserved areas in south and east Atlanta if traveling by public transit. Conceptualizing access to medical services spatially and by travel mode may help bridge gaps between patient needs and service availability and improve HIV outcomes.
现有的艾滋病护理服务可及性衡量指标均未在单一指标中同时考虑到与服务机构的空间距离和提供者相关特征。我们开发并应用了一种工具，用于：（1）量化获得艾滋病护理服务（供给）的空间可及性，以及（2）确定亚特兰大地区在艾滋病病例（需求）方面交通方式不同的服务不足地区。
基于一项关于艾滋病护理参与情况的研究、一个艾滋病护理提供者数据库的数据以及来自AIDSVu.org按邮政编码分区（ZCTA）统计的艾滋病病例数，我们拟合了一个离散选择模型，以估计在定义患者获得护理服务方面最为显著的医疗机构特征。修正后的空间引力模型分别根据离散选择模型的结果，针对驾车和乘坐公共交通出行的情况量化供给可及性。通过ZCTA计算相对可及性得分，并针对每种交通方式确定服务不足地区（定义为供给可及性低且艾滋病病例数高的地区）。
最终模型中保留的特征包括：出行距离、医疗机构可用时长、辅助服务的可及性以及是否接收瑞安·怀特项目患者。对于两种交通方式，城市地区的艾滋病护理提供者供给均高于郊区/农村地区，乘坐公共交通出行时供给可及性较低。如果乘坐公共交通出行，服务不足地区集中在亚特兰大的南部和东部，与许多贫困程度高的地区重叠。在亚特兰大，确诊感染艾滋病病毒的患者中，约7.7%驾车出行时居住在服务不足地区，64.3%乘坐公共交通出行时居住在服务不足地区。
这些研究结果凸显了乘坐公共交通出行时亚特兰大南部和东部的服务不足地区。从空间和交通方式角度对获得医疗服务的可及性进行概念化，可能有助于弥合患者需求与服务可及性之间的差距，并改善艾滋病防治效果。
