Atrium Health, Department of Community Health, Charlotte, NC, United States of America.
University of South Carolina, Department of Epidemiology and Biostatistics, Arnold School of Public Health, Columbia, SC, United States of America.
Am J Emerg Med. 2021 Aug;46:225-232. doi: 10.1016/j.ajem.2020.07.034. Epub 2020 Jul 19.
To examine whether and how avoidable emergency department (ED) utilization is associated with ambulatory or primary care (APC) utilization, insurance, and interaction effects.
A cross-sectional analysis of electronic health records from 70,870 adults residing in Mecklenburg County, North Carolina, who visited an ED within a large integrated healthcare system in 2017.
APC utilization was measured as total visits, categorized as: 0, 1, and > 1. Insurance was defined as the method of payment for the ED visit as: Medicaid, Medicare, private, or uninsured. Avoidable ED utilization was quantified as a score (aED), calculated as the sum of New York University Algorithm probabilities multiplied by 100. Quantile regression models were used to predict the 25th, 50th, 75th, 95th, and 99th percentiles of avoidable ED scores with APC visits and insurance as predictors (Model 1) and with an interaction term (Model 2).
Having >1 APC visit was negatively associated with aED at the lower percentiles and positively associated at higher percentiles. A higher aED was associated with having Medicaid insurance and a lower aED was associated with having private insurance, compared to being uninsured. In stratified models, having >1 APC visit was negatively associated with aED at the 25th percentile for the uninsured and privately insured, but positively associated with aED at higher percentiles among the uninsured, Medicaid-insured, and privately insured.
The association between APC utilization and avoidable ED utilization varied based on segments of the distribution of ED score and differed significantly by insurance type.
研究可避免的急诊(ED)就诊是否与以及如何与门诊或初级保健(APC)就诊、保险相关,并探讨其中的交互作用。
这是一项对 2017 年居住在北卡罗来纳州梅克伦堡县、在大型综合医疗保健系统内的 70870 名成年人的电子健康记录进行的横断面分析。
APC 就诊次数作为总就诊次数进行测量,分为:0、1 和>1。保险定义为 ED 就诊的支付方式:医疗补助、医疗保险、私人保险或无保险。可避免的 ED 就诊次数通过纽约大学算法概率的乘积乘以 100 来量化(aED)。使用分位数回归模型预测 APC 就诊次数和保险作为预测因子(模型 1)和交互项(模型 2)的情况下,aED 分数的 25%、50%、75%、95%和 99%分位数。
APC 就诊次数超过 1 次与较低分位的 aED 呈负相关,与较高分位的 aED 呈正相关。与无保险相比,aED 较高者的医疗保险,aED 较低者的私人保险。在分层模型中,无保险和私人保险的 APC 就诊次数超过 1 次与 aED 的 25%分位呈负相关,而无保险、医疗补助保险和私人保险的 aED 较高分位呈正相关。
APC 就诊与 ED 可避免就诊之间的关联基于 ED 评分分布的不同部分而有所不同,且与保险类型显著不同。