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预测南卡罗来纳州新冠疫苗接种移动健康诊所的利用率:战略资源分配的统计框架

Predicting mobile health clinic utilization for COVID-19 vaccination in South Carolina: A statistical framework for strategic resource allocation.

作者信息

Gezer Fatih, Howard Kerry A, Bennett Kevin J, Litwin Alain H, Sease Kerry K, Rennert Lior

机构信息

Department of Public Health Sciences, Clemson University, Clemson, South Carolina, United States of America.

Center for Public Health Modeling and Response, Clemson University, Clemson, South Carolina, United States of America.

出版信息

PLOS Glob Public Health. 2025 Jun 4;5(6):e0003837. doi: 10.1371/journal.pgph.0003837. eCollection 2025.

Abstract

Mobile health clinics (MHCs) are effective tools for providing health services to disadvantaged populations, especially during health emergencies. However, patient utilization of MHC services varies substantially. Strategies to increase utilization are needed to maximize the effectiveness of MHC services by serving more patients in need. The purpose of this study is to develop a statistical framework to identify and prioritize high-risk communities for delivery of MHCs during health emergencies. Prisma Health MHCs delivered COVID-19 vaccines to communities throughout South Carolina between February 20, 2021, and February 17, 2022. In this retrospective study, we used generalized linear mixed effects models and ordinal logistic regression models to identify factors associated with, and predictive of, MHC utilization for COVID-19 vaccination by census tract. The MHCs conducted 260 visits to 149 sites and 107 census tracts. The site-level analysis showed that visits to schools (RR = 2.17, 95% CI = 1.47-3.21), weekend visits (RR = 1.38, 95% CI = 1.03-1.83), and visits when the resources were limited (term 1: 7.11, 95% CI = 4.43-11.43) and (term 2: 2.40, 95% CI = 1.76-3.26) were associated with greater MHC utilization for COVID-19 vaccination. MHC placement near existing vaccination centers (RR = 0.79, 95% CI = 0.68-0.93) and hospitals (RR = 0.83, 95% CI = 0.71-0.96) decreased utilization. Predictive models identified 1,227 (94.7%) census tracts with more than 250 individuals per MHC visit when vaccine resources were limited. Predictions showed satisfactory accuracy (72.6%). The census tracts with potential of high MHC demand had higher adolescent, 30-44 years old, and non-White populations; lower Primary Care Practitioners per 1,000 residents; fewer hospitals; and higher cumulative COVID-19 emergency department visits and deaths (compared to census tracts with low MHC demand). After the vaccines became widely available, the demand at MHCs declined. These study findings can improve MHC allocation by identifying and prioritizing medically underserved communities for strategic delivery of these limited resources, especially during health emergencies.

摘要

移动健康诊所(MHCs)是为弱势群体提供健康服务的有效工具,尤其是在突发卫生事件期间。然而,患者对MHC服务的利用率差异很大。需要采取提高利用率的策略,以便通过为更多有需要的患者提供服务来最大限度地提高MHC服务的有效性。本研究的目的是建立一个统计框架,以确定在突发卫生事件期间提供MHC服务的高风险社区并对其进行优先排序。2021年2月20日至2022年2月17日期间,普isma健康移动健康诊所向南卡罗来纳州各地的社区提供了新冠疫苗。在这项回顾性研究中,我们使用广义线性混合效应模型和有序逻辑回归模型,按普查区确定与新冠疫苗接种的MHC利用率相关并可预测该利用率的因素。这些移动健康诊所对149个地点和107个普查区进行了260次访问。地点层面的分析表明,到学校的访问(相对风险=2.17,95%置信区间=1.47 - 3.21)、周末访问(相对风险=1.38,95%置信区间=1.03 - 1.83)以及资源有限时的访问(项1:7.11,95%置信区间=4.43 - 11.43)和(项2:2.40,95%置信区间=1.76 - 3.26)与新冠疫苗接种的MHC利用率更高相关。MHC设在现有疫苗接种中心附近(相对风险=0.79,95%置信区间=0.68 - 0.93)和医院附近(相对风险=0.83,95%置信区间=0.71 - 0.96)会降低利用率。预测模型确定了1227个(94.7%)普查区,在疫苗资源有限时,每个MHC访问点有超过250人。预测显示出令人满意的准确性(72.6%)。MHC需求潜力高的普查区青少年、30 - 44岁人群和非白人人口比例更高;每1000名居民中的初级保健医生人数更少;医院数量更少;以及新冠累计急诊就诊人数和死亡人数更多(与MHC需求低的普查区相比)。在疫苗广泛供应后,移动健康诊所的需求下降,这些研究结果可通过确定医疗服务不足社区并对其进行优先排序,以便战略性地分配这些有限资源,从而改善移动健康诊所的资源分配,尤其是在突发卫生事件期间。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed29/12136404/20066c19065b/pgph.0003837.g001.jpg

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