Department of Industrial Engineering, Tsinghua University, Beijing 100084, China.
School of Business, Wake Forest University, Winston-Salem, NC 27106, United States.
Public Health. 2023 Aug;221:116-123. doi: 10.1016/j.puhe.2023.06.011. Epub 2023 Jun 9.
This study aimed to investigate how people's health-seeking behaviors evolve in the COVID-19 pandemic by community and medical service category.
This is a longitudinal study using mobility data from 19 million mobile devices of visits to all types of health facility locations for all US states.
We examine the variations in weekly in-person medical visits across county, neighborhood, and specialty levels. Different regression models are used for each level to investigate factors that influence the disparities in medical visits. County-level analysis explores associations between county medical visit patterns, political orientation, and COVID-19 infection rate. Neighborhood-level analysis focuses on neighborhood socio-economic compositions as potential determinants of medical visit levels. Specialty-level analysis compares the evolution of visit disruptions in different specialties.
A more left-leaning political orientation and a higher local infection rate were associated with larger decreases in in-person medical visits, and these associations became stronger, moving from the initial period of stay-at-home orders into the post-lockdown period. Initial reactions were strongest for seniors and those of high socio-economic status, but this reversed in post-lockdown period where socio-economically disadvantaged communities stabilized at a lower level of medical visits. Neighborhoods with more female and young people exhibited larger decreases in in-person medical visits throughout the initial and post-lockdown periods. The evolution of disruptions diverges across medical specialties, from only short-term disruption in specialties such as dentistry to increasing disruption, as in cardiology.
Given distinct patterns in visit between communities, medical service categories, and between different periods in the pandemic, policy makers, and providers should concentrate on monitoring patients in disrupted specialties who overlap with the at-risk contexts and socio-economic factors in future health emergencies.
本研究旨在通过社区和医疗服务类别调查 COVID-19 大流行期间人们的就医行为如何演变。
这是一项使用来自全美 1900 万部移动设备的访问各类医疗设施地点的流动数据进行的纵向研究。
我们检查了县、邻里和专科各级每周当面就医次数的变化。使用不同的回归模型对每个级别进行分析，以调查影响医疗就诊差异的因素。县级分析探讨了县医疗就诊模式、政治倾向和 COVID-19 感染率之间的关联。邻里级分析侧重于邻里社会经济构成作为医疗就诊水平的潜在决定因素。专科级分析比较了不同专科就诊中断的演变。
更倾向于左派的政治倾向和更高的本地感染率与当面医疗就诊次数的减少呈正相关，而且这些关联在从居家令的初始阶段到封锁后的阶段变得更强。最初的反应在老年人和高社会经济地位的人中最强，但在封锁后的阶段，社会经济劣势社区稳定在较低的医疗就诊水平，这种反应发生了逆转。女性和年轻人较多的邻里地区在整个初始和封锁后阶段当面就医次数下降幅度更大。从仅在牙科等专科出现短期中断到像心脏病学那样中断增加，各医疗专科的中断演变存在差异。
鉴于社区、医疗服务类别之间以及大流行不同时期之间就诊之间存在明显差异，政策制定者和提供者应在未来的卫生紧急情况下，集中监测在受干扰的专科中与高危环境和社会经济因素重叠的患者。
