Participant characteristics by forgone care1.

Evidence suggests that reductions in healthcare utilization, including forgone care, during the COVID-19 pandemic may be contributing towards excess morbidity and mortality. The objective of this study was to describe individual and community-level correlates of forgone care during the COVID-19 pandemic. We conducted a cross-sectional, secondary data analysis of participants (n = 2,003) who reported needing healthcare in two population-representative surveys conducted in Baltimore, MD in 2021 and 2021–2022. Abstracted data included the experience of forgone care, socio-demographic data, comorbidities, financial strain, and community of residence. Participant’s community of residence were linked with data acquired from the Baltimore Neighborhood Indicators Alliance relevant to healthcare access and utilization, including walkability and internet access, among others. The data were analyzed using weighted random effects logistic regression. Individual-level factors found to be associated with increased odds for forgone care included individuals age 35–49 (compared to 18–34), female sex, experiencing housing insecurity during the pandemic, and the presence of functional limitations and mental illness. Black/African American individuals were found to have reduced odds of forgone care, compared to any other race. No community-level factors were significant in the multilevel analyses. Moving forward, it will be critical that health systems identify ways to address any barriers to care that populations might be experiencing, such as the use of mobile health services or telemedicine platforms. Additionally, public health emergency preparedness planning efforts must account for the unique needs of communities during future crises, to ensure that their health needs can continue to be met. Finally, additional research is needed to better understand how healthcare access and utilization practices have changed during versus before the pandemic.

有证据表明，在新冠疫情（COVID-19 pandemic）期间，医疗服务利用缩减（包括放弃就医）或可导致额外的发病率与死亡率。本研究旨在描述新冠疫情期间放弃就医行为的个体及社区层面关联因素。我们对2021年及2021-2022年在马里兰州巴尔的摩开展的两项人群代表性调查的参与者（n=2003）开展了横断面二次数据分析，这些参与者均报告存在医疗服务需求。提取的数据涵盖放弃就医经历、社会人口学资料、合并症、经济压力以及居住社区信息。研究人员将参与者的居住社区与巴尔的摩社区指标联盟（Baltimore Neighborhood Indicators Alliance）获取的医疗服务可及性与利用相关数据进行关联，此类数据包括可步行性、互联网接入情况等。本研究采用加权随机效应logistic回归（weighted random effects logistic regression）对数据进行分析。结果显示，与放弃就医风险升高相关的个体层面因素包括：年龄处于35-49岁区间者（相较于18-34岁人群）、女性、疫情期间经历住房不稳定、存在功能障碍与精神疾病。与其他种族相比，黑人/非裔美国人放弃就医的风险更低。多水平分析未发现具有统计学意义的社区层面因素。展望未来，医疗系统亟需探索解决人群面临的各类就医障碍的方案，例如应用移动医疗服务或远程医疗（telemedicine）平台。此外，公共卫生应急备灾规划需在未来的危机中充分考量社区的独特需求，以确保其健康需求得以持续满足。最后，仍需开展更多研究，以更清晰地理解疫情期间与疫情前相比，医疗服务可及性及利用行为发生的变化。