Characterizing Health Care Delays and Interruptions in the United States During the COVID-19 Pandemic: Internet-Based, Cross-sectional Survey Study.
Characterizing Health Care Delays and Interruptions in the United States During the COVID-19 Pandemic: Internet-Based, Cross-sectional Survey Study.
复制标题
DOI：
10.2196/25446
复制
发表时间：
2021-05-19
影响因子：
7.4
通讯作者：
Veldhuis C
中科院分区：
文献类型：
--
作者：
Papautsky EL;Rice DR;Ghoneima H;McKowen ALW;Anderson N;Wootton AR;Veldhuis C
与以往的灾害相比，2019冠状病毒病大流行具有更广泛的地理传播范围和可能更持久的影响。针对COVID-19传播的必要预防措施导致现场卫生保健服务延迟，特别是在大流行开始时。在美国的样本中，我们检查了大流行开始时医疗保健延误（定义为取消和推迟）的比率，并描述了这种延误的原因。作为2020年4月在社交媒体上发布的一项基于互联网的调查的一部分，我们向美国的2570名参与者询问了因COVID-19大流行而导致的医疗保健延误。研究探讨了参与者的人口统计数据和自我报告的对总体健康状况和COVID-19大流行的担忧，这些都是医疗保健延误的重要决定因素。除了所有延误外，我们还关注了以下三种主要类型的延误，这是本研究的主要结果：牙科、预防和诊断护理延误。对于每个结果，我们使用双变量统计检验（t检验和卡方检验）和多元逻辑回归模型来确定哪些因素与医疗延误相关。报告的获得卫生保健的最大障碍是对SARS-CoV-2感染的恐惧（126/ 374,33.6%）。近一半（1227/2570,47.7%）的参与者报告说，他们经历了医疗保健延误。在经历过保健延误并进一步澄清其所经历的延误类型（921/1227,75.1%）的人中，报告的受延误影响最大的三种护理类型包括牙科（351/921,38.1%）、预防（269/921,29.2%）和诊断（151/921,16.4%）护理。logistic回归模型显示，年龄（P<.001）、性别认同（P<.001）、教育程度（P=.007）和自我报告的总体健康担忧（P<.001）与经历医疗保健延迟显著相关。自我报告的对一般健康的担忧与经历牙科护理的延迟呈负相关。然而，根据逻辑回归模型，该预测因子与诊断测试延迟呈正相关。此外，年龄与诊断测试的延迟呈正相关。预防护理延迟的多重逻辑回归中没有因素保持显著性，尽管种族和延迟之间存在趋势（有色人种比白人参与者经历的延迟更少），但不显著（P=.06）。从COVID-19病例最初激增中吸取的教训可以为未来潜在中断的系统性缓解战略提供信息。本研究通过探索这种延误的决定因素，解决了医疗保健延误的需求方面。需要对大流行期间的卫生保健延误进行更多研究，包括研究其对患者层面结果的短期和长期影响，如死亡率、发病率、精神健康、人们的生活质量和疼痛体验。
The COVID-19 pandemic has broader geographic spread and potentially longer lasting effects than those of previous disasters. Necessary preventive precautions for the transmission of COVID-19 has resulted in delays for in-person health care services, especially at the outset of the pandemic. Among a US sample, we examined the rates of delays (defined as cancellations and postponements) in health care at the outset of the pandemic and characterized the reasons for such delays. As part of an internet-based survey that was distributed on social media in April 2020, we asked a US–based convenience sample of 2570 participants about delays in their health care resulting from the COVID-19 pandemic. Participant demographics and self-reported worries about general health and the COVID-19 pandemic were explored as potent determinants of health care delays. In addition to all delays, we focused on the following three main types of delays, which were the primary outcomes in this study: dental, preventive, and diagnostic care delays. For each outcome, we used bivariate statistical tests (t tests and chi-square tests) and multiple logistic regression models to determine which factors were associated with health care delays. The top reported barrier to receiving health care was the fear of SARS-CoV-2 infection (126/374, 33.6%). Almost half (1227/2570, 47.7%) of the participants reported experiencing health care delays. Among those who experienced health care delays and further clarified the type of delay they experienced (921/1227, 75.1%), the top three reported types of care that were affected by delays included dental (351/921, 38.1%), preventive (269/921, 29.2%), and diagnostic (151/921, 16.4%) care. The logistic regression models showed that age (P<.001), gender identity (P<.001), education (P=.007), and self-reported worry about general health (P<.001) were significantly associated with experiencing health care delays. Self-reported worry about general health was negatively related to experiencing delays in dental care. However, this predictor was positively associated with delays in diagnostic testing based on the logistic regression model. Additionally, age was positively associated with delays in diagnostic testing. No factors remained significant in the multiple logistic regression for delays in preventive care, and although there was trend between race and delays (people of color experienced fewer delays than White participants), it was not significant (P=.06). The lessons learned from the initial surge of COVID-19 cases can inform systemic mitigation strategies for potential future disruptions. This study addresses the demand side of health care delays by exploring the determinants of such delays. More research on health care delays during the pandemic is needed, including research on their short- and long-term impacts on patient-level outcomes such as mortality, morbidity, mental health, people’s quality of life, and the experience of pain.
登录
查看更多内容
影响因子：
6.7
作者：
Marouf N;Cai W;Said KN;Daas H;Diab H;Chinta VR;Hssain AA;Nicolau B;Sanz M;Tamimi F
通讯作者：
Tamimi F
影响因子：
3.9
作者：
Coppock, Alexander
通讯作者：
Coppock, Alexander
影响因子：
5.5
作者：
Farley, Thomas A.;Dalal, Mehul A.;Frieden, Thomas R.
通讯作者：
Frieden, Thomas R.
影响因子：
9.7
作者：
Maciosek, Michael V.;Coffield, Ashley B.;Solberg, Leif I.
通讯作者：
Solberg, Leif I.
影响因子：
2.7
作者：
Flume, P;Gray, S;Virella-Lowell, I
通讯作者：
Virella-Lowell, I