Patient-related barriers to some virtual healthcare services among cancer patients in the USA: a population-based study
Patient-related barriers to some virtual healthcare services among cancer patients in the USA: a population-based study
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DOI：
10.2217/cer-2020-0187
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发表时间：
2021-01-15
影响因子：
2.1
通讯作者：
Abdel-Rahman, Omar
中科院分区：
文献类型：
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作者：
Abdel-Rahman, Omar
目的：评估美国癌症患者在基于人群的队列中使用某些虚拟医疗保健工具的患者相关障碍。材料与方法：审查了国家健康访谈调查数据集（2011-2018年），并纳入了具有癌症诊断史和关于虚拟医疗保健利用（定义为[a]在过去12个月内在互联网上填写处方和/或[B]在过去12个月内通过电子邮件与医疗保健提供者通信）的完整信息的成年参与者（>= 18岁）。关于视频会议电话和电话的信息在国家健康访谈调查数据集中不可用;因此，本研究未对其进行检查。多变量逻辑回归分析被用来评估与虚拟护理工具的利用相关的因素。结果如下：当前分析共纳入25，121名参与者;其中4499名参与者（17.9%）在过去12个月内使用过虚拟护理，20，622名参与者（82.1%）在过去12个月内没有使用虚拟护理。在多变量逻辑回归中，以下因素与虚拟医疗保健工具的使用率较低相关：（随年龄增长的连续比值比[OR]：0.987; 95% CI：0.984-0.990），非裔美国人（非裔美国人vs白色人种的OR：0.608; 95% CI：0.517-0.715），未婚状态（未婚与已婚相比的OR：0.689; 95%CI：0.642-0.739），教育水平较低（教育高中OR：0.284; 95%CI：0.259-0.311），英语能力较弱（不熟练与非常熟练的OR：0.224; 95%CI：0.091-0.552）和较低的年收入（收入45，000的OR：0.582; 95%CI：0.523-0.647）。总结：年龄较大的患者，非裔美国人种族，教育程度较低，收入较低和英语水平较低的患者不太可能使用上述研究的虚拟医疗保健工具。需要进一步努力解决远程医疗获取方面的差距。
Objective: To assess the patient-related barriers to access of some virtual healthcare tools among cancer patients in the USA in a population-based cohort. Materials & methods: National Health Interview Survey datasets (2011-2018) were reviewed and adult participants (>= 18 years old) with a history of cancer diagnosis and complete information about virtual healthcare utilization (defined by [a] filling a prescription on the internet in the past 12 months and/or [b] communicating with a healthcare provider through email in the past 12 months) were included. Information about video-conferenced phone calls and telephone calls are not available in the National Health Interview Survey datasets; and thus, they were not examined in this study. Multivariable logistic regression analysis was used to evaluate factors associated with the utilization of virtual care tools. Results: A total of 25,121 participants were included in the current analysis; including 4499 participants (17.9%) who utilized virtual care in the past 12 months and 20,622 participants (82.1%) who did not utilize virtual care in the past 12 months. The following factors were associated with less utilization of virtual healthcare tools in multivariable logistic regression: older age (continuous odds ratio [OR] with increasing age: 0.987; 95% CI: 0.984-0.990), African-American race (OR for African American vs white race: 0.608; 95% CI: 0.517-0.715), unmarried status (OR for unmarried compared with married status: 0.689; 95% CI: 0.642-0.739), lower level of education (OR for education high school: 0.284; 95% CI: 0.259-0.311), weaker English proficiency (OR for no proficiency vs very good proficiency: 0.224; 95% CI: 0.091-0.552) and lower yearly earnings (OR for earnings 45,000: 0.582; 95% CI: 0.523-0.647). Conclusion: Older patients, those with African-American race, lower education, lower earnings and weak English proficiency are less likely to access the above studied virtual healthcare tools. Further efforts are needed to tackle disparities in telemedicine access.