Lineberger Comprehensive Cancer Center, North Carolina Cancer Hospital, Chapel Hill, NC, USA.
University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Support Care Cancer. 2021 Oct;29(10):6069-6077. doi: 10.1007/s00520-021-06147-3. Epub 2021 Mar 31.
The COVID-19 pandemic has exacerbated cancer treatment disparities, including accessibility to resources. We describe the process and outcomes of a new proactive, virtual nurse-led, resource center navigation model enhanced by using volunteer patient navigators. Using known patient risk factors, this model provides interventions to reduce barriers to care, with an emphasis on non-English-speaking populations.
Patients were included if they (1) were in active cancer treatment and (2) had one or more known risk factors: distance from cancer hospital, needing complex care, 65 years or older, malignant hematological diagnosis, new treatment start, lives alone, non-English speaker, or a new hospital discharge. Nurse navigators triaged referrals to appropriate team members who identified and addressed barriers to care.
The program engaged with 586 adult cancer patients over 1459 encounters. The most common risk factors included distance (59.7%), complex care (48.8%), and new treatment start (43.5%). The most common interventions were core education (69.4%), emotional support (61.2%), and education (35.7%). Statistical differences were found between Spanish-speaking (n = 118) and non-Spanish-speaking patients (n = 468). While Spanish-speaking patients had fewer risk factors (1.95 vs. 2.80, p ≤ .0001), they had nearly double the number of visits (4.27 vs. 2.04, p ≤ .0001) and 69% more interventions (8.26 vs. 4.90, p ≤ .0001). Many patients (42.7%) required follow-up visits.
We successfully established a new navigation model for the resource center during the pandemic that identified and reduced barriers to care, particularly in the Spanish-speaking population.
COVID-19 大流行加剧了癌症治疗方面的差异,包括获取资源的机会。我们描述了一种新的积极主动的、虚拟护士主导的、资源中心导航模式的过程和结果,该模式通过使用志愿者患者导航员得到了增强。利用已知的患者风险因素,该模型提供了减少护理障碍的干预措施,重点关注非英语患者。
如果患者(1)正在接受癌症的积极治疗,且(2)具有一个或多个已知的风险因素,包括距离癌症医院较远、需要复杂护理、年龄在 65 岁或以上、恶性血液病诊断、开始新的治疗、独居、非英语使用者或新的出院,则将其纳入研究。护士导航员对转介进行分类,将其分配给适当的团队成员,由这些团队成员确定并解决护理障碍。
该项目在 1459 次就诊中与 586 名成年癌症患者进行了互动。最常见的风险因素包括距离较远(59.7%)、复杂护理(48.8%)和新的治疗开始(43.5%)。最常见的干预措施是核心教育(69.4%)、情感支持(61.2%)和教育(35.7%)。西班牙语患者(n = 118)和非西班牙语患者(n = 468)之间存在统计学差异。尽管西班牙语患者的风险因素较少(1.95 比 2.80,p ≤.0001),但他们的就诊次数几乎翻了一番(4.27 比 2.04,p ≤.0001),干预措施增加了 69%(8.26 比 4.90,p ≤.0001)。许多患者(42.7%)需要随访就诊。
我们在大流行期间成功地为资源中心建立了一种新的导航模式,该模式确定并减少了护理障碍,特别是在西班牙语患者中。