基于社区的远程医疗项目留存率的预测因素:老年人远程医疗干预项目(TIPS)研究
Predictors of Retention for Community-Based Telehealth Programs: A Study of the Telehealth Intervention Program for Seniors (TIPS).
作者信息
Schiaffino Melody K, Zhang Zhan, Sachs David, Migliaccio John, Huh-Yoo Jina
机构信息
School of Public Health, San Diego State University, San Diego, CA.
School of Computer Science and Information Systems, Pace University, New York, NY.
出版信息
AMIA Annu Symp Proc. 2022 Feb 21;2021:1089-1098. eCollection 2021.
Community-based telehealth programs (CTPs) allow patients to regularly monitor health at community-based facilities. Evidence from community-based telehealth programs is scarce. In this paper, we assess factors of retention-patients remaining active participants-in a CTP called the Telehealth Intervention Programs for Seniors (TIPS). We analyzed 5-years of data on social, demographic, and multiple chronic conditions among participants from 17 sites (N=1878). We modeled a stratified multivariable logistic regression to test the association between self-reported demographic factors, caregiver status, presence of multiple chronic conditions, and TIPS retention status by limited English proficient (LEP) status. Overall, 59.5% of participants (mean age: 75.8yrs, median 77yrs, SD 13.43) remained active. Significantly higher odds of retention were observed among LEP females, English-speaking diabetics, and English proficient (EP) participants without a caregiver. We discuss the impact of CTPs in the community, the role of caregiving, and recommendations for how to retain successfully recruited non-English speaking participants.
基于社区的远程医疗项目(CTP)使患者能够在社区设施中定期监测健康状况。关于基于社区的远程医疗项目的证据很少。在本文中,我们评估了名为“老年人远程医疗干预项目”(TIPS)的一个CTP中患者留存率的相关因素,即患者持续作为活跃参与者的情况。我们分析了来自17个地点的参与者(N = 1878)的5年社会、人口统计学和多种慢性病数据。我们建立了一个分层多变量逻辑回归模型,以检验自我报告的人口统计学因素、照顾者状况、多种慢性病的存在情况以及按英语水平有限(LEP)状态划分的TIPS留存状态之间的关联。总体而言,59.5%的参与者(平均年龄:75.8岁,中位数77岁,标准差13.43)仍保持活跃。在LEP女性、说英语的糖尿病患者以及没有照顾者的英语熟练(EP)参与者中,观察到留存率显著更高。我们讨论了CTP在社区中的影响、照顾的作用以及关于如何留住成功招募的非英语参与者的建议。