基于短信和互联网的自我报告系统,加强疫苗安全性监测,美国大型综合医疗保健系统的启示:前瞻性队列研究。

IF 5.4 2区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
Debbie E Malden, Julianne Gee, Sungching Glenn, Zhuoxin Li, Denison S Ryan, Zheng Gu, Cassandra Bezi, Sunhea Kim, Amelia Jazwa, Michael M McNeil, Eric S Weintraub, Sara Y Tartof
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引用次数: 0

摘要

背景:基于短信和互联网的自我报告系统可以补充现有的疫苗安全监测系统,但实际参与模式尚未得到大规模评估:基于短信和互联网的自我报告系统可以补充现有的疫苗安全监控系统,但实际参与模式尚未得到大规模评估:本研究旨在描述一个大型综合医疗保健系统中名为 "Kaiser Permanente Side Effect Monitor (KPSEM) "的新型短信和互联网自我报告系统的参与率:我们对 2021 年 4 月 23 日至 2023 年 7 月 31 日期间接种 COVID-19 疫苗的南加州凯泽医疗集团(KPSC)患者进行了一项前瞻性队列研究。患者通过传单、短信、电子邮件或患者医疗保健门户网站收到邀请。在同意接种后,患者会收到定期调查,以评估每次接种后 5 周内的不良反应。与医疗记录的链接提供了人口统计学和临床数据。在本研究中,我们描述了 KPSEM 的参与率,即在接种 COVID-19 疫苗后 35 天内提供同意并完成至少一次调查:约有 8%(164,636 人/2,091,975 人)的疫苗接种患者在 35 天内表示同意并完成至少一次调查。参与率最低的是 12-17 岁儿童的父母(1349/152928,参与率为 0.9%),参与率最高的是 61-70 岁的老年人(39844/329,487,参与率为 12.1%)。与其他种族和族裔相比,非西班牙裔白种人更有可能参与(分别为 13.1% vs 3.9%-7.5%; PConclusions:这项真实世界的前瞻性研究表明,通过综合医疗保健系统实施的新型数字化疫苗安全自我报告系统可以达到很高的参与率。与参与者电子健康记录的链接是该监测系统的另一个独特优势。我们还发现某些弱势群体的参与率较低,这可能会对解释从类似数字系统收集的数据产生影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Texting- and Internet-Based Self-Reporting System for Enhanced Vaccine Safety Surveillance With Insights From a Large Integrated Health Care System in the United States: Prospective Cohort Study.

Background: SMS text messaging- and internet-based self-reporting systems can supplement existing vaccine safety surveillance systems, but real-world participation patterns have not been assessed at scale.

Objective: This study aimed to describe the participation rates of a new SMS text messaging- and internet-based self-reporting system called the Kaiser Permanente Side Effect Monitor (KPSEM) within a large integrated health care system.

Methods: We conducted a prospective cohort study of Kaiser Permanente Southern California (KPSC) patients receiving a COVID-19 vaccination from April 23, 2021, to July 31, 2023. Patients received invitations through flyers, SMS text messages, emails, or patient health care portals. After consenting, patients received regular surveys to assess adverse events up to 5 weeks after each dose. Linkage with medical records provided demographic and clinical data. In this study, we describe KPSEM participation rates, defined as providing consent and completing at least 1 survey within 35 days of COVID-19 vaccination.

Results: Approximately, 8% (164,636/2,091,975) of all vaccinated patients provided consent and completed at least 1 survey within 35 days. The lowest participation rates were observed for parents of children aged 12-17 years (1349/152,928, 0.9% participation rate), and the highest participation was observed among older adults aged 61-70 years (39,844/329,487, 12.1%). Persons of non-Hispanic White race were more likely to participate compared with other races and ethnicities (13.1% vs 3.9%-7.5%, respectively; P<.001). In addition, patients residing in areas with a higher neighborhood deprivation index were less likely to participate (5.1%, 16,503/323,122 vs 10.8%, 38,084/352,939 in the highest vs lowest deprivation quintiles, respectively; P<.001). Invitations through the individual's Kaiser Permanente health care portal account and by SMS text message were associated with the highest participation rate (19.2%, 70,248/366,377 and 10.5%, 96,169/914,793, respectively), followed by email (19,464/396,912, 4.9%) and then QR codes on flyers (25,882/2,091,975, 1.2%). SMS text messaging-based surveys demonstrated the highest sustained daily response rates compared with internet-based surveys.

Conclusions: This real-world prospective study demonstrated that a novel digital vaccine safety self-reporting system implemented through an integrated health care system can achieve high participation rates. Linkage with participants' electronic health records is another unique benefit of this surveillance system. We also identified lower participation among selected vulnerable populations, which may have implications when interpreting data collected from similar digital systems.

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来源期刊
JMIR mHealth and uHealth
JMIR mHealth and uHealth Medicine-Health Informatics
CiteScore
12.60
自引率
4.00%
发文量
159
审稿时长
10 weeks
期刊介绍: JMIR mHealth and uHealth (JMU, ISSN 2291-5222) is a spin-off journal of JMIR, the leading eHealth journal (Impact Factor 2016: 5.175). JMIR mHealth and uHealth is indexed in PubMed, PubMed Central, and Science Citation Index Expanded (SCIE), and in June 2017 received a stunning inaugural Impact Factor of 4.636. The journal focusses on health and biomedical applications in mobile and tablet computing, pervasive and ubiquitous computing, wearable computing and domotics. JMIR mHealth and uHealth publishes since 2013 and was the first mhealth journal in Pubmed. It publishes even faster and has a broader scope with including papers which are more technical or more formative/developmental than what would be published in the Journal of Medical Internet Research.
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