Abdel-Qader Derar H, Abdel-Qader Hasan, Silverthorne Jennifer, Kongkaew Chuenjid, Al Nimrawi Moh'd, Al Meslamani Ahmad Z, Obeidat Nathir M, Hayajneh Wail, Hawari Feras, Arabi Souraya Z, AbuRuz Salahdein
Faculty of Pharmacy & Medical Sciences, University of Petra, Amman, Jordan.
Al Rashid Hospital Center, Amman, Jordan.
PLoS One. 2025 Jan 3;20(1):e0312050. doi: 10.1371/journal.pone.0312050. eCollection 2025.
There is a paucity of research regarding COVID-19 vaccines administration errors (VAEs) during the COVID-19 pandemic. This study aimed to investigate the prevalence, types, severity, causes and predictors of VAEs in Jordan during the recent pandemic.
This was a 3-day (Sunday, Tuesday and Thursday of the third week of November 2021) prospective, covert observational point prevalence study. It involved direct observation of vaccination administration practices by covert observers who recorded data on a standardized form, documenting the administration process, observed errors, and contextual factors, such as workload, distractions, and interruptions directly after each observation. Univariate and multivariable logistic models were constructed in order to identify predictors of VAEs.
The point prevalence of VAEs was 2.4% (209 errors / 8743 vaccine doses). These VAEs were categorized into six types: timing (interval) error (69, 33.0%) dosing error (60, 28.7%), incorrect vaccine product (42, 20.1%), site/route error (17, 8.1%), documentation error (15, 7.2%), and other (6, 2.9%). Most errors were minor (133, 63.6%) and moderate (63, 30.1%). There were 174 (54.9%) healthcare provider-related contributing factors and 102 (32.2%) patient-related factors. Receiving the vaccine in the Southern region compared to Capital region (aOR: 1.92; 95% confidence intervals, 95%CI: 1.41-2.49; p = 0.001) and receiving the vaccine during peak hours compared to regular hours (aOR: 2.18; 95%CI: 1.58-3.86; p = 0.002) were significant predictors of VAEs.
Though infrequent, VAEs had prevalence higher than previously reported in the literature, posing serious public health challenges, which might have compromised immunization efficacy and patient safety. Identifying these errors' causes and formulating strategies to reduce them is crucial for enhancing vaccination results.
关于新冠疫情期间新冠疫苗接种管理错误(VAE)的研究较少。本研究旨在调查近期疫情期间约旦VAE的发生率、类型、严重程度、原因及预测因素。
这是一项为期3天(2021年11月第三周的周日、周二和周四)的前瞻性、隐蔽观察性现况研究。研究包括由隐蔽观察者直接观察疫苗接种管理操作,观察者使用标准化表格记录数据,记录接种过程、观察到的错误以及诸如工作量、干扰和每次观察后直接出现的中断等背景因素。构建单变量和多变量逻辑模型以识别VAE的预测因素。
VAE的现况发生率为2.4%(209例错误/8743剂疫苗)。这些VAE分为六种类型:时间(间隔)错误(69例,33.0%)、剂量错误(60例,28.7%)、疫苗产品错误(42例,20.1%)、接种部位/途径错误(17例,8.1%)、记录错误(15例,7.2%)和其他(6例,2.9%)。大多数错误为轻微(133例,63.6%)和中度(63例,30.1%)。有174个(54.9%)与医护人员相关的促成因素和102个(32.2%)与患者相关的因素。与首都地区相比,在南部地区接种疫苗(调整后比值比:1.92;95%置信区间,95%CI:1.41 - 2.49;p = 0.001)以及与正常时间相比在高峰时段接种疫苗(调整后比值比:2.18;95%CI:1.58 - 3.86;p = 0.002)是VAE的显著预测因素。
尽管VAE不常见,但其发生率高于文献中先前报道的水平,带来了严重的公共卫生挑战,这可能会损害免疫效果和患者安全。识别这些错误的原因并制定减少错误的策略对于提高疫苗接种效果至关重要。