tetano
Editor, Senior Moderator
PLoS One
. 2025 Jan 3;20(1):e0312050.
doi: 10.1371/journal.pone.0312050. eCollection 2025. Investigating the point prevalence, types, severity, causes and predictors of vaccines administration errors during COVID-19 pandemic in Jordan
Derar H Abdel-Qader[SUP] 1 2 [/SUP], Hasan Abdel-Qader[SUP] 3 [/SUP], Jennifer Silverthorne[SUP] 4 [/SUP], Chuenjid Kongkaew[SUP] 5 [/SUP], Moh'd Al Nimrawi[SUP] 6 [/SUP], Ahmad Z Al Meslamani[SUP] 7 8 [/SUP], Nathir M Obeidat[SUP] 9 [/SUP], Wail Hayajneh[SUP] 10 11 [/SUP], Feras Hawari[SUP] 3 [/SUP], Souraya Z Arabi[SUP] 12 [/SUP], Salahdein AbuRuz[SUP] 13 [/SUP]
Affiliations
Background: 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.
Method: 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.
Results: 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.
Conclusion: 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.
. 2025 Jan 3;20(1):e0312050.
doi: 10.1371/journal.pone.0312050. eCollection 2025. Investigating the point prevalence, types, severity, causes and predictors of vaccines administration errors during COVID-19 pandemic in Jordan
Derar H Abdel-Qader[SUP] 1 2 [/SUP], Hasan Abdel-Qader[SUP] 3 [/SUP], Jennifer Silverthorne[SUP] 4 [/SUP], Chuenjid Kongkaew[SUP] 5 [/SUP], Moh'd Al Nimrawi[SUP] 6 [/SUP], Ahmad Z Al Meslamani[SUP] 7 8 [/SUP], Nathir M Obeidat[SUP] 9 [/SUP], Wail Hayajneh[SUP] 10 11 [/SUP], Feras Hawari[SUP] 3 [/SUP], Souraya Z Arabi[SUP] 12 [/SUP], Salahdein AbuRuz[SUP] 13 [/SUP]
Affiliations
- PMID: 39752371
- DOI: 10.1371/journal.pone.0312050
Background: 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.
Method: 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.
Results: 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.
Conclusion: 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.