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1.
Appl Clin Inform ; 15(2): 265-273, 2024 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-38286429

RESUMO

BACKGROUND: Manual data entry is time-consuming, inefficient, and error prone. In contrast, leveraging two-dimensional (2D) barcodes and barcode scanning tools is a rapid and effective practice for automatically entering vaccine data accurately and completely. CDC pilots documented clinical and public health impacts of 2D barcode scanning practices on data quality and completeness, time savings, workflow efficiencies, and staff experience. OBJECTIVES: Data entry practices and entered records from routine and mass vaccination settings were analyzed. Data quality improvement opportunities were identified. METHODS: A sample of 50 million emergency use authorization (EUA) coronavirus disease 2019 (COVID-19) vaccine records were analyzed for accuracy and completeness across three data fields: lot number, expiration date, and National Drug Code (NDC). The EUA COVID-19 vaccines lacked a 2D barcode containing these data fields, which necessitated manual data entry at administration. A CDC pilot at clinic compared scanned and manually entered data for routine vaccines across these same data fields. RESULTS: Analysis of 50 million manually entered EUA COVID-19 vaccine administration records indicated significant gaps in data accuracy and completeness across three data fields. Over half of the analyzed EUA vaccine NDCs (53%) and one-third of the expiration dates (35%) had missing or inaccurate data recorded. Pilot data also showed many errors when manually entered. However, when the pilot's routine vaccines were scanned (out of 71,969 records), nearly all entries were complete and accurate across all three data fields (ranging from 99.7% to 99.999% accurate). CONCLUSION: Vaccine 2D barcode scanning practices increased data accuracy and completeness (up to 99.999% accurate) across data fields assessed. When used consistently, vaccine 2D barcode scanning can resolve issues demonstrated in manually entered data. To realize these benefits, the immunization community should widely use scanning practices. To increase use, CDC developed a Vaccine 2D Barcode National Adoption Strategy and implementation resources.


Assuntos
Confiabilidade dos Dados , Vacinas , Humanos , Vacinas contra COVID-19 , Imunização , Instituições de Assistência Ambulatorial , Atenção à Saúde
2.
J Healthc Qual ; 43(1): 39-47, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-32544140

RESUMO

BACKGROUND: Recording vaccine data accurately can be problematic in medical documentation, including blank and inaccurate records. Vaccine two-dimensional (2D) barcode scanning has shown promise, yet scanner use to record vaccine data is limited. We sought to identify strategies to improve scanning rates and assess changes in accuracy. METHODS: Between January and June 2017, 27 pilot sites within a large health system were assigned to one of four groups to test strategies to maximize scanner use: training only, commitment card, scanning report, or combination. Seventy-two thousand vaccine records were assessed for completeness, accuracy, and scanning. RESULTS: Significant increases in vaccinator scanning rates found with commitment card and scanning report inclusion (alone and paired) compared with the training-only group. Record completeness and accuracy significantly improved with use of scanning. When manually entered, about 1 in 9 records had a missing or inaccurate expiration date; when scanned, this dropped to 1 in 5,000. CONCLUSIONS: Pilot findings indicate 2D scanning has the potential to eliminate most omissions and inaccuracies in vaccine records. Such data are critical during a recall or need to trace specific vaccines or patients. IMPLICATIONS: Consistent use and expanded adoption of 2D scanning can meaningfully improve the quality of vaccine records and clinical practices.


Assuntos
Confiabilidade dos Dados , Documentação/normas , Rotulagem de Medicamentos/normas , Processamento Eletrônico de Dados/normas , Registros Eletrônicos de Saúde/normas , Vacinação/normas , Vacinas , Humanos , Projetos Piloto , Estados Unidos
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