Streamlining data recording through optical character recognition: a prospective multi-center study in intensive care
Prompak Nitayavardhana1, Keibun Liu2,3,4, Kiyomitsu Fukaguchi5,6
1Division of Cardiothoracic Surgery, Department of Surgery, Faculty of Medicine, Siriraj Hospital, Bangkok, Thailand.
Critical Care (London, England)
|March 19, 2025
Summary
Optical character recognition (OCR) systems streamline clinical data entry, significantly reducing time and errors. This technology enhances data completeness and accuracy, improving patient database management.
Area of Science:
- Medical Informatics
- Clinical Data Management
- Health Technology Assessment
Background:
- Manual data entry into large patient databases is resource-intensive and time-consuming.
- Optical Character Recognition (OCR) technology offers potential to improve data entry efficiency and accuracy.
- Reducing the burden on healthcare personnel is a key objective in clinical data management.
Purpose of the Study:
- To evaluate the effectiveness of an OCR-enhanced system for clinical data entry.
- To compare data completeness, accuracy, and time efficiency against manual data entry methods.
- To assess user satisfaction with the OCR-based data entry tool.
Main Methods:
- A prospective, multi-center observational study was conducted in intensive care units (ICUs) across 3 countries.
- Critically-ill patients requiring invasive mechanical ventilation and extracorporeal life support were included.
- Clinical photos were uploaded via an OCR-enhanced case record form and compared to manual entry.
Main Results:
- The OCR system demonstrated high data completeness (98.5%) and accuracy (96.9%) in validation.
- Data entry time was significantly reduced by an average of 43.9% compared to manual methods.
- User satisfaction was high, with an overall recommendation rate of 4.25 out of 5.
Conclusions:
- OCR-based data entry systems effectively and efficiently facilitate data entry into clinical databases.
- These systems represent a promising tool for future clinical data management and research.
- Encouraging wider adoption of OCR systems can enhance understanding of their clinical and research applications.
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