Streamlining data recording through optical character recognition: a prospective multi-center study in intensive care units

Abstract

BACKGROUND: The manual entry of data into large patient databases requires significant resources and time. It is possible that a system that is enhanced with the technology of optical character recognition (OCR) can facilitate data entry, reduce data entry errors, and decrease the burden on healthcare personnel. METHODS: This was a prospective multi-center observational study across intensive care units (ICU) in 3 countries. Subjects were critically-ill and required invasive mechanical ventilation and extracorporeal life support. Clinical photos from various medical devices were uploaded using an OCR-enhanced case record form. The degree of data completeness, data accuracy, and time saved in entering data were compared with conventional manual data entry. RESULTS: The OCR-based system was developed with 868 photos and validated with 469 photos. In independent validation by 8 untrained personnel involving 1018 data points, the overall data completeness was 98.5% (range 98.2-100%), while the overall data accuracy was 96.9% (range 95.3-100%). It significantly reduced data entry time compared to manual entry (mean reduction 43.9% [range 27.0-1.1%]). The average data entry time needed per patient were 3.4 (range 1.2-5.9) minutes with the OCR-based system, compared with 6.0 (range 2.2-8.1) minutes with manual data entry. Users reported high satisfaction with the tool, with an overall recommendation rate of 4.25 ± 1.04 (maximum of 5). CONCLUSION: An OCR-based data entry system can effectively and efficiently facilitate data entry into clinical databases, making it a promising tool for future clinical data management. Wider uptake of these systems should be encouraged to better understand their strengths and limitations in both clinical and research settings.

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