Program Information
Biometrically Accepted Patient Records
A Basavatia1*, S Kalnicki2 , M Garg3 , J Fret4 , A Lukaj5 , R Yaparpalvi6 , L Hong7 , W Tome'8 , (1) ,,,(2) Montefiore Medical Center, Bronx, New York, (3) Montefiore Medical Center, Bronx, New York, (4) Montefiore Information Technology, Yonkers, New York, (5) Montefiore Medical Center, Bronx, New York, (6) Montefiore Medical Center, Bronx, NY, (7) Montefiore Medical Center, Bronx, NY, (8) Montefiore Medical Center/Albert Einstein College of Medicine, Bronx, New York
Presentations
SU-E-T-502 Sunday 3:00PM - 6:00PM Room: Exhibit HallPurpose: To implement a clinically useful palm vein pattern recognition biometric system to treat the correct treatment plan to the correct patient each and every time and to check-in the patient into the department to access the correct medical record.
Methods: A commercially available hand vein scanning system was paired to Aria and utilized an ADT interface from the hospital electronic health system. Integration at two points in Aria, version 11 MR2, first at the appointment tracker screen for the front desk medical record access and second at the queue screen on the 4D treatment console took place for patient daily time-out. A test patient was utilized to check accuracy of identification as well as to check that no unintended interactions take place between the 4D treatment console and the hand vein scanning system. This system has been in clinical use since December 2013.
Results: Since implementation, 445 patients have been enrolled into our biometric system. 95% of patients learn the correct methodology of hand placement on the scanner in the first try. We have had two instances of patient not found because of a bad initial scan. We simply erased the scanned metric and the patient enrolled again in those cases. The accuracy of the match is 100% for each patient, we have not had one patient misidentified. We can state this because we still use patient photo and date of birth as identifiers. A QA test patient is run monthly to check the integrity of the system.
Conclusion: By utilizing palm vein scans along with the date of birth and patient photo, another means of patient identification now exits. This work indicates the successful implementation of technology in the area of patient safety by closing the gap of treating the wrong plan to a patient in radiation oncology.
Funding Support, Disclosures, and Conflict of Interest: FOJP Service Corporation covered some of the costs of the hardware and software of the palm vein pattern recognition biometric system.
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