Clinical Study of Using Biometrics to Identify Patient and Procedure

Jason W Sohn; Haksoo Kim; Samuel B Park; Soyoung Lee; James I Monroe; Thomas B Malone; Timothy Kinsella; Min Yao; Charles Kunos; Simon S Lo; Robert Shenk; Mitchell Machtay

doi:10.3389/fonc.2020.586232

Clinical Study of Using Biometrics to Identify Patient and Procedure

Front Oncol. 2020 Dec 1:10:586232. doi: 10.3389/fonc.2020.586232. eCollection 2020.

Authors

Jason W Sohn¹, Haksoo Kim², Samuel B Park³, Soyoung Lee¹, James I Monroe⁴, Thomas B Malone⁵, Timothy Kinsella⁶, Min Yao⁷, Charles Kunos⁸, Simon S Lo⁹, Robert Shenk¹⁰, Mitchell Machtay^{7

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Affiliations

¹ Radiation Oncology, Allegheny Health Network, Pittsburgh, PA, United States.
² Proton Therapy Center, National Cancer Center, Goyang, South Korea.
³ Cure-In Incorporated, Goyang, South Korea.
⁴ Radiation Oncology, Mercy Hospital South, St. Louis, MO, United States.
⁵ Carlow International Incorporated, Fairfax, VA, United States.
⁶ Radiation Oncology, Warren Alpert Medical School of Brown University, Providence, RI, United States.
⁷ Radiation Oncology, University Hospitals of Cleveland, Case Western Reserve University School of Medicine, Cleveland, OH, United States.
⁸ Cancer Therapy Evaluation Program, National Cancer Institute, Rockville, MD, United States.
⁹ Radiation Oncology, University of Washington School of Medicine, Seattle, WA, United States.
¹⁰ Surgical Oncology, University Hospitals of Cleveland, Case Western Reserve University School of Medicine, Cleveland, OH, United States.
¹¹ Penn State Cancer Institute, Hershey, PA, United States.

Abstract

Purpose: To reduce patient and procedure identification errors by human interactions in radiotherapy delivery and surgery, a Biometric Automated Patient and Procedure Identification System (BAPPIS) was developed. BAPPIS is a patient identification and treatment procedure verification system using fingerprints.

Methods: The system was developed using C++, the Microsoft Foundation Class Library, the Oracle database system, and a fingerprint scanner. To register a patient, the BAPPIS system requires three steps: capturing a photograph using a web camera for photo identification, taking at least two fingerprints, and recording other specific patient information including name, date of birth, allergies, etc. To identify a patient, the BAPPIS reads a fingerprint, identifies the patient, verifies with a second fingerprint to confirm when multiple patients have same fingerprint features, and connects to the patient's record in electronic medical record (EMR) systems. To validate the system, 143 and 21 patients ranging from 36 to 98 years of ages were recruited from radiotherapy and breast surgery, respectively. The registration process for surgery patients includes an additional module, which has a 3D patient model. A surgeon could mark 'O' on the model and save a snap shot of patient in the preparation room. In the surgery room, a webcam displayed the patient's real-time image next to the 3D model. This may prevent a possible surgical mistake.

Results: 1,271 (96.9%) of 1,311 fingerprints were verified by BAPPIS using patients' 2^nd fingerprints from 143 patients as the system designed. A false positive recognition was not reported. The 96.9% completion ratio is because the operator did not verify with another fingerprint after identifying the first fingerprint. The reason may be due to lack of training at the beginning of the study.

Conclusion: We successfully demonstrated the use of BAPPIS to correctly identify and recall patient's record in EMR. BAPPIS may significantly reduce errors by limiting the number of non-automated steps.

Keywords: assurance; biometrics; oncology; surgery; verification.