The use of privacy-protected computer vision to measure the quality of healthcare worker hand hygiene

International Journal for Quality in Health Care : Journal of the International Society for Quality in Health Care
Sari AwwadDavid J Gattas

Abstract

(i) To demonstrate the feasibility of automated, direct observation and collection of hand hygiene data, (ii) to develop computer visual methods capable of reporting compliance with moment 1 (the performance of hand hygiene before touching a patient) and (iii) to report the diagnostic accuracy of automated, direct observation of moment 1. Observation of simulated hand hygiene encounters between a healthcare worker and a patient. Computer laboratory in a university. Healthy volunteers. Sensitivity and specificity of automatic detection of the first moment of hand hygiene. We captured video and depth images using a Kinect camera and developed computer visual methods to automatically detect the use of alcohol-based hand rub (ABHR), rubbing together of hands and subsequent contact of the patient by the healthcare worker using depth imagery. We acquired images from 18 different simulated hand hygiene encounters where the healthcare worker complied with the first moment of hand hygiene, and 8 encounters where they did not. The diagnostic accuracy of determining that ABHR was dispensed and that the patient was touched was excellent (sensitivity 100%, specificity 100%). The diagnostic accuracy of determining that the hands were rubbed ...Continue Reading

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Citations

Mar 29, 2020·Current Treatment Options in Infectious Diseases·Fidelma FitzpatrickGerard Lacey
Jul 28, 2020·Journal of the American Medical Informatics Association : JAMIA·Amit SinghArnold Milstein
Nov 25, 2020··Mary-Louise McLawsBranislav Kusy

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