Comparative analysis of personal protective equipment nonadherence detection: computer vision versus human observers.

Objectives: Human monitoring of personal protective equipment (PPE) adherence among healthcare providers has several limitations, including the need for additional personnel during staff shortages and decreased vigilance during prolonged tasks. To address these challenges, we developed an automated computer vision system for monitoring PPE adherence in healthcare settings. We assessed the system performance against human observers detecting nonadherence in a video surveillance experiment.

Factors associated with correction of personal protective equipment nonadherence in a multidisciplinary emergency department setting: A retrospective video review.

Background: Despite local and national recommendations, health care provider adherence to personal protective equipment (PPE) varied during the COVID-19 pandemic. Previous studies have identified factors influencing initial PPE adherence but did not address factors influencing behaviors leading to correction after initial nonadherence.

Methods: We conducted a retrospective video review of 18 pediatric resuscitations involving aerosol-generating procedures from March 2020 to December 2022 to identify factors associated with nonadherence correction.

A microdiscectomy surgical video annotation framework for supervised machine learning applications.

Purpose: Lumbar discectomy is among the most common spine procedures in the US, with 300,000 procedures performed each year. Like other surgical procedures, this procedure is not excluded from potential complications. This paper presents a video annotation methodology for microdiscectomy including the development of a surgical workflow.