An evaluation of Hospital Emergency Department (HED) adherence to universal precautions

Abstract

A longitudinal cross sectional study of Hospital Emergency Department (HED) procedures over a nine month period was conducted. A total of 1,541 procedures were observed on 56 randomly selected 8-h work shifts. Shifts were distributed: 34% day shift; 34% evening shift; and 32% on the night shift. Observations on the evening shift were oversampled to capture an adequate number of trauma patients. Observations were distributed: 33% day shift; 39% evening shift; and 28% on the night shift. Measurements included: type of procedure; adherence to specific barrier technique, i.e., use of gloves, gowns, masks, and eye protection; and occurrence of adverse exposure. Ten types of HED procedures were documented and analyzed. Computerized tracking of study observations established periodic rates of HED health care worker (HCW) adherence to universal precautions. These data are important for internal quality control/assurance programs and rate comparisons within and across institutions over time. The longitudinal evaluation of the database revealed that glove compliance increased over the period of the study and adverse exposure decreased. Conducting ongoing or periodic observational studies of this kind are important and necessary in order to gauge HED response to the epidemiologic challenges of urban society.

Infection Prevention in the Emergency Department

“…The same holds true during non-emergent clinical encounters, despite the potential for exposure to blood and other body fluids. 12,43,45,46 In surveys of ED HCP, commonly cited barriers to adherence to standard precautions have included lack of time, a perception that a patient is at low risk for being infected with HIV or another bloodborne pathogen, interference with dexterity and technical skills, and poor access to PPE at the bedside. [47][48][49][50][51] In some cases, HCP also report uncertainty of which protective barriers to use and when, reflecting inadequate training or knowledge retention.…”

Development of a Machine-Learning Algorithm for Predicting the Arrival Time and Assessing Factors Influencing Patient Arrival at Hospital Emergency Department – Preliminary Study

“…The causes of overcrowding are important for many reasons and have implications for patient arrival times or patient handling times by medical staff [33,39,42]. It is worth noting that changes in meteorological factors beyond a certain range can cause thermal imbalances in the body, which can promote the development of many diseases [53], also aff ecting both the arrival time and the number of patients in hospitals.…”