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A New Performance Metric to Estimate the Risk of Exposure to Infection in a Health Care Setting: Descriptive Study
BACKGROUND: Despite several measures to monitor and improve hand hygiene (HH) in health care settings, health care-acquired infections (HAIs) remain prevalent. The measures used to calculate HH performance are not able to fully benefit from the high-resolution data collected using electronic monitor...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8851339/ https://www.ncbi.nlm.nih.gov/pubmed/35107424 http://dx.doi.org/10.2196/32384 |
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author | Hadian, Kimia Fernie, Geoff Roshan Fekr, Atena |
author_facet | Hadian, Kimia Fernie, Geoff Roshan Fekr, Atena |
author_sort | Hadian, Kimia |
collection | PubMed |
description | BACKGROUND: Despite several measures to monitor and improve hand hygiene (HH) in health care settings, health care-acquired infections (HAIs) remain prevalent. The measures used to calculate HH performance are not able to fully benefit from the high-resolution data collected using electronic monitoring systems. OBJECTIVE: This study proposes a novel parameter for quantifying the HAI exposure risk of individual patients by considering temporal and spatial features of health care workers’ HH adherence. METHODS: Patient exposure risk is calculated as a function of the number of consecutive missed HH opportunities, the number of unique rooms visited by the health care professional, and the time duration that the health care professional spends inside and outside the patient’s room without performing HH. The patient exposure risk is compared to the entrance compliance rate (ECR) defined as the ratio of the number of HH actions performed at a room entrance to the total number of entrances into the room. The compliance rate is conventionally used to measure HH performance. The ECR and the patient exposure risk are analyzed using the data collected from an inpatient nursing unit for 12 weeks. RESULTS: The analysis of data collected from 59 nurses and more than 25,600 records at a musculoskeletal rehabilitation unit at the Toronto Rehabilitation Institute, KITE, showed that there is no strong linear relation between the ECR and patient exposure risk (r=0.7, P<.001). Since the ECR is calculated based on the number of missed HH actions upon room entrance, this parameter is already included in the patient exposure risk. Therefore, there might be scenarios that these 2 parameters are correlated; however, in several cases, the ECR contrasted with the reported patient exposure risk. Generally, the patients in rooms with a significantly high ECR can be potentially exposed to a considerable risk of infection. By contrast, small ECRs do not necessarily result in a high patient exposure risk. The results clearly explained the important role of the factors incorporated in patient exposure risk for quantifying the risk of infection for the patients. CONCLUSIONS: Patient exposure risk might provide a more reliable estimation of the risk of developing HAIs compared to ECR by considering both the temporal and spatial aspects of HH records. |
format | Online Article Text |
id | pubmed-8851339 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-88513392022-03-10 A New Performance Metric to Estimate the Risk of Exposure to Infection in a Health Care Setting: Descriptive Study Hadian, Kimia Fernie, Geoff Roshan Fekr, Atena JMIR Form Res Original Paper BACKGROUND: Despite several measures to monitor and improve hand hygiene (HH) in health care settings, health care-acquired infections (HAIs) remain prevalent. The measures used to calculate HH performance are not able to fully benefit from the high-resolution data collected using electronic monitoring systems. OBJECTIVE: This study proposes a novel parameter for quantifying the HAI exposure risk of individual patients by considering temporal and spatial features of health care workers’ HH adherence. METHODS: Patient exposure risk is calculated as a function of the number of consecutive missed HH opportunities, the number of unique rooms visited by the health care professional, and the time duration that the health care professional spends inside and outside the patient’s room without performing HH. The patient exposure risk is compared to the entrance compliance rate (ECR) defined as the ratio of the number of HH actions performed at a room entrance to the total number of entrances into the room. The compliance rate is conventionally used to measure HH performance. The ECR and the patient exposure risk are analyzed using the data collected from an inpatient nursing unit for 12 weeks. RESULTS: The analysis of data collected from 59 nurses and more than 25,600 records at a musculoskeletal rehabilitation unit at the Toronto Rehabilitation Institute, KITE, showed that there is no strong linear relation between the ECR and patient exposure risk (r=0.7, P<.001). Since the ECR is calculated based on the number of missed HH actions upon room entrance, this parameter is already included in the patient exposure risk. Therefore, there might be scenarios that these 2 parameters are correlated; however, in several cases, the ECR contrasted with the reported patient exposure risk. Generally, the patients in rooms with a significantly high ECR can be potentially exposed to a considerable risk of infection. By contrast, small ECRs do not necessarily result in a high patient exposure risk. The results clearly explained the important role of the factors incorporated in patient exposure risk for quantifying the risk of infection for the patients. CONCLUSIONS: Patient exposure risk might provide a more reliable estimation of the risk of developing HAIs compared to ECR by considering both the temporal and spatial aspects of HH records. JMIR Publications 2022-02-02 /pmc/articles/PMC8851339/ /pubmed/35107424 http://dx.doi.org/10.2196/32384 Text en ©Kimia Hadian, Geoff Fernie, Atena Roshan Fekr. Originally published in JMIR Formative Research (https://formative.jmir.org), 02.02.2022. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Hadian, Kimia Fernie, Geoff Roshan Fekr, Atena A New Performance Metric to Estimate the Risk of Exposure to Infection in a Health Care Setting: Descriptive Study |
title | A New Performance Metric to Estimate the Risk of Exposure to Infection in a Health Care Setting: Descriptive Study |
title_full | A New Performance Metric to Estimate the Risk of Exposure to Infection in a Health Care Setting: Descriptive Study |
title_fullStr | A New Performance Metric to Estimate the Risk of Exposure to Infection in a Health Care Setting: Descriptive Study |
title_full_unstemmed | A New Performance Metric to Estimate the Risk of Exposure to Infection in a Health Care Setting: Descriptive Study |
title_short | A New Performance Metric to Estimate the Risk of Exposure to Infection in a Health Care Setting: Descriptive Study |
title_sort | new performance metric to estimate the risk of exposure to infection in a health care setting: descriptive study |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8851339/ https://www.ncbi.nlm.nih.gov/pubmed/35107424 http://dx.doi.org/10.2196/32384 |
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