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877. Use of Statistical Process Control Charts for Early Detection of Healthcare Facility-Associated Nontuberculous Mycobacterial Outbreaks

BACKGROUND: Nontuberculous mycobacteria (NTM) are increasingly implicated in healthcare facility-associated (HCFA) outbreaks. However, systematic methods for NTM surveillance and outbreak detection are lacking and represent an emerging need. We examined how statistical process control (SPC) might pe...

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Autores principales: Baker, Arthur W, Maged, Ahmed, Haridy, Salah, Stout, Jason E, Seidelman, Jessica L, Lewis, Sarah S, Anderson, Deverick J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7776486/
http://dx.doi.org/10.1093/ofid/ofaa439.1065
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author Baker, Arthur W
Maged, Ahmed
Haridy, Salah
Stout, Jason E
Seidelman, Jessica L
Lewis, Sarah S
Anderson, Deverick J
author_facet Baker, Arthur W
Maged, Ahmed
Haridy, Salah
Stout, Jason E
Seidelman, Jessica L
Lewis, Sarah S
Anderson, Deverick J
author_sort Baker, Arthur W
collection PubMed
description BACKGROUND: Nontuberculous mycobacteria (NTM) are increasingly implicated in healthcare facility-associated (HCFA) outbreaks. However, systematic methods for NTM surveillance and outbreak detection are lacking and represent an emerging need. We examined how statistical process control (SPC) might perform in NTM outbreak detection. METHODS: SPC charts were optimized for surgical site infection surveillance and adapted to analyze 3 NTM outbreaks that occurred from 2013-2016 at a single hospital. The first 2 outbreaks occurred contemporaneously and consisted of pulmonary Mycobacterium abscessus complex (MABC) acquisition and cardiac surgery-associated extrapulmonary MABC infection, respectively. The third outbreak was a pseudo-outbreak of Mycobacterium avium complex (MAC) at a bronchoscopy suite. We retrospectively analyzed monthly rates of unique patients who had: 1) positive respiratory cultures for MABC obtained on hospital day 3 or later; 2) positive non-respiratory cultures for MABC; and 3) positive bronchoalveolar lavage (BAL) cultures for MAC collected at the bronchoscopy suite. For each outbreak, we used these rates to construct a standardized moving average (MA) SPC chart with MA span of 3 months. Rolling baselines were estimated from average rates for months 7 through 12 prior to each monthly data point. SPC detection was indicated by the first data point above the upper control limit (UCL) of 3 standard deviations. Traditional surveillance detection was defined as the time of outbreak detection by routine infection control procedures. RESULTS: SPC detection occurred 5, 4, and 9 months prior to traditional surveillance outbreak detection for the three outbreaks, respectively (Figures 1 and 2). Prospective NTM surveillance using the MA chart potentially would have prevented an estimated 19 cases of pulmonary MABC, 9 cases of extrapulmonary MABC, and 80 cases of BAL MAC isolation (Table). No data points exceeded the UCL during 95 cumulative months of post-outbreak surveillance, suggesting low burden of false positive SPC signals. Figure 1. Use of a moving average statistical process control (SPC) chart for early detection of hospital-associated outbreaks of pulmonary Mycobacterium abscessus complex (MABC) and cardiac surgery-associated extrapulmonary MABC infection. The pulmonary chart analyzes cases of hospital-onset respiratory isolation of MABC. The extrapulmonary chart analyzes cases of positive non-respiratory cultures for MABC. CL, center line; LCL, lower control limit; UCL, upper control limit. [Image: see text] Figure 2. Use of a moving average statistical process control (SPC) chart for early detection of a pseudo-outbreak of Mycobacterium avium complex (MAC) that occurred at a bronchoscopy suite. The chart analyzes cases of MAC isolated from bronchoalveolar lavage cultures. CL, center line; LCL, lower control limit; UCL, upper control limit. [Image: see text] Table. Estimated cases of hospital-associated nontuberculous mycobacteria that would have been prevented by prospective surveillance with a moving average statistical process control (SPC) chart. [Image: see text] CONCLUSION: A single MA SPC chart detected 3 HCFA NTM outbreaks an average of 6 months earlier than traditional surveillance. SPC has potential to improve NTM surveillance, promoting early cluster detection and prevention of HCFA NTM. DISCLOSURES: All Authors: No reported disclosures
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spelling pubmed-77764862021-01-07 877. Use of Statistical Process Control Charts for Early Detection of Healthcare Facility-Associated Nontuberculous Mycobacterial Outbreaks Baker, Arthur W Maged, Ahmed Haridy, Salah Stout, Jason E Seidelman, Jessica L Lewis, Sarah S Anderson, Deverick J Open Forum Infect Dis Poster Abstracts BACKGROUND: Nontuberculous mycobacteria (NTM) are increasingly implicated in healthcare facility-associated (HCFA) outbreaks. However, systematic methods for NTM surveillance and outbreak detection are lacking and represent an emerging need. We examined how statistical process control (SPC) might perform in NTM outbreak detection. METHODS: SPC charts were optimized for surgical site infection surveillance and adapted to analyze 3 NTM outbreaks that occurred from 2013-2016 at a single hospital. The first 2 outbreaks occurred contemporaneously and consisted of pulmonary Mycobacterium abscessus complex (MABC) acquisition and cardiac surgery-associated extrapulmonary MABC infection, respectively. The third outbreak was a pseudo-outbreak of Mycobacterium avium complex (MAC) at a bronchoscopy suite. We retrospectively analyzed monthly rates of unique patients who had: 1) positive respiratory cultures for MABC obtained on hospital day 3 or later; 2) positive non-respiratory cultures for MABC; and 3) positive bronchoalveolar lavage (BAL) cultures for MAC collected at the bronchoscopy suite. For each outbreak, we used these rates to construct a standardized moving average (MA) SPC chart with MA span of 3 months. Rolling baselines were estimated from average rates for months 7 through 12 prior to each monthly data point. SPC detection was indicated by the first data point above the upper control limit (UCL) of 3 standard deviations. Traditional surveillance detection was defined as the time of outbreak detection by routine infection control procedures. RESULTS: SPC detection occurred 5, 4, and 9 months prior to traditional surveillance outbreak detection for the three outbreaks, respectively (Figures 1 and 2). Prospective NTM surveillance using the MA chart potentially would have prevented an estimated 19 cases of pulmonary MABC, 9 cases of extrapulmonary MABC, and 80 cases of BAL MAC isolation (Table). No data points exceeded the UCL during 95 cumulative months of post-outbreak surveillance, suggesting low burden of false positive SPC signals. Figure 1. Use of a moving average statistical process control (SPC) chart for early detection of hospital-associated outbreaks of pulmonary Mycobacterium abscessus complex (MABC) and cardiac surgery-associated extrapulmonary MABC infection. The pulmonary chart analyzes cases of hospital-onset respiratory isolation of MABC. The extrapulmonary chart analyzes cases of positive non-respiratory cultures for MABC. CL, center line; LCL, lower control limit; UCL, upper control limit. [Image: see text] Figure 2. Use of a moving average statistical process control (SPC) chart for early detection of a pseudo-outbreak of Mycobacterium avium complex (MAC) that occurred at a bronchoscopy suite. The chart analyzes cases of MAC isolated from bronchoalveolar lavage cultures. CL, center line; LCL, lower control limit; UCL, upper control limit. [Image: see text] Table. Estimated cases of hospital-associated nontuberculous mycobacteria that would have been prevented by prospective surveillance with a moving average statistical process control (SPC) chart. [Image: see text] CONCLUSION: A single MA SPC chart detected 3 HCFA NTM outbreaks an average of 6 months earlier than traditional surveillance. SPC has potential to improve NTM surveillance, promoting early cluster detection and prevention of HCFA NTM. DISCLOSURES: All Authors: No reported disclosures Oxford University Press 2020-12-31 /pmc/articles/PMC7776486/ http://dx.doi.org/10.1093/ofid/ofaa439.1065 Text en © The Author 2020. Published by Oxford University Press on behalf of Infectious Diseases Society of America. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Poster Abstracts
Baker, Arthur W
Maged, Ahmed
Haridy, Salah
Stout, Jason E
Seidelman, Jessica L
Lewis, Sarah S
Anderson, Deverick J
877. Use of Statistical Process Control Charts for Early Detection of Healthcare Facility-Associated Nontuberculous Mycobacterial Outbreaks
title 877. Use of Statistical Process Control Charts for Early Detection of Healthcare Facility-Associated Nontuberculous Mycobacterial Outbreaks
title_full 877. Use of Statistical Process Control Charts for Early Detection of Healthcare Facility-Associated Nontuberculous Mycobacterial Outbreaks
title_fullStr 877. Use of Statistical Process Control Charts for Early Detection of Healthcare Facility-Associated Nontuberculous Mycobacterial Outbreaks
title_full_unstemmed 877. Use of Statistical Process Control Charts for Early Detection of Healthcare Facility-Associated Nontuberculous Mycobacterial Outbreaks
title_short 877. Use of Statistical Process Control Charts for Early Detection of Healthcare Facility-Associated Nontuberculous Mycobacterial Outbreaks
title_sort 877. use of statistical process control charts for early detection of healthcare facility-associated nontuberculous mycobacterial outbreaks
topic Poster Abstracts
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7776486/
http://dx.doi.org/10.1093/ofid/ofaa439.1065
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