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1232. Potential Health and Cost Outcomes of Optimized Statistical Process Control Use for Surgical Site Infection Surveillance

BACKGROUND: Surgical site infections (SSIs) are common (160,000–300,000 per year in the United States) and costly ($6,000–$25,500 per event) healthcare-associated infections with potentially lethal outcomes (2.1%–6.7% mortality rate). A prior analysis by our group suggested that statistical process...

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Autores principales: Nehls, Nicole, Ilieş, Iulian, Benneyan, James C, Baker, Arthur W, Anderson, Deverick J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6808829/
http://dx.doi.org/10.1093/ofid/ofz360.1095
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author Nehls, Nicole
Ilieş, Iulian
Benneyan, James C
Baker, Arthur W
Anderson, Deverick J
author_facet Nehls, Nicole
Ilieş, Iulian
Benneyan, James C
Baker, Arthur W
Anderson, Deverick J
author_sort Nehls, Nicole
collection PubMed
description BACKGROUND: Surgical site infections (SSIs) are common (160,000–300,000 per year in the United States) and costly ($6,000–$25,500 per event) healthcare-associated infections with potentially lethal outcomes (2.1%–6.7% mortality rate). A prior analysis by our group suggested that statistical process control (SPC) can detect SSI outbreaks earlier than traditional epidemiological surveillance methods. This study aimed to quantify the potential impact of SPC surveillance on patient outcomes (prevented SSIs and deaths) and healthcare costs. METHODS: We retrospectively analyzed 30 SSI outbreaks occurring over a period of 8 years in a network of 50 community hospitals from the Southeastern United States. We applied 24 control chart variations, including 2 optimized for SSI surveillance, 6 with expert-defined pre-outbreak baselines (used in our pilot study), 4 with lagged rolling baselines (idem), and 12 common practice ones (using rolling baselines with no lag or fixed baselines). The charts used procedure-specific data from either the outbreak hospital or the entire network to compute baseline SSI rates. We calculated the average SSI rates during, before and after the outbreaks, and the months elapsed between SPC and traditional detection. We then used these values to estimate the number of SSIs that could have been prevented by SPC, and corresponding deaths avoided and cost savings (Figure 1). RESULTS: Optimized charts detected 96% of the outbreaks earlier than traditional surveillance, while pilot study and common practice charts did so only 65% (58%) of the time (Figure 2). Optimized charts could potentially prevent 15.2 SSIs, 0.64 deaths, and save $226,000 in excess care costs per outbreak. Overall, charts using network baselines performed better than those relying on local hospital data. Commonly used variations were the least effective, but were still able to improve on traditional surveillance (Figure 3). CONCLUSION: SPC methods provide a great opportunity to prevent infections and deaths and generate cost savings, ultimately improving patient safety and care quality. While common practice SPC charts can also speed up outbreak detection, optimized SPC methods have a significantly higher potential to prevent SSIs and reduce healthcare costs. [Image: see text] [Image: see text] [Image: see text] DISCLOSURES: All authors: No reported disclosures.
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spelling pubmed-68088292019-10-28 1232. Potential Health and Cost Outcomes of Optimized Statistical Process Control Use for Surgical Site Infection Surveillance Nehls, Nicole Ilieş, Iulian Benneyan, James C Baker, Arthur W Anderson, Deverick J Open Forum Infect Dis Abstracts BACKGROUND: Surgical site infections (SSIs) are common (160,000–300,000 per year in the United States) and costly ($6,000–$25,500 per event) healthcare-associated infections with potentially lethal outcomes (2.1%–6.7% mortality rate). A prior analysis by our group suggested that statistical process control (SPC) can detect SSI outbreaks earlier than traditional epidemiological surveillance methods. This study aimed to quantify the potential impact of SPC surveillance on patient outcomes (prevented SSIs and deaths) and healthcare costs. METHODS: We retrospectively analyzed 30 SSI outbreaks occurring over a period of 8 years in a network of 50 community hospitals from the Southeastern United States. We applied 24 control chart variations, including 2 optimized for SSI surveillance, 6 with expert-defined pre-outbreak baselines (used in our pilot study), 4 with lagged rolling baselines (idem), and 12 common practice ones (using rolling baselines with no lag or fixed baselines). The charts used procedure-specific data from either the outbreak hospital or the entire network to compute baseline SSI rates. We calculated the average SSI rates during, before and after the outbreaks, and the months elapsed between SPC and traditional detection. We then used these values to estimate the number of SSIs that could have been prevented by SPC, and corresponding deaths avoided and cost savings (Figure 1). RESULTS: Optimized charts detected 96% of the outbreaks earlier than traditional surveillance, while pilot study and common practice charts did so only 65% (58%) of the time (Figure 2). Optimized charts could potentially prevent 15.2 SSIs, 0.64 deaths, and save $226,000 in excess care costs per outbreak. Overall, charts using network baselines performed better than those relying on local hospital data. Commonly used variations were the least effective, but were still able to improve on traditional surveillance (Figure 3). CONCLUSION: SPC methods provide a great opportunity to prevent infections and deaths and generate cost savings, ultimately improving patient safety and care quality. While common practice SPC charts can also speed up outbreak detection, optimized SPC methods have a significantly higher potential to prevent SSIs and reduce healthcare costs. [Image: see text] [Image: see text] [Image: see text] DISCLOSURES: All authors: No reported disclosures. Oxford University Press 2019-10-23 /pmc/articles/PMC6808829/ http://dx.doi.org/10.1093/ofid/ofz360.1095 Text en © The Author(s) 2019. 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 Abstracts
Nehls, Nicole
Ilieş, Iulian
Benneyan, James C
Baker, Arthur W
Anderson, Deverick J
1232. Potential Health and Cost Outcomes of Optimized Statistical Process Control Use for Surgical Site Infection Surveillance
title 1232. Potential Health and Cost Outcomes of Optimized Statistical Process Control Use for Surgical Site Infection Surveillance
title_full 1232. Potential Health and Cost Outcomes of Optimized Statistical Process Control Use for Surgical Site Infection Surveillance
title_fullStr 1232. Potential Health and Cost Outcomes of Optimized Statistical Process Control Use for Surgical Site Infection Surveillance
title_full_unstemmed 1232. Potential Health and Cost Outcomes of Optimized Statistical Process Control Use for Surgical Site Infection Surveillance
title_short 1232. Potential Health and Cost Outcomes of Optimized Statistical Process Control Use for Surgical Site Infection Surveillance
title_sort 1232. potential health and cost outcomes of optimized statistical process control use for surgical site infection surveillance
topic Abstracts
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6808829/
http://dx.doi.org/10.1093/ofid/ofz360.1095
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