Using the Number of N95® Filtering Facepiece Respirator Models as an Indicator of Supply Chain Stability in a US Health-Care System
Personal protective equipment (PPE) supply chain disruptions force US health-care entities to adopt conservation strategies such as procurement from different respirator manufacturers. This research seeks to better understand how the number of respirator models on hand can serve as an indicator of N...
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| Veröffentlicht in: | Disaster medicine and public health preparedness 2024-01, Vol.18, p.e10-e10, Article e10 |
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| container_title | Disaster medicine and public health preparedness |
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| creator | Furek, Alexa Edirisooriya, Mihili Casey, Megan Haas, Emily J. |
| description | Personal protective equipment (PPE) supply chain disruptions force US health-care entities to adopt conservation strategies such as procurement from different respirator manufacturers. This research seeks to better understand how the number of respirator models on hand can serve as an indicator of N95 filtering facepiece respirator (FFR) supply chain stability or disruption.
Researchers looked at differences in the mean number of N95 FFR models, averaged weekly, from 10 hospitals in a health-care system over 15 wk from June 1 to September 10, 2020. Participating hospitals entered near-daily PPE inventory data by manufacturer and model number.
A linear mixed effect model was run in SPSS v. 26 using a random intercept for hospitals, with week as a fixed predictor and mean number of respirator models (averaged weekly) on hand as the dependent variable. Each week showed a small but significant effect compared with the past week (
< 0.001), where the average weekly number of respirator models on hand decreased.
The limited data may indicate a resolution of supply chain disruptions and warrant further investigation. Consequently, the number of respirator models may be applicable as an indicator of supply chain stability and be more easily ascertained and tracked by health-care entities. |
| doi_str_mv | 10.1017/dmp.2024.9 |
| format | Article |
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Researchers looked at differences in the mean number of N95 FFR models, averaged weekly, from 10 hospitals in a health-care system over 15 wk from June 1 to September 10, 2020. Participating hospitals entered near-daily PPE inventory data by manufacturer and model number.
A linear mixed effect model was run in SPSS v. 26 using a random intercept for hospitals, with week as a fixed predictor and mean number of respirator models (averaged weekly) on hand as the dependent variable. Each week showed a small but significant effect compared with the past week (
< 0.001), where the average weekly number of respirator models on hand decreased.
The limited data may indicate a resolution of supply chain disruptions and warrant further investigation. Consequently, the number of respirator models may be applicable as an indicator of supply chain stability and be more easily ascertained and tracked by health-care entities.</description><identifier>ISSN: 1935-7893</identifier><identifier>EISSN: 1938-744X</identifier><identifier>DOI: 10.1017/dmp.2024.9</identifier><identifier>PMID: 38287526</identifier><language>eng</language><publisher>New York, USA: Cambridge University Press</publisher><subject>Coronaviruses ; COVID-19 ; Disease prevention ; Emergency preparedness ; Employees ; Health care ; Hospitals ; Humans ; Masks ; N95 Respirators ; Occupational Exposure ; Occupational health ; Occupational safety ; Original Research ; Pandemics ; Personal Protective Equipment ; Protective equipment ; Respiratory Protective Devices ; Supply chains ; Ventilators, Mechanical</subject><ispartof>Disaster medicine and public health preparedness, 2024-01, Vol.18, p.e10-e10, Article e10</ispartof><rights>The Author(s), 2024. Published by Cambridge University Press on behalf of Society for Disaster Medicine and Public Health, Inc</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c311t-52a043ac5cafe601e79855ed4615b1bef2f48925730948edbe9926274ca47a63</cites><orcidid>0000-0001-5128-470X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.cambridge.org/core/product/identifier/S1935789324000090/type/journal_article$$EHTML$$P50$$Gcambridge$$H</linktohtml><link.rule.ids>164,314,780,784,27924,27925,55628</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38287526$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Furek, Alexa</creatorcontrib><creatorcontrib>Edirisooriya, Mihili</creatorcontrib><creatorcontrib>Casey, Megan</creatorcontrib><creatorcontrib>Haas, Emily J.</creatorcontrib><title>Using the Number of N95® Filtering Facepiece Respirator Models as an Indicator of Supply Chain Stability in a US Health-Care System</title><title>Disaster medicine and public health preparedness</title><addtitle>Disaster med. public health prep</addtitle><description>Personal protective equipment (PPE) supply chain disruptions force US health-care entities to adopt conservation strategies such as procurement from different respirator manufacturers. This research seeks to better understand how the number of respirator models on hand can serve as an indicator of N95 filtering facepiece respirator (FFR) supply chain stability or disruption.
Researchers looked at differences in the mean number of N95 FFR models, averaged weekly, from 10 hospitals in a health-care system over 15 wk from June 1 to September 10, 2020. Participating hospitals entered near-daily PPE inventory data by manufacturer and model number.
A linear mixed effect model was run in SPSS v. 26 using a random intercept for hospitals, with week as a fixed predictor and mean number of respirator models (averaged weekly) on hand as the dependent variable. Each week showed a small but significant effect compared with the past week (
< 0.001), where the average weekly number of respirator models on hand decreased.
The limited data may indicate a resolution of supply chain disruptions and warrant further investigation. 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This research seeks to better understand how the number of respirator models on hand can serve as an indicator of N95 filtering facepiece respirator (FFR) supply chain stability or disruption.
Researchers looked at differences in the mean number of N95 FFR models, averaged weekly, from 10 hospitals in a health-care system over 15 wk from June 1 to September 10, 2020. Participating hospitals entered near-daily PPE inventory data by manufacturer and model number.
A linear mixed effect model was run in SPSS v. 26 using a random intercept for hospitals, with week as a fixed predictor and mean number of respirator models (averaged weekly) on hand as the dependent variable. Each week showed a small but significant effect compared with the past week (
< 0.001), where the average weekly number of respirator models on hand decreased.
The limited data may indicate a resolution of supply chain disruptions and warrant further investigation. Consequently, the number of respirator models may be applicable as an indicator of supply chain stability and be more easily ascertained and tracked by health-care entities.</abstract><cop>New York, USA</cop><pub>Cambridge University Press</pub><pmid>38287526</pmid><doi>10.1017/dmp.2024.9</doi><tpages>5</tpages><orcidid>https://orcid.org/0000-0001-5128-470X</orcidid></addata></record> |
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| ispartof | Disaster medicine and public health preparedness, 2024-01, Vol.18, p.e10-e10, Article e10 |
| issn | 1935-7893 1938-744X |
| language | eng |
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| source | MEDLINE; Cambridge Journals |
| subjects | Coronaviruses COVID-19 Disease prevention Emergency preparedness Employees Health care Hospitals Humans Masks N95 Respirators Occupational Exposure Occupational health Occupational safety Original Research Pandemics Personal Protective Equipment Protective equipment Respiratory Protective Devices Supply chains Ventilators, Mechanical |
| title | Using the Number of N95® Filtering Facepiece Respirator Models as an Indicator of Supply Chain Stability in a US Health-Care System |
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