| Literature DB >> 35047956 |
Alasdair Munro1,2, Jacqui Prieto3,4, Emmanouil Mentzakis5, Mohammed Dibas4, Nitin Mahobia4, Peter Baker4, Sarah Herbert4, Trevor Smith4, Matthew Hine4, Joann Hall4, Angie McClarren4, Mike Davidson4, Julie Brooks4, Jane Fisher4, David Griffiths4, Hywel Morgan6, Corrado Giulietti5, Saul N Faust1,2, Paul Elkington1,2.
Abstract
Objectives: The provision of high-quality personal protective equipment (PPE) has been a critical challenge during the COVID-19 pandemic. We evaluated an alternative strategy, mass deployment of a powered air-purifying respirator (PeRSo), in a large university hospital.Entities:
Keywords: COVID-19; economic analysis; healthcare; nosocomial infection; personal protective equipment; respirator
Year: 2021 PMID: 35047956 PMCID: PMC8757687 DOI: 10.3389/fmedt.2021.729658
Source DB: PubMed Journal: Front Med Technol ISSN: 2673-3129
Figure 1Types of PPE described in the manuscript. (A) Droplet protection: a disposable Type IIR surgical mask and visor. (B) Aerosol protection: a disposable tight fitting FFP3 mask and visor. (C,D) PeRSo with the long hood type, which was the type issued during the period of the survey. (E,F) PeRSo with short hood type that exposes the ears, developed in response to the initial user feedback. In all instances, a plastic apron and gloves complete the PPE.
Demographics of respondents.
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| Female | 101/140 (72.1%) | 133/172 (77.3%) |
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| <25 y | 17/140 (12.1%) | 14/172 (8.1%) |
| 25–30 y | 37/140 (26.4%) | 43/172 (24.9%) |
| 30–35 y | 30/140 (21.4%) | 37/172 (21.4%) |
| 35–40 y | 16/140 (11.4%) | 25/172 (14.5%) |
| 40–50 y | 31/140 (22.1%) | 38/172 (22%) |
| >50 y | 9/140 (6.4%) | 16/172 (9.3%) |
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| Allied health professional | 14/140 (10%) | 14/172 (8.1%) |
| Advanced nurse practitioner | 4/140 (2.9%) | 5/172 (2.9%) |
| Healthcare assistant | 23/140 (16.4%) | 36/172 (20.9%) |
| Nurse | 48/140 (34.3%) | 59/172 (34.3%) |
| Doctor | 34/140 (24.3%) | 39/172 (22.7%) |
| Other | 17/140 (12.1%) | 19/172 (11%) |
Survey responses.
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| Droplet | 82 | 2 (2.4%) | 27 (32.9%) | 30 (36.6%) | 18 (22%) | 5 (6.1%) |
| Airborne | 45 | 3 (6.7%) | 12 (26.7%) | 13 (28.9%) | 15 (33.3%) | 2 (4.4%) |
| PeRSo | 147 | 4 (2.7%) | 25 (17%) | 33 (22.5%) | 74 (50.4%) | 11 (7.5%) |
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| Droplet | 82 | 0 (0%) | 4 (4.9%) | 11 (13.4%) | 41 (50%) | 26 (31.7%) |
| Airborne | 45 | 0 (0%) | 1 (2.2%) | 15 (33.3%) | 25 (55.6%) | 4 (8.9%) |
| PeRSo | 146 | 0 (0%) | 5 (3.4%) | 29 (19.9%) | 86 (58.9%) | 26 (17.8%) |
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| Droplet | 81 | 0 (0%) | 6 (7.4%) | 11 (13.6%) | 42 (51.9%) | 22 (27.2%) |
| Airborne | 45 | 0 (0%) | 9 (20%) | 9 (20%) | 22 (48.9%) | 5 (11.1%) |
| PeRSo | 146 | 0 (0%) | 17 (11.6%) | 38 (26%) | 82 (56.2%) | 9 (6.2%) |
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| Droplet | 82 | 0 (0%) | 4 (4.9%) | 43 (52.4%) | 31 (37.8%) | 4 (4.9%) |
| Airborne | 45 | 0 (0%) | 3 (6.8%) | 21 (47.7%) | 17 (38.6%) | 3 (6.8%) |
| PeRSo | 147 | 0 (0%) | 4 (2.7%) | 56 (38.1%) | 80 (54.4%) | 7 (4.7%) |
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| Droplet | 82 | 4 (4.9%) | 21 (25.6%) | 21 (25.6%) | 28 (34.2%) | 8 (9.8%) |
| Airborne | 45 | 1 (2.2%) | 8 (17.8%) | 7 (15.6%) | 25 (55.6%) | 4 (8.9%) |
| PeRSo | 147 | 0.0% | 4 (2.7%) | 22 (15%) | 71 (48.3%) | 50 (34%) |
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| Droplet | 82 | 3 (3.7%) | 12 (14.6%) | 40 (48.8%) | 23 (28.1%) | 4 (4.9%) |
| Airborne | 45 | 2 (4.4%) | 8 (17.8%) | 12 (26.7%) | 20 (44.4%) | 3 (6.7%) |
| PeRSo | 147 | 2 (1.4%) | 14 (9.5%) | 36 (24.5%) | 74 (50.3%) | 21 (14.3%) |
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| Droplet | 77 | 3 (3.9%) | 14 (18.2%) | 32 (41.6%) | 25 (32.5%) | 3 (3.9%) |
| Airborne | 39 | 1 (2.6%) | 12 (30.8%) | 19 (48.7%) | 7 (18%) | 0 (0%) |
| PeRSo | 143 | 4 (2.8%) | 40 (27.8%) | 56 (39.2%) | 36 (25.2%) | 7 (4.9)% |
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| Droplet | 77 | 0 (0%) | 7 (9.1%) | 18 (23.4%) | 20 (26%) | 32 (41.6%) |
| Airborne | 39 | 0 (0%) | 3 (7.7%) | 7 (18%) | 18 (46.2%) | 11 (28.2%) |
| PeRSo | 144 | 1 (0.7%) | 5 (3.5%) | 26 (18.1%) | 48 (33.3%) | 64 (44.4%) |
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| Droplet | 77 | 3 (3.9%) | 7 (9.1%) | 25 (32.5%) | 13 (16.9%) | 29 (37.7%) |
| Airborne | 39 | 2 (5.1%) | 11 (28.2%) | 13 (33.3%) | 8 (20.5%) | 5 (12.8%) |
| PeRSo | 143 | 12 (8.4%) | 39 (27.3%) | 70 (49%) | 19 (13.3%) | 3 (2.1%) |
Statistical analysis of paired survey responses (Wilcoxon signed rank).
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| Droplet | 35 | 0 (0%) | 12 (34.3%) | 13 (37.1%) | 9 (25.7%) | 1 (2.9%) | −1 (−1.5, −0.4) | 0.011 |
| PeRSo | 1 (2.9%) | 4 (11.4%) | 8 (22.9%) | 18 (51.4%) | 4 (11.4%) | |||
| Airborne | 14 | 1 (7.1%) | 4 (28.6%) | 4 (28.6%) | 5 (35.7%) | 0 (0%) | −1.5 (−2.5, 0.5) | 0.087 |
| PeRSo | 0 (0%) | 2 (14.3%) | 1 (7.1%) | 11 (78.6%) | 0 (0%) | |||
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| Droplet | 35 | 0 (0%) | 0 (0%) | 3 (8.6%) | 19 (54.3%) | 13 (37.1%) | 1 (0, 1.5) | 0.06 |
| PeRSo | 0 (0%) | 4 (11.4%) | 2 (5.7%) | 21 (60%) | 8 (22.9%) | |||
| Airborne | 14 | 0 (0%) | 0 (0%) | 6 (42.9%) | 7 (50%) | 1 (7.1%) | −1 (-1.5, 2.4) | 0.095 |
| PeRSo | 0 (0%) | 0 (0%) | 1 (7.1%) | 11 (78.6%) | 2 (14.3%) | |||
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| Droplet | 35 | 0 (0%) | 0 (0%) | 3 (8.6%) | 21 (60%) | 11 (31.4%) | 1.5 (1, 2) | <0.001 |
| PeRSo | 0 (0%) | 6 (17.1%) | 4 (11.4%) | 24 (68.6%) | 1 (2.9%) | |||
| Airborne | 14 | 0 (0%) | 3 (21.4%) | 4 (28.6%) | 6 (42.9%) | 1 (7.1%) | −2 (1.5, 1) | 0.916 |
| PeRSo | 0 (0%) | 2 (14.3%) | 5 (35.7%) | 7 (50%) | 0 (0%) | |||
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| Droplet | 35 | 0 (0%) | 2 (5.7%) | 20 (57.1%) | 13 (37.1%) | 0 (0%) | −1 (−1, 0) | 0.044 |
| PeRSo | 0 (0%) | 2 (5.7%) | 11 (31.4%) | 19 (54.3%) | 3 (8.6%) | |||
| Airborne | 14 | 0 (0%) | 1 (7.1%) | 7 (50%) | 6 (42.9%) | 0 (0%) | −1 (−1, 0) | 0.182 |
| PeRSo | 0 (0%) | 0 (0%) | 6 (42.9%) | 7 (50%) | 1 (7.1%) | |||
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| Droplet | 35 | 2 (5.7%) | 13 (37.1%) | 10 (28.6%) | 10 (28.6%) | 0 (0%) | −2 (−2.5, −1.5) | <0.0001 |
| PeRSo | 0 (0%) | 1 (2.9%) | 3 (8.6%) | 14 (40%) | 17 (48.6%) | |||
| Airborne | 14 | 0 (0%) | 5 (35.7%) | 2 (14.3%) | 7 (50%) | 0 (0%) | −1.5 (−2, −1) | 0.007 |
| PeRSo | 0 (0%) | 0 (0%) | 2 (14.3%) | 8 (57.1%) | 4 (28.6%) | |||
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| Droplet | 35 | 1 (2.9%) | 7 (20%) | 18 (51.4%) | 9 (25.7%) | 0 (0%) | −1 (−1.5, −0.5) | 0.006 |
| PeRSo | 0 (0%) | 5 (14.3%) | 11 (31.4%) | 12 (34.3%) | 7 (20%) | |||
| Airborne | 14 | 0 (0%) | 4 (28.6%) | 6 (42.9%) | 4 (28.6%) | 0 (0%) | −1 (−1.5, 0.5) | 0.168 |
| PeRSo | 1 (7.1%) | 1 (7.1%) | 2 (14.3%) | 10 (71.4) | 0 (0%) | |||
A negative median difference indicates a response in favor of the PeRSo.
indicates a statistically significant difference.
should have legend: 60% Confidence interval due to sample size and variability.
Figure 2PeRSo cost savings. (A) Comparisons between PeRSo and FFP3 facemasks. (B) Comparisons between PeRSo and a mixture of FFP3 and surgical facemasks. Positive values represent simulation outcomes where PPE costs are greater than PeRSo costs. The dashed line represents the boundary of PeRSo deployment becoming cost saving, with outcomes further to the right implying greater saving from PeRSo use.
Figure 3Modeling of cumulative annual cost of three PPE strategies based on admission rates at University Hospital Southampton intensive care unit admissions. (A) Total cost accumulated over 12 months. (B) Cumulative costs over time, with ITU admission rate plotted in background to demonstrate waves.
Figure 4Staff absence rates due to COVID19 were lower in Southampton than equivalent large UK teaching hospitals. Average daily absence rates per 1,000 clinically active staff are presented for the first quarter of 2021, as reported by individual hospital trusts to the national database. University Hospital Southampton is red, and the initial peak in the New Year rapidly fell, and remained low, coinciding with the progressive roll-out of PeRSo respirators.
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| Director and nursing leads for infection prevention and control | Protocols for use, donning and doffing, assessment of usage areas |
| Medical and nursing director | Prioritizing staff for roll-out; ensuring compliance with regulatory guidance |
| Communications | Updating all staff on deployment and prioritization strategy of new PPE; news release to inform public |
| Logistics and estates | Deployment centers, storage areas, charging stations |
| Education team | Training staff in use, cleaning, storage, return at the end of contract |
| Procurement and purchasing | Confirming contract and delivery schedule, liaising with design team for technical aspects of manufacture, replacement hoods, spare batteries, on-site storage arrangements |
| Local industry | Production of units, shipping in parts, regulatory approvals |
| University | Initial concept and prototype evaluation; prospective analysis of deployment |
| End users: Doctors, nurses, healthcare assistants, research teams, phlebotomists, cleaning staff, porters | Compliance with training, storage, ongoing use, return when leaving post |