Methods In April 2020, UK health systems were challenged to expand critical care capacity rapidly during the first wave of the COVID-19 pandemic so that they could accommodate patients with respiratory and multiple organ failure. Here, we describe the preparation and adaptive responses of a large critical care unit to the oncoming burden of disease. Our changes were similar to the revolution in manufacturing brought about by ‘Long Shops’ of 1853 when Richard Garrett and Sons of Leiston started mass manufacture of traction engines. This innovation broke the whole process into smaller parts and increased productivity. When applied to COVID-19 preparations, an assembly line approach had the advantage that our ICU became easily scalable to manage an influx of additional staff as well as the increase in admissions. Healthcare professionals could be replaced in case of absence and training focused on a smaller number of tasks.
Results Compared with the equivalent period in 2019, the ICU provided 30.9% more patient days (2599 to 3402), 1845 of which were ventilated days (compared with 694 in 2019, 165.8% increase) while time from first referral to ICU admission reduced from 193.8±123.8 min (±SD) to 110.7±76.75 min (±SD). Throughout, ICU maintained adequate capacity and also accepted patients from neighbouring hospitals. This was done by managing an additional 205 doctors (70% increase), 168 nurses who had previously worked in ICU and another 261 nurses deployed from other parts of the hospital (82% increase).
Our large tertiary hospital ensured a dedicated non-COVID ICU was staffed and equipped to take regional emergency referrals so that those patients requiring specialist surgery and treatment were treated throughout the COVID-19 pandemic.
Conclusions We report how the challenge of managing a huge influx of patients and redeployed staff was met by deconstructing ICU care into its constituent parts. Although reported from the largest colocated ICU in the UK, we believe that this offers solutions to ICUs of all sizes and may provide a generalisable model for critical care pandemic surge planning.