Intended for healthcare professionals

  1. Jacqui Thornton
  1. London
  1. jacqui{at}jacquithornton.com

As the UK’s coronavirus patients begin to leave ICUs, Jacqui Thornton examines how the NHS plans to meet a “tsunami of need”

Covid-19 has shone a bright light on the impressive work of NHS intensive care units (ICUs) around the UK. Now, as the first patients who have had the new virus and spent days ventilated in ICUs are discharged, the Chartered Society of Physiotherapy predicts a “tsunami of rehabilitation needs.”

Already there are question marks about whether appropriate rehabilitation—physical, cognitive, and psychological—will be available for the huge numbers of people who will need to deal with the enormous impact of a stay in critical care.

Rehabilitation after a heart attack, trauma, or stroke has well established pathways. But rehabilitation for many of the thousands of people who spend time in intensive care every year is not automatic—despite severe muscle wastage and deconditioning, sleep disorders and severe fatigue, memory problems, anxiety, depression, and post-traumatic stress disorder.1 These “general” ICU patients may be the sickest people in the country, but once they leave they may be getting the least support.

Lack of clarity and consistency of access

In 2017 the National Institute for Health and Care Excellence set out quality standards for adults after critical illness,2 which were welcomed by specialists. However, it remains hard to say how many people who need this kind of rehabilitation receive it, as there are no consistently collected standardised data. In England, Wales, and Northern Ireland some 224 748 admissions were made to 263 NHS adult critical care units in 2018-19.3 Experts suggest that two thirds of such patients would need some kind of rehabilitation.

One area where data are collected is pulmonary rehabilitation for people with chronic obstructive pulmonary disease (COPD), which is offered to only 13% of eligible patients despite good evidence.4 There is also regional variability: …

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