Tech firms helping NHS plan coronavirus response

Four technology companies are helping the NHS model the consequences of moving resources to best tackle the coronavirus pandemic.

Data collected via the NHS's 111 telephone service is to be mixed with other sources to help predict where ventilators, hospital beds, and medical staff will be most in need. Amazon, Microsoft, Palantir and London-based Faculty AI are helping health chiefs, with Secretary of State Matt Hancock expected to sign off the plan soon.

The goal is to provide the NHS with interactive dashboards that pull together the disparate data it and its partners already hold. This will involve using data about: what ventilators are being used where; levels of staff sickness; patient occupancy levels of hospitals broken down by general beds, specialist beds and critical beds; capacity of A&E departments; and length of stays of patients with coronavirus.

Using the data, decision makers will then be able to better understand how the virus is spreading at a local level in order to identify risk to particularly vulnerable populations, proactively increase resources in emerging hotspots, ensure critical equipment is supplied to the facilities with the greatest need and divert patients to the facilities that are best able to care for them based on demand, resources and staffing capacity.

Although the project is likely to give rise to privacy concerns, particular given Palantir’s involvement, the NHS intends to make sure that all the data involved has been anonymised so that personal details cannot be tied back to any individual. Once the coronavirus crisis passes, the healths service will destroy all records.

A source explained: "Every hospital is going to be thinking: Have we got enough ventilators? Well we need to keep ours because who knows what's going to happen - and that might not be the optimal allocation of ventilators. Without a holistic understanding of how many we've got, where they are, who can use them, who is trained, where do we actually have patients who need them most urgently, we risk not making the optimal decisions."