One of the many lessons to emerge from the Covid-19 crisis is that managing and mapping the resourcing of healthcare personnel effectively during a pandemic is a matter of life and death.

UK healthcare leaders have faced immense organisational challenges ensuring hospitals, care homes, and other residential care facilities have the right level of appropriately skilled healthcare and support staff, while at the same time ensuring worker movement and deployment doesn’t trigger new infection outbreaks.

The NHS and private healthcare providers have been heroic in their efforts. Against a backdrop of PPE shortages and inadequate testing, decision-makers have shown agility and endurance. The rescheduling of non-urgent appointments, triaging of primary care, greater use of online diagnostic platforms, and retraining people into new roles have all helped spread the load. Meanwhile dedicated healthcare staff continue to work long hours to ensure as many patients are treated as possible.

Despite this determined response, the complexity of the Covid-19 logistical challenge has resulted in a series of systemic stress points ranging from concerns about the way that the UK’s seven overflow Covid-19 hospitals will be staffed, to under-reporting of Covid-19 illness among doctors. Most recently the deployment of agency workers in care homes has come under scrutiny as has the high incidence of Covid-19 infection within hospitals.

What happens to the UK’s overstretched healthcare workforce if there is a second wave of Covid-19 post-lockdown, or a flu surge in the autumn? And how will the system manage the flow of Covid-19 cases when normal service is resumed?

Digitally-powered tech has evolved to the point that it can assume much of the logistical and scheduling pressure of healthcare staffing in a pandemic. Big data, analytics, cloud computing, and data visualisation are just a few of the tools that have a key role to play.

British Columbia (B.C.)’s big data healthcare solution aimed at managing staffing in its long-term care and assisted living facilities during the pandemic, is a case in point. When Covid-19 reached the province, the B.C. Ministry of Health and the B.C. Public Health Officer quickly recognised that workers and residents in the province’s care homes were particularly at risk from cross contamination between sites, as it’s common for workers to work across multiple sites. The province enacted a Single Site Initiative aimed at limiting workers to working at a single site of their choice for the duration of the epidemic.

Ahead of framing the legislation, B.C. officials sought to map how care homes were staffed currently and how this needed to change to minimise the spread of infection. Analytics were used to balance optimum staffing supply and demand at each of the care homes together with workers’ first choice of sites to work from.

Mapping the optimum number of staff required at each site in advance allowed B.C. health officials to frame legislation that stood the best chance of reducing the risk of Covid-19 transmission between facilities.

The B.C. government’s overall approach to preventing the spread of Covid-19 seems to have paid off, with B.C. reporting a lower number of cases than some of the other provinces. What’s more, there have been far fewer deaths in B.C. care homes compared to other provinces. Experts are attributing this outcome to B.C.’s swift move to enact measures such as the Single Site Initiative.

Could a similar approach to B.C.’s big data healthcare solution be used to tackle some of the UK’s complex healthcare resourcing issues?

Post Covid-19, could it provide a blueprint for managing seasonal outbreaks such as flu and for distinctive social contexts such as prisons?

The first iteration of the B.C. big data healthcare solution was up and running in five days. However, for a tech driven healthcare solution to be effective, it requires several steps to be put in place:

  1. Maximise pre-existing data: The data required to make this kind of digital-first approach work isn't overly complicated, but it can be difficult to utilise. The first step is to transform the relevant data stores to be consistent and easily accessible. B.C.’s solution was based around payroll data supplied by employers as a result of an executive order from the B.C. government. Working with pre-existing data gives an immediate springboard, and meant the tech team could execute the solution in days rather than weeks.
  2. Make it easy. Any digital solution requiring a large number of people to input their data, needs to be easy to use. The B.C. Single Site Initiative used an app featuring a streamlined user journey, via an easy to use web interface. This meant it was straightforward both for employers to upload the data and for multi-site workers to enter their preferred employment site.
  3. Ensure stakeholder buy-in early on: While care home employers were mandated to share employee data, the B.C.experience was that employers were more comfortable about providing payroll data once they were reassured it was collected securely and in a way that ensured privacy. Unions also needed to be reassured that their members were not going to suffer financially as a result of B.C.’s Single Site legislation – which meant they were included in dialogues about overtime and wage differentials across sites.
  4. Embrace the cloud: When it comes to effective staffing solutions in a pandemic, speed to market is massively aided by deploying existing cloud architecture. Using Google Cloud Platform and Atlassian tools, made it possible to design and deliver a highly secure data analytics pipeline that collected staffing data in real time for over 100,000 healthcare workers, at over 1,200 facilities in B.C.
  5. Visualise the problem: Extracting and interpreting data about staffing requirements during a crisis is given a significant boost by using data visualisation models. Data visualisation makes it possible for analysts to comprehend large volumes of interconnected data, and assess how the situation is evolving in real-time. This in turn enables health authorities to make informed decisions about optimal resourcing.
  6. Keep iterating: It’s important to keep iterating the original system to ensure it is as accurate as possible. Version two of the B.C. big data healthcare initiative now live in the province, is a logged in validated system that does all the data cleansing at the front end, so the user will only be able to submit data if it's clean.

Conclusion

In the context of the current pandemic and any future outbreaks, big data, analytics, cloud computing, and data visualisation can be harnessed to develop a real time picture of worker movement and cross-contamination hotspots, allowing healthcare leaders to make critical resourcing decisions across both public and private healthcare facilities. What’s more this sort of “big data healthcare” solution can be deployed in multiple contexts such as prisons, schools, campuses and other institutions.

While it’s never too late to adopt a big data healthcare solution, the earlier it’s implemented, the better the outcome for front line workers, residents and policy-makers alike.

Andrew Dunbar GM EMEA of global digital consultancy Appnovation