Multifaceted, analytical approach to COVID-19 decision-making
The complexity of COVID-19’s constantly changing dynamics is such that the rapid collection and analysis of data sources is vital in identifying hotspots and forecasting peak demand, among others.
Life-threatening pandemics, such as the current COVID-19 crisis, create extraordinary challenges for governments, healthcare systems and supply chains. In seeking to overcome these difficulties, analytics can help medical establishments and governments to more accurately visualise, forecast and make informed decisions about the unique challenges created by such crises.
By putting data to work and using it to support analytics-based decisions, many benefits can be gained. These include assisting hospitals to use predictive analytics to allocate critical, high-demand resources; collaborating with public health officials to build epidemiology models that forecast impacts on populations and infrastructure; and working with governments to optimise medical resources so citizens get the best health outcomes possible.
"The response to COVID-19 has been made more complex by the pandemic's constantly changing dynamics, which requires health and government decision-makers to quickly understand, measure and react,” says Akesh Lalla, country manager of SAS.
“This response requires a multifaceted approach, including the ability to rapidly collect data and integrate data sources, forecast peak demand and identify hotspots where inventory and personnel shortages will affect care, and taking action to prioritise and allocate resources.”
All around the globe, the implementation of analytics has played a critical role in the fight against this disease. In Rome, for example, there has been an urgent need for information from the services and departments involved in the COVID-19 emergency. This includes predicting, in the short term, the number of cases; analysing diagnostic/therapeutic information collected from medical records; reporting and optimising allocation of resources; and preparing analysis tools with artificial intelligence (AI) in order to plan a longer-term response.
“The rapid co-ordination of medical resources, made possible by effective analysis of all the relevant information, informs data-driven decisions that help make the best choices for patients. Analytical software can also help to solve one of the greatest challenges of any pandemic: namely forecasting where and – most importantly – when intensive-care personnel and resources are needed.
“Using analytics software, it becomes possible to not only show the current use of existing intensive care beds, but also to forecast the expected demand for resources. Armed with this data, government agencies and hospitals can adjust the deployment of resources in advance, to meet expected demand. In addition, interactive reporting on the current situation can be made available to facilitate better planning of staff and supplies.”
It is obvious that medical resource optimisation is critical in times like these, which is why in the US, innovative models have been created to help hospitals forecast patient volume, bed capacity, ventilator availability and more. These models provide timely, reliable information for hospitals and health departments to optimise healthcare delivery for COVID-19 and other patients, and to predict impacts on supply chain, finance and other critical areas.
“Unlike standard forecasts that focus on a projection based on a single set of assumptions, these analytical models are able to create worst-case, best-case and most-likely scenarios, and can adjust in real-time as the situation and data change. For example, the models could easily factor in something like social distancing's dampening effect on disease spread,” continues Lalla.
“These models can be used to support decision-making, enabling hospitals to predict and plan for future demands on the health system, such as ICU beds, personal protective equipment and ventilators.”
Furthermore, in Bulgaria, they have implemented an integrated platform that provides a national centralised register of COVID-19-related cases in the country. This platform digitalises personal and medical data collection from institutions working with COVID-19-related cases, adds Lalla, such as regional health inspectors, border police, the Ministry of the Interior, general practitioners, hospitals, laboratories and municipalities.
“When this platform is integrated with advanced analytics, the system provides interactive, multidimensional visualisations and automated analysis of epidemiological data, as well as predictions about the potential impact of the epidemic.”
“There is no doubt that knowledge is empowering, which is why it is so critical to use the most advanced analytics technology available, in innovative ways, to help our medical and government experts make the best decisions to respond to the pandemic. After all, it is only through information, analysis and understanding that we can hope to defeat this virus,” Lalla concludes.