Interview with Ira Haavisto, Senior Research Manager at the Nordic Healthcare Group Finland, responsible for the public healthcare system analysis work package of the EU-funded Health Emergency Response in Interconnected Systems project.
Why was intensive care unit occupancy an interesting research topic for the Health Emergency Response in Interconnected Systems project (HERoS)?
We performed a regression analysis of country features and healthcare system factors, and we found that none of those features directly correlate to COVID-19-related mortality. This is probably because European health systems are quite homogeneous, and the quality of care is generally good. However, the results might have been different if we had included data from countries outside Europe.
Then, after analysing data on health system utilisation during the COVID-19 pandemic, we saw that the capacity of intensive care units (ICUs) was a bottleneck in the treatment of COVID-19 patients. Therefore, we gathered information on beds, respirators and personnel at normal capacity and usage times, plus during the current COVID-19 burden. We were interested in the difference between the potential additional COVID-19-related demand and ICU availability at European level, so we developed a visualisation tool for ICU occupancy rates in Europe from spring to autumn 2020.
What was the biggest challenge you faced when developing this tool?
Estimating the utilisation of ICU capacity in different countries and regions during the COVID-19 crisis in the spring of 2020 turned out to be rather challenging. Data on the numbers of COVID-19 patients occupying the ICU and the total ICU capacity of a hospital in a normal state was often available. However, data regarding temporary ICU capacity increases, non-COVID-19 utilisation and buffer capacities was not.
How does the visualisation tool deal with improvisation, like if a hospital increases ICU capacity by converting other rooms or through a transfer of resources from another one? Does it receive real-time information?
The tool does not receive real-time data because hospital information in Europe is not so readily available. However, we know that even in cases where the tool showed that countries had reached their maximum theoretical ICU capacity, patients were still being treated, so we assume that such improvisation did take place.
What are the key take-home messages from this ICU capacity analysis?
One is that up-to-date information and data sharing, data transparency and data accuracy lead to faster responses and closer collaboration, thereby improving reaction times and leading to a more rapid ICU scale-up.
Another key finding is the possibility of cooperation, not only within a country but also transnationally at European level. Having this information readily available during the pandemic could have sped up decision-making and even allowed the transfer of resources such as personnel and equipment, in addition to patients. This could make a big difference in a health crisis like the one we are facing now.