Triaging COVID-19 patients

This case study illustrates how the Maastricht University Medical Center handled the great influx of patients during the start of the COVID-19 pandemic. The center succeeded in quickly separating patients from non-patients, by implementing Avola Decision as a triage tool.

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Which challenges did the client face?

The Maastricht University Medical Center faced a lot of complexity about the best triage for patients that were being rushed into the emergency rooms during the start of the COVID-19 pandemic. In order to assess the best care and protect the medical staff and non-COVID-19 patients, the aim of the Maastricht University Medical Center was to strictly shift COVID-19 and non-COVID-19 patients at the ER. However the protocols on how to triage these patients to the proper wards were complex and changed frequently.

We Are Not, a consultancy firm in the healthcare industry, specializes in developing intelligent solutions that assist medical professionals in guaranteeing the quality and safety of healthcare. They advised the medical center to use Avola Decision for this assignment because it allows Decision Modelling and it would enable them to treat patients consistently.

How did we solve this?

The parties discussed the complexity of medical decisions that needed to be made for COVID-19 patients with the medical staff. Bottlenecks in the current process were identified and some crucial inconsistencies were discovered.

This was achieved through decision modeling in Avola Decision. Each CLA was modeled: the specifications made into business rules and the business rules gathered into a decision model. These models were then automated through Avola Decision. Now, when a worker registers his or her working hours the system will assign them to the correct CLA and the calculations will be made automatically. No manual corrections are needed anymore, and the complete calculation is logged so that it is clear why this outcome was reached.

Then We Are Not used the decision models of Avola Decision to translate the protocols of the medical center into clear rules. The next step was to translate the triage rules into decision models which were then automated in Avola Decision within a week. The result was that the medical staff and the other hospital staff now had access to a clear and consistent triage tool for COVID-19 patients. If the protocols changed, the rules could quickly be adapted in Avola Decision. As a result the healthcare staff at the ER just had to follow the application, knowing that it would consequently guide them through the latest version of the protocol.

Which results did Maastricht University Medical Center observe?

By leveraging Avola Decision as a triage tool the medical staff benefitted from various advantages. They no longer had to plow through the latest versions of the protocols. Changes were added to Avola Decision immediately, enabling the hospital to ‘go live’ with a new protocol with the push of a button. This enabled the medical staff to make informed decisions at speed.

The platform improved the transparency and consistency of the decision-making process. For the first time, the knowledge of the medical staff was translated into clear rules. Their decision-making process regarding the triage of patients was no longer a black box but became fully transparent and consistent.

By capturing complex decisions in Avola Decision, they no longer have to keep this complex knowledge in their heads. It makes their decision-making process transparent and brings clarity and allows healthcare professionals to spend more time on their patients.

Eventually, about fifty staff members working in the ER used the triage tool on a daily basis until the number of COVID-19 infections decreased. The hospital screened nearly 2000 people using Avola Decision and it allowed them to treat patients quickly and consistently, ensuring the best possible triage in a chaotic time.

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