Intelligent tool for prioritization automates the distribution of cases at Patienterstatningen

Case: Patienterstatningen

Automatic prioritization and distribution of cases ensure a smooth flow in Patienterstatningen’s case processing.

Automatic visitation frees up time and reduces case accumulation

Which compensation cases are most urgent at the moment, and which caseworker is most qualified and has the time to assess the cases? This prioritization and distribution of new compensation cases take place all the time at Patienterstatningen, which each year processes around 11,000 compensation cases from patients who have been injured in the healthcare system or as a result of side effects after medication.

So far, four office managers have distributed cases to the individual lawyers’ desks manually based on a prioritization of which cases were most urgent and who was best for the task. Now, this prioritization and distribution of cases happen automatically. It frees up time for other tasks and ensures a smooth and fair case flow for the benefit of both staff and patients.

Patienterstatningen expects that the solution will give them a more even case flow because cases should not accumulate now. Previously, it took an average of 30 days before a case was assigned to a caseworker. With the help of the new engine, the cases only lie an average of 2.5 days before they are assigned a caseworker.

Automatic prioritization and distribution once an hour

The engine built by twoday kapacity has two different tasks:

Prioritization

Initially, the engine prioritizes the cases according to which ones are most urgent. For this purpose, Patienterstatningen has set a number of priority parameters on which the cases are ranked. Based on a total of eight priority parameters, the engine reviews all the cases once an hour. In this way, the engine keeps the priority of the cases updated in case their condition should change or more urgent cases occur.

Distribution

The engine then distributes the cases to relevant caseworkers based on the employees’ qualifications and capacity at the given time. The engine takes into account significantly more data than is possible for a human while ensuring that no cases are forgotten.

"If an office manager had to review all the cases once an hour based on the many different parameters, the person would never finish. The engine, on the other hand, can do it at rapid speed".

Thomas Harding Brix, IT Manager, Patienterstatningen

Ongoing assessment and optimization

Following a pilot project in one legal office, the engine has today been implemented in all legal offices at Patienterstatningen. In the future, an ongoing assessment and optimization of the engine will follow.

“It has been essential for us from the start to involve the employees who were to use the tool so that they could shape how the engine prioritized cases so that it became a valuable tool. The engine is still being fine-tuned, but the cases are distributed as the office managers themselves would have done. So we are very happy with that.” – Thomas Harding Brix, IT Manager, Patienterstatningen.

The project has also been extremely well run by Kapacity, says Thomas Harding Brix and elaborates:

“The process has exceeded all expectations. The consultant was good at getting to know our business and data in a very short time. In addition, the consultant has been really good at running the project as well.” – Thomas Harding Brix, IT Manager, Patienterstatningen.

Technical details about the engine

The engine is a Bottle Application in Python and can thus be easily integrated into Patienterstatningen’s main application.The linear model is fully configurable through a UI available to the relevant users of the solution. New parameters can be made from day to day through open placeholders for suddenly emerging needs.

"The technology allows us to constantly identify the most urgent cases and make a thorough prioritization and distribution. In other words, we receive fantastic help with a complex task that we cannot do at the same speed ourselves".

Thomas Harding Brix, IT Manager, Patienterstatningen

Other Data Science projects in the pipeline

Over the past five years, Patienterstatningen has digitized internal business procedures and processes – most recently with the help of Data Science. But the project does not end here. Patienterstatningen continues to see great potential in harnessing artificial intelligence.

The next step is that the prioritization engine must be further developed by Kapacity so it can be used in other parts of the case processing as well. A Machine Learning model must, for example, prioritize the order in which a compensation case is to be discussed with a doctor, and at the same time identify and anticipate cases that, based on numerous similar cases, can be decided without a medical assessment.

This model will allow Patienterstatningen to process certain cases more quickly, as the medical assessments can be a bottleneck in the case processing.

About Patienterstatningen

Patienterstatningen deals with compensation claims from patients who have been injured in connection with treatment at, for example, a hospital, at their own doctor, or as a result of side effects after a medicine.