Yet, how do you identify risk groups? The great thing about process mining for hospitals is the ability to add contextual patient data. This allows us to filter on specific patient groups and identify possible risk groups that are e.g. more likely to be re-admitted than others. We made a visualization of this in the following figure. The right side offers diagnostic info and filters on tests or indicators. These allow us to discover how age, temperature, or death rates vary compared to the average patient. For ER readmissions, the average patient is older, has higher leucocytes levels, and a higher critical temperature. These patients should thus receive extra attention to see whether their admission cannot be avoided in the future.
The last step in this analysis of process mining for hospitals is a conformance test. It allows us to compare the designed process with what really happens. We define key performance indicators (KPIs) that compare violations against the conforming cases. For this case, we defined throughput time and activities per case. As 28% of cases involve a return to the ER, a root-cause analysis could be useful and reducing them will have a beneficial financial impact. In California (US) alone, sepsis hospital readmissions amount to an annual estimated cost of $500 M. Thus, reducing this by 20% and assuming equal spread over the 344 hospitals in California, each can save on average $290,000 annually. Subsequently, a conformance check like this is key for identifying root causes and continuously monitoring them. You can find a simplified version of the conformance checker in the link at the end of this article.
Process automation and continuous improvement checking
All the above already gives a good overview of possible areas of improvement within a hospital-patient treatment process. By finding initial bottlenecks, inefficiencies and with the help of the AI-powered assistant, the hospital is able to continuously analyse new incoming data to spot e.g. new seasonal trends, dynamic changes in their processes, and novel violations. These can then act as triggers for further actions such as notifying the correct people or adjusting forecasts in other IT systems.
Process Mining with Apolix
This analysis shows interesting insights into processes mining for hospitals. As data specialists, we are here to help you on this journey. We support setting up initial analyses, educate your workforce, and offer strategic advice on your analytics strategy. Moreover, as data enthusiasts, we love to explore new opportunities to put your data to work – Are you curious about how process mining can make your organisation more efficient? We love to discuss this over an (online) coffee!