Datadriven optimalisation of the Admission Process
In the interview with Willem Teunissen of De Zorgondernemers, it came up several times: in order to really optimise the admission process in mental health care, data is needed. Only when you have insight into the inflow, outflow and throughput and have made the various queues in the process measurable, can you see where the bottlenecks are. But how do you acquire that data? What is needed?
Figure out the current process
First of all, you have to map out the current process. How is the admission process set up? Does what is documented correspond with what happens in practice? Which stakeholders are involved in each step? How does a patient move through this process, at what points does the patient end up in a queue? In what ways can the patient start the process, move on or leave? Does each step have a logical and efficient follow-up? How are emergency admissions handled?
The importance of measuring
You can then analyse step by step which data can be linked to each step of the process and what the various stakeholders in the process want to have insight into (think, in addition to planners, healthcare providers and IT specialists, also of those working in strategy and policy). Once you have mapped out what everyone wants to know, it is time to explore how to collect this information. Has the admission process already been digitalised? Then check what is already available out-of-the-box and contact your supplier for the data you are missing.
If you still need to digitalise the process, you are in a position to indicate with your intended supplier(s) what data you need during the acquisition process. Before you start the digitalisation project, you will know whether your intended solution meets your data requirements.
Please note: historical data is often virtually impossible to retrieve, so it is important to make things measurable as soon as possible.
Optimalisation!
Once you have enough data to do meaningful analyses, you can see where the bottlenecks and opportunities lie. Are there empty beds on a regular basis? Why is this? Is the queue longer than expected in a certain part of the process? What is the impact of holiday periods and public holidays on capacity management? Do certain registrations regularly lead to mistakes?
In addition, insight into the entire process means that you can work on a predictive waiting time for different scenarios - think of a regular admission, emergency admissions, admissions for certain types of patients, etcetera. By making this transparent, you can better manage the expectations of both patients and practitioners.
Want to discuss?
Many of our customers use our Admissions24 module in combination with DataWarehouse24. With this powerful combination, you digitalise the process and have numerous opportunities to use large amounts of data for all kinds of analyses. We are happy to discuss your organisation's data requirements with you.