Health & Medical

Faster throughput times of care referrals at specialized healthcare clinics

Before deploying a virtual employee, the Customer Service Department at healthcare clinics had to process up to 750 care referrals a week, all manually! Imaginably, this process took up a lot of time. We offered a solution that resulted in improved data quality in the electronic patient records. Also, the faster throughput times of patients freed up time for medical staff to have more personal interaction with each patient.

3 weeks delivery time
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Use case: Processing up to 750 referrals a week manually

Multiple emails come in on a daily basis at the Customer Service Department (CSD) at a healthcare clinic. These emails contain healthcare referrals, and these are to be processed manually by the CSD. First off, the referrals have to be entered into their electronic patient record system, EMMA. Then, the employee uses the referral to check whether the patient is already registered into this system. If this is not the case, the patient is added to the electronic record, based on its social service number. Lastly, the worker must add the referral documents to the patient record as well.

The number of referrals goes up to 750 a week, and all of these referrals are processed manually. The fact that each transaction has a lengthy throughput time, makes the entire process time consuming. Consequently, patients might not be addressed in a timely manner. The time invested in processing these referrals manually is valuable time that could be spent on the patients instead.

Applied technologies

Robotic Process Automation

2

Months to ROI

2701

Hours saved anually

95%

Error reduction

200%

Increased time efficiency

Our solution: Deploy a virtual employee to automate referral processing

This lengthy process does have all the requirements needed to implement a smart UiPath RPA-based solution. We built a robot that constantly monitors the mailbox from the CSD. When an email containing a referral comes in, the virtual employee reads the email and extracts the relevant information. It then decides how much of all information is to be added to the electronic patient record of this respective patient. All these steps are performed in the background. Our robot was built to perform the following tasks, after being triggered manually at the office:

  • Read and extract healthcare referral from email
  • Check whether patient exists in electronic patient record system (EMMA)
  • If not, add the patient to record system based on its social service number
  • Add referral documents to patient record

Now that our solution has been implemented, 2701 hours are annually saved, reducing the significant amount of workload of the CSD! These hours can now be used for more value-adding tasks. Also, patients can now be helped 20 hours earlier, which positively contributes to the patient experience.

Our RPA-based robot offers a solution that is effective, efficient and reliable. Employees of the customer service department have less administrative tasks and can refocus on work that matters!

Integrated applications for this case

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Inspiratie

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