Scaling a medical billing product with Python and integrating multiple EHRs at once




San Francisco, USA




2 RPA developers


Python, Docker, Google Cloud Platform


4 months

Superbill automation use-case


EHR systems integrated


patients processed daily


men-hours saved monthly


av. cost of a patient profile creation


Superbill is a San Francisco-based ​​Medtech company helping healthcare providers manage insurance claims, medical billings & process reimbursements. They provide solutions for healthcare providers (clinics, hospitals) and individual clients.


The SuperBill team approached us with the mission of optimizing insurance claims processing and passing the client's EHR data to SuperBill's medical billing system - SuperPay. Due to the lack of public API or easy integration options in many EHRs, it hasn't proven easy. Before the arrangement, most of these tasks were done manually.

The SuperBill team also wanted to leverage the patients' network of their healthcare providers and convert them into individual clients. From the providers' perspective, it's a win-win situation: patients get reimbursed for free, providers get paid the total rate, and the billing of their clients is taken care of.

A secondary goal was to automate several manual EHR-related operations.

Finally, the automated workflow had to be fully HIPAA-compliant and in line with all California and US regulations.

Automate processes in healthcare


SuperBill collaborates with multiple health providers (clinics, hospitals), all using various EHR solutions.

From the SuperBill perspective, the user content of these EHRs is one enormous list of potential clients.

To reach out to them, we have created a biller-level user in every clinic EHR system. Then, the RPA bot would automatically log in to the tool, scan the patients' profiles, and identify these prospects who will be eligible for SuperPay service. We even automatically registered/activated the biller accounts with a separate bot!

These prospects would be automatically approached (via email) with a "Join the SuperPay platform!" proposal. If they agree to join the platform, the bot will automatically download all the personal and billing information from the EHR and pass it to the SuperBill system.

This way, new patients have been enrolled in the platform almost effortlessly.

From the clinic's perspective, this is only a beneficial situation - the profit generated from a single patient did not change. But, at the same time, the whole billing effort has been taken care of by the SuperBill team.

On top of that, we have also created several bots automating various functions in SuperBill's workflows, such as:

  1. Patient payment method updates. The bot needed to log in to SimplePractice, find the patient's profile, and change the payment method to a different credit card.
  2. Retrieving claims details. Which allowed to have end-to-end data collection automatically.
  3. The process of account creation is from the link. When you add a user to SimplePractice, they receive an email and must create a new account. Unfortunately, they were doing it manually, which took quite a lot of time, was mind-numbingly dull, and was prone to human error.
  4. They were creating patients in SimplePractice in bulk. It took us 60 minutes to upload the first thousand patients. At the same time, an employee would do it for a couple of days.


Regarding the technical side, we used Python instead of a ready-to-use RPA framework.

Python comes with challenges mainly due to the need for built-in RPA facilities. But on the other hand, it allows for better meshing with existing, non-RPA code. Integration with existing code was the most vital driver to that decision, especially when it comes to the code communicating with other EHRs via API and integration with existing flows.

The solution has been deployed on the Google Cloud Platform’s Cloud Run. It allowed for easy scaling of the solution to quickly process as many patients as required. Using GCP also allowed for simple integration with Gmail to send emails to patients and receive emails from EHRs.

Here is a quick sneak pick of creating patient profiles and scheduling appointments in TheraNest EHR:


We have built a custom system that automatically processes insurance claims and passes the patients' data from various EHRs to SuperBill's SuperPay system in seconds without errors.

The system created by the Flobotics team allowed SuperBill to achieve scalability never seen before. Before that, all the efforts had been made manually, which took a lot of time (and money!) and was prone to human mistakes.

We have also automated several functions in SuperBill's system, such as patient creation, account creation, or updating payment methods, further streamlining SuperBill's operations.



Thanks to using Python, the platform yielded excellent results, especially regarding costs, which was a priority for SuperBill. The solution is portable, cost-effective, simple to deploy for someone with no RPA experience, and its architecture is easy to understand.

After delivering the first part of the project, we continued collaborating with SuperBill, integrating more EHR systems and further developing automated features.

SuperBill - thank you for your trust!


EHR systems integrated


patients processed daily


men-hours saved monthly


av. cost of a patient profile creation

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