When doctors get more annoyed at their software than at their bitter coffee, you know the workflow is broken. In a typical day radiologists bounce between scheduling systems, image viewers, reporting tools, and dictation apps, each demanding its own clicks and logins. Instead of a clear flow from scan to report, they fight distractions at every step.
That is why together with our customer we have been building a platform that pulls all the daily tools of radiologists into a single, streamlined workspace. One of the key pieces we brought into that workflow is MD.ai, an AI-powered reporting and dictation system.
In this post we will share how we integrated it so that doctors can spend less time juggling apps and more time dictating reports that matter.
Our vision for MD.ai integration
In this platform, the daily workflow begins with the worklist, a list of imaging exams that each radiologist needs to review. When a radiologist selects an exam in the worklist, the platform launches all applications that are part of the configured workflow for that imaging center. These can include an image viewer for opening scans, a PACS system for retrieving images, a dictation or reporting tool such as MD.ai, or scheduling and patient data modules. Each application runs in its own interface but listens to the platform for context and commands, performing its role in sync with the others.
For MD.ai this means opening the reporting window already linked to the selected exam, refreshing automatically as the radiologist moves to the next case, and closing once the report is complete. No additional logins are required, since the platform passes user identity directly. At the same time, MD.ai returns status updates such as Draft, Signed, or Discarded back to the platform, so the worklist always reflects the current state of each exam.
How we built the MD.ai integration
The trick with integrations like this is to make the hard stuff invisible. MD.ai should not feel like another app on the side, it should act as if reporting was built into the platform from the start. To achieve that, the platform takes care of all the background work, passing the right data to MD.ai, listening for events in return, and keeping everything in sync.
Here is how the flow looks in practice:
MD.ai was wired into the platform so that everything just flows. There are no second password screens. The system carries a secure site-level token with every request, so radiologists get in without another login. There is no hunting for the right case either. When a radiologist opens an exam in the worklist, the platform passes the exam context straight to MD.ai. The right report opens immediately in the reporting window without extra steps. There is no mess of open windows. The same reporting window stays active and refreshes automatically as the doctor moves through the queue.
MD.ai also talks back to the platform. It sends updates whenever a report is opened, saved, or completed. The platform listens, updates the status in the worklist, switches icons, and closes reports once they are finished. For admins, setup is painless. A simple configuration screen is all it takes to add the endpoint, drop in the token, and enable the integration on the Clinical Info page.
The result in numbers
Before integration, opening MD.ai and bringing up the correct report could take 30 to 40 seconds. Now it loads in less than 10 seconds. With 40 to 50 reports per doctor each day, this saves around 15 to 20 minutes of effort for every radiologist, and across a full team it adds up to several hours of regained focus daily.
The bigger difference is not just in speed but in accuracy. Automated status updates and exam closures cut down on manual steps, reduce the chance of errors, and keep the reporting flow continuous. This lets radiologists direct more of their attention to patients’ data and helps clinics handle more cases without additional strain on staff.
Bringing it all together
Our team specializes in building healthcare integrations that eliminate repetitive actions, reduce the risk of errors, and improve the efficiency of clinical staff. The MD.ai integration is one of many examples where we made a third-party system operate as a seamless part of a larger workflow.
We deliver these projects with attention to detail, predictable results, and scalable architectures that adapt to new sites and environments. If your organization is planning to modernize radiology workflows or integrate multiple clinical systems, we are ready to support you with proven expertise.
