About the Customer

A prominent urology expert with an expansive reach, our client offers top-tier treatments across 30+ locations in Georgia through a dedicated team of 40+ providers. Their commitment? To constantly improve patient outcomes. Their challenge? Delving deep into two years of unstructured urologic data to gauge treatment effectiveness.

Tangled Data and Disconnected Silos  

Struggling with limitations in their EHR system, the client faced the challenge of extracting and summarizing crucial physician progress notes to diagnose kidney stones in specific patients. The absence of structured data hindered their ability to track vital details like stone size, changes over time, and location, impeding assessments of patients' health improvements or decline. They needed a solution to discern trends in two years of data, vital for effective treatments and averting life-threatening situations. The crux of the problem was to inspect volumes of unstructured data where doctors' notes and observations lacked a predictable template with each entry having a unique narrative.

Steps Toward Success   

The client, through their EHR system, extracted a file containing patient visits reported in the last two years. The shared file included crucial details such as: Patient ID, Visit Type, Date of Visit, and Treating Physician. An ingenious RPA solution was built to tirelessly scan through each entry, locate the corresponding patient record in the EHR system and inspect the progress reports for keywords like: “echogenic”, “foci”, “kidney”, “left” and “right”. When all these keywords occurred in the same sentence, it was obvious it included the size too, which was also captured as part of the scrutiny

The insights gathered were immediately added to the excel file against each patient’s record. This was then used by key stakeholders to derive insights on the well-being of their patients. The primary aim was to prioritize those severely impacted with stones larger than 0.6 cm, making it necessary for potent treatments. The data was leveraged to assess treatment efficacy by meticulously comparing stone sizes and ascertain whether they exhibited any growth over time, demanding providers deliver better treatment methods.

The shared report became a lens through which patterns emerged, revealing the frequency of a patient's hospital visits and the impact of treatment delivered on their patient’s well-being, an effort that would have proved to be futile with manual intervention.  

Improving Care Delivery Through Automation 

Efficiency Redefined

Efficiency Redefined: The bot processed a staggering 900-1000 records in merely 8 hours, needing not more than 30 seconds to derive insights. 

 Precision Perfected

Boasting a 99% accuracy rate, the bot autonomously identified patients with kidney stones, eliminating any need for human intervention.   

Data-Driven Decisions

The client, now empowered with crystallized insights, bases their medical strategies on tangible data, enhancing patient care. 

Technology Stack 

Let's Move to Value Based Care

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