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How AI used in hospitals improved clinical decision-making by 80% for Atria

Deveshi Dabbawala

June 9, 2025
Table of Content

Atria Healthcare is transforming how healthcare providers manage complex patient data with advanced AI tools used in their hospitals. Recognizing the burden clinicians face with fragmented and voluminous medical records, Atria built the PHA Generator, a Gen AI-powered platform that helps healthcare professionals perform faster, more accurate patient health assessments (PHAs), spot high-risk conditions, and make better medical decisions with AI used in hospitals.

The problem: fragmented data and delayed clinical decisions

As hospitals generated more patient data each year, clinical teams found it increasingly difficult to use them effectively. With health records scattered across systems and buried in unstructured formats, as much as 40% of critical health signals were either delayed or entirely missed. This often left doctors reacting to issues rather than preventing them. Fragmented software tools, siloed information, and limited analytics further compounded the challenge, forcing clinicians to spend valuable time piecing together a patient’s story.

For Atria, enabling earlier risk prediction and sharper clinical decisions wasn’t optional, it was essential to their business model. The stakes were high and they chose to drive AI use in hospitals: better insights meant faster interventions, improved care delivery, and measurable gains in hospital efficiency.

The solution: PHA generator

To solve these challenges, Atria built the PHA generator, an AI-powered tool designed to help care teams make faster, better-informed decisions by turning complex patient data into clear, real-time insights, driving effectiveness with AI used in hospital workflows.

Complete health picture

The PHA generator brings together all kinds of patient information, from lab tests and prescriptions to doctors’ notes, into one place. It creates a full, connected view of each patient’s health, so nothing gets missed.

Smarter risk detection

The system scans patient histories to identify warning signs and predict potential health issues early. It helps doctors focus on the patients who need urgent attention.

Spotting sudden changes

It tracks patterns in patient data over time and flags any major changes, like a sudden rise in blood pressure or unusual lab results, so care teams can respond quickly.

Clear, actionable insights

Before or during appointments, the tool provides doctors with personalized summaries and areas for investigation. This helps them explain conditions better, recommend the right treatments, and make every minute with the patient count.

Easy to use, hard to miss

The insights are automatically shared through everyday tools like Google Docs and Slack. Doctors and nurses also get real-time alerts, ensuring quick action when it matters most. This ease of integration exemplifies how AI used in hospitals can complement clinical workflows.

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The impact: faster decisions, better predictions, and proactive patient care

Atria’s PHA Generator is helping hospitals deliver more proactive and personalized care with measurable impact:

  • 60% time saved on manual data analysis, freeing up clinician hours for direct patient care
  • 70% more holistic patient view, improving clinical decisions with unified, real-time health summaries
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“GoML is our strategic partner in building the layer of Generative AI that helps our teams analyze and interact with the broad set of clinical data we collect."

Satwik Seshasai, CTO, Atria.

Lessons for other healthcare providers

Common pitfalls to avoid

  • Ignoring unstructured patient data from scope and using them only for manual analysis
  • Allowing patient data to remain fragmented across lab systems, clinical notes, and prescriptions
  • Treating Gen AI as a simple tech upgrade instead of a frontline care enabler

Advice for teams facing similar challenges

  • Invest in systems that unify structured and unstructured data into a single, actionable view
  • Start with a high-impact use case like early risk detection to drive adoption
  • Design AI tools that deliver insights during clinical care, not just to dashboards
  • Involve clinicians early to ensure the solution fits real-world needs

Want to boost care team efficiency by 60% and catch high-risk cases earlier?

Let GoML help you take AI used in hospitals to the frontlines of patient care, just like Atria did.

Outcomes

40%
Enhanced Data Integration: Seamlessly integrates data from multiple sources, providing a unified and comprehensive view of patient health.
60%
Increased Operational Efficiency: Reduces the time and effort required for data retrieval and analysis, freeing up healthcare professionals to focus more on patient care.
70%
Improved Accuracy: Minimizes errors associated with manual data handling, enhancing the accuracy of clinical assessments and decisions.