Data Integration
The system integrates real-time data from the provider's Electronic Medical Records (EMR) system and healthcare professionals' input. This ensures that all patient information is accurately captured and summarized.

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Client
A Fortune 100 Financial Services Company
Industry
Healthcare & Pharma
Capabilities
GenAI patient summarization, EMR data integration, and Azure OpenAI
Key outcomes
More time for direct patient care, reduced documentation time, and lower operational costs
Overview
In the field of home healthcare, effective patient care and operational efficiency are critical to delivering quality services. A leading healthcare provider faced challenges in streamlining internal processes and enhancing patient engagement. To address these issues, the organization partnered with Photon to develop a Generative AI (GenAI)-driven solution to automate patient summarization, providing healthcare professionals with more time for direct patient care and improving overall care outcomes.
The Challenges
Traditional methods of documentation and review, involving multiple healthcare professionals, were time-consuming and prone to inefficiencies. The main challenges included:
Summarizing patient care required input from various professionals, leading to delays and potential inconsistencies.
The provider needed a system that provided a concise and accurate summary of patient encounters, ensuring that all caregivers were informed of the latest care updates.
The manual process of summarizing patient data was resource-intensive, reducing the time available for direct patient care.
The solution
The system integrates real-time data from the provider's Electronic Medical Records (EMR) system and healthcare professionals' input. This ensures that all patient information is accurately captured and summarized.

GenAI is used to generate initial patient care summaries based on the latest data. Healthcare professionals can then review and refine these summaries, ensuring comprehensive and up-to-date documentation.

Every two weeks, the system generates a summary of each patient’s care over the previous 14 days. This update serves as the foundation for planning the next phase of care, improving overall care coordination and decision-making.

Technical stack
Azure OpenAI
Powers the AI-driven summarization and natural language processing capabilities.
Azure SQL Server
Manages the storage and querying of patient records.
Electronic Medical Records (EMR) System
Serves as the primary data source for patient information, integrated into the AI-powered solution.
Results
With automated summaries, healthcare professionals have more time to focus on direct patient care, improving patient outcomes and care continuity.
The automated process has significantly reduced the time spent on documentation, freeing up resources and improving overall workflow.
By streamlining the summarization process, the healthcare provider has reduced operational costs while increasing healthcare professionals' retention, as they are less burdened with administrative tasks.
Conclusion
This GenAI-powered patient summarization solution enabled the healthcare provider to significantly enhance patient care and streamline its operations. By reducing the time spent on manual documentation and improving the accuracy of patient summaries, the provider achieved better patient outcomes and greater operational efficiency. This case study highlights how AI can drive transformational change in healthcare service delivery.
"AI is revolutionizing healthcare operations by automating time-consuming tasks like patient care documentation. With GenAI, healthcare providers can focus more on delivering quality care, while also improving efficiency and reducing administrative burden. This technology is truly transforming the way healthcare organizations operate."

Mukund Balasubramanian
Co-founder & CTO, Photon