Transforming clinical libraries into a GenAI-powered clinical advisor | HCLTech

Transforming clinical libraries into a generative AI-powered clinical advisor

Enhancing healthcare outcomes requires more than manual processes. To revolutionize how this provider’s clinicians access information to inform decision making, it turned to the power of Microsoft Azure OpenAI and GPT-4.
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The Business Challenge

As one of America’s largest not-for-profit health plans, the client’s physicians are responsible for making medical decisions for 12.5 million members. To help ensure care is delivered in the most efficient and effective manner possible, it is continuously looking to refine its medical practices.

10,000

Clinicians

Not-for-profit healthcare

Business vertical

North America

Geography

To find information critical for diagnoses and clinical decision making, the client’s 10,000 clinicians historically needed to search extensive clinical libraries. The client’s ambition was to enable clinicians to swiftly access relevant documents and summaries — as well as valuable advice based on trusted data sources — by transforming its existing Clinical Library into a generative AI-powered Clinical Advisor.

The goal was to enable clinicians to quickly understand critical content to improve decision making with professional accuracy — so they could have more time for patient care.

Challenge

To enhance healthcare outcomes for over 10,000 clinicians, the solution needed to:

  • Improve the efficiency of searches by offering advanced search features
  • Empower clinicians to uncover necessary information, both stated and unstated
  • Deliver concise document summaries for quick understanding
  • Tailor responses to healthcare specialists’ needs
The Business Challenge

The Generative AI Transformation

HCLTech took on the client’s challenge with gusto, building a comprehensive solution integrated with Microsoft Azure OpenAI 
and the nuanced understanding that GPT-4 is more than a search tool 
— it’s an interactive, responsive environment that can adapt to unique requirements at scale.

We integrated state-of-the-art technologies — like Retrieval-Augmented Generated and Fusion — to dramatically improve the precision of information retrieval and ensure responses are both 
relevant and reliable. This also improved the outcomes of similarity searches, helping clinicians quickly locate and match alike data 
points within the large datasets.

The GenAI Transformation
New York Jets

By leveraging various smaller language models fine-tuned for distinct tasks, the system flow summarizes complex data, interprets queries or learns from past interactions to improve future responses. This enables the solution to deliver on the nuanced need of every clinician, offering customized insight with precision. Its multi-persona capability ensures that, regardless of if the clinician is a cardiologist, a general practitioner or any specialty in between, they receive the information tailored to their practice, patients and questions.

A key feature of the solution is integration with LLMOps, which provides the foundation for continuous improvement of the system and operational excellence over time. With this added observability, nothing is missed. Additionally, the robust capabilities of Microsoft technologies, combined with HCLTech’s innovative approach, ensure a scalable and efficient deployment that meets the dynamic needs of modern healthcare environments.

The Business Results

By building the system with cloud capabilities that enable it to scale seamlessly, the solution:

Maintains performanceMaintains performance
Ensures reliabilityEnsures reliability
Doesn’t compromiseDoesn’t compromise

Boosted by an underlying framework that is robust against hallucination, the system stands out in its capacity to analyze and generate information.

It represents a shift toward more proactive, transparent healthcare — not only for the client but for the future of healthcare as a whole. It’s a new paradigm, where every piece of data is an accessible, actionable asset.