The client, a private equity-backed healthcare technology company, is focused on enabling intelligent, coordinated care by automating care plan creation. As demand for personalized and outcome-driven healthcare increased, the ability to design accurate, timely, and effective care plans became critical to improving patient outcomes and satisfaction. However, existing processes were highly manual and resource-intensive, leading to inefficiencies, higher costs, and redundant clinical efforts such as repeated tests and avoidable hospital readmissions. The lack of proactive capabilities limited the organization’s ability to identify high-risk patients early and manage chronic conditions effectively. Additionally, care planning lacked a data-driven foundation, making it difficult to scale population health management initiatives. The client needed a faster, more intelligent approach to care plan creation that improves accuracy, efficiency, and clinical outcomes.
Ascendion leveraged its GenAI expertise to build a web application that analyzes high-risk patients and automatically generates personalized care plans.
The solution uses GenAI to process patient data and generate care plans that include goals, interventions, and long-term outcomes. This enables healthcare professionals to create structured and consistent care plans more efficiently while improving decision support.
A healthcare-specific knowledge base was created and embedded into the vector database to enhance the intelligence and relevance of generated care plans. The platform leverages Azure OpenAI LLM capabilities along with prompt engineering and vector database integration to support accurate and context-aware outputs.
Tech Stack: Azure, OpenAI, LangChain, Python, Vector Database (Pinecone), Prompt Engineering, Retrieval QA
The GenAI-driven platform improved efficiency, care quality, and innovation in healthcare plan creation.
At BMS, we wanted our consultants to focus on the possible, freeing up time lost to reading endless CV’s that could instead be used to really engage with people who are looking for that first step in their sales career. The solution we adopted found the right balance between machine efficiency and human empathy.
– Graham Halewood,
Chief Operations Officer
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