EHR Search and Summarization
Our client is a leading healthcare organization in UK, with more than 1,000 bed occupancy and employing over 200 clinicians. Our customer possesses a vast repository of patient data within their Electronic Health Records (EHRs).
Problem Statement
Clinicians spend a significant portion of their time analyzing extensive Electronic Health Records (EHRs) to gather patient information. This time-consuming process can lead to Delayed Diagnoses and errors. In cases where the patient is unconscious and unable to tell allergies, preexisting conditions, NLP powered EHR search becomes a life-saving feature.
Our Solution
We developed an AI-powered EHR search and summarization solution which is composed of:
- Natural Language Processing for Document search
- Training Deep Learning Models to Identify and extract information
- RAG model to create concise and informative summaries highlighting key findings
Business Benefits
- Reduced Search Time by helping clinicians find relevant information 35% faster.
- The summaries created with the help of this RAG model accurately represents key findings 95% of time.
- Streamlined workflows minimize the need for staff assistance in locating information within EHRs, leading to cost savings upto 20%.
