Smart Tools for Physicians: Automating Patient Care with AI
Artificial intelligence continues to transform healthcare, providing doctors with powerful tools for patient care. These innovative solutions not only improve diagnostic accuracy but also simplify many processes, effectively reducing the workload on healthcare professionals.
In this article, we explore how we developed an “Assistant” for our client’s clinic, designed to support doctors in their daily tasks.
Our Client
We were approached by a private clinic with a large team of specialists that has been providing medical services and consultations for many years. Given the high patient volume, the clinic’s physicians experience a significant workload. To help ease this burden, our client reached out for assistance.
Client’s Challenges and Objectives
Our client tasked us with reducing the paperwork burden on their doctors. This involves automating daily, routine data collection from patients.
The goal was also to eliminate the human factor in patient interactions. Doctors are only human, and during consultations, they may miss crucial details needed for accurate diagnoses or treatment recommendations. Our objective was to create a system that would always capture these details and even offer preliminary diagnoses.
AI Collects and Analyzes Patient Documents
One of the key features of our system is the automation of collecting and analyzing patient medical data, such as test results and scans. Now, doctors no longer need to gather this information from each new patient themselves - the “Assistant” handles it automatically. The AI conducts a preliminary analysis of the patient’s test results, identifies anomalies, and sends the findings to the physician.
How it Works
Once a patient schedules an appointment, the “Assistant” connects to their electronic medical record through the doctor’s personal profile and platform. AI queries the API using a function-calling method, after which large language models process the data, scanning for deviations from the norm. Logical Volume Manager (LVM) technology helps organize the data, while LLaMA 3.2 analyzes it. Utilizing extensive data sources, the model compares patient metrics (e.g., test results) against standard values based on official medical references, such as ICD-10 codes for disease classification. Retrieval Augmented Generation (RAG) supports the retrieval of this information.
The processed data is then sent to the doctor through RESTful API, allowing seamless integration with medical systems like CRM. This reduces preparation time for appointments and eliminates the need for manual data review.
Problem Solved
The AI system provides pre-structured reports with preliminary diagnoses, freeing doctors from routine tasks and allowing them to prepare for consultations more efficiently
AI-Driven Assistant
On the day of the appointment, we’ve already collected the patient’s data and shared it with the doctor, who can now rely on the “Assistant” to interact with the patient without needing to take notes manually. The AI secretary ensures that nothing is missed, recording the entire conversation, identifying key points, and creating complete medical documents. The full-text transcript is also available for the doctor’s review.
How it Works
The Automatic Speech Recognition (ASR) technology, based on Deepgram Voice AI’s Speech-to-Text API, records conversations between the physician and the patient. The data is then processed by LLaMA 3.2, which highlights critical points from the conversation.
Sentiment analysis technology, based on neural network models, helps assess the patient’s emotional state. For document creation, AI utilizes Robotic Process Automation (RPA), which automates the generation of standard medical documents, customized to reflect each patient’s data.
Problem Solved:
Doctors no longer need to document each patient complaint manually, as the AI automatically generates medical reports that can be quickly reviewed and edited as needed.
Conclusion
- Automated data collection and analysis simplify the preparation process. The “Assistant” provides structured reports with preliminary diagnoses, speeding up workflows.
- All patient interactions are recorded in their electronic medical records, relieving healthcare staff from manual documentation.
- By automating routine tasks, doctors can concentrate more on patient care.
The use of automation tools developed within BroutonLab’s AI healthcare platform enhances the accuracy and quality of services. These solutions simplify and improve patient interactions, making healthcare more precise and efficient.