AI-Powered Copilot for Doctors

Client

MedTech Startup

Services

Web development

Industry

Healthcare

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The Brief

Our Client is a MedTech Startup specializing in building AI automation tools. These tools powered by natural language processing and machine learning are designed to eliminate administrative work for doctors and reduce healthcare providers workload. The platform does this by improving and automating healthcare operations or tasks like medical transcriptions, automating patient data entry, scheduling, and billing tasks.
Apart from turning doctor-patient conversations into prescription notes(with a feature known as Scribe), this AI-powered copilot offers real-time support to medical professionals for clinical decision-making, diagnosis accuracy, and treatment planning during consultations by providing data-driven insights and recommendations based on the patients unique needs and diagnoses.
Besides having a 100% HIPAA-compliant AI infrastructure, Doctor AI Model Offered customization of the entire environment to healthcare operators through voice or natural language. Along with featuring a patient-centered approach to generative AI, this platform can be directly integrated into some widely used EHRs & EMRs(like Athena Health, DrChrono, Elation, EPIC, Cerner), and popular platforms like AWS, Google Cloud, Azure, etc. To offer wide social adaptability and ease of use, the Doctor-LM is trained to provide multilingual support in nearly 19 languages.

The Challenge

In the healthcare industry, medical professionals face immense pressure from the administrative workload that comes from patient care. Essential tasks such as medical transcriptions, patient data entry, scheduling, and billing are time-consuming. Additionally, during consultations, doctors need support with clinical decision-making to increase diagnosis accuracy and optimize treatment planning. There was a crucial demand for a solution that not only automates these administrative tasks but also aids in real-time clinical decision-making, integrating seamlessly with existing Electronic Health Records (EHRs) and Electronic Medical Records (EMRs) systems, and supporting a multilingual interface to cater to diverse patient populations.

The Solution

We collaborated with the client to develop Doctor AI Model, a comprehensive AI automation tool powered by advanced natural language processing (NLP) and machine learning (ML) algorithms. Our solution, crafted in the past, focused on significantly reducing the administrative burden on healthcare providers through the automation of various tasks, including:

Medical Transcriptions and Patient Data Entry

Our team of Expert AI/ML developers implemented NLP and text-to-speech technologies to accurately transcribe doctor-patient conversations into detailed prescription notes and seamlessly input patient data into the system. This automation improved operational efficiency and accuracy.

Real-time Clinical Decision Support

Solutions provided real-time support during medical consultations. Utilizing data-driven insights and recommendations to each patient’s needs and diagnostic records, this helped professionals in making informed clinical decisions to improve diagnosis accuracy and treatment planning.

Integration with EHRs and EMRs

We ensured full integration with widely used EHRs and EMRs platforms like Athena Health, DrChrono, Elation, EPIC, and Cerner. This seamless integration facilitated a unified healthcare management system, simplifying access to patient records and improving workflow efficiency.

HIPAA-Compliant AI Infrastructure

Our team ensured and developed a 100% HIPAA-compliant AI environment, prioritizing patient data security and confidentiality above all. This adherence to compliance standards ensured the trustworthiness and reliability of the solution in handling sensitive medical data.

The Impact

MindInventory expertise and determination resulted in a groundbreaking AI solution that addresses the challenges presented by clients and sets new standards for AI-driven healthcare automation. Here are some of the impacts of the solutions our team implemented:

33%

Enhanced Prescription Note Generation

27%

Optimized AI Model Performance

56%

Improved Overall Efficiency