MetaHealth Analytica LLC

My Practice

At MetaHealth Analytica, Dr. Amir Rahimi specializes in leveraging data science and machine learning to revolutionize the healthcare industry. As the founder and chief scientist, Dr. Rahimi brings extensive experience as a healthcare data scientist with a background in particle physics. His mission is to provide bespoke solutions that drive efficiency, accuracy, and innovation, empowering healthcare providers with actionable insights to enhance patient care and optimize operations. Dr. Rahimi's bio is available here.

My Mission

At MetaHealth Analytica, I am committed to transforming healthcare through advanced data analytics and predictive modeling, with a focus on building custom solutions from the ground up for each client. My expertise lies in leveraging cutting-edge machine learning and statistical techniques to extract actionable insights from complex healthcare data. I create tailored solutions that address the specific needs and challenges of each client, ensuring that no two models are the same. By optimizing operations, improving patient outcomes, and enabling informed decision-making, my approach empowers healthcare providers to deliver more efficient and effective care.

Here are some examples of custom-built solutions I’ve developed:

Tailored Predictive Modeling for Critical Health Conditions

I developed a predictive model specifically designed to improve early detection and management of sepsis, enabling healthcare providers to act swiftly and prevent life-threatening outcomes. By assessing both long-term and immediate risks, the model enhances patient safety and optimizes resource allocation.

This data-driven approach is custom-built to address the unique needs of each client and can be tailored to other critical conditions, providing actionable insights that improve patient care and outcomes.

Custom Early Detection Model for Incidental Findings

I developed a custom model to improve the detection of incidental findings in radiology notes, enabling healthcare providers to identify high-risk cases for timely follow-up and early intervention. This streamlined approach supports better patient outcomes by enhancing the detection process.

Each model is built specifically for the client's needs, integrating advanced technology to promptly address critical findings and improve the quality of care.

Bespoke Predictive Model for High-Risk ED Visits

I developed a predictive model to assess the likelihood of emergency department visits for patients with a history of Substance Use Disorder. By identifying high-risk patients, the model enables healthcare providers to take early action and reduce costly ED encounters.

This solution is uniquely crafted to address the specific challenges of each client, ensuring it aligns with their particular needs and healthcare objectives.

Tailored Predictive Modeling for Demand and Resource Management

I developed predictive models to help healthcare providers manage demand, improve patient access, and optimize scheduling and staffing. These models forecast demand across specialties and patient populations, enhancing operational efficiency.

Each solution is specifically designed to address the unique needs of the client, ensuring effective resource management and improved patient outcomes.

Customized Provider Workload Optimization Solutions

I developed a model to optimize patient assignments to healthcare providers based on risk profiles and utilization patterns. This ensures balanced workloads and improved patient care by preventing overburdening or underutilization of providers.

Each solution is specifically designed to meet the client's needs, enhancing both provider efficiency and the quality of care delivered.