To address these challenges, Teqfocus, a San Francisco-based IT consulting firm, has developed a groundbreaking solution leveraging Salesforce Suite Products and AWS.

By facilitating data-driven decision-making and proactive health management, Teqfocus’ predictive Patient’s Health Risk Solution empowers Payers/HMOs to design personalized insurance plans, optimize resource allocation, and enhance customer engagement. This innovative approach transforms healthcare management, delivering superior outcomes for all stakeholders.

This solution leverages Salesforce Data Cloud to harmonize and unify data from multiple siloed systems. This integration provides a comprehensive and cohesive view of each patient’s health status.

Additionally, by utilizing Data Cloud’s latest Bring Your Own Model (BYOM) feature, this incorporate advanced AI models to predict patient risk levels with remarkable accuracy. This powerful combination of unified data and cutting-edge AI enables payers to make data-driven decisions, implement proactive health management strategies, design personalized insurance plans, optimize resource allocation, and enhance customer engagement.

Connecting external systems that have patient data with Salesforce Data Cloud ensures only relevant data is passed to the cloud.

There are hundreds of connectors to easily ingest data from any source or system into Data Cloud.

Examples of systems/Data Streams that can be connected include:

• System 1: Electronic Health Records (EHR)
• System 2: Claims Data Systems
• Additional Systems: Online Forms, Medical Devices, etc.

Map the data to a standardized model that’s natively integrated with the Salesforce metadata framework.

Data Cloud harmonizes all the data into a single model with a 360-degree view of the patient.

AWS SageMaker accelerates the process of building and deploying machine learning models, making it easier for developers and data scientists to leverage the power of machine learning in their applications.

Key features include automatic model tuning to optimize performance, managed notebooks for interactive data exploration and model development, and built-in capabilities for model monitoring and debugging. SageMaker supports deployment of models to production environments with built-in scalability and monitoring.

In Salesforce Data Cloud, Once the dataset is ready in DMO it is set to the model deployed in AWS SageMaker. Below is the high level architecture on how these two systems connect.

The Model Builder in Salesforce Data Cloud facilitates the connection to the endpoint, schema review, and activation of the model for creating prediction jobs.

Settings from Data Cloud include connecting to the endpoint URL form AWS, detailing the schema, creation of new prediction job where the predictions can be returned from AWS.

AWS Sagemaker then fetches Data from Salesforce Data Cloud for its model to calculate Predictions. Once predictions are generated, they are passed on to Data Cloud for viewing.

The summary of the number of high-risk to low-risk patients can be visualized using Salesforce Data Clous Reports and Dashboards, providing actionable insights for Payers/HMOs to optimize their strategies.

And Next best Actions can be triggered based on these results.

Patient Health Risk Calculator by Teqfocus is poised to revolutionize healthcare management for payers/HMOs, providing them with the tools and insights needed to deliver personalized care, optimize resource allocation, and make informed strategic decisions.