Healthcare data has become an important part in the research and development of the biomedical health sector. Our client came up with a well known noble problem of improving the quality of care without compromising on the cost. The analytics solution was well thought out to provide predictable disease and cost outcomes.
Live updates of the data in the solution platform with end to end data pipeline including ETL transformation, Exploratory Data Analysis, ML pipeline, MLOps, App Data store and Cache etc.
Integrating the predictive elements into the Data pipeline with reports and decisions embedded.
Customised Rules engine for managing care gaps which is a huge set of rules on disease, symptom and procedure parameters.
Capturing the high-risk patients to alert the insurance and care providers.
Managing Data inconsistencies and varieties of data models from different insurance carriers and employer groups.
Designed and built batch data pipelines for the data ingestion and processing with appropriate logs and validation checkpoints.
Designed and built a well sophisticated web application for the insurance provider and care provider to understand the health of the population and manage the cost incurred.
Designed and implemented robust and scalable cloud Infrastructure end to end with best practices to manage data reliability and scalability.
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