• Industry

    Revenue Cycle Management (RCM) Firm

  • Project Type

    Data Engineering, Data Visualization

  • Technologies

    Power BI, Amazon Redshift,Amazon Glue, Python

The challenge

  • The client, a revenue cycle management firm based in the USA, specializes in helping healthcare practices and clinics streamline and maximize revenue through timely and accurate billing, coding, and reimbursement processes.
  • They faced challenges in integrating diverse EDI data sets, including 837 and 835 transactions, from partner practice management systems.
  • Handling large volumes of data, they sought a platform with efficient data processing and analytics capabilities while maintaining optimal performance.
  • The primary goal was to provide actionable insights to independent practice management systems to reduce costs.

The solution

  • The development team partnered with the client to create a next-gen data analytics platform, focusing on empowering independent practice management systems.
  • A robust data aggregation tool was developed for seamless integration and analysis of diverse EDI data sets.
  • To ensure scalability, AWS Redshift was leveraged as a dynamic data storage and analysis tool. Smooth data ingestion was facilitated using Amazon Glue, effortlessly handling a wide range of EDI datasets, such as 837, 835, and 270/271 transactions.
  • By establishing a unified data infrastructure, a holistic view of the revenue cycle was provided, enabling comprehensive analysis.
  • Power BI was employed to create insightful reports and visualizations that drive informed decision-making. Key performance indicators were showcased through tailored reports and intuitive dashboards.
  1. The solution provided real-time KPI visibility, reduced claim denials, expedited payments, and improved billing accuracy.
  2. Enhanced patient outcomes by alleviating administrative burdens.
  3. This transformation not only revolutionized the healthcare industry but also ushered in a new era of cost savings and operational efficiency.
  1. Seamless integration of diverse EDI data sets for comprehensive analysis.
  2. Efficient data processing and analytics capabilities for large volumes of data.
  3. Provide actionable insights to independent practice management systems to reduce costs.

Project outcomes

  1. Real-time KPI visibility for improved revenue cycle management.
  2. Reduced claim denials and expedited payments.
  3. Improved billing accuracy and enhanced patient outcomes.

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