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Provider Claims benchmarking analytics (PROD)

Business Opportunity

In the dynamic landscape of healthcare provider management, there are challenges and opportunities that present a compelling business case for leveraging dynamic benchmarking. The challenges include the lack of real-time insights into provider performance, manual threshold setting leading to suboptimal decision-making, and the difficulty in identifying performance clusters among providers. However, these challenges also open up opportunities to utilize AI models for dynamic threshold calculation, enhance decision-making through data-driven insights, and improve operational efficiency and provider management.

Link to Canvas Dashboard :Provider Claims benchmarking analytics (PROD)

Solution / Approach

In addressing the challenges and seizing the opportunities presented by dynamic benchmarking, a comprehensive solution approach is essential. By implementing dynamic benchmarking criteria such as Region > Market Name, Tier Size: 1, 2, 3, and E, and Facility vs Professional, healthcare providers can gain valuable insights into their performance clusters. The methodology involves utilizing AI models to dynamically calculate thresholds, cluster providers based on performance metrics, and implement region-specific benchmarking for enhanced insights.

The implementation steps include data collection to gather provider performance data, AI model training to develop algorithms for dynamic threshold calculation, and benchmarking execution to periodically analyze and update benchmarks. This holistic approach ensures that healthcare providers can make informed decisions, optimize operational efficiency, and enhance overall performance management.

Architecture

archdiagram

Key Metrics

  • Performance Clusters: Identify Good vs Bad providers based on dynamic benchmarks and cluster providers into tiers for targeted analysis.
  • Thresholds: Analyze median threshold values for different regions and provider types, and understand tier-wise threshold variations for in-depth performance evaluation.
  • Provider Spread: Examine approval percentages and market sizes for different provider tiers, and assess the impact of enterprise-level thresholds on provider performance.

Tech Stack

  • Python

Next Steps

The next steps to improve the Provider Claims benchmarking analytics system involve enhancing data quality, optimizing AI models for better accuracy, and incorporating user feedback to address any identified issues and refine the overall solution.

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