Using AI to optimize medical coding and billing for mental health
Using AI to optimize medical coding and billing for mental health Mental health facilities have a unique set of circumstances when it comes to billing and coding for services. They
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A large volume of data is now available in the public marketplace, but unfortunately, it is not user-friendly or easily interpretable. We need a complex data engineering platform and data engineering experts to get value out of this data jungle.
Data accessibility is an ongoing challenge. Providers are hosting data in a different format than payers Data Quality is a concern as well. Companies are finding it extremely difficult to analyze and extract tangible insight.
The available pricing data in a silo is insufficient unless combined with healthcare billing, revenue, and cost data sets to derive meaningful insights
Scalable data platform to ingest, process, and store a large volume of pricing data from payers, providers, and employers.
Prebuilt models that are trained on prior data for predictive and generative AI.
Extensible data platform to include additional healthcare datasets (claims, quality, finance, cost, revenue, etc.) for complete visibility.
Weekly refreshed and curated data sets from multiple partners in an easily consumable format for analytics use cases across the healthcare network.
Comprehensive standardization and data quality check to manage data inconsistencies.
Using AI to optimize medical coding and billing for mental health Mental health facilities have a unique set of circumstances when it comes to billing and coding for services. They
Healthcare Pricing Analytics for Providers- The five-minute guide What is Pricing Analytics With the power of advanced analytics, modern pricing and profitability management are re
Provider Contract Negotiation Powered By Transparency Data U.S. health systems have long struggled with the painstaking process of analyzing and modeling payer reimbursements, lead
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