Semantic Health
Simplifying Medical Coding and Auditing with AI

Medical auditing and coding are operational and financial pillars of every healthcare provider. However, the state of existing coding and auditing software does not match the evolving requirements of healthcare organizations. This has left many healthcare providers using manual, error-prone, and expensive software to complete critical coding and auditing. Medical coders must comb through an enormous amount of complex clinical documentation to identify relevant information, map key clinical events, and accurately code diagnoses and treatments. In light of the complex and inefficient workflows, medical coders and auditors are often under significant time constraints and pressure.

Blazing the trail in this regard with its proprietary platform that unifies coding and auditing workflows with AI-powered insights is Semantic Health. With the company’s health information platform, healthcare providers can improve clinical documentation, automatically assign medical codes based on clinical evidence, identify data quality deficiencies, and generate a longitudinal patient narrative.

“Our machine learning experts stay at the cutting-edge of clinical natural language processing (NLP) models and identify unique patient population indicators to optimize medical coding and audit processes. This is the secret to our AI-powered coding and auditing platform,” says Laith Sarhan, Director of Business and Legal Operations at Semantic Health. Additionally, the company’s platform can make unstructured healthcare data actionable and power several ancillary capabilities, like powerful data analytics that can improve operational efficiencies, care delivery, and population health management.

Semantic Health currently offers two solutions, namely Semantic Coder and Semantic Auditor. The company’s AI assisted coding platform essentially helps coders consolidate their workflow (including clinical documentation) into one user interface and supports them with code suggestions powered by Semantic Health’s AI models.

Semantic Coder aims to assist coders and auditors optimize their efficiency and execute base-level codes independently. The second platform is an AI-based data quality auditing tool that helps coding and auditing teams double-check coded data and identify critical flagged issues such as missed secondary codes, unspecified codes, conflicting evidence, and weak evidence. The Semantic Auditor platform provides coders and auditors with the highest levels of accuracy for their data and visibility into the most high-value opportunities.

Today, these platforms are used by several hospital sites across Canada. Semantic Health has consistently found new data quality opportunities previously lost due to manual operational processes in these engagements. In fact, out of every 15,000 in-patient charts analyzed with Semantic Health’s platform, 500 cases brought additional business opportunities for care providers.

Such value additions are substantiated by the fact that clients’ internal audit teams corroborate the finding of Semantic Health’s audit platform nearly 85 percent of the time. This unprecedented accuracy means that the Semantic Health platform can help identify a significant amount of money that a client organization has been leaving on the table due to data discrepancies. Beyond the financial opportunities, all the data quality opportunities are fed back into a higher quality data layer for client organizations. Users can also integrate other use cases outside the revenue cycle into their coding and auditing workflow, including analytics, population, health management, and workforce optimization.

Considering the popularity of Semantic Health’s coding and auditing platforms amongst Canadian hospitals, Semantic Health is now running multiple pilot projects in the U.S. as well. Moving ahead, the company plans to kickstart its U.S. operation by making these solutions more widely available to American healthcare organizations.