Diagnoss, a startup located in Berkeley, California and supported by The House, a startup studio specializing in machine learning, has introduced its coding assistant designed for medical billing, the company announced.

This software delivers immediate feedback regarding documentation and coding practices.

Diagnoss emphasizes that inaccuracies in coding can significantly impact the financial stability of hospitals. The COVID-19 pandemic severely affected healthcare providers, leading to hospital occupancy rates falling below 60% and placing approximately 25% of them at risk of closure within a year if disruptions to care persisted.

Given these financial challenges, even a single coding mistake could be the factor that leads a healthcare provider to financial hardship.

“Physicians typically dedicate an average of 16 minutes to administrative tasks for each patient, accumulating to several hours daily. Furthermore, a substantial percentage – as high as 30% – of submitted codes contain errors, causing delays or denials in reimbursement. We are confident that recent advancements in artificial intelligence and machine learning now allow us to tackle these inefficiencies, which contribute to both physician burnout and financial difficulties,” stated Abboud Chaballout, founder and CEO of Diagnoss.

Diagnoss functions similarly to a grammar checker, but its natural language processing technology is specifically designed to analyze physician documentation. The company’s offerings include suggesting appropriate evaluation and management codes for patient visits, identifying incomplete information within doctors’ notes, and forecasting potential diagnosis and procedure codes based on a review of the documentation.

A Diagnoss analysis of 39,000 anonymized electronic health record charts indicated that its machine coding service achieved approximately 50% greater accuracy compared to human coders.

Healthcare practices are currently utilizing Diagnoss’ service through an existing collaboration with DrChrono, a provider of mobile electronic health record solutions.