Diagnoss, the Berkeley, Calif.-based startup backed by the machine learning-focused startup studio The House, has launched its coding assistant for medical billing, the company said.
The software provides real-time feedback on documentation and coding.
Coding problems can be the difference between success and failure for hospitals, according to Diagnoss. Healthcare providers were decimated by the COVID-19 outbreak, with hospitals operating below 60% capacity and one-fourth of them facing the potential for closing in a year if the pandemic continues to disrupt care.
The cost pressures mean that any coding error can be the financial push that forces a healthcare provider over the edge.
“For every patient encounter, a physician spends an average of 16 minutes on administration, which adds up to several hours every single day. In addition, codes entered are often wrong – up to a 30% error rate – resulting in missed or delayed reimbursements. We believe that, with the great progress we’ve seen with artificial intelligence and machine learning, we can finally address some of these inefficiencies that are leading to physician burnout and financial strain,” said Abboud Chaballout, founder and chief executive of Diagnoss, in a statement.
Diagnoss acts like a grammar checking tool, but its natural language processing software is focused on reading doctor’s notes. The company’s tools can provide evaluation and management code for patient encounters; point out missing information in doctors’ notes; and provide predictions about the diagnosis and procedure codes that could apply after reviewing a doctor’s notes.
In a study of 39,000 de-identified EHR charts, the company found that its machine coding service was about 50% more accurate than human coders, according to a Diagnoss review.
Physician practices are already using Diagnoss’ service through a previously announced partnership with the mobile EHR vendor, DrChrono .
