First AI to Refine Medical Coding by Exploring Therapeutic Data

02 June 2022 | Thursday | News

Medical AI start-up Aesop Technology announced a new partnership that made their new product, DxPrime, available in the Olive Library.
Image Source : Public Domain

Image Source : Public Domain

DxPrime provides physicians and clinical documentation improvement (CDI) teams with information about missing and wrongly coded diagnoses and procedures to correct the patient's chart in just a few clicks. It makes completing discharge summaries, prioritizing work for CDI teams, and medical coding much easier, faster, and less error-prone.

If the patient record is incorrect, you cannot code correctly.

Completeness, precision, and validity of medical documentation are critical for all healthcare stakeholders. Without correct patient records, patients could receive improper discharge instructions and a sub-optimal continuum of care. Providers also can struggle to estimate the length of stay and code insurance claims correctly, resulting in denials and loss of revenue.

Approximately 10% of inpatient claims are denied, of which more than 85% (or about $35 billion) result in unnecessary losses. Many of these denials occur because of errors in the patient record that occur upstream from the claims process. Diagnosis input errors are difficult for physicians to avoid because the knowledge of coding systems is different from what they need to learn to provide great patient care. Modern medicine's complexity has caused 14,400 diseases to be included in ICD-10, further classified into 68,000 ICD-10-CM and 87,000 ICD-10-PCS codes.

"Physicians, CDI team, and coders have to spend a lot of time poring through medical records to find the key clinical diagnoses among the vast amount of information available," said Jim Long, CEO of AESOP. "After that, they have to follow a series of inefficient steps on the computer to complete the input process, and search functionality for ICD codes often is not helpful. The whole process is complex, time-consuming, and error-prone.

When the physicians input the improper diagnosis, it also has downstream implications. When using DxPrime, we have helped physicians often notice they did not correctly code complications such as urinary tract infections and respiratory failure. By assisting them in inputting the proper diagnoses, our partners have seen an increase in revenue of 5-10% per inpatient."

State-of-the-art machine learning assisted physician data entry.

DxPrime provides high-quality suggestions to support physician data entry based on a machine learning model (published in the Healthcare journal) that has been run on top of data from 3.2 Billion patient visits, including vast amounts of structured information. It allows DxPrime to use items from the patient record like lab test results and medications ordered when predicting a diagnosis.

This comprehensive model utilizes artificial intelligence to efficiently compensate for traditional CDSS and NLP weaknesses to find correct or missed diagnoses.


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