Computer assisted coding has been around the industry for years. Typical functionality includes keyword matching paired with a series of 'if-then' rules to suggest ICD-10 and CPT codes, plus search functionality to help replace physical coding books.
However, as all coding professionals know, medical coding requires a significant amount of experience and judgement that is frankly impossible to capture via these two manually programmed methods, which are more formally known as 'Expert Systems'.
Expert systems were popular in the 1990’s but proved to be an inadequate approach to solving language comprehension tasks at scale because after you’ve solved or mapped out all of the basic cases, or common encounter types, it becomes impossible and unwieldy to make a rule for every possible scenario a coder will encounter.
Fully automated medical coding, which has been pioneered by Synaptec Health, in contrast relies on the latest in Artificial Intelligence (AI), including Machine Learning; which is the process of training algorithms with real-world examples to recognize patterns and ultimately replicate human judgements.
The key difference from computer assisted coding is that rather than relying on manually entered keywords such as 'chest pain' or fragile if-then rules, machine learning is able to asses a far greater number of factors, in the thousands, per encounter to make a coding determination. Synaptec Health's models have been trained on millions of encounters, coded by Synaptec Health's certified coding team, and are thus able to quickly and accurately recreate the process humans use to analyze and code an encounter.
In order to use technology as a solution to accurately code charts at scale, it is essential to use a Machine Learning based approach.
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If you'd like to learn more about how Synaptec Health's fully automated coding software can help your business, reach out at email@example.com or (415) 234-0768.