Understand physician meaning
Criteria-based UR systems depend on statistics and discrete rules, but effective UR requires understanding physician judgement in documentation. Between 60% to 70% of clinical information within a patient record resides in the clinical text. Criteria-based systems can have difficulty understanding the intent behind this unstructured data.
Some criteria-based systems are beginning to use AI as a glorified word search tool, but many such tools aren’t sophisticated enough for the job. They may recognize the terms “history of smoking” or “chest pain” in patient records, but they aren’t designed to understand the context.
Fully leveraged AI incorporates more sophisticated and advanced technology. It interprets the meaning of physician documentation, and puts key terms found by AI into context. It applies bi-directional processing methodology that recognizes key phrases and considers them in relation to high-risk factors and low-risk factors along with how they’re used linguistically.
For example, a fully leveraged AI solution would recognize that “no reported history of smoking” indicates an absence of smoking. But criteria-based systems are likely to see “history of smoking” and conclude that the patient smokes.