Sentinel is a unique and novel Data Inferencing and Natural Language Processing (NLP) system. It is a system that lends itself for use in any data/query deployment and across any knowledge domain. The current deployable is geared for use in the medical knowledge domain with the subdomain of medical billing.
There is nothing on the market quite like Sentinel. There are analogs that can perform the same function as Sentinel, but not in the same manner as Sentinel.
A key difference between Sentinel and all other inferencing systems is that once data has been parsed and inferenced, it can be maintained for use in any other query imaginable. This is "magic" of the system. Deployed properly, Sentinel will be an ever changing, ever growing, ever representative conglomeration of current and past data, which can be used in a myriad of functions.
In the medical billing arena, Sentinel exhibits higher degrees of accuracy when compared to other computer assisted coding systems. The reason for the higher level of accuracy is that Sentinel rule sets were created by humans interpreting language (medical language in the current iteration). Language is an art. As such, language cannot ever be accurately defined by mathematical statements. Any system that tries to evaluate or define language by mathematical statements will be inherently flawed, and never be able to offer results that will be consistently error free.
Sentinel has been tested as a Computer Assisted Coding tool at more than 30 hospitals. The result at each facility was an increase in bottom line billing of an average of 3%. The value and potential uses of the databased information from the billing process are discussed in the Hospital Use of Sentinel white paper available for viewing.
Other potential uses of Sentinel are discussed in other white papers available here.