Natural Language Processing (NLP)

Clinical documentation used in coding and charge capture comes from a variety of sources and in variety of formats. In most cases, clinical documentation is a disparate collection of contents ranging from free text, unstructured text, HL7 messages and template driven structured content.


Medical Coding and Charging require documentation that comprises personal health information of patients as well as other personal information such as Doctors, Nurses, etc. Such information must be protected from those who don’t have a need to know.

Rules Engine

Medical Coding, especially charge determination for subjective services such as E&M Level determination and Performance Measures, or services based on verbose documentation such as Surgical Procedures, requires many rules to be evaluated before arriving at the correct charge.

Coding Engines

Medical Savant delivers multiple coding engines, each with its own unique characteristics.


These requirements are a natural candidate for a workflow system that coordinates activities among various users and data flow of data among multiple participating systems over a long-duration process. MedicalSavant software platform delivers flexible powerful workflow features:

Medical Savant solution is built on several innovative technology building blocks. Each solution, tailored to a specific healthcare provider environment such as Emergency Room, Radiology Centers or Urgent Care Centers, is an integrated package of the required technology modules, organized as a processing pipeline with a purpose-built workflow user interface.

Medical Coding and Charge Capture are an important and perhaps the most knowledge intensive aspect of Healthcare Revenue Cycle Management. Consequently, the knowledge workers are a scarce and highly sought after resource, particularly in healthcare providers serving diverse and remote areas. Medical Coding and Charge Capture are further challenged by complex and often incomplete medical documentation that requires these scarce coding resources to spend 10-30 minutes on each hospital encounter, often involving follow-up with healthcare professionals who treated the patient, making the overall coding process unproductive and expensive. Charge Capture, especially in Evaluation and Management (E&M) Level, is challenged by the subjective nature of E&M coding rules, resulting in a high degree of variation in charges captured by coders of different skill levels. Lastly, frequent changes in policies either within the provider environment or by the payer necessitate expensive and time-consuming retraining of coders.

Medical Savant solutions are based on a special class of knowledge base artificial intelligence (AI) software platform. On one hand, the software platform encapsulates knowledge required for coding and charge capture such as medical vocabulary and taxonomy, clinical associations, anatomical hierarchy, disease categories, medical necessity rules, and reimbursement policies of providers and payers. On the other hand, the software platform incorporates and emulates the intelligence of experienced and skilled coders such as natural language processing skills, algorithmic capabilities of deriving and sequencing codes and learning abilities. By leveraging the knowledge contained within the software, Medical Savant solutions emulate highly skilled coders and perform most of the labor-intensive coding and charging functions. By allowing new rules to be learnt by or configured in the software, Medical Savant greatly simplifies and accelerates adoption of changes in healthcare reimbursement policies and virtually eliminates retraining of coders and the knowledge gap that exists among the coders. Lastly, the software platform resides in the cloud, thereby enabling continuous improvement of user experience and eliminating expensive installation and maintenance of systems.