Automated clinical indicator recognition with natural language processing

Abstract

Computer-based, natural language processing systems and methods are provided for review of clinical documentation and other medical records, and for clinical documentation improvement. The systems and methods are configured to review documents in the record using a natural language processor and to identify clinical indicators with associated contextual information. The clinical indicators are compared to scenarios to generate markers based on an information model. The markers used to generate physician queries and other informational requests with supporting evidence for each query based on indicators identified in the record. In additional examples, pragmatic guidelines including business-based rules can also be utilized, either in combination with, or as part of, the scenarios in the information model.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS[0001]This application is a continuation of U.S. application Ser. No. 14 / 019,489, filed Sep. 5, 2013, of which is incorporated by reference herein.BACKGROUND[0002]This disclosure relates generally to clinical documentation and, specifically, to automated techniques for recognizing clinical indicators of disease. In particular, the disclosure relates to natural language processor techniques for clinical document review, including automated recognition of disease indicators.[0003]Broadly speaking, clinical documentation improvement (CDI) initiatives seek to improve the quality of provider documentation in order to better reflect the services rendered and more accurately represent the complete patient encounter. CDI programs can benefit many clinical and administrative functions in healthcare delivery, including coding, quality measures reporting, care management, outcomes analysis, risk analysis, and subsequent care decisions. These benefits are ...

AI Technical Summary

Benefits of technology

This patent describes a computer system that can review medical records and suggest ways to improve them. The system uses natural language processing to analyze patient documents and identify important information. It compares these indicators to pre-defined scenarios and creates markers that doctors can use to quickly find relevant information. The system can also use business rules to guide doctors in their decisions. Overall, this system helps streamline medical records review and improves the accuracy and efficiency of medical records management.

Problems solved by technology

Like coding, CDI programs can be labor intensive and require highly trained specialists to execute.

With existing programs it is not possible to effectively review every chart and patient encounter in order to identify and select the greatest opportunities for improvement.

Where physician queries must be communicated back to the provider, moreover, it is notoriously difficult to integrate this feedback into the provider workflow using standard communications mechanisms such as email and fax technology.

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