Working with computer-assisted coding, natural language processing

April 30th, 2019

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Note:  The following article synopsis was NOT provided by HCPro. It was created by Find-A-Code/innoviHealth.

Article Overview

This article discusses the role of computer-assisted coding and natural language processing in CDI and inpatient coding workflows. It explains why these tools require ongoing human review, describes broad categories of implementation challenges, and highlights the importance of coordination with physicians, CDI staff, IT, and analysts. It is relevant to CDI professionals, coders, and healthcare leaders evaluating or using documentation technology.

Why This Topic Matters

The article helps readers understand how automation can support documentation review while still requiring human judgment to maintain accuracy and workflow quality.

Article Sections

  1. NLP

    This section introduces natural language processing in the CDI context and discusses how the technology fits into documentation workflows. It focuses on adoption, oversight, and the need for physician review and training.

  2. CAC

    This section presents computer-assisted coding as a documentation-to-code support tool and outlines general challenges that can arise when it interprets records. It emphasizes the relationship between automated suggestions and CDI review.

  3. Making the best of the situation

    This section covers broader strategies for working with technology teams and improving workflow use of documentation tools. It also addresses CDI education, policy review, and the ongoing role of human expertise.

What You Will Learn

  • How CAC and NLP fit into CDI and coding workflows
  • Common implementation and oversight concerns associated with documentation technology
  • Ways CDI teams can coordinate with physicians, IT staff, and analysts
  • Why human review remains important when using automated documentation tools

Who Should Read This

  • CDI specialists
  • Inpatient coders
  • Coding managers
  • Clinical documentation improvement leaders
  • Health information management professionals
  • Healthcare IT and analytics staff

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