Revenue cycle management: How to measure, manage, and minimize leakage

March 23rd, 2021

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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 mid-revenue cycle revenue leakage in healthcare organizations and outlines broad approaches to reduce it through stronger documentation integrity, compliant CDI practices, retrospective review processes, auditing, and technology support. It is aimed at revenue cycle, CDI, coding, and healthcare financial leadership audiences evaluating ways to improve workflow efficiency and reduce lost revenue.

Why This Topic Matters

Revenue leakage can affect reimbursement, operational efficiency, and reporting accuracy. The article is relevant to organizations looking to better align clinical documentation, coding quality, and technology-enabled review processes.

Article Sections

  1. A difficult problem

    This section introduces common barriers to managing leakage in the mid-revenue cycle, including challenges affecting physicians, CDI specialists, and coders. It also describes how legacy tools and manual workflows can contribute to ongoing inefficiency.

  2. Focus on documentation integrity over documentation improvement

    This section contrasts broad documentation integrity with narrower improvement-focused approaches and explains why that distinction matters to CDI and coding workflows. It also presents core principles supporting compliant documentation review.

  3. Implement a robust retrospective and code review process

    This section discusses retrospective review as a final opportunity to address documentation and coding issues before billing and reporting. It also covers operational considerations for making review processes more effective.

  4. Invest in CDI auditing

    This section outlines high-level audit planning considerations, including scope, case selection, volume, and who should perform the audit. It emphasizes using audits to identify weak points and potential sources of leakage.

  5. A new approach

    This section describes how machine learning can support CDI workflows and reduce reliance on repetitive manual tasks. It also addresses broader automation concepts in documentation review and case prioritization.

What You Will Learn

  • How mid-revenue cycle leakage can affect healthcare organizations
  • Why documentation integrity is a central CDI concern
  • How retrospective review and auditing fit into leakage reduction
  • How automation and machine learning may support CDI workflows
  • What operational challenges can affect physicians, CDI specialists, and coders

Who Should Read This

  • Revenue cycle leaders
  • Clinical documentation integrity professionals
  • Medical coders
  • Hospital finance teams
  • Healthcare administrators
  • CDI auditors

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