Our client is a large U.S. health system with 1,000+ beds across multiple hospitals. As they prepared to implement an AI-powered coding solution, they sought to validate the readiness of their physician documentation with a CDI Audit. Leadership prioritized assessing discharge summary accuracy to benchmark physician performance, ensure a smooth transition, and maximize the value of their AI investment.
Challenge
As part of their AI readiness planning, our client sought to evaluate the effectiveness of its current documentation and coding operations. Leadership wanted to understand how consistently physician discharge summaries captured clinically supported diagnoses, and whether existing practices were optimized to support accurate DRG assignment and financial performance in an AI-enabled environment.
Solution
Managed Resources conducted a focused retrospective CDI and coding audit to assess physician documentation readiness ahead of AI coding adoption. The audit reviewed 165 inpatient encounters across high-impact DRG families, evaluating discharge summary completeness, clinical validation, and coding alignment.
Findings informed targeted physician education, CDI workflow improvements, and a post-audit action plan designed to strengthen documentation practices and support a successful AI coding transition.
Results
While evaluating documentation completeness and DRG alignment, we identified a recurring disconnect between clinically supported diagnoses and final coded outputs. 33% of the audited cases had incomplete discharge summaries that reflected all clinically validated and codable conditions.
Post-Audit Action Plan
After conducting its initial inpatient CDI and coding audit, Managed Resources recommended a comprehensive post-audit action plan to address gaps and improve operational efficiency ahead of AI rollout.
1. Develop and deploy physician education modules focused on discharge summary best practices
2. Conduct CDI refresher education on query best practices and clinical validation criteria
3. Share coding examples with coding department for additional educational opportunities
4. Establish ongoing workflows and query escalation pathways for CDI specialists when summaries omit critical diagnoses
5. Conduct reaudit to validate corrections before AI transition
Notable Finding: Physician Variance
A review of attending physician data, showed that over 30% of attending physicians sampled did not write the discharge summaries for any of the patients they admitted. Managed Resources provided post-audit training to improve physician workflows.
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Conclusion
Establishing documentation readiness is a critical step before introducing AI-driven coding technologies. This case study highlights how a targeted CDI audit can provide organizations with a clear operational baseline, identify physician documentation variability, and reduce risk prior to implementation.
Connect with Managed Resources to learn how a pre-AI implementation CDI Audit can help your healthcare organization confidently prepare for AI-adoption.