Reducing the Reported Mortality Index Within a Neurocritical Care Unit Through Documentation and Coding Accuracy.

Area of Science:

• Healthcare Quality Improvement
• Critical Care Medicine
• Health Informatics

Background:

• The mortality index is a key quality metric, but can be influenced by documentation and coding practices.
• Inaccurate coding may unfairly reflect poorly on hospital performance.
• Neurosurgical and neurological patient outcomes are critical areas for quality assessment.

Purpose of the Study:

• To reduce the reported mortality index for neurosurgery and neurology patients.
• To improve documentation and coding accuracy through direct incorporation of mortality modeling.
• To establish an internal benchmark for quality assessment.

Main Methods:

• Developed a spreadsheet tool based on Vizient Inc. methodology to identify coding and documentation discrepancies.
• Retrospectively analyzed patient data to pinpoint factors affecting the mortality index.
• Implemented prospective changes in documentation and coding practices.

Main Results:

• Prospective implementation led to a significant reduction in the calculated mortality index.
• The reported Vizient mortality index also showed a drastic decrease.
• The study validated the effectiveness of targeted documentation and coding improvements.

Conclusions:

• Integrating knowledge of mortality index modeling into clinical documentation and coding practices is effective.
• This approach significantly lowers the reported mortality index for neurocritical care patients.
• The methodology provides a valuable internal benchmark and a tool for inter-institutional comparison.