Download PDF
Open Access
CC BY-NC-ND 4.0 · Appl Clin Inform 2025; 16(05): 1909-1916
DOI: 10.1055/a-2767-1161
Case Report

Improving the Observed-to-Expected Mortality Ratio with the Combination of Standardized Documentation and a Multidisciplinary Mortality Review Committee

Authors

  • Ellen Overson   *

    1   Division of Hospital Medicine, University of Minnesota Medical School, Minneapolis, Minnesota, United States

  • Jacob Wagner   *

    1   Division of Hospital Medicine, University of Minnesota Medical School, Minneapolis, Minnesota, United States

  • James Grace

    1   Division of Hospital Medicine, University of Minnesota Medical School, Minneapolis, Minnesota, United States

  • Melissa Haala

    2   Inpatient Coding and Clinical Documentation Improvement, North Memorial Health, Robbinsdale, Minnesota, United States

  • Bradley Burns

    3   Department of Emergency Medicine, M Health Fairview Ridges Hospital, Burnsville, Minnesota, United States

  • Abraham Jacob

    4   Division of Pediatric Hospital Medicine, M Health Fairview, Quality Improvement, Minneapolis, Minnesota, United States

  • Rebecca Markowitz

    1   Division of Hospital Medicine, University of Minnesota Medical School, Minneapolis, Minnesota, United States

Funding None.
Further Information
Also available at
  Permissions and Reprints

Abstract

Background

Many academic medical centers (AMCs) rely on systems like the Vizient Quality and Accountability Scorecard to track quality metrics such as the observed-to-expected (O/E) mortality ratio. The O/E mortality ratio calculation relies on clinical documentation. Missed documentation of diagnoses and risk factors for mortality leads to an underestimated expected mortality, which negatively affects the O/E metric.

Objectives

We aimed to reduce our O/E mortality ratio from a median of 1.08 (± 0.10) to a median well below 0.90 within 12 months by improving the accuracy of clinical documentation.

Methods

We used a continuous quality improvement process that began with creating a rule-based tool within a standardized documentation template. The tool was designed to pull pertinent discrete electronic health record data into clinician documentation. The tool only pulled in data that were present on admission, and it especially prioritized inclusion of frequently missed risk factors according to prior coding query data. We then formed a multidisciplinary mortality review committee where providers reviewed mortality cases, made suggestions for documentation clarification, and found potential diagnoses and risk factors that the patient had which were missing from the documentation. We then leveraged the committee's expertise and feedback to improve the rule-based clinical tool.

Results

Over the 21-month period following implementation, the median O/E mortality ratio decreased by 30%, from 1.08 (± 0.10) to 0.72 (± 0.13) and consistently remained below the prior levels. Importantly, the intervention also led to a reduction in the total number of coding queries sent to clinicians, indicating a lower administrative burden for clinicians and coders.

Conclusion

Our interventions showed a clear improvement in the O/E mortality ratio at our AMC and in the expected mortality percentage compared with other similar institutions without significantly increasing burden on clinicians or coding specialists.

Keywords

clinical documentation - clinical documentation integrity - clinical notes - inpatient care - quality improvement - mortality review - mortality risk factors - observed to expected mortality ratio - clinical coding queries

Protection of Human and Animal Subjects

This project was reviewed by our local institutional review board who determined it did not meet the definition for human research.


Note

Data from the Vizient Clinical Data Base used by permission of Vizient, Inc.


Ethical Approval

Institutional review board reviewed the work (approval no.: STUDY00024292) and deemed it not human research.


* These authors contributed equally to this work




Publication History

Received: 25 June 2025

Accepted: 06 December 2025

Accepted Manuscript online:
12 December 2025

Article published online:
24 December 2025

© 2025. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

Georg Thieme Verlag KG
Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany