The Morbidity and Mortality Assessment Tool (MMAT): Design and Proof of Concept

Tandis Soltani1, KeyYan Tsoi1, Aidan Charles1

  • 1Surgical Residency Program, University of Central Florida College of Medicine/Hospital Corporation of America, Graduate Medical Education Consortium, Ocala, Florida; University of Central Florida, College of Medicine, Orlando, Florida.

Abstract

Insights

A new Morbidity and Mortality Assessment Tool (MMAT) was developed to track surgical complications discussed in Morbidity and Mortality Conferences (MMC). This tool helps identify recurring issues and improve patient care by analyzing contributing factors.

Area of Science:

  • Medical education
  • Surgical quality improvement
  • Healthcare systems analysis

Background:

  • Traditional Morbidity and Mortality Conferences (MMC) in surgical residencies struggle with validating outcomes and preventing recurring errors.
  • The anecdotal nature of MMC can hinder the integration and education of best practices.
  • A need exists for a structured tool to measure and track factors contributing to surgical complications.

Purpose of the Study:

  • To introduce and present results from a novel Morbidity and Mortality Assessment Tool (MMAT).
  • To demonstrate MMAT's capability in measuring and tracking factors related to surgical complications discussed in MMC.
  • To provide a data-driven approach to surgical quality assessment.

Main Methods:

  • Three years of MMC presentations were compiled into a database.
  • Data were categorized by resident year, service line, presentation month, and contributing factors (Systems-Based, Direct Patient Care, Interpersonal Communication).
  • A review committee of residents and faculty assigned contributing factors to each case.

Main Results:

  • Lack of knowledge, technical error, lack of experience, lack of supervision, and failure to communicate were identified in over 10% of cases.
  • A "July Effect" was observed in the Trauma service, with a significant increase in "Failure to Communicate" errors during July.
  • Analysis revealed specific patterns in error types and their frequency.

Conclusions:

  • The Morbidity and Mortality Assessment Tool (MMAT) enables longitudinal data collection from MMC.
  • MMAT facilitates the recognition of patterns to improve healthcare systems and institutional memory.
  • This data-driven approach supports evidence-based improvements in surgical care.