# A Mathematical Model Based on Stratifying the Severity of Medical Errors for Building Scenarios for Clinical Cases With Branching

## TL;DR

This paper introduces a new mathematical model for creating branching clinical simulations based on the severity of medical errors.

## Contribution

A novel mathematical model and scoring system for building branching clinical scenarios based on medical error severity.

## Key findings

- A score system was developed to evaluate clinical decisions with scores ranging from 0 to 10.
- The model stratifies decision-making steps and was internally validated and implemented.
- Participants were divided into groups to test the model's effectiveness in clinical simulations.

## Abstract

Background

There are no mathematical models or score systems available for assessing and creating clinical case simulations based on branching scenario scripts.

Objective

This study aimed to develop a mathematical model based on stratifying the severity of medical errors for building clinical cases with branching scenarios for clinical simulation.

Methods

This study was undertaken from August 2020 to August 2023. To build a mathematical model for building scenarios of clinical cases with branching, the classification of the seriousness of medication errors was used. A mathematical model was built for predicting and modeling the development of a clinical situation and as an assessment strategy. The study recruited a total of 34 participants, with 16 participants assigned to the branching scenarios without the mathematical model group and 18 participants assigned to the branching scenarios with the mathematical model group.

Results

A simple diagram of score based on stratification of the severity of medical errors and correct decisions in clinical practice for building interactive training scenarios with branching was proposed. According to this score system algorithm, each clinical decision-making step is scored points with plus or minus, from 0 to 10. The sum of the points for each block in the decision-making process is then added up. Each step in the overall clinical decision-making strategy is stratified by the proposed algorithm, and finally, the results of internal validation and implementation are presented.

Conclusion

A mathematical model and score system for building clinical case scenarios based on branching and classification of the seriousness of medication errors was developed. This system could help in the prediction and modeling of the development of events in particular clinical situations and the assessment of competency formation in medical simulation as well.