Default bias in medical patient simulators: Differences in availability and procedures

IF 1.6
Human factors in healthcare Pub Date : 2023-06-01 Epub Date: 2023-04-01 DOI:10.1016/j.hfh.2023.100040
Katelyn R. Schwieters, Nichole L. Morris, Curtis M. Craig
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引用次数: 0

Abstract

Introduction

Default biases in the design of new medical training technologies may lead to disparities, especially for women and people of color in patient treatment and outcomes in prehospital emergency services and combat medicine. The goal of this work was to develop a taxonomy of medical patient simulators to determine their demographic makeup and whether there was evidence of default bias in product catalogs.

Methods

The authors identified 114 full-body patient simulators from seven major medical device companies. Simulator demographic information (e.g., patient sex/gender, race/skin tone) and simulator prehospital care procedure features (e.g., tension pneumothorax, massive hemorrhage) were cataloged using company website information sheets and product catalogs using a binary coding system. Procedures were further classified into two categories: sensitive procedures and non-sensitive procedures.

Results

Findings revealed that although several companies offer demographically diverse patient simulators, marketing of many existing patient simulators use the white, male body as the featured default patient. Female patient simulators and simulated patients of color were significantly less likely to have procedure capabilities that allow for the practice of treating sensitive areas of the body compared to default male patient simulators.

Discussion

Default bias in the design of medical patient simulators illustrate the importance of inclusive design to improve medical decision-making and reduce disparities in civilian and military patient outcomes and care. Practice implications include increasing the diversity of complex medical patient simulators, removing default selections, and featuring female and patients of color in product catalogs.

医疗病人模拟器中的默认偏差:可用性和程序的差异
新医疗培训技术设计中的默认偏差可能导致差异,特别是对妇女和有色人种在院前急救服务和战斗医学中的患者治疗和结果。这项工作的目标是开发医疗病人模拟器的分类,以确定其人口构成,以及产品目录中是否存在默认偏差的证据。方法选取了7家大型医疗器械公司的114台全身病人模拟器。使用公司网站信息表对模拟器人口统计信息(例如,患者性别/性别、种族/肤色)和模拟器院前护理程序特征(例如,张力性气胸、大出血)进行分类,并使用二进制编码系统对产品目录进行分类。程序进一步分为敏感程序和非敏感程序两类。研究结果显示,尽管有几家公司提供不同人口统计的患者模拟器,但许多现有患者模拟器的营销使用白人男性身体作为特征默认患者。与默认的男性患者模拟器相比,女性患者模拟器和有色人种的模拟患者明显不太可能具有允许治疗身体敏感区域的操作能力。讨论医疗患者模拟器设计中的默认偏差说明了包容性设计对于改善医疗决策和减少平民和军队患者结果和护理差异的重要性。实践影响包括增加复杂医疗患者模拟器的多样性,删除默认选择,以及在产品目录中突出女性和有色人种患者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Human factors in healthcare
Human factors in healthcare Industrial and Manufacturing Engineering, Occupational Therapy
CiteScore
1.40
自引率
0.00%
发文量
0
审稿时长
145 days
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