FW-HTF-P: Understanding the Social and Ethical Implications of Algorithmic Decision Making by Nurses Using the Rothman Index in a Large-Scale Hospital Setting

FW-HTF-P：了解护士在大型医院环境中使用罗斯曼指数进行算法决策的社会和伦理影响

• 批准号: 2026607
• 负责人: Shion Guha
• 金额: $ 15万
• 依托单位: Marquette University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2026607&HistoricalAwards=false
• 关键词: FW; HTF; Understanding; Social; Ethical

With a shift towards value-based care, healthcare organizations are seeking innovative ways to improve the quality of care while reducing costs. The next several decades will see a rise in algorithm-driven patient care and the widespread use of data-driven warning systems such as the Rothman Index. The Rothman Index is an algorithmic system that uses patient information, lab results, and other health-related data to predict health deterioration. Algorithmic systems such as the Rothman will undoubtedly change what it means to daily work in the field of healthcare, demanding new kinds of expertise and communication from an already over-extended workforce. While such systems may reduce staffing needs, they do not eliminate the need for human oversight and intervention. Understanding how traditionally trained healthcare practitioners interact with such systems is, therefore, vital for the successful implementation of algorithmic patient care. To accomplish this goal, this project seeks to expand our understanding of how nurses in the Virtual Intensive Care Unit (VICU) make algorithmically informed workplace decisions using the Rothman Index. More broadly, the project examines how healthcare workers mediate between algorithms and patient interaction. Consequently, it informs future training protocols, system redesign and revision, and overall optimization of similar futuristic algorithmic tools. This project will employ a participatory and worker-centered design process for implementing algorithmic patient care through close collaborations with healthcare workers to advance the technical design of the Rothman Index. It will focus on the experiences of the virtual nurses, the providers who currently mediate between the Rothman Index alerts and health practitioners on the floor, in making actual algorithmic decisions. The project’s foundation is relationship-building with relevant hospital stakeholders followed by collecting and analyzing preliminary data about experiences with the Rothman Index in the VICU work environment, including observations and interviews with virtual nursing staff and deidentified quantitative usage data extracted from the Rothman Index system. Drawing on preliminary findings, hospital stakeholders will be engaged in participatory design to improve workplace protocols and practices around algorithmic decision making. Subsequently, this project will inform three fundamental research challenges: (1) technical communication research on how cognition and memory facilitate workplace writing processes and the impacts of electronic systems on patient-provider and provider-provider communication; (2) organizational research on the synergistic mechanisms that successfully enable VICU; and (3) computer science research on the social and ethical implications of algorithmic interventions such as the Rothman Index. Furthermore, this research will open door to studying many related problems: (a) feasibility of algorithmic patient care for preventative population outreach programs; (b) predictions of job displacements caused by algorithmic patient care implementation and anticipatory workforce training; (c) future algorithmic design for healthcare workplaces.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

随着向基于价值的护理转变，医疗保健组织正在寻求创新的方法来提高护理质量，同时降低成本。在接下来的几十年里，算法驱动的患者护理将会增加，数据驱动的预警系统（如Rothman Index）也会得到广泛使用。罗斯曼指数是一个算法系统，使用患者信息，实验室结果和其他健康相关数据来预测健康恶化。Rothman等医疗系统无疑将改变医疗保健领域的日常工作，要求已经过度扩展的劳动力提供新的专业知识和沟通。虽然这些系统可以减少人员配置需求，但它们并没有消除对人工监督和干预的需求。因此，了解传统医疗从业人员如何与这些系统互动，对于成功实施算法患者护理至关重要。为了实现这一目标，该项目旨在扩大我们对虚拟重症监护室（VICU）护士如何使用Rothman指数做出算法知情的工作场所决策的理解。更广泛地说，该项目研究了医护人员如何在算法和患者互动之间进行调解。因此，它为未来的训练协议、系统重新设计和修订以及类似未来算法工具的整体优化提供了信息。该项目将采用参与式和以工作者为中心的设计流程，通过与医疗保健工作者的密切合作来实施算法患者护理，以推进Rothman指数的技术设计。它将专注于虚拟护士的经验，目前在罗斯曼指数警报和地板上的健康从业者之间进行调解的提供者，在做出实际的算法决策时。该项目的基础是与相关医院利益相关者建立关系，然后收集和分析有关VICU工作环境中Rothman Index经验的初步数据，包括对虚拟护理人员的观察和访谈，以及从Rothman Index系统中提取的去识别定量使用数据。根据初步研究结果，医院利益相关者将参与参与设计，以改善围绕算法决策的工作场所协议和实践。随后，本项目将告知三个基础研究挑战：（1）关于认知和记忆如何促进工作场所写作过程以及电子系统对患者与提供者和提供者与提供者沟通的影响的技术沟通研究;（2）关于成功实现VICU的协同机制的组织研究;（3）计算机科学研究算法干预的社会和伦理影响，如罗斯曼指数。此外，这项研究将打开大门，研究许多相关的问题：（a）算法的病人护理的预防性人口外展计划的可行性;（B）算法的病人护理的实施和预期的劳动力培训所造成的就业转移的预测;（c）第（1）款该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的学术价值和更广泛的影响审查标准。

项目成果

Communication and Algorithmic Decision Making in a Virtual Healthcare Context: Extended Abstract

虚拟医疗环境中的通信和算法决策：扩展摘要

• DOI: 10.1145/3472714.3473669
• 发表时间: 2021
• 期刊: The 39th ACM International Conference on Design of Communication. Association for Computing Machinery
• 作者: Campbell, Lillian;George, Amrita;Guha, Shion
• 通讯作者: Guha, Shion

An Overview Of Synergistic Organizational Resources In Algorithm-enabled Virtual Patient Care

算法支持的虚拟患者护理中协同组织资源概述

• 发表时间: 2021
• 期刊: INFORMS Annual Meeting
• 作者: Dr. Amrita George, Dr. Lillian

Practitioner Attitudes towards an Early Warning System: From Professional Distraction to Relational Support

从业者对早期预警系统的态度：从专业干扰到关系支持

• 发表时间: 2021
• 期刊: IEEE International Professional Communication Conference
• 作者: Dr. Lillian Campbell, Dr. Amrita