人工智能对相关健康职业中行政和管理角色的影响

摘要(中文译文)

本研究探讨了人工智能（AI）技术如何支持联合卫生工作者的非诊断/非治疗角色，考察了AI可能对劳动力构成的挑战和风险，并强调了随着AI使用增长有待拓展的领域。我们对14位关键知情人进行了12次访谈，这些知情人熟悉特定联合卫生职业以及AI如何融入其角色。来自同行评审文献和灰色文献的主题与空白为我们半结构化访谈指南提供了依据。我们采用快速内容分析法，围绕以下任务总结了访谈发现：转录、医疗编码/计费、翻译/口译、排班、沟通以及数据收集/管理。我们还围绕确保AI素养总结了相关发现。联合卫生职业（通常被认为是指医师、护士和牙医以外的职业）不直接参与患者诊断和治疗，其与AI的互动程度各不相同。在这些联合卫生角色中使用AI的积极描述包括：劳动力需求超过供给的情况，以及AI可部署用于某些常规行政任务、并可能通过让劳动力专注于更复杂和更有回报的任务来提高工作满意度的情况。AI使用在有助于提高效率时（例如促进沟通）也被积极描述。由于AI可能产生有偏见或错误的结果，对其应用的警示包括需要额外的工作人员时间来监测结果，并避免对患者安全和组织运营产生负面影响。有助于提升整个卫生劳动力AI素养的教育被认为对其适当使用至关重要。迄今为止，大多数承担行政/管理角色的联合卫生工作者的工作尚未面临被AI取代的风险。然而，AI使用的迅速扩大，加之提供者职业倦怠的持续影响和卫生系统面临的财务压力，可能促使人们更加关注使用AI来补偿缩减的劳动力，包括许多联合卫生职业。

Abstract

This study explored how artificial intelligence (AI) technologies support the nondiagnosing/nontreatment roles of allied health workers, examining challenges and risks AI may pose for the workforce and highlighting areas for expansion as AI use grows. We conducted 12 interviews with 14 key informants familiar with specific allied health occupations and how AI has been incorporated into their roles. Themes and gaps identified from peer-reviewed and gray literature informed our semi-structured interview guide. We used rapid content analysis to summarize findings from interviews around the following tasks: transcription, medical coding/billing, translation/interpretation, scheduling, communication, and data collection/management. We also summarized findings around ensuring AI literacy. Allied health occupations (typically considered occupations other than physicians, nurses, and dentists) not directly involved in patient diagnosis and treatment have varying levels of interaction with AI. Positive descriptions of AI use in these allied health roles included situations where workforce demand exceeds supply and where AI can be deployed for some routine administrative tasks and may improve job satisfaction by allowing the workforce to focus on more complex and rewarding tasks. AI use was also described positively where it contributed to increased efficiency, for example, in facilitating communications. Because AI can produce biased or erroneous results, cautions about its applications included needing additional staff time to monitor outcomes and avoid negative impacts on patient safety and an organization's operations. Education that contributes to AI literacy across the health workforce is considered critical for its appropriate use. To date, most allied health workers' jobs with administrative/management roles have not been at risk of replacement by AI. AI's rapidly expanding use, however, combined with the ongoing impacts of provider burnout and financial pressures on health systems, could incentivize increased interest in using AI to compensate for a downsized workforce, including many allied health occupations.

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