FIM Research Institute for Information Management, University of Bayreuth, Branch Business and Information Systems Engineering of the Fraunhofer FIT, Wittelsbacherring 10, 95444, Bayreuth, Germany.
University St. Gallen, Dufourstrasse 50, 9000, St. Gallen, Switzerland.
BMC Health Serv Res. 2024 Apr 3;24(1):420. doi: 10.1186/s12913-024-10894-4.
Artificial intelligence (AI) applications pave the way for innovations in the healthcare (HC) industry. However, their adoption in HC organizations is still nascent as organizations often face a fragmented and incomplete picture of how they can capture the value of AI applications on a managerial level. To overcome adoption hurdles, HC organizations would benefit from understanding how they can capture AI applications' potential.We conduct a comprehensive systematic literature review and 11 semi-structured expert interviews to identify, systematize, and describe 15 business objectives that translate into six value propositions of AI applications in HC.Our results demonstrate that AI applications can have several business objectives converging into risk-reduced patient care, advanced patient care, self-management, process acceleration, resource optimization, and knowledge discovery.We contribute to the literature by extending research on value creation mechanisms of AI to the HC context and guiding HC organizations in evaluating their AI applications or those of the competition on a managerial level, to assess AI investment decisions, and to align their AI application portfolio towards an overarching strategy.
人工智能(AI)应用为医疗保健(HC)行业的创新铺平了道路。然而,由于组织经常面临如何在管理层面上获取 AI 应用价值的碎片化和不完整的情况,因此它们在 HC 组织中的采用仍处于起步阶段。为了克服采用障碍,HC 组织将受益于了解他们如何利用 AI 应用的潜力。我们进行了全面的系统文献回顾和 11 次半结构化专家访谈,以确定、系统地描述和描述 15 个业务目标,这些目标转化为 HC 中 AI 应用的六个价值主张。我们的研究结果表明,AI 应用程序可以具有多个业务目标,这些目标可以集中在降低风险的患者护理、先进的患者护理、自我管理、流程加速、资源优化和知识发现上。我们通过将 AI 创造价值的机制的研究扩展到 HC 背景,并指导 HC 组织在管理层面上评估他们的 AI 应用或竞争的 AI 应用,以评估 AI 投资决策,并使他们的 AI 应用组合与总体战略保持一致,从而为文献做出了贡献。