Wolff Justus, Pauling Josch, Keck Andreas, Baumbach Jan
TUM School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany.
Strategy Institute for Digital Health, Hamburg, Germany.
J Med Internet Res. 2020 Feb 20;22(2):e16866. doi: 10.2196/16866.
Positive economic impact is a key decision factor in making the case for or against investing in an artificial intelligence (AI) solution in the health care industry. It is most relevant for the care provider and insurer as well as for the pharmaceutical and medical technology sectors. Although the broad economic impact of digital health solutions in general has been assessed many times in literature and the benefit for patients and society has also been analyzed, the specific economic impact of AI in health care has been addressed only sporadically.
This study aimed to systematically review and summarize the cost-effectiveness studies dedicated to AI in health care and to assess whether they meet the established quality criteria.
In a first step, the quality criteria for economic impact studies were defined based on the established and adapted criteria schemes for cost impact assessments. In a second step, a systematic literature review based on qualitative and quantitative inclusion and exclusion criteria was conducted to identify relevant publications for an in-depth analysis of the economic impact assessment. In a final step, the quality of the identified economic impact studies was evaluated based on the defined quality criteria for cost-effectiveness studies.
Very few publications have thoroughly addressed the economic impact assessment, and the economic assessment quality of the reviewed publications on AI shows severe methodological deficits. Only 6 out of 66 publications could be included in the second step of the analysis based on the inclusion criteria. Out of these 6 studies, none comprised a methodologically complete cost impact analysis. There are two areas for improvement in future studies. First, the initial investment and operational costs for the AI infrastructure and service need to be included. Second, alternatives to achieve similar impact must be evaluated to provide a comprehensive comparison.
This systematic literature analysis proved that the existing impact assessments show methodological deficits and that upcoming evaluations require more comprehensive economic analyses to enable economic decisions for or against implementing AI technology in health care.
积极的经济影响是决定是否投资医疗行业人工智能（AI）解决方案的关键因素。这对医疗服务提供者、保险公司以及制药和医疗技术行业最为重要。尽管数字健康解决方案的广泛经济影响在文献中已被多次评估，并且对患者和社会的益处也已得到分析，但AI在医疗保健领域的具体经济影响仅得到零星探讨。
本研究旨在系统回顾和总结专门针对医疗保健领域AI的成本效益研究，并评估它们是否符合既定的质量标准。
第一步，基于既定和调整后的成本影响评估标准方案，定义经济影响研究的质量标准。第二步，根据定性和定量的纳入与排除标准进行系统的文献综述，以识别相关出版物，用于深入分析经济影响评估。最后一步，根据为成本效益研究定义的质量标准，评估已识别的经济影响研究的质量。
很少有出版物全面探讨经济影响评估，且所审查的关于AI的出版物的经济评估质量显示出严重的方法学缺陷。根据纳入标准，在66篇出版物中，只有6篇可纳入分析的第二步。在这6项研究中，没有一项进行了方法学上完整的成本影响分析。未来研究有两个需要改进的方面。第一，需要纳入AI基础设施和服务的初始投资及运营成本。第二，必须评估实现类似影响的替代方案，以提供全面的比较。
这项系统的文献分析证明，现有的影响评估存在方法学缺陷，未来的评估需要更全面的经济分析，以便就医疗保健领域是否实施AI技术做出经济决策。
