Bharadwaj Prateek, Nicola Lauren, Breau-Brunel Manon, Sensini Federica, Tanova-Yotova Neda, Atanasov Petar, Lobig Franziska, Blankenburg Michael
Global Market Access Manager Radiology, Bayer, Berlin, Germany.
CEO/Partner, Triad Radiology Associates; Chair, Ultrasound Commission, ACR; Chair, Reimbursement Committee, ACR.
J Am Coll Radiol. 2024 Oct;21(10):1677-1685. doi: 10.1016/j.jacr.2024.02.034. Epub 2024 Mar 16.
A comprehensive return on investment (ROI) calculator was developed to evaluate the monetary and nonmonetary benefits of an artificial intelligence (AI)-powered radiology diagnostic imaging platform to inform decision makers interested in adopting AI.
A calculator was constructed to calculate comparative costs, estimated revenues, and quantify the clinical value of using an AI platform compared with no use of AI in radiology workflows of a US hospital over a 5-year time horizon. Parameters were determined on the basis of expert interviews and a literature review. Scenario and deterministic sensitivity analyses were conducted to evaluate calculator drivers.
In the calculator, the introduction of an AI platform into the hospital radiology workflow resulted in labor time reductions and delivery of an ROI of 451% over a 5-year period. The ROI was increased to 791% when radiologist time savings were considered. Time savings for radiologists included more than 15 8-hour working days of waiting time, 78 days in triage time, 10 days in reading time, and 41 days in reporting time. Using the platform also provided revenue benefits for the hospital in bringing in patients for clinically beneficial follow-up scans, hospitalizations, and treatment procedures. Results were sensitive to the time horizon, health center setting, and number of scans performed. Among those, the most influential outcome was the number of additional necessary treatments performed because of AI identification of patients.
The authors demonstrate a substantial 5-year ROI of implementing an AI platform in a stroke management-accredited hospital. The ROI calculator may be useful for decision makers evaluating AI-powered radiology platforms.
开发了一个全面的投资回报率(ROI)计算器,以评估人工智能(AI)驱动的放射诊断成像平台的货币和非货币效益,为有兴趣采用AI的决策者提供信息。
构建了一个计算器,用于计算比较成本、估计收入,并量化在5年时间范围内,美国一家医院放射科工作流程中使用AI平台与不使用AI相比的临床价值。参数是根据专家访谈和文献综述确定的。进行了情景分析和确定性敏感性分析,以评估计算器的驱动因素。
在该计算器中,将AI平台引入医院放射科工作流程可减少劳动时间,并在5年内实现451%的投资回报率。若考虑放射科医生节省的时间,投资回报率将提高到791%。放射科医生节省的时间包括超过15个8小时工作日的等待时间、78天的分诊时间、10天的阅片时间和41天的报告时间。使用该平台还为医院带来了收益,吸引患者进行有益临床的后续扫描、住院和治疗程序。结果对时间范围、健康中心设置和扫描执行数量敏感。其中,最具影响力的结果是因AI识别患者而进行的额外必要治疗的数量。
作者证明了在一家获得中风管理认证的医院实施AI平台可获得可观的5年投资回报率。该投资回报率计算器可能对评估AI驱动的放射科平台的决策者有用。