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2023 Industry Perceptions Survey on AI Adoption and Return on Investment.
Goldburgh, Mitchell; LaChance, Michael; Komissarchik, Julia; Patriarche, Julia; Chapa, Joe; Chen, Oliver; Deshpande, Priya; Geeslin, Matthew; Komissarchik, Julia; Kottler, Nina; Patriarche, Julia; Sommer, Jennifer; Ayers, Marcus; Vujic, Vedrana.
Afiliação
  • Goldburgh M; NTT DATA, Tokyo, Japan. Mitchell.Goldburgh@nttdata.com.
  • LaChance M; LaChance Executive Consulting, Washington, DC, USA.
  • Komissarchik J; Glendor, Inc., Draper, UT, USA.
  • Patriarche J; A.I. Analysis, Inc., Seattle, WA, USA.
  • Chen O; HOPPR, Chicago, IL, USA.
  • Deshpande P; Department of Electrical and Computer Engineering, Opus College of Engineering, Marquette University, Milwaukee, WI, USA.
  • Geeslin M; Deparment of Radiology, University of Vermont, Burlington, VT, USA.
  • Komissarchik J; Glendor, Inc., Draper, UT, USA.
  • Kottler N; Radiology Partners, El Segundo, CA, USA.
  • Patriarche J; A.I. Analysis, Inc., Seattle, WA, USA.
  • Sommer J; Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA.
  • Ayers M; NTT DATA, Tokyo, Japan.
  • Vujic V; NTT DATA, Tokyo, Japan.
J Imaging Inform Med ; 2024 Aug 20.
Article em En | MEDLINE | ID: mdl-39164452
ABSTRACT
This SIIM-sponsored 2023 report highlights an industry view on artificial intelligence adoption barriers and success related to diagnostic imaging, life sciences, and contrasts. In general, our 2023 survey indicates that there has been progress in adopting AI across multiple uses, and there continues to be an optimistic forecast for the impact on workflow and clinical outcomes. This report, as in prior years, should be seen as a snapshot of the use of AI in imaging. Compared to our 2021 survey, the 2023 respondents expressed wider AI adoption but felt this was behind the potential. Specifically, the adoption has increased as sources of return on investment with AI in radiology are better understood as documented by vendor/client use case studies. Generally, the discussions of AI solutions centered on workflow triage, visualization, detection, and characterization. Generative AI was also mentioned for improving productivity in reporting. As payor reimbursement remains elusive, the ROI discussions expanded to look at other factors, including increased hospital procedures and admissions, enhanced radiologist productivity for practices, and improved patient outcomes for integrated health networks. When looking at the longer-term horizon for AI adoption, respondents frequently mentioned that the opportunity for AI to achieve greater adoption with more complex AI and a more manageable/visible ROI is outside the USA. Respondents focused on the barriers to trust in AI and the FDA processes.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: J Imaging Inform Med Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: J Imaging Inform Med Ano de publicação: 2024 Tipo de documento: Article