Data and code for: Patterns of Artificial Intelligence Adoption by Hospitals

Principal Investigator(s):  View help for Principal Investigator(s) Avi Goldfarb, University of Toronto; Xianda (Hentry) He, University of Southern California; Florenta Teodoridis, University of Southern California

Version:  View help for Version V1

Name File Type Size Last Modified
Readme.pdf application/pdf 49.7 KB 05/19/2025 10:36:AM
aea2025_dataconstruction_2024_12_16.do text/plain 9.3 KB 01/10/2025 10:52:AM
aea2025_tables_2024_12_16.do text/plain 21.2 KB 05/09/2025 12:39:PM

Project Citation: 

Goldfarb, Avi, He, Xianda (Hentry), and Teodoridis, Florenta. Data and code for: Patterns of Artificial Intelligence Adoption by Hospitals. Nashville, TN: American Economic Association [publisher], 2025. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2025-05-20. https://doi.org/10.3886/E229061V1

Project Description

Summary:  View help for Summary This study examines AI adoption in US hospitals using three distinct datasets: (i) Survey data from the American Hospital Association on AI for operations-related uses (27% adopt), (ii) Employment data from Revelio Labs on workers at hospitals with AI skills (14% adopt), and (iii) Publication data from Dimensions on hospital-affiliated researcher publications (8% adopt). Consistent with adoption patterns for the business internet and for electronic medical records, AI adoption is higher in metro areas and in larger hospitals. In contrast to the business internet, metro area and firm size do not appear to be substitute correlates with adoption.
Funding Sources:  View help for Funding Sources SSHRC

Scope of Project

Subject Terms:  View help for Subject Terms hospital technology adoption; artificial intelligence
JEL Classification:  View help for JEL Classification
      I19 Health: Other
      O33 Technological Change: Choices and Consequences; Diffusion Processes
Geographic Coverage:  View help for Geographic Coverage united states
Time Period(s):  View help for Time Period(s) 2000 – 2022
Collection Date(s):  View help for Collection Date(s) 2024 – 2024 (2024)

Methodology

Data Source:  View help for Data Source Revelio Labs
AHA hospital survey
Dimensions
Unit(s) of Observation:  View help for Unit(s) of Observation hospital-year

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Published Versions

V1 [2025-05-20]

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