Hospital incentives and implementation support for appropriate adoption of robotic surgery: a scoping review and evidence-informed framework
- 1Department of Information Systems and Business Analytics, Florida International University, Miami, USA
- 2Department of Information Science and Systems, Morgan State University, Baltimore, USA
Abstract
Hospitals that acquire robotic-assisted surgery (RAS) platforms often seek to increase utilization, yet surgeons and operating-room teams bear the learning, coordination, and early efficiency costs of adoption. This scoping review mapped evidence on hospital incentives and broader implementation support for appropriate surgeon adoption of RAS. Following JBI guidance and a registered protocol, we searched PubMed/MEDLINE, Embase, Scopus, Web of Science, and IEEE Xplore to September 2026, supplemented by Google Scholar and citation searching, and reported findings following PRISMA-ScR. Two reviewers independently screened 1,058 records and included 17 sources (12 empirical studies; five reviews or recommendation documents). No included source evaluated a hospital incentive program, so the evidence was indirect. Nine of the 12 empirical studies used US data, and none linked incentive or support exposure to the appropriateness of patient selection or to patient outcomes. Industry payments were associated with greater robotic use; one observational evaluation linked proficiency-based training with shorter operative times and lower unadjusted costs; and qualitative studies identified barriers related to training, staffing, operating access, and credentialing. Using the capability, opportunity, and motivation (COM-B) model to organize these findings, we propose a four-layer framework (clinical justification, capability, operating opportunity, and governance), map the evidence to each layer, and specify a minimum configuration for hospitals with limited resources. The framework is a set of testable proposals, not a validated intervention. Hospital support appears most defensible when it addresses a documented barrier within a clinically justified service, and robotic case volume alone does not adequately measure program success.
Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1007/s11701-026-04142-6.
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BibTeX
@article{esmaeilzadeh2026hospital,
title = {{Hospital incentives and implementation support for appropriate adoption of robotic surgery: a scoping review and evidence-informed framework}},
author = {Pouyan Esmaeilzadeh and Shirin Hasavari},
journal = {Journal of Robotic Surgery},
year = {2026},
month = nov,
doi = {10.1007/s11701-026-04142-6},
url = {https://doi.org/10.1007/s11701-026-04142-6},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - Hospital incentives and implementation support for appropriate adoption of robotic surgery: a scoping review and evidence-informed framework
AU - Pouyan Esmaeilzadeh
AU - Shirin Hasavari
PY - 2026
DA - 2026/11/05
JO - Journal of Robotic Surgery
DO - 10.1007/s11701-026-04142-6
UR - https://doi.org/10.1007/s11701-026-04142-6
AB - Hospitals that acquire robotic-assisted surgery (RAS) platforms often seek to increase utilization, yet surgeons and operating-room teams bear the learning, coordination, and early efficiency costs of adoption. This scoping review mapped evidence on hospital incentives and broader implementation support for appropriate surgeon adoption of RAS. Following JBI guidance and a registered protocol, we searched PubMed/MEDLINE, Embase, Scopus, Web of Science, and IEEE Xplore to September 2026, supplemented by Google Scholar and citation searching, and reported findings following PRISMA-ScR. Two reviewers independently screened 1,058 records and included 17 sources (12 empirical studies; five reviews or recommendation documents). No included source evaluated a hospital incentive program, so the evidence was indirect. Nine of the 12 empirical studies used US data, and none linked incentive or support exposure to the appropriateness of patient selection or to patient outcomes. Industry payments were associated with greater robotic use; one observational evaluation linked proficiency-based training with shorter operative times and lower unadjusted costs; and qualitative studies identified barriers related to training, staffing, operating access, and credentialing. Using the capability, opportunity, and motivation (COM-B) model to organize these findings, we propose a four-layer framework (clinical justification, capability, operating opportunity, and governance), map the evidence to each layer, and specify a minimum configuration for hospitals with limited resources. The framework is a set of testable proposals, not a validated intervention. Hospital support appears most defensible when it addresses a documented barrier within a clinically justified service, and robotic case volume alone does not adequately measure program success. Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1007/s11701-026-04142-6.
SN - 1863-2483
SN - 1863-2491
ER -