The IDEAL framework in neurosurgery: a bibliometric analysis

Acta Neurochir (Wien). 2020 Dec;162(12):2939-2947. doi: 10.1007/s00701-020-04477-5. Epub 2020 Jul 10.

Abstract

Background: The Idea, Development, Exploration, Assessment and Long-term study (IDEAL) framework was created to provide a structured way for assessing and evaluating novel surgical techniques and devices.

Objectives: The aim of this paper was to investigate the utilization of the IDEAL framework within neurosurgery, and to identify factors influencing implementation.

Methods: A bibliometric analysis of the 7 key IDEAL papers on Scopus, PubMed, Embase, Web of Science, and Google Scholar databases (2009-2019) was performed. A second journal-specific search then identified additional papers citing the IDEAL framework. Publications identified were screened by two independent reviewers to select neurosurgery-specific articles.

Results: The citation search identified 1336 articles. The journal search identified another 16 articles. Following deduplication and review, 51 relevant articles remained; 14 primary papers (27%) and 37 secondary papers (73%). Of the primary papers, 5 (36%) papers applied the IDEAL framework to their research correctly; two were aligned to the pre-IDEAL stage, one to the Idea and Development stages, and two to the Exploration stage. Of the secondary papers, 21 (57%) explicitly discussed the IDEAL framework. Eighteen (86%) of these were supportive of implementing the framework, while one was not, and two were neutral.

Conclusion: The adoption of the IDEAL framework in neurosurgery has been slow, particularly for early-stage neurosurgical techniques and inventions. However, the largely positive reviews in secondary literature suggest potential for increased use that may be achieved with education and publicity.

Keywords: Evidence; IDEAL framework; Innovation; Neurosurgery; Research; Surgery.

Publication types

  • Review

MeSH terms

  • Bibliometrics
  • Humans
  • Inventions
  • Neurosurgery*
  • Neurosurgical Procedures / methods*