Factors predicting timely implementation of radiotherapy innovations: the first model

Rachelle R. Swart*, Maria Jg Jacobs, Cheryl Roumen, Ruud Houben, Folkert Koetsveld, Liesbeth J. Boersma

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

4 Citations (Web of Science)


Objective: The improvement of radiotherapy depends largely on the implementation of innovations, of which effectivity varies widely. The aim of this study is to develop a prediction model for successful innovation implementation in radiotherapy to improve effective management of innovation projects.

Methods: A literature review was performed to identify success factors for innovation implementation. Subsequently, in two large academic radiotherapy centres in the Netherlands, an inventory was made of all innovation projects executed between 2011 and 2017. Semi-structured interviews were performed to record the presence/ absence of the success factors found in the review for each project. Successful implementation was defined as timely implementation, yes/no. Cross-tables, X-2 tests, t-tests and Benjamin-Hochberg correction were used for analysing the data. A multivariate logistic regression technique was used to build a prediction model.

Results: From the 163 identified innovation projects, only 54% were successfully implemented, We found 31 success factors in literature of which 14 were significantly related to successful implementation in the innovation projects in our study. The prediction model contained the following determinants: (1) sufficient and competent employees, (2) complexity, (3) understanding/awareness of the project goals and process by employees, (4) feasibility and desirability. The area Under the curve (AUC) of the prediction model was 0.86 (0.8-0.92, 95%CI).

Conclusion: A prediction model was developed for successful implementation of innovation in radiotherapy.

Original languageEnglish
Article number20200613
Number of pages9
JournalBritish Journal of Radiology
Issue number1117
Publication statusPublished - 2021


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