Factors predicting timely implementation o radiotherapy innovations: the first model

被引:7
|
作者
Swart, Rachelle R. [1 ]
Jacobs, Maria Jg [2 ]
Roumen, Cheryl [1 ]
Houben, Ruud [1 ]
Koetsveld, Folkert [3 ]
Boersma, Liesbeth J. [1 ]
机构
[1] Maastricht Univ, GROW Sch Oncol, Dept Radiat Oncol Maastro, Med Ctr, Maastricht, Netherlands
[2] Tilburg Univ, Tilburg Sch Econ & Management, Tilburg, Netherlands
[3] Netherlands Canc Inst, Dept Radiat Oncol, Amsterdam, Netherlands
来源
BRITISH JOURNAL OF RADIOLOGY | 2021年 / 94卷 / 1117期
关键词
HEALTH-CARE; INTERVENTIONS; MEDICINE; GAP;
D O I
10.1259/bjr.20200613
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
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.
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页数:9
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