Evaluating the impact of prediction models: lessons learned, challenges, and recommendations

Diagnostic and Prognostic Research

Yvonne Vergouwe¹  Teus H. Kappen²  Karel G. M. Moons²  Cor J. Kalkman²  Wilton A. van Klei²  Leo van Wolfswinkel² 

[1] Department of Public Health, Erasmus Medical Center;Division of Anesthesiology, Intensive Care and Emergency Medicine, University Medical Center Utrecht, Utrecht University;

关键词: Prediction models;    Impact studies;    Implementation;    Diagnosis;    Prognosis;    Study design;   

DOI  :  10.1186/s41512-018-0033-6

来源: DOAJ

【 摘 要 】

Abstract An important aim of clinical prediction models is to positively impact clinical decision making and subsequent patient outcomes. The impact on clinical decision making and patient outcome can be quantified in prospective comparative—ideally cluster-randomized—studies, known as ‘impact studies’. However, such impact studies often require a lot of time and resources, especially when they are (cluster-)randomized studies. Before envisioning such large-scale randomized impact study, it is important to ensure a reasonable chance that the use of the prediction model by the targeted healthcare professionals and patients will indeed have a positive effect on both decision making and subsequent outcomes. We recently performed two differently designed, prospective impact studies on a clinical prediction model to be used in surgical patients. Both studies taught us new valuable lessons on several aspects of prediction model impact studies, and which considerations may guide researchers in their decision to conduct a prospective comparative impact study. We provide considerations on how to prepare a prediction model for implementation in practice, how to present the model predictions, and how to choose the proper design for a prediction model impact study.

【 授权许可】

Unknown