Table 3 How to present the model predictions?
From: Evaluating the impact of prediction models: lessons learned, challenges, and recommendations
Facilitators: features that increase the ease of use of a prediction model | |
 F.1 Add a decision recommendation to the predicted probabilities | |
  Directive prediction tools may be easier for physicians to use in their decision making than assistive prediction tools that provide only predicted probabilities without decision recommendations. | |
 F.2 Automatic calculation and presentation of the model’s probability within the physician’s workflow | |
  Minimizing manual predictor value entry and integrating the estimation of the model’s probability in the electronic patient record will facilitate the ease of use of a prediction model for care providers. | |
 F.3 Provide the reasoning or research evidence behind the predicted probability | |
  Enhances face value, acceptation and belief in the model, and thus the willingness to use the model’s probabilities to guide decision making. | |
Barriers that may decrease the ease of use of a prediction model | |
 B.1 A predicted probability may be difficult to use in decision making, especially without corresponding recommendations | |
  Weighing the numerical probabilities with other available information will require more cognitive effort from physicians when the probabilities are presented without a corresponding recommendation on subsequent treatment or additional diagnostic testing. | |
 B.2 When the targeted physicians use an intuitive rather than analytical process of decision making | |
  When an existing decision-making process is mostly intuitive, it may require more cognitive effort to use probabilistic knowledge in decision making. | |
 B.3 When the predicted outcome is not a main concern for the physicians | |
  Physicians will not prioritize their time and efforts to use a prediction model in their decisions, when they consider other problems or outcomes to be more important. | |
 B.4 A prediction model does not weigh the benefits and risks of treatment or additional diagnostics regarding the patient’s (co)morbidity | |
  When a physician has more sources of information about the benefits and risks of subsequent treatment decisions, she/he will still have to weigh the model’s predicted probability from the model against this information, which is often perceived as cumbersome. |