Barriers and facilitators perceived by physicians when using prediction models in practice

Kappen, Teus H.; Loon, Kim van; Kappen, Martinus A.M.; Wolfswinkel, Leo van; Vergouwe, Yvonne; Klei, Wilton A. van; Moons, Karel G.M.; Kalkman, Cor J.

doi:10.1016/j.jclinepi.2015.09.008

Cited by 54 publications

(66 citation statements)

References 38 publications

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“…The 95% CIs were calculated from the covariance matrix for the variable study, allocation group, predicted probability, and their interaction terms. Further methodologic information and the numerical results of the regression models are available in Additional file 1 way to decrease the required cognitive effort and increase the ease of use of the prediction tool, as supported by our results (Table 3, F.1) [38]. This does not mean that probabilities alone cannot be useful.…”

Section: Addressing the Physician's Perspectivesupporting

confidence: 62%

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

et al. 2018

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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.

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Section: Addressing the Physician's Perspectivesupporting

confidence: 62%

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

et al. 2018

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“…Compliance with institutional protocols is improved somewhat by educational strategies and decision prompting. 77,78 Kappen et al 79 recently reported their investigation into the failure of risk-prompting strategy for PONV to influence patient outcome. The reluctance of the clinicians to change practice was based in part on risk management, ie, the lack of risk-benefit consideration for drugs.…”

Section: Implementation Gapsmentioning

confidence: 99%

“…Additional factors were the low priority given to PONV as an important health care outcome and the reliance on intuition to make decisions regarding prophylaxis. 79…”

Section: Implementation Gapsmentioning

confidence: 99%

Ambulatory anesthesia and postoperative nausea and vomiting: predicting the probability

Hegarty

Buckley

McCaul

2016

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Nausea and vomiting are distinctly unpleasant symptoms that may occur after surgery and anesthesia, and high priority is given to their prevention by patients. Research in this area is plentiful and has focused on event prediction and pharmacological prophylaxis but despite this, postoperative nausea and vomiting (PONV) typically occurs in 20%-30% of patients in contemporary practice. Prediction of postoperative and postdischarge nausea and vomiting is particularly important in the ambulatory surgical population as these symptoms may occur following discharge from hospital and continue for up to one week when access to antiemetic therapies is limited. Many of the existing predictive scoring systems are based on data from inpatient populations and limited to the first 24 hours after surgery. Scoring systems based on data from ambulatory surgical populations to predict PONV are only moderately good. The best-performing systems in ambulatory patients are those of Sinclair and Sarin with an area under the receiver operating characteristic curve of 0.78 and 0.74, respectively, but are limited by the short duration of follow-up and a greater emphasis on nausea than vomiting. Given that the ability to predict both PONV and postdischarge nausea and vomiting is clearly limited, emphasis has been placed on prophylactic strategies that incorporate antiemetic medication, intravenous hydration, and nonnarcotic analgesia. PONV has been reduced to <10% in institutions using multimodal approaches. Scoring systems may facilitate "risk tailoring" in which patient risk profile is used as a stratification method for pharmacointervention.

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“…Poor knowledge about PONV management negatively affects the patient, but there are situations in which health professionals can't intervene PONV even if the factors causing nausea, and vomiting are identified by professionals (5). Knowledge and perception of health professionals regarding the consequences of PONV are limited, which leads them not to give attention to prevention strategies (6).…”

Section: Introductionmentioning

confidence: 99%

Knowledge and practice of postoperative nausea, vomiting management, and predictors of knowledge among health professionals in referral hospitals of northwest Ethiopia, 2019

Yetneberk¹,

Fentie²,

Yimer³

et al. 2020

Preprint

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Background Good knowledge conjoined with evident practice of postoperative nausea, and vomiting management is vital for the optimal management of patients. On the other hand, inadequate knowledge and poor practice of health professionals on postoperative nausea vomiting risk reduction and management come up with complications, reduce patient satisfaction, increase patient, and hospital costs. Objective To assess knowledge, practice, and predictors of knowledge regarding postoperative nausea and vomiting management among health professionals working in referral hospitals in northwest Ethiopia. Methods A multicenter cross-sectional study was conducted on 407 health professionals from February 27 to March 30, 2019, in referral hospitals in northwest Ethiopia. Stratified random Sampling followed by simple random sampling was used to select the study participants. Both bivariable and multivariable logistic regression were used to identify factors associated with the knowledge level of health professionals in PONV management. In the multivariable analysis, variables with a p-value <0.05 were considered statistically significant. Results 52.8% of the study participants had good knowledge of PONV management (95% CI: 47.9-57.2). Male professionals were 1.95 times more likely knowledgeable as compared with females. The odds of physicians being knowledgeable were 5.36 times more likely than midwives, while the odds of anesthetists being knowledgeable were 3.88 times more likely than midwives. Professionals trained on PONV management were 5.32 (AOR: 5.32; 95%CI: 1.58, 17.89) times more likely knowledgeable than those who did not train. Conclusions Nearly fifty % of healthcare providers working in the perioperative working areas had poor knowledge of PONV management. Gender, profession, and training on PONV management were factors significantly affecting the knowledge level of health professionals. Regular training seminars, continuous professional development, adherence to the latest guidelines, and conducting clinical audits are recommended to increase knowledge and improve the practices of health professionals in postoperative nausea vomiting management.

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Barriers and facilitators perceived by physicians when using prediction models in practice

Cited by 54 publications

References 38 publications

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

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

Ambulatory anesthesia and postoperative nausea and vomiting: predicting the probability

Knowledge and practice of postoperative nausea, vomiting management, and predictors of knowledge among health professionals in referral hospitals of northwest Ethiopia, 2019

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