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- W3025109669 abstract "Purpose To assess the performance of statistical modeling in predicting follow-up adherence of incidentally detected pulmonary nodules (IPN) on CT, based on patient variables (PV), radiology report related variables (RRRV) and physician-patient communication variables (PPCV). Methods 200 patients with IPN on CT were retrospectively identified and randomly selected. PV (age, gender, smoking status, ethnicity), RRRV (nodule size, patient context, whether follow-up recommendations were provided) and PPCV (whether referring physician documented IPN and ordered follow-up on the electronic medical record) were recorded. Primary outcome was whether patients received appropriate follow-up within +/- 1 month of the recommended time frame. Statistical methods included logistic regression and machine learning (K-nearest neighbors and support vector machine). Results Adherence was low, with or without recommendations provided in the radiology report (23.4 %–27.4 %). Whether the referring physician ordered follow-up was the dominant predictor of adherence in all models. The following variables were statistically significant predictors of whether referring physician ordered follow-up: recommendations provided in the radiology report, smoking status, patient context and nodule size (FDR logworth of respectively 21.18, 11.66, 2.35, 1.63, p < 0.05). Prediction accuracy varied from 72 % (PV) to 93 % (PPCV, all variables). Conclusion PPCV are the most important predictors of adherence. Amongst all variables, patient context, smoking status, nodule size, and whether the radiologist provided follow-up recommendations in the report were all statistically significant predictors of patient follow-up adherence, supporting the utility of statistical modeling for analytics, quality assurance and optimization of outcomes related to IPN." @default.
- W3025109669 created "2020-05-21" @default.
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- W3025109669 date "2020-07-01" @default.
- W3025109669 modified "2023-10-18" @default.
- W3025109669 title "Statistical modeling can determine what factors are predictive of appropriate follow-up in patients presenting with incidental pulmonary nodules on CT" @default.
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- W3025109669 doi "https://doi.org/10.1016/j.ejrad.2020.109062" @default.
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