Open AccessAccuracy of Clinicians’ Ability to Predict the Need for Intensive Care Unit Readmission
Author(s) -
Juan C. Rojas,
Patrick G. Lyons,
Teresa Jiang,
Megha Kilaru,
Leslie McCauley,
J. Picart,
Kyle Carey,
Dana P. Edelson,
Vineet M. Arora,
Matthew M. Churpek
Publication year - 2020
Publication title -
annals of the american thoracic society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.035
H-Index - 114
eISSN - 2329-6933
pISSN - 2325-6621
DOI - 10.1513/annalsats.201911-828oc
Subject(s) - medicine , interquartile range , intensive care unit , emergency medicine , receiver operating characteristic , confidence interval , saps ii , prospective cohort study , intensive care medicine , apache ii
Rationale: Determining when an intensive care unit (ICU) patient is ready for discharge to the ward is a complex daily challenge for any ICU care team. Patients who experience unplanned readmissions to the ICU have increased mortality, length of stay, and cost compared with those not readmitted during their hospital stay. The accuracy of clinician prediction for ICU readmission is unknown. Objectives: To determine the accuracy of ICU physicians and nurses for predicting ICU readmissions Methods: We conducted a prospective study in the medical ICU of an academic hospital from October 2015 to September 2017. After daily rounding for patients being transferred to the ward, ICU clinicians (nurses, residents, fellows, and attendings) were asked to report the likelihood of readmission within 48 hours (using a 1-10 scale, with 10 being "extremely likely"). The accuracy of the clinician prediction score (1-10) was assessed for all clinicians and by clinician type using sensitivity, specificity, and area under the curve (AUC) for the receiver operating characteristic curve for predicting the primary outcome, which was ICU readmission within 48 hours of ICU discharge. Results: A total of 2,833 surveys was collected for 938 ICU-to-ward transfers, of which 40 (4%) were readmitted to the ICU within 48 hours of transfer. The median clinician likelihood of readmission score was 3 (interquartile range, 2-4). When physician and nurse likelihood scores were combined, the median clinician likelihood score had an AUC of 0.70 (95% confidence interval [CI], 0.62-0.78) for predicting ICU readmission within 48 hours. Nurses were significantly more accurate than interns at predicting 48-hour ICU readmission (AUC, 0.73 [95% CI, 0.64-0.82] vs. AUC, 0.60 [95% CI, 0.49-0.71]; P = 0.03). All other pairwise comparisons were not significantly different for predicting ICU readmission within 48 hours ( P > 0.05 for all comparisons). Conclusions: We found that all clinicians surveyed in our ICU, regardless of the level of experience or clinician type, had only fair accuracy for predicting ICU readmission. Further research is needed to determine if clinical decision support tools would provide prognostic value above and beyond clinical judgment for determining who is ready for ICU discharge.