Discriminative Accuracy of Physician and Nurse Predictions for Survival and Functional Outcomes 6 Months After an ICU Admission.

IMPORTANCE: Predictions of long-term survival and functional outcomes influence decision making for critically ill patients, yet little is known regarding their accuracy. OBJECTIVE: To determine the discriminative accuracy of intensive care unit (ICU) physicians and nurses in predicting 6-month patient mortality and morbidity, including ambulation, toileting, and cognition. DESIGN, SETTING, AND PARTICIPANTS: Prospective cohort study conducted in 5 ICUs in 3 hospitals in Philadelphia, Pennsylvania, and enrolling patients who spent at least 3 days in the ICU from October 2013 until May 2014 and required mechanical ventilation, vasopressors, or both. These patients' attending physicians and bedside nurses were also enrolled. Follow-up was completed in December 2014. MAIN OUTCOMES AND MEASURES: ICU physicians' and nurses' binary predictions of in-hospital mortality and 6-month outcomes, including mortality, return to original residence, ability to toilet independently, ability to ambulate up 10 stairs independently, and ability to remember most things, think clearly, and solve day-to-day problems (ie, normal cognition). For each outcome, physicians and nurses provided a dichotomous prediction and rated their confidence in that prediction on a 5-point Likert scale. Outcomes were assessed via interviews with surviving patients or their surrogates at 6 months. Discriminative accuracy was measured using positive and negative likelihood ratios (LRs), C statistics, and other operating characteristics. RESULTS: Among 340 patients approached, 303 (89%) consented (median age, 62 years [interquartile range, 53-71]; 57% men; 32% African American); 6-month follow-up was completed for 299 (99%), of whom 169 (57%) were alive. Predictions were made by 47 physicians and 128 nurses. Physicians most accurately predicted 6-month mortality (positive LR, 5.91 [95% CI, 3.74-9.32]; negative LR, 0.41 [95% CI, 0.33-0.52]; C statistic, 0.76 [95% CI, 0.72-0.81]) and least accurately predicted cognition (positive LR, 2.36 [95% CI, 1.36-4.12]; negative LR, 0.75 [95% CI, 0.61-0.92]; C statistic, 0.61 [95% CI, 0.54-0.68]). Nurses most accurately predicted in-hospital mortality (positive LR, 4.71 [95% CI, 2.94-7.56]; negative LR, 0.61 [95% CI, 0.49-0.75]; C statistic, 0.68 [95% CI, 0.62-0.74]) and least accurately predicted cognition (positive LR, 1.50 [95% CI, 0.86-2.60]; negative LR, 0.88 [95% CI, 0.73-1.06]; C statistic, 0.55 [95% CI, 0.48-0.62]). Discriminative accuracy was higher when physicians and nurses were confident about their predictions (eg, for physicians' confident predictions of 6-month mortality: positive LR, 33.00 [95% CI, 8.34-130.63]; negative LR, 0.18 [95% CI, 0.09-0.35]; C statistic, 0.90 [95% CI, 0.84-0.96]). Compared with a predictive model including objective clinical variables, a model that also included physician and nurse predictions had significantly higher discriminative accuracy for in-hospital mortality, 6-month mortality, and return to original residence (P < .01 for all). CONCLUSIONS AND RELEVANCE: ICU physicians' and nurses' discriminative accuracy in predicting 6-month outcomes of critically ill patients varied depending on the outcome being predicted and confidence of the predictors. Further research is needed to better understand how clinicians derive prognostic estimates of long-term outcomes.

Contributors to Intensive Care Unit Clinicians' Predictions of Patient Outcomes: A Qualitative Analysis.

BACKGROUND: Information about a critically ill patient's prognosis is important to the shared decision-making process. The factors that physicians and nurses consider when generating their prognoses are not well understood. OBJECTIVE: To explore the factors that intensive care unit clinicians consider when prognosticating for their patients. METHODS: Intensive care unit clinicians (physicians and nurses) were asked to predict 6-month survival and describe the patient-related factors that they considered in their prognoses. The reported factors were tallied and compared with predictions of 6-month survival or death and with correct and incorrect predictions. RESULTS: Physicians and nurses completed 254 and 286 surveys, respectively, for 303 patients. Of 23 factors identified, the 3 most frequently reported were acute conditions, medical history and comorbid conditions, and trajectory. For patients predicted to be alive at 6 months, physicians commonly mentioned the factors procedures and age; nurses mentioned behavior patterns, previous experiences, and social support. For patients predicted to be dead at 6 months, both groups commonly mentioned cancer. Factors with the highest ratios of correct to incorrect predictions reported by physicians were procedures and definitive treatment; those reported by nurses were procedures, behavior patterns, and current functional status. CONCLUSIONS: Intensive care unit clinicians use various patient factors to inform their prognoses. Clinicians use different factors when predicting survival than when predicting death. Some factors are reported more frequently for correct predictions than for incorrect predictions.

Patients' perceptions and ICU clinicians predictions of quality of life following critical illness.

PURPOSE: To determine how patients perceive their quality of life (QOL) six months following critical illness and to measure clinicians' discriminative accuracy of predicting this outcome. MATERIALS AND METHODS: This prospective cohort study of intensive care unit (ICU) survivors asked patients to report their QOL strictly at six months compared to one month before their critical illness as better, the same, or worse. ICU physicians and nurses made six-month QOL predictions for these patients. RESULTS: Of 162 critical illness survivors, 33% (n = 53) of patients reported six-month QOL as better, 33% (n = 54) the same, and 34% (n = 55) worse. Abnormal cognition and inability to return to primary pastime or original place of residence (p < .05 for all) were associated with worse self-reported QOL at six months in multivariable regression. Predictions of patient perceptions of QOL at six months were pessimistic and had low discriminative accuracy for both physicians (sensitivity 56%, specificity 53%) and nurses (sensitivity 49%, specificity 57%). CONCLUSIONS: Among survivors of critical illness, one-third each reported their six-month post-ICU QOL as better, the same, or worse. Self-reported six-month QOL was associated with six-month function. ICU clinicians should use caution in predicting self-reported QOL, as discriminative accuracy was poor in this cohort.

Six-Month Morbidity and Mortality among Intensive Care Unit Patients Receiving Life-Sustaining Therapy. A Prospective Cohort Study.

RATIONALE: Understanding long-term outcomes of critically ill patients may inform shared decision-making in the intensive care unit (ICU). OBJECTIVES: To quantify 6-month functional outcomes of general ICU patients, and develop a multivariable model comprising factors present during the first ICU day to predict which patients will return to their baseline function 6 months later. METHODS: We conducted a prospective cohort study in three medical ICUs and two surgical ICUs in three hospitals. We enrolled patients who spent at least 3 days in the ICU and received mechanical ventilation for more than 48 hours and/or vasoactive infusions for more than 24 hours. RESULTS: We measured 6-month outcomes including survival, return to original place of residence, and physical and cognitive function. Of 303 enrolled patients, 299 (98.7%) had complete follow-up at 6 months. Among the 169 patients (56.5%) who survived to 6 months, 82.8% returned home, 81.9% were able to toilet, 71.3% were able to ambulate 10 stairs, and 62.4% reported normal cognition. Overall, 31.1% of patients returned to their baseline status on these measures. Factors associated with not returning to baseline included higher APACHE III score, being a medical patient, older age, nonwhite race, recent hospitalization, prior transplantation, and a history of cancer or of neurologic or liver disease. A model including only these Day 1 factors had good discrimination (area under receiver operating characteristic curve, 0.778; 95% confidence interval, 0.724-0.832) and calibration (difference between observed and expected P value, 0.36). CONCLUSIONS: Among patients spending at least 3 days in an ICU and requiring even brief periods of life-sustaining therapy, nearly one-half will be dead and less than one-third will have returned to their baseline status at 6 months. Of those who survive, the majority of patients will be back at home at 6 months. Future research is needed to validate this multivariable model, including readily available patient characteristics available on the first ICU day, that seems to identify patients who will return to baseline at 6 months.