An evaluation of physician predictions of discharge on a general medicine service

Abstract

The goal of this study was to evaluate general medicine physicians' ability to predict hospital discharge. We prospectively asked study subjects to predict whether each patient under their care would be discharged on the next day, on the same day, or neither. Discharge predictions were recorded at 3 time points: mornings (7-9 am), midday (12-2 pm), or afternoons (5-7 pm), for a total of 2641 predictions. For predictions of next-day discharge, the sensitivity (SN) and positive predictive value (PPV) were lowest in the morning (27% and 33%, respectively), but increased by the afternoon (SN 67%, PPV 69%). Similarly, for same-day discharge predictions, SN and PPV were highest at midday (88% and 79%, respectively). We found that although physicians have difficulty predicting next-day discharges in the morning prior to the day of expected discharge, their ability to correctly predict discharges continually improved as the time to actual discharge decreased. Journal of Hospital Medicine 2015;10:808-810. © 2015 Society of Hospital Medicine.

Ready to Go Home? Assessment of Shared Mental Models of the Patient and Discharging Team Regarding Readiness for Hospital Discharge

“…The potential importance of this disagreement is substantiated by prior work suggesting that divergence in readiness ratings between nurses and patients are associated with postdischarge coping difficulties. 28 Previous readiness for discharge has been measured from the perspective of the patient, 20,21,27,28 nurse, 20,[25][26][27][28] and physician, 37 yet rarely has the teams' perspective been examined. We add to this literature by measuring the team's perspective, as well as agreement between team and patient, on the individual patient's readiness for discharge.…”

Application of Predictive Modelling to Improve the Discharge Process in Hospitals

“…This study was carried out with the intention to predict the discharge process TAT so as to coordinate better services for patients and patient's family or caregivers on the final day of their hospital stay, which will leave them with a lasting impression of the hospital. Although many studies have explored the benefits of predicting the time of discharge from the length-of-stay (LOS) point of view, very little research has been done on prediction of the TAT for the discharge process [9][10][11]. Consequently, the effectiveness and benefits of this type of prediction mechanism has not been studied in detail.…”

Physician predictions of length of stay of patients admitted with heart failure

“…Physician predictions of length of stay have been found to be inaccurate in a center's oncologic intensive care unit population . Sullivan et al found that academic general medicine physicians predicted discharge with 27% sensitivity the morning prior to next‐day discharge, which improved significantly to 67% by the afternoon, concluding that physicians can provide meaningful discharge predictions the afternoon prior to next‐day discharge . By focusing on patients with heart failure, a major driver of hospitalization and readmission, and comparing providers by level of experience, we augment this existing body of work.…”

“…Physicians are not able to accurately prognosticate whether patients will experience short‐term outcomes such as readmissions or mortality . Likewise, physicians do not predict length of stay accurately for heterogeneous patient populations, even on the morning prior to anticipated discharge . Prediction accuracy for patients admitted with heart failure, however, has not been adequately studied.…”