Participants in the non-contact group will be monitored by anesthesia control tower clinicians who will utilize AlertWatch and integrating machine-learning forecasting algorithms for adverse outcomes predictions, but who will not contact the postoperative provider unless it is clinically necessary for patient safety purposes.

PACU and ward providers caring for participants in the brief contact group will be notified by Anesthesia Control Tower clinicians before arrival if the patient's forecast for mortality is in the top 15% of historical PACU patients. The notification will contain a brief summary of the patient's forecast risk of major adverse events.

PACU and ward providers caring for participants in the full contact group will be notified by Anesthesia Control Tower clinicians before arrival if the patient's forecast for mortality is in the top 15% of historical PACU patients. The notification will contain a report card of the patient's forecast risk of major adverse events, explanatory machine-learning outputs, most influential pre- and intraoperative data, and predicted treatments.

Real-time data will be monitored through the AlertWatch system as well as the electronic health record. Risk forecasts of adverse events (30 day mortality, acute kidney injury, postoperative delirium, respiratory failure), PACU length of stay, and hospital length of stay will be generated by a machine learning algorithm. Additional outputs identifying the most important predictors and their effects will be combined with risk forecasts to form a report card.

Admission to a "critical care" bed regardless of rationale or duration at any point in the follow up time frame. Patients who expire without transfer to ICU will be marked as positive.

Postoperative laboratory values and urine output will be used to calculate Kidney Disease Improving Global Outcomes grades of acute kidney injury. Where unavailable, baseline Glomerular filtration rate will be assumed to be age, sex, and body size normal.