Abstract: Technologies are provided for leveraging machine learning to predict the likelihood of near-future OUD for patients presenting in an emergency department. A model is trained with data corresponding to one or more of: gender, age, prior opioid use disorder diagnosis, prior opioid use disorder events, prior opioids, prior emergency department encounters, prior inpatient encounters, other medications, drug screening tests, hepatitis C tests, tobacco use questionnaires, prior results from medical tests, social history questionnaires, or other diagnoses to predict opioid use disorder risk for a population of patients. Upon receiving information available at an emergency department triage for a patient, the trained model is utilized to predict the opioid use disorder risk for the patient over a predetermined period of time.

Abstract: Methods, systems, and computer-readable media are disclosed herein for predicting medication induced respiratory depression in patients. Herein, when indications are received for particular events being logged to a computerized clinical workflow, a query of patient's clinical record(s) is preformed to locate predetermined factors that are associated with medication induced respiratory depression. An overall value is calculated to stratify the possibility of adverse respiratory events for the patient. Warnings, detailed intervention instructions, and complete medical orders can be automatically generated and provided to a clinician and/or automatically input to the clinical workflow of the patient for performance.

Abstract: A method includes receiving a request to initiate a group gift indicating a gift date on which the group gift should be sent to a receiver of the gift. The method further includes determining, electronic devices to send invitations to contribute to the group gift and sending the invitations to the electronic devices. The invitations prompt a user to respond with a single action whether the user would like to contribute or not. The method further includes receiving responses from the electronic devices indicating an approval to contribute to the group gift or a refusal to contribute to the group gift. The method further includes initiating a physical gift purchase as part of the group gift and sending a message to a gift receiver electronic device that includes information about a monetary gift.

Abstract: A method includes receiving a request to initiate a group gift indicating a gift date on which the group gift should be sent to a receiver of the gift. The method further includes determining, electronic devices to send invitations to contribute to the group gift and sending the invitations to the electronic devices. The invitations prompt a user to respond with a single action whether the user would like to contribute or not. The method further includes receiving responses from the electronic devices indicating an approval to contribute to the group gift or a refusal to contribute to the group gift. The method further includes initiating a physical gift purchase as part of the group gift and sending a message to a gift receiver electronic device that includes information about a monetary gift.

Abstract: A method includes receiving a request to initiate a group gift indicating a gift date on which the group gift should be sent to a receiver of the gift. The method further includes determining, electronic devices to send invitations to contribute to the group gift and sending the invitations to the electronic devices. The invitations prompt a user to respond with a single action whether the user would like to contribute or not. The method further includes receiving responses from the electronic devices indicating an approval to contribute to the group gift or a refusal to contribute to the group gift. The method further includes initiating a physical gift purchase as part of the group gift and sending a message to a gift receiver electronic device that includes information about a monetary gift.

Abstract: Methods, computer systems, and computer-storage medium are provided for providing an emergency department centralized interactive display. A segmentable summary of patients within an ED allows a clinician to view a specific area within the ED or a summary of patients assigned to the clinician including unassigned patients sorted by acuity and length of stay. A throughput summary for a patient indicates throughput and whether actions are pending for the patient. A patient summary for the patient that includes information collected at triage, links to documentation from previous visits, care plans, a do not resuscitate order, home medications, and/or history. A provider summary provides information regarding providers for the patient and allows the clinician to designate an attending physician to the patient. In various embodiments, additional summary information is provided giving the ED clinician an efficient one-stop shop for performing ED duties.