Opioid Use Disorder Predictor

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,...

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Bibliographische Detailangaben
Hauptverfasser:	Jarrett, Lindsey Gay, Khotilovich, Vadim, Barbre, Megan, Lindsey, Leslie, Staples, Alan, Martin, Jennifer, Lovejoy, Bennett
Format:	Patent
Sprache:	eng
Schlagworte:	ADVERTISING APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND,DEAF OR MUTE CALCULATING COMPUTING COUNTING CRYPTOGRAPHY DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES DIAGNOSIS DIAGRAMS DISPLAY EDUCATION EDUCATIONAL OR DEMONSTRATION APPLIANCES GLOBES HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA HUMAN NECESSITIES HYGIENE IDENTIFICATION INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS MEDICAL OR VETERINARY SCIENCE PHYSICS PLANETARIA SEALS SURGERY SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
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Beschreibung
Zusammenfassung:	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. The predicted opioid use disorder risk for the patient is provided within the patient chart over the predetermined period of time and may include details corresponding to risk factors specific to the patient and risk mitigation options.