Patent ID: 11923075
Assignee: THE RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK
Field: Medical technology (Instruments)
Classification: CPC G | IPC G

Claim 6:
7. A method of determining physician attribution among a plurality of physicians related to in-patient care of a patient, the method comprising a processing device that executes operations comprising:
receiving a plurality of sets of physician treatment notes related to the in-patient care of the patient, each set of the plurality of sets of physician treatment notes associated with a respective physician of the plurality of physicians;
assigning a feature vector to each physician of the plurality of physicians, the feature vector including assignment of a plurality of feature values, each feature value of the plurality of feature values being associated with a different type of physician treatment note and indicating a number of issued physician treatment notes of the different type, indicative of clinical progress of the patient at various stages of the in-patient care;
automatically determining a weight vector for each feature vector, the weight vector including determination of a plurality of predicted feature weights associated with respective plurality of feature values using machine learning analysis, each predicted feature weight of the plurality of predicted feature weights indicating a level of priority associated with the type of physician treatment note of a respective feature value, the level of priority being different for each of the plurality of predicted feature weights, wherein the machine learning analysis that determines the predicted feature weights is based on a training data set of patients, physicians, and associated physician treatment notes related to providing in-patient care to the patients;
computing an attribution score for each physician of the plurality of physicians based on the feature values of the feature vector and the predicted feature weights of the weight vector associated with the physician; and
generating a clinical representation on a user interface, the clinical representation displaying a plurality of attribution scores of the plurality of physicians to the in-patient care of the patient, and identifying a physician with a highest attribution score from the plurality of attribution scores as an attributed physician predicted to be most responsible for the in-patient care of the patient.