Patent ID: 11942215
Assignee: MOTIVE MEDICAL INTELLIGENCE
Field: Medical technology (Instruments)
Classification: CPC G | IPC G

Claim 20:
21. A non-transitory computer-readable storage medium having embodied thereon instructions, which when executed by a processor, perform steps of a method, the method comprising:
training a deep neural network, the deep neural network trained by an evidence engine with evidentiary support including medical journals, health studies, clinical guidelines, or standards bodies, the deep neural network;
receiving, by a first input node, physician-directed health care service data for a previous stress test as coded and unstructured narrative text, the first input node configured to adjust for a factor lacking in claims data including undocumented comorbidities, hedging in diagnostic uncertainty, strength of clinical support, ulterior motives, defensive medicine, a presence for each factor equating to incremental statistical variability that is calculated to a sum, added to a statistical range of better practice and results in an adjusted range of better practice;
receiving, by a second input node, a set of metrics associated with appropriateness of a stress test;
configuring a plurality of intermediary deep neural network nodes, the plurality of intermediary deep neural network nodes having a weight, bias and threshold directing an analysis of the deep neural network on physician-directed health care service data for the stress test;
generating, by a secure intelligent networked engine having the deep neural network, a first output node comprising a knowledge narrative representing a plain-text description of an appropriateness measure for the stress test and a range of better practice comprising limits of the appropriateness measure, where an appropriateness measures score exceeds an upper limit in a case of overuse of a service, or is below a lower limit in a case of underuse of a service that results from operation of the deep neural network on input elements;
generating, by the secure intelligent networked engine having the deep neural network, a second output node generating a second output that comprises a rate of inappropriateness of the stress test, the inappropriateness having a numerator representing a number of stress tests with nuclear imaging that occurred within thirty days of an evaluation and management visit to a cardiologist and having a denominator representing stress testing that occurred within thirty days of the evaluation and management visit to the cardiologist, excluding cases with inpatients, outpatients with symptoms of acute coronary syndrome or patients who had a cardiac-related emergency department visit within a thirty day period;
generating a dynamic feedback communicatively coupling the knowledge narrative and range of better practice node and the rate of inappropriateness of the stress test for a specific health care service for continuous learning of the deep neural network;
generating a third output node comprising the appropriateness measures score for cardiovascular stress testing; and
generating a fourth output node comprising a cumulative appropriateness practice score to reflect a physician's performance across multiple measures or practice areas.