Patent ID: 11880888
Assignee: THE FEINSTEIN INSTITUTES FOR MEDICAL RESEARCH
Field: Medical technology (Instruments)
Classification: CPC G | IPC G

Claim 0:
1. A method, comprising:
executing, by at least one processor of a plurality of backend computing devices, a claim document generator microservice and an adjudication microservice collocated in a scalable claim management platform;
wherein the scalable claim management platform, comprises at least one load balancer, and is configured to:
dynamically scale a number of backend computing devices based on data traffic assessed by the at least one load balancer so as to maximize computational and load efficiencies in the plurality of backend computing devices,
interact with a plurality of frontend computing devices comprising a plurality of provider computing devices associated with a plurality of providers and a plurality of payer computing devices associated with a plurality of payers through an application programming interface (API) layer comprising a plurality of APIs,
relay data associated with a plurality of patients between any of the plurality of provider computing devices and the claim document generator microservice, and
provide, for any of the plurality of provider computing devices and any of the plurality of payer computing devices via the API layer, a same access to a trusted medical knowledge database stored in a plurality of electronic resources that is trusted by the plurality of providers and the plurality of payers,

wherein the claim document generator microservice is programmed to:
receive a new patient indication from at least one first provider computing device from the plurality of provider computing devices associated with at least one first provider from the plurality of providers;
wherein the new patient indication indicates that at least one first patient from the plurality of patients requested at least one medical service associated with the at least one first provider;

generate a patient-specific data container object in response to the new patient indication;
wherein the patient-specific data container object comprises a plurality of patient-specific data elements associated with the at least one medical service provided to at least one first patient;

transmit over a communication network, at least one first API call to the trusted medical knowledge database stored on the plurality of electronic resources;
wherein the at least one first API call programs the trusted medical knowledge database to:
identify a first plurality of patient-specific medical-necessity information data objects associated with the at least one medical service provided to the at least one first patient, and
transmit the first plurality of patient-specific medical-necessity information data objects to the claim document generator microservice;

receive over the communication network, from the trusted medical knowledge database, the first plurality of patient-specific medical-necessity information data objects;
input the plurality of patient-specific data elements of the patient-specific data container object and the first plurality of patient-specific medical-necessity information data objects into a first machine learning engine that has been trained to predict:
a first plurality of reference claim document objects, and
a first medical-necessity score for each of the first plurality of reference claim document objects;

rank each of the first plurality of reference claim document objects using the first medical-necessity score to obtain a first ranked plurality of reference-claim document objects;
instruct the at least one first provider computing device to display on a graphic user interface (GUI), to at least one physician associated with the at least one first provider, the first ranked plurality of reference-claim document objects;
receive at least one chosen reference-claim document object from the first ranked plurality of reference-claim document objects chosen by the at least one physician through the GUI to justify providing the at least one medical service to the at least one first patient;
build a patient-specific service-specific-claim file object based at least in part on:
(i) the at least one chosen reference-claim document object, and
(ii) the plurality of patient-specific data elements of the patient-specific data container object;

store the patient-specific service-specific-claim file object in the patient-specific data container object; and
submit the patient-specific data container object to the adjudication microservice;

wherein the adjudication microservice is programmed to:
receive, from the claim document generator microservice, the patient-specific data container object associated with the at least one first patient having received the at least one medical service from the at least one first provider from the plurality of providers;
wherein the patient-specific data container object comprises:
(i) the patient-specific service-specific-claim file object, and
(ii) the plurality of patient-specific data elements associated with the at least one medical service provided to the at least one first patient;

transmit over the communication network, at least one second API call to the trusted medical knowledge database stored on the plurality of electronic resources;
wherein the at least one second API call programs the trusted medical knowledge database to:
identify a second plurality of patient-specific medical-necessity information data objects associated with the at least one medical service provided to the at least one first patient that exclude any patient-specific medical-necessity data objects associated with a medical-necessity justification by the at least one first provider for providing the at least one medical service to the at least one first patient, and
transmit the second plurality of patient-specific medical-necessity information data objects to the adjudication microservice;

receive over the communication network, from the trusted medical knowledge database, the second plurality of patient-specific medical-necessity information data objects;
input the plurality of patient-specific data elements of the patient-specific data container object and the second plurality of patient-specific medical-necessity information data objects into a second machine learning engine that has been trained to predict:
a second plurality of reference claim document objects, and
a second medical-necessity score, for each of the second plurality of reference claim document objects, that excludes any association with the medical-necessity justification by the at least one first provider;

rank each of the second plurality of reference claim document objects using the second medical-necessity score to obtain a second ranked plurality of reference-claim document objects;
assign a third medical-necessity score to the patient-specific service-specific-claim file object based on a comparison between the patient-specific service-specific-claim file object and the second ranked plurality of reference-claim document objects;
determine a payment determination based on one of:
(i) the patient-specific service-specific-claim file object is payment-rejected when the third medical-necessity score is lower than a predefined medical-necessity threshold score or
(ii) the patient-specific service-specific-claim file object is payment-approved when the third medical-necessity score is greater than the predefined medical-necessity threshold score;
send, when the patient-specific service-specific-claim file object is payment-approved, a payment request to a transactor to send a payment to an account of the at least one first provider for the at least one medical service provided to the at least one first patient based at least in part on the third medical-necessity score;
store in the patient-specific data container object at least:
(i) the second ranked plurality of reference-claim document objects,
(ii) a first data object comprising the third medical-necessity score, and
(iii) a second data object comprising the payment determination that the patient-specific service-specific-claim file object is payment-approved or payment-rejected; and

store the patient-specific data container object in a blockchain database.