Systems and methods to process a healthcare transaction in a heterogeneous environment comprised of mainframe and cloud based systems in real-time

A system for processing healthcare transactions, the system comprising:

• a healthcare transaction splitter configured to:
• receive data associated with a healthcare transaction;
• provide first data of the healthcare transaction to a cloud computing platform;
• and
• provide second data of the healthcare transaction to a mainframe platform;
• a cloud computing platform that includes at least a first processor and at least a first memory including instructions that, when executed by the first processor, cause the first processor to:
• generate, using an attribute engine on the cloud computing device and using historical requests for healthcare services, a machine learning model configured to generate one or more predictions indicating associations between healthcare attributes;
• train, based on healthcare attributes associated with healthcare services, the machine learning model that generates one or more predictions indicating associations between the healthcare attributes;
• receive a request for coverage of a healthcare service under a health insurance plan, wherein the request for coverage is associated with the healthcare transaction and corresponds to a member;
• determine a first healthcare attribute and a second healthcare attribute associated with the healthcare service based on at least the first data, wherein determining the first healthcare attribute and the second healthcare attribute includes:
• providing the request for coverage of the healthcare service to the machine learning model;
• and
• receiving, from the machine learning model, an indication of the first healthcare attribute and the second healthcare attribute;
• and
• store the first healthcare attribute and the second healthcare attribute;
• and
• the mainframe platform comprising a second processor and a second memory including instructions that, when executed by the second processor, cause the second processor to:
• receive the request for coverage of the healthcare service under the health insurance plan, wherein the request for coverage is associated with the healthcare transaction;
• determine eligibility of the member under the health insurance plan;
• in response to determining that the member is eligible under the health insurance plan, determine, based on at least the second data, if the healthcare service is covered by the health insurance plan;
• in response to determining if the healthcare service is covered by the health insurance plan, receive the first healthcare attribute and the second healthcare attribute;
• and
• in response to a value associated with the first healthcare attribute being greater than a value associated with the second healthcare attribute, generate a response to the request for coverage of the healthcare service under the health insurance plan indicating the value associated with the second healthcare attribute;
• and
• subsequently train, by the attribute engine on the cloud computing platform, the machine learning model using a k-nearest neighbor algorithm and based on identified associations (i) between the first healthcare attribute and the second healthcare attribute, and (ii) between at least one other healthcare attribute and at least one of the first healthcare attribute and the second healthcare attribute, wherein the attribute engine outputs the subsequently trained machine learning model.