Systems and methods for managing health treatment

A computer implemented method for managing healthcare diagnosis and treatment, comprising:

• creating on a workflow engine at least one triggerable workflow comprising at least one rule;
• communicating bi-directionally through an interface with at least one of:
• a patient, a provider, an electronic health records system, electronic medical records system, an external application, an external data source, and a machine learning engine;
• performing with the machine learning engine:
• processing an input comprising at least one of a data source, a variable, and a rule;
• recognizing at least one pattern among the input;
• and
• generating an output comprising an assignment of a probability relative to the input;
• determining an appropriate test based on the output of the machine learning engine;
• ordering the test;
• and/or
• administering the test to the patient;
• processing the test results;
• and
• transmitting the test results.

A non-transitory computer-readable medium storing instructions that, when executed by one or more processors of a healthcare diagnosis and treatment management system, causes the healthcare diagnosis and treatment management system to:

• monitor at least one data source for a workflow trigger comprising at least one of an order, a test result, an appointment, a patient demographic, a patient status, a patient history, a patient communication, and a condition;
• trigger a workflow upon the detection of a workflow trigger, wherein the workflow comprises:
• a first decision-making layer configured to manage at least one of a rule, a patient test, and a patient communication;
• a second decision-making layer configured to manage at least one workflow, wherein the workflow comprises at least one rule;
• and
• a third decision-making layer configured to manage at least one machine learning model, wherein the machine learning model is configured to process data relevant to the workflow and to determine a probability of a condition to be tested;
• wherein the three decision-making layers are configured to communicate among one another and with external resources;
• execute the steps of the workflow to analyze data relating to a patient and to determine an appropriate test for the patient, wherein the appropriateness of the test is determined with the assistance of the machine learning model;
• order the test for the patient;
• and/or
• administer the test to the patient;
• process the results of the test;
• and
• transmit the results of the test.

A non-transitory computer-readable medium storing instructions that, when executed by one or more processors of a healthcare diagnosis and treatment management system, causes the healthcare diagnosis and treatment management system to:

• create on a workflow engine at least one triggerable workflow comprising at least one rule;
• communicate bi-directionally through an interface with at least one of:
• a patient, a provider, an electronic health records system, electronic medical records system, an external application, an external data source, or a machine learning engine;
• perform with the machine learning engine:
• processing an input comprising at least one of a data source, a variable, and a rule;
• recognizing at least one pattern among the input;
• and
• generating an output comprising an assignment of a probability relative to the input;
• determine an appropriate test based on the output of the machine learning engine;
• order the test;
• and/or
• administer the test to the patient;
• process the test results;
• and
• transmit the test results.