Systems and Methods for Assessing Whether Medical Procedures Should Be Approved

Abstract

A rules engine that allows constructing and processing rules within a software application using protocol driven processing. A machine learning algorithm may be used to assess requested procedures that are initially rejected. The machine learning algorithm may also be saved periodically or at the time of each assessment and accessed at a later time.

What is claimed is: 
     
         1 . A system for assessing whether one or more medical procedures should be approved, comprising:
 a computer memory having a non-transitory machine-readable medium comprising machine-executable code recorded thereon, said machine-executable code comprising instructions for:
 processing medical data and a first set of clinical criteria using a first machine learning algorithm to generate a first output indicating whether a first medical procedure should be approved; 
 after generating the first output, saving a first state of the machine learning algorithm; 
 displaying on a computer screen an indication of whether the procedure is approved; 
 processing a second set clinical criteria using the machine learning algorithm to generate a second output indicating whether a second medical procedure should be approved, wherein the machine learning algorithm is converted from the first state to a second state; 
 after generating the second output indicating whether the second medical procedure should be approved, retrieving the first state of the machine learning algorithm; and 
 after retrieving the first state of the machine learning algorithm, processing a third set of clinical criteria using the machine learning algorithm in the second state to generate a third output indicating whether a second medical procedure should be approved. 
   
     
     
         2 . The system of  claim 1 , wherein the machine-executable code further comprises instructions for displaying on the computer screen one or more alternative procedures. 
     
     
         3 . The system of  claim 2 , wherein the medical data comprises one or more selected from the group consisting of a patient's age, a patient's gender, a patient's weight, a patient's height, and the number of times the procedure has been previously administered. 
     
     
         4 . The system of  claim 2 , wherein the machine learning algorithm is a neural network. 
     
     
         5 . The system of  claim 4 , wherein the medical data comprises one or more selected from the group consisting of a patient's age, a patient's gender, a patient's weight, a patient's height, and the number of times the procedure has been previously administered. 
     
     
         6 . The system of  claim 1 , wherein the medical data comprises one or more selected from the group consisting of a patient's age, a patient's gender, a patient's weight, a patient's height, and the number of times the procedure has been previously administered. 
     
     
         7 . The system of  claim 6 , wherein the machine learning algorithm is a neural network. 
     
     
         8 . A method for assessing whether one or more medical procedures should be approved, comprising:
 processing medical data and a first set of clinical criteria using a first machine learning algorithm to generate a first output indicating whether a first medical procedure should be approved;   after generating the first output, saving a first state of the machine learning algorithm;   displaying on a computer screen an indication of whether the procedure is approved;   receiving a second set of clinical criteria;   processing a second set clinical criteria using the machine learning algorithm to generate a second output indicating whether a second medical procedure should be approved, wherein the machine learning algorithm is converted from the first state to a second state;   after generating the second output indicating whether the second medical procedure should be approved, retrieving the first state of the machine learning algorithm; and   after retrieving the first state of the machine learning algorithm, process a third set of clinical criteria using the machine learning algorithm in the second state to generate a third output indicating whether a second medical procedure should be approved.   
     
     
         9 . The method of  claim 8 , further comprising displaying on the computer screen one or more alternative procedures. 
     
     
         10 . The method of  claim 9 , wherein the medical data comprises one or more selected from the group consisting of a patient's age, a patient's gender, a patient's weight, a patient's height, and the number of times the procedure has been previously administered. 
     
     
         11 . The method of  claim 9 , wherein the machine learning algorithm is a neural network. 
     
     
         12 . The method of  claim 11 , wherein the medical data comprises one or more selected from the group consisting of a patient's age, a patient's gender, a patient's weight, a patient's height, and the number of times the procedure has been previously administered. 
     
     
         13 . The method of  claim 8 , wherein the medical data comprises one or more selected from the group consisting of a patient's age, a patient's gender, a patient's weight, a patient's height, and the number of times the procedure has been previously administered. 
     
     
         14 . The method of  claim 13 , wherein the machine learning algorithm is a neural network. 
     
     
         15 . The system of  claim 1 , wherein the machine learning algorithm is a neural network. 
     
     
         16 . The method of  claim 8 , wherein the machine learning algorithm is a neural network. 
     
     
         17 . A system for assessing whether one or more medical procedures should be approved, comprising:
 a computer memory having a non-transitory machine-readable medium comprising machine-executable code recorded thereon, said machine-executable code comprising instructions for:
 processing medical data and a first set of clinical criteria using a first machine learning algorithm to generate a first output indicating whether a first medical procedure should be approved; 
 after generating the first output, saving a first state of the machine learning algorithm; 
 displaying on a computer screen an indication of whether the procedure is approved; 
 processing a second set clinical criteria using the machine learning algorithm to generate a second output indicating whether a second medical procedure should be approved, wherein the machine learning algorithm is converted from the first state to a second state; 
 after generating the second output, saving the second state of the machine learning algorithm and retrieving the first state of the machine learning algorithm; 
 receiving a third set of clinical criteria; 
 processing a third set clinical criteria using the machine learning algorithm to generate a third output indicating whether a third medical procedure should be approved, wherein the machine learning algorithm is converted from the second state to a third state; 
 after generating the third output, retrieving the first state of the machine learning algorithm. 
   
     
     
         18 . The system of  claim 17 , wherein the machine-executable code further comprises instructions for displaying on the computer screen one or more alternative procedures. 
     
     
         19 . The system of  claim 17 , wherein the medical data comprises one or more selected from the group consisting of a patient's age, a patient's gender, a patient's weight, a patient's height, and the number of times the procedure has been previously administered. 
     
     
         20 . The system of  claim 17 , wherein the machine learning algorithm is a neural network.