Patent Document ID: 20160350492
Application ID: 15233564
Patent Flag: 0

Claim One:
1. A method for identifying a patient as a candidate for a specific treatment, comprising interactions between a medical care provider, a computer containing a processor comprising a first clinical outcome tracking and analysis module, a client device comprising a second clinical outcome tracking and analysis module that is communicatively linked to the first clinical outcome tracking and analysis module via a network, and a medical professional user in need of the patient candidate, the method comprising: (a) executing on the processor comprising the first clinical outcome tracking and analysis module the steps of: A) accounting for biological variance up-front by grouping patients in a patient population by: (i) Receiving, collecting and recording in a database personal health information from each patient in the patient population, the personal health information comprising each parameter that characterizes each patient in the patient population; (ii) sorting the personal health information for each patient in the patient population using a sorting filter, (i) to provide a sorted set of personal health information for that population, and (ii) to identify patients satisfying each parameter in the patient population; (iii) classifying like personal health information, and grouping types of patients in the patient population, based on the personal health information associated with the patient population by generating and assigning a plurality of nodal addresses within the first clinical outcome tracking and analysis module, wherein the generating and assigning said plurality of nodal addresses comprises: (1) Representing each nodal address as a discrete punctuated string of digits comprising a prefix, a middle, and a suffix that represent a set of preselected variables that partition the sorted and classified information into a clinically relevant set of health information; (2) Reducing trillions of possible permutations to a reduced number of clinically meaningful permutations based on the discrete punctuated string of digits representing each nodal address that enable analysis of first behavioral and then consequent clinical and cost outcome variance from an ideal value, expressed as best clinical outcome at lowest possible cost, in a requisite time needed to alert for necessary care and avoidance of unnecessary care, thereby increasing the value of care, meaning better clinical outcomes at a lowest possible cost; (3) allowing the user (a′) to identify certain of the personal health information as a desired set of characteristics, and (b′) to add one or more attribute(s) to the personal health information to identify the personal health information of each patient as being on an equal level of importance to other health information in the patient population database, (4) reducing processing requirements and time for processing to make real-time monitoring of medical provider performance efficient based on the discrete punctuated string of digits representing each nodal address and based on the reduction in permutations; and (5) enabling prediction of key points in time for alerting a medical professional with respect to a specific patient that is a good candidate for the desired treatment; B. identifying the specific patient as a candidate for the desired treatment for each nodal address by: analyzing the clinically relevant set of personal health information for the subset of the patient population for one or more patients in the subset of the patient population; C. the first clinical outcome and tracking analysis module communicating an alert over the network to the client device comprising the second clinical outcome tracking and analysis module that enables the medical professional user to access the sorted nodal address data records to precisely identify the specific patient for which the medical professional is searching; (b). the medical professional user of the client device being able to assess the benefits of the specific treatment for a defined patient population at the lowest possible cost.