COMPUTATIONAL MEDICAL TREATMENT PLAN METHOD AND SYSTEM WITH MASS MEDICAL ANALYSIS

• US 20150339442A1
• Filed: 06/03/2015
• Published: 11/26/2015
• Est. Priority Date: 12/04/2013
• Status: Active Application

• Current Assignee: MBL Company Limited (Mbl Denmark A/S)
• Original Assignee: Mark Oleynik
• Inventors: OLEYNIK, Mark
• Application Number:
  US14/730,144
• Publication Number:
  US 20150339442A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients
• CPC Class Codes: Y02A 90/10 Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

The present disclosure is directed toward global medical data analysis methods, systems, and computer program products for analyzing, classifying, and matching mass amounts of medical information from many sources and across different regions. The global medical data analysis system includes a medical main server that contains an intelligent medical engine, which is communicatively coupled to a central database, a confidential electronic medical records database, and further communicatively coupled through a network to hospitals, clinics, and other medical sources. The intelligent medical engine receives voluminous medical record, potentially from different countries, regions, and continents. Electronic Medical records are sourced from hospitals, clinics, and other medical sources, which are fed into the intelligent medical engine for large-scale analysis and correlation of patients'"'"' medical records globally. The analysis starts by degrouping (classifying) medical records into multiple levels of subgroups according to patient clinical parameters, disease templates, treatments and outcomes. When a new patient enters the system, that patient'"'"'s parameters and disease template are matched against the closest subgroups to suggest treatments with potentially favorable outcomes.

Claims

1. A computer-implemented method for processing electronic medical records, comprising:

storing a plurality of objective medical data for a plurality of patients, each patient'"'"'s objective medical data being structured into multiple elements for use in storing the objective medical data, each patient'"'"'s objective medical data containing at least parameters of the patient, diseases of the patients, treatments that the patient underwent and outcomes of the treatments;

degrouping the plurality of patients'"'"' objective medical data to classify the plurality of objective medical data into subgroups, the classifying step including at least one level of classifications based on each patient'"'"'s parameters, disease, and treatment that each patient underwent for the disease, and the outcome of the treatment, iteratively repeating the process, once for each subgroup in each level, until a set of subgroups smaller than the previously generated subgroups are identified wherein the patients in the smaller subgroups have substantially similar clinically-relevant parameters and substantially similar outcomes;

receiving a new patient'"'"'s disease template with the new patient'"'"'s objective medical data based on the patient'"'"'s disease, the new patient'"'"'s template including at least the clinically-relevant parameters of the new patient, and at least one disease of the new patient; and

matching the new patient'"'"'s parameters and disease to the corresponding parameters and disease of the degrouped subgroups

selecting an effective treatment protocol based on the associated disease of the degrouped subgroups wherein the selected treatment protocol is the shortest treatment protocol.