SIMULATION OF HEALTH STATES AND NEED FOR FUTURE MEDICAL SERVICES
Systems and methods are provided for simulating a patient health state by determining one or more relationships within patient data, creating enriched data elements based on the determined relationships, and using a machine learning module to simulate a future health state of the patient and predict a future medical service need.
1 . A method for predicting a future health state, the method comprising:
ingesting healthcare data of a patient received from one of a plurality of patient data providers;
transmitting the ingested healthcare data to a data store;
transmitting the data store to a machine learning module, wherein the machine learning module applies at least one algorithm selected from the set comprising transformation algorithms, normalization operations, and refinement operations; and
using the machine learning module to predict a needed future treatment for the patient based on a predicted future health state for the patient.
2 . The method of claim 1 , wherein the healthcare data derives from an electronic medical record.
3 . The method of claim 1 , wherein the healthcare data derives from a pharmacy database.
4 . The method of claim 1 , wherein the healthcare data derives from a laboratory database.
5 . The method of claim 1 , wherein the healthcare data derives from an insurer database.
6 . The method of claim 1 , wherein the healthcare data derives from a physician's database.
7 . The method of claim 1 , wherein the machine learning module is configured to train a machine learned model that is leveraged by a test management system.
8 . The method of claim 1 , wherein the machine learning module is configured to train a machine learned model that is leveraged by a prescription monitoring system.
9 . The method of claim 1 , wherein the machine learning module is configured to train a machine learned neural network model.
10 . The method of claim 9 , wherein the machine learned neural network model is a recurrent neural network model.
11 . The method of claim 1 , wherein the machine learning module is configured to train a Bayesian model.
12 . The method of claim 1 , wherein the machine learning module is configured to train an artificial intelligence system.
13 . The method of claim 1 , wherein the machine learning module is configured to train a rules-based recommendation system.
14 . The method of claim 13 , wherein the rules-based recommendation system includes rules for determining the appropriateness of a treatment.
15 . The method of claim 14 , wherein the treatment is a prescription medication.
16 . The method of claim 13 , wherein the configuration of the machine learning module to train a rules-based recommendation system includes using training data from a prescription medication data set.
17 . The method of claim 13 , wherein the configuration of the machine learning module to train a rules-based recommendation system includes using training data from a prescription medication data set.
18 . The method of claim 13 , wherein the configuration of the machine learning module to train a rules-based recommendation system includes using training data from a patient outcomes data set.
19 . A method for determining a medical service need, the method comprising:
ingesting, by a computing device, patient data of a patient received from one of a plurality of patient data providers;
transmitting the ingested data to a data store;
transmitting the data store to a machine learning module, wherein the machine learning module wherein applies at least one algorithm selected from the set comprising transformation algorithms, normalization operations, and refinement operations; and
using the machine learning module to simulate a future health state for the patient;
matching the simulated future health state to a predicted patient medical service need;
matching the predicted patient medical service need to at least one of the patient's healthcare providers; and
transmitting an alert to the at least one healthcare provider indicating the predicted patient medical service need.
20 . The method of claim 19 , wherein the machine learning simulation uses a digital twin of the patient.