Predictive modeling of respiratory disease risk and events

Abstract

An application server predicts respiratory disease risk, rescue medication usage, exacerbation, and healthcare utilization using trained predictive models. The application server includes model modules and submodel modules, which communicate with a database server, data sources, and client devices. The submodel modules train submodels by determining submodel coefficients based on training data from the database server. The submodel modules further determine statistical analysis data and estimates for medication usage events, healthcare utilization, and other related events. The model modules combine submodels to predict respiratory disease risk, exacerbation, rescue medication usage, healthcare utilization, and other related information. Model outputs are provided to users, including patients, providers, healthcare companies, electronic health record systems, real estate companies and other interested parties.

What is claimed is: 
     
         1 . A method comprising:
 accessing a respiratory disease risk model comprising a logistic regression function trained to predict a respiratory disease risk for a geographic region based on an impact of environmental measurements within the geographic region on an expected incident of medication usage events for a user within the geographic region, the respiratory disease risk model trained using a dataset of geographic regions, wherein each geographic region of the training dataset is associated with one or more environmental parameters and is labeled with an expected incidence of medication usage events and a respiratory disease risk;   generating a respiratory disease risk for a given geographic region by inputting one or more environmental measurements for the given geographic region to the respiratory disease risk model; and   sending a respiratory disease risk notification to a computing device associated with a user in the geographic region including the respiratory disease risk and the expected incidence of medication usage events for the given geographic region.