Modeling and benchmarking health care affordability and availability

A method for modeling health care affordability and health care availability across a population of individuals, the method comprising:

• modeling the health care affordability by
• obtaining, by processing circuitry, historic claims data representing populations of a plurality of entities and demographic information of the populations of the plurality of entities,
• determining, by the processing circuitry, chronic conditions of the populations of the plurality of entities,
• using the historic claims data, the demographic information of the populations of the plurality of entities, and the chronic conditions of the populations of the plurality of entities, training one or more utilization machine learning models to estimate usage of a plurality of medical plan features in view of a plurality of chronic conditions,
• determining, by the processing circuitry, census data regarding the population of individuals, the census data comprising, for each individual, an age or an age range, a gender, and a geographic location,
• determining, by the processing circuitry, an income level distribution across the population of individuals,
• using the census data, segmenting, by the processing circuitry, the population of individuals into a plurality of census divisions, the plurality of census divisions comprising, for each respective demographic category of a plurality of demographic categories, a respective division within the respective demographic category,
• for each chronic condition of the plurality of chronic conditions, determining, by the processing circuitry, a respective estimated chronic condition distribution among the plurality of census divisions,
• providing, to the one or more utilization machine learning models, the plurality of census divisions of the population of individuals and the respective estimated chronic condition distribution for each chronic condition of the plurality of chronic conditions, wherein the one or more utilization machine learning models are configured to model, for each respective census division of the plurality of census divisions, a respective estimated utilization of the plurality of medical plan features for a subset of the population of individuals belonging to the respective census division as a distribution of usage of each respective plan feature of the plurality of medical plan features,
• for each respective medical plan feature of the plurality of medical plan features, determining, by the processing circuitry, at least one unit cost of the respective medical plan feature, wherein the unit cost represents an estimated out-of-pocket cost to at least a portion of the population,
• by the processing circuitry, using the unit costs of the plurality of medical plan features and the distribution of usage of each respective plan feature of the plurality of medical plan features, calculating a plurality of estimated costs comprising, for each respective census division of the plurality of census divisions, at least one respective estimated cost to a portion of the population of individuals belonging to the respective census division, and
• using the income level distribution, calculating, by the processing circuitry based at least in part on the plurality of estimated costs, at least one set of metrics representing relative affordability;
• using the geographic location of the census data for each member of the population of individuals, modeling the health care availability by calculating, by the processing circuitry, at least one distribution of health provider shortages for the population of individuals;
• and
• preparing, by the processing circuitry for presentation via a graphical user interface, a presentation comprising the at least one set of metrics and the at least one distribution of health provider shortages.