MULTICOMMODITY SYSTEM AND METHOD FOR CALCULATING MARKET DYNAMICS IN HEALTH NETWORKS SYSTEMS
A multi-commodity system and method for calculating market dynamics in health network systems are disclosed. The system and method may incorporate a process that computes the influence of several transactional based entities within a business based health architecture. The system and method may: (1) calculate the diffusion of information theoretic data, (2) compute the influencers in each of the area of business driven health sectors and (3) optimize entity matching likelihoods across health network silos.
1 . An apparatus, comprising:
a processor and a memory;
the processor being configured to receive a plurality of health inputs, the plurality of health inputs associated with a plurality of health entities;
the processor being configured to calculate for each entity, an entity ranking within each homogeneous system using the plurality of health inputs associated with the plurality of health entities; and
the processor being configured to model a commodity flow for each health entity based on the ranking for each health entity.
2 . The apparatus of claim 1 further comprising the processor being configured to generate one or more outputs based on the modeled commodity flow, the outputs being one of a market prediction, a partnership matching, a targeted market segmentation and a recommendation.
3 . The apparatus of claim 1 , wherein the processor being configured to calculate the entity ranking for each entity calculates the entity ranking for each entity using V ⊂ {P α ,P r ,C,S,T} where P A represents one or more payors, P r represented one or more providers, C represents one or more consumers, S represents one or more services and T represents one or more transactions observed within the healthcare network.
4 . The apparatus of claim 1 , wherein each health input is a graph schema for each homogeneous system.
5 . The apparatus of claim 4 , wherein each homogeneous system is one of a provider network, a consumer network, a service network and a transaction network.
6 . The apparatus of claim 1 , wherein the processor being configured to calculate the entity ranks further comprises the processor being configured to diffuse the health inputs to generate the entity ranks.
7 . The apparatus of claim 1 , wherein the processor being configured to model a commodity flow further comprises the processor being configured to determine a maximum network capacity for each health entity.
8 . The apparatus of claim 7 , wherein the processor being configured to model a commodity flow further comprises the processor being configured to estimate a hetoergeneous system connectivity for each health entity.
9 . A method, comprising:
receiving a plurality of health inputs, the plurality of health inputs associated with a plurality of health entities;
calculating, for each entity, an entity ranking within each homogeneous system using the plurality of health inputs associated with the plurality of health entities; and
modeling a commodity flow for each health entity based on the ranking for each health entity.
10 . The method of claim 9 further comprising generating one or more outputs based on the modeled commodity flow, the outputs being one of a market predictions, a partnership matching, a targeted market segmentation and a recommendation.
11 . The method of claim 9 , wherein calculating the entity ranking for each entity further comprises calculating the entity ranking for each entity using V ⊂ {P α ,P r ,C,S,T} where P A represents one or more payors, P r represented one or more providers, C represents one or more consumers, S represents one or more services and T represents one or more transactions observed within the healthcare network.
12 . The method of claim 9 , wherein each health input is a graph schema for each homogeneous system.
13 . The method of claim 12 , wherein each homogeneous system is one of a provider network, a consumer network, a service network and a transaction network.
14 . The method of claim 9 , wherein calculating the entity ranks further comprises diffusing the health inputs to generate the entity ranks.
15 . The method of claim 9 , wherein modeling the commodity flow further comprises determining a maximum network capacity for each health entity.
16 . The method of claim 15 , wherein modeling the commodity flow further comprises estimating a hetoergeneous system connectivity for each health entity.