MULTIVARIATE COMPUTATIONAL SYSTEM AND METHOD FOR OPTIMAL HEALTHCARE SERVICE PRICING
A multivariate computational system and method for optimal healthcare service pricing are disclosed. The system and method may use a computational process that integrates arbitrary sources of healthcare service price and quality information into a model. The model adapts over time such that it determines the optimal price for individual or aggregate healthcare service queries based on regional and temporal adjustments, as well as any of a number of service quality metrics.
1 . An apparatus for optimal healthcare service pricing, comprising:
a computer having a processor;
the computer having a pricing model store that is configured to store a plurality of pricing models for a healthcare service; and
the computer having a pricing model adjusting engine that is configured to adjust a pricing model stored in the pricing model store, the pricing model adjusting engine being configured to adjust a pricing model based on one or more external healthcare pricing sources and a quality score of each provider of a particular healthcare service.
2 . The apparatus of claim 1 , wherein the pricing model adjusting engine is configured to adjust the pricing model using a scaling factor.
3 . The apparatus of claim 2 , wherein the scaling factor is a non-linear scaling factor.
4 . The apparatus of claim 3 , wherein the non-linear scaling factor further comprises one of a logistic scaling factor, a gamma scaling factor and a polynomial scaling factor.
5 . The apparatus of claim 2 , wherein the scaling factor is a linear scaling factor.
6 . The apparatus of claim 1 , wherein the quality score for each provider further comprises a multivariate estimator of provider quality.
7 . The apparatus of claim 6 , wherein the quality score for each provider further comprises a provider efficiency score, a provider reputation score and a legal score.
8 . The apparatus of claim 1 further comprising a provider store that stores a plurality of providers for the particular healthcare service in a sparse matrix.
9 . The apparatus of claim 8 , wherein the sparse matrix has a triple for each provider.
10 . The apparatus of claim 1 further comprising one or more computing devices, wherein each computing device is configured to interface with the computer to receive one or more pricing estimates for the particular particular healthcare service.
11 . The apparatus of claim 1 , wherein the one or more external healthcare pricing sources further comprise one of more of health insurance claims data, federal, state and local government healthcare service agencies and price information scraped from websites.
12 . The apparatus of claim 1 , wherein the one or more external healthcare pricing sources further comprise one of more of customer or peer review data and patient outcome data.
13 . A method for optimal healthcare service pricing, comprising:
storing, in a computing having a pricing model store, a plurality of pricing models for a healthcare service;
adjusting, by a pricing model adjusting engine of the computer, a pricing model stored in the pricing model store; and
wherein the pricing model is adjusted based on one or more external healthcare pricing sources and a quality score of each provider of a particular healthcare service.
14 . The method of claim 13 , wherein adjusting the pricing model further comprises adjusting the pricing model using a scaling factor.
15 . The method of claim 14 , wherein the scaling factor is a non-linear scaling factor.
16 . The method of claim 15 , wherein the non-linear scaling factor further comprises one of a logistic scaling factor, a gamma scaling factor and a polynomial scaling factor.
17 . The method of claim 14 , wherein the scaling factor is a linear scaling factor.
18 . The method of claim 13 , wherein the quality score for each provider further comprises a multivariate estimator of provider quality.
19 . The method of claim 18 , wherein the quality score for each provider further comprises a provider efficiency score, a provider reputation score and a legal score.
20 . The method of claim 13 further comprising storing a plurality of providers for the particular healthcare service in a sparse matrix.
21 . The method of claim 20 , wherein the sparse matrix has a triple for each provider.
22 . The method of claim 13 , wherein the one or more external healthcare pricing sources further comprise one of more of health insurance claims data, federal, state and local government healthcare service agencies and price information scraped from websites.
23 . The method of claim 13 , wherein the one or more external healthcare pricing sources further comprise one of more of customer or peer review data and patient outcome data.