Statistical financial system and method to value patient visits to healthcare provider organizations for follow up prioritization

A hardware storage device having code embodied therein, the code comprising:

• an instruction for reading historical healthcare visit data associated with one or more healthcare provider visits, the healthcare provider data including at least one previously generated attribute pattern associated with one or more past healthcare provider visits, each healthcare provider visit comprising a combination of professional services and healthcare items that are to be provided to a patient at the healthcare provider visit, each professional service and healthcare item having an associated monetary value;
• an instruction for performing a statistical analysis on the historical healthcare visit data;
• an instruction for creation of attribute patterns using statistical variables, the attribute patterns comprising one or more visit-related variables associated with the professional services and healthcare items that are to be provided as part of the healthcare provider visit, wherein the visit-related variables comprise a selected subset of independent and dependent variables used when calculating a value for the current healthcare provider visit, wherein the independent variables are selected based on their predictive power according to the at least one previously generated attribute pattern, wherein a higher predictive power is manifest where the difference between a predicted monetary value and a real monetary value has an optimal Sharpe ratio, a minimum standard deviation, and an average approaching zero,
• wherein the attribute pattern is determined according to one or more rules executed within an analytical and rules engine that provides a configurable way to augment machine instructions from a compiled language, the analytical and rules engine being configured to take into account environment-specific variables that influence the attribute pattern determination, wherein the machine instructions are executed in the analytical and rules engine along with the one or more rules;
• an instruction for accepting healthcare data inputs including healthcare data inputs for at least one current healthcare visit;
• an instruction to analyze said healthcare data inputs for data exceptions and issues;
• an instruction to raise alerts on said data exceptions;
• an instruction to compare said healthcare data inputs including the at least one previously generated attribute pattern against said attribute patterns resulting in an assignment of a predicted monetary value, a weight, or a priority to said healthcare visits including the healthcare visit, or to the alerts, or to both, the weight or priority indicating the order in which follow-up tasks performed after the healthcare provider visit are to be carried out for the healthcare provider visit.

A computer system comprising the following:

• one or more processors;
• one or more computer-readable storage media having stored thereon computer-executable instructions that, when executed by the one or more processors, cause the computing system to perform a method for assigning a monetary value to a healthcare provider visit, the method comprising the following:
• instantiating an interface layer that provides an interface for a user to interact with a remote client, including accessing, via the remote client, one or more portions of healthcare provider data associated with a healthcare provider visit, the healthcare provider data including at least one previously generated attribute pattern associated with one or more past healthcare provider visits, the healthcare provider visit comprising a combination of professional services and healthcare items that are to be provided to a patient at the healthcare provider visit, each professional service and healthcare item having an associated monetary value;
• determining an attribute pattern that includes one or more visit-related variables associated with the professional services and healthcare items that are to be provided as part of the healthcare provider visit, wherein the visit-related variables comprise a selected subset of independent and dependent variables used when calculating a value for the current healthcare provider visit based on one or more historical healthcare provider visits, wherein the independent variables are selected based on their predictive power according to the at least one previously generated attribute pattern, wherein a higher predictive power is manifest where the difference between a predicted monetary value and a real monetary value has an optimal Sharpe ratio, a minimum standard deviation, and an average approaching zero,
• wherein the attribute pattern is determined according to one or more rules executed within an analytical and rules engine that provides a configurable way to augment machine instructions from a compiled language, the analytical and rules engine being configured to take into account environment-specific variables that influence the attribute pattern determination, wherein the machine instructions are executed in the analytical and rules engine along with the one or more rules;
• comparing the healthcare provider data associated with the healthcare provider visit including the at least one previously generated attribute pattern to the determined attribute pattern to match the at least one previously generated attribute pattern with the newly determined attribute pattern in order to assign a monetary value, a weight, or a priority to the healthcare provider visit;
• and
• based on the comparison of the healthcare provider data to the determined attribute pattern, and prior to the healthcare provider visit taking place, calculating a predicted monetary value, a weight or a priority for the healthcare provider visit, the predicted monetary value, weight or priority indicating the order in which follow-up tasks performed after the healthcare provider visit are to be carried out for the healthcare provider visit.