# US 10,770,181 B2 · Systems and methods for reducing resource consumption via information technology infrastructure

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- Number: US 10,770,181 B2
- Document ID: US10770181B2
- Status: Granted
- Kind: B2
- Application number: 15/237,361
- Filed: 2016-08-15
- Published: 2017-06-22
- Granted: 2020-09-08
- Earliest claimed: 2015-12-16
- Assignees: Alegeus Technologies, LLC
- Applicants: Alegeus Technologies, LLC
- Inventors: John Bull; Chris Rodkey
- Web page: https://patentgrep.com/patent/US10770181B2

## CPC

- G06Q 40/123: {Tax preparation or submission}
- G06F 16/24578: {using ranking}
- G06Q 10/10: Office automation; Time management
- G16H 10/20: for electronic clinical trials or questionnaires
- G16H 50/30: for calculating health indices; for individual health risk assessment
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA

## Abstract

The present disclosure is directed to reducing resource consumption via information technology infrastructure. A server of the present disclosure receives one or more data packets including data indicating a healthcare transaction event. The server selects healthcare trend model trained by the server using previously received data packets. The server determines a correlation coefficient between each of a plurality of healthcare related recommendations and the selected healthcare trend model. The server retrieves a notification template from a notification data structure that maps to the highest ranking healthcare related recommendation. The server generates a request to deliver the notification corresponding to the highest ranking healthcare related recommendation at a destination address of a computing device of a participant.

## Claims

### Claim 1

A system to reduce resource consumption via information technology infrastructure, comprising:
a communications interface executed by a server and configured to receive one or more data packets including data indicating a healthcare transaction event corresponding to a participant of a plurality of participants of a healthcare management platform, wherein the healthcare transaction event includes a denial;
a forecast engine executed by the server and configured to:
identify a machine learning engine configured to train healthcare trend models that predict resource allocations to reduce resource consumption using at least one of decision tree learning, a predictive model, association rule learning, support vector machines, clustering, or reinforcement learning;
train, using the machine learning engine, the healthcare trend model to include a baseline threshold for one or more features using previously received data packets including data indicating healthcare transaction events corresponding to the plurality of participants of the healthcare management platform;
select the healthcare trend model to provide healthcare related recommendations to the plurality of participants of the healthcare management platform maintained by the server;
initiate, based on a comparison between the healthcare transaction event and the baseline threshold of the selected healthcare trend model, a notification engine to cause the notification engine to reduce resource consumption of information technology infrastructure;
the notification engine executed by the server and configured to:
perform, responsive to initiation by the forecast engine, a lookup in a recommendation data structure using an identifier of the selected healthcare trend model to identify a plurality of healthcare related recommendations linked with the selected healthcare trend model;
determine a correlation coefficient between each of the plurality of healthcare related recommendations and the selected healthcare trend model, wherein the correlation coefficient indicates a likelihood that the plurality of healthcare related recommendations reduces resource consumption of information technology infrastructure by reducing an occurrence of denied transactions;
select, based on a rank of each correlation coefficient, a highest ranking healthcare related recommendation of the plurality of healthcare related recommendations configured to reduce resource consumption of information technology infrastructure by reducing the occurrence of denied transactions;
retrieve, responsive to the selection of the highest ranking healthcare related recommendation, a notification template from a notification template data structure that maps to the highest ranking healthcare related recommendation;
generate, using the notification template, a notification corresponding to the highest ranking healthcare related recommendation configured to reduce a likelihood of future occurrences of the healthcare transaction event;
generate a request to deliver the notification corresponding to the highest ranking healthcare related recommendation at a destination address of a computing device of the participant; and
transmit, to the computing device via a communication channel established between the server and the computing device, responsive to the request, the notification to the computing device of the participant to reduce a likelihood of future occurrences of the healthcare transaction event.

### Claim 2 (depends on 1)

The system of claim 1, wherein the server is further configured to:
retrieve a denial healthcare trend model responsive to the healthcare transaction event including the denial;
select, based on the denial healthcare trend model, a denial recommendation comprising a recommended processing configuration responsive to a processing configuration that resulted in the denial healthcare transaction event.

### Claim 3 (depends on 1)

The system of claim 1, wherein the server is further configured to:
retrieve a denial healthcare trend model responsive to the healthcare transaction event including the denial; and
select, based on the denial healthcare trend model, a denial recommendation comprising a recommended resource allocation responsive to determining that an insufficient amount of resources resulted in the denial healthcare transaction event.

### Claim 4 (depends on 1)

The system of claim 1, wherein the healthcare transaction event includes a partial denial and the server is further configured to:
retrieve a denial healthcare trend model responsive to the healthcare transaction event including the partial denial; and
select, based on the denial healthcare trend model, a denial recommendation comprising an ordered list including at least one qualifying item and at least one non-qualifying item responsive to determining that the denial healthcare transaction event resulted from a transaction including one or more qualifying items and one or more non-qualifying items.

### Claim 5 (depends on 1)

The system of claim 1, wherein the server is further configured to:
categorize the healthcare transaction event into a first category selected from a plurality of categories;
determine, from the healthcare trend model, that a metric of the first category meets or exceeds a threshold for the first category; and
select, responsive to the determination of the metric meeting or exceeding the threshold, the highest ranking healthcare related recommendation.

### Claim 6 (depends on 1)

The system of claim 1, wherein the server is further configured to:
generate a first vector based on the healthcare transaction event and one or more healthcare transaction events of the participant;
identify a second vector for each of a plurality of healthcare transaction trend models;
determine for each of the plurality of healthcare transaction trend models, a distance between the first vector and the second vector;
identify a minimum distance from the determined distance for each of the plurality of healthcare transaction trend models; and
select the healthcare trend model corresponding to the minimum distance.

### Claim 7 (depends on 1)

The system of claim 1, wherein the server is further configured to:
categorize the healthcare transaction event into a first category selected from a plurality of categories;
determine, from the healthcare trend model, that a metric of the first category is below a threshold; and
select, responsive to the determination of the metric below the threshold, the highest ranking healthcare related recommendation.

### Claim 8 (depends on 1)

The system of claim 1, further comprising the healthcare management platform configured to:
receive electronic healthcare transactions;
process the electronic healthcare transactions to cause healthcare transaction events; and
store, in a database, the healthcare transaction events.

### Claim 9 (depends on 1)

The system of claim 1, wherein the healthcare transaction events include one or more of a claim payment, a card denial, a password change, or a received deposit.

### Claim 10 (depends on 1)

The system of claim 1, wherein the server is further configured to:
receive the previously received data packets from a device of an administrator remote from the server via an administrator interface rendered by the server on the device of the administrator.

### Claim 11

A method of reducing resource consumption via information technology infrastructure, comprising:
receiving, by a server via a communications interface, one or more data packets including data indicating a healthcare transaction event corresponding to a participant of a plurality of participants of a healthcare management platform, wherein the healthcare transaction event includes a denial;
identifying, by the server, a machine learning engine configured to train healthcare trend models that predict resource allocations to reduce resource consumption using at least one of decision tree learning, a predictive model, association rule learning, support vector machines, clustering, or reinforcement learning;
training, by the server using the machine learning engine, the healthcare trend model to include a baseline threshold for one or more features using previously received data packets including data indicating healthcare transaction events corresponding to the plurality of participants of the healthcare management platform;
selecting, by the server, the healthcare trend model to provide healthcare related recommendations to the plurality of participants of the healthcare management platform maintained by the server;
initiating, by the server, based on a comparison between the healthcare transaction event and the baseline threshold of the selected healthcare trend model, a notification engine to cause the notification engine to reduce resource consumption of information technology infrastructure
performing, by the notification engine of the server responsive to initiation, a lookup in a recommendation data structure using an identifier of the selected healthcare trend model to identify a plurality of healthcare related recommendations linked with the selected healthcare trend model;
determining, by the server, a correlation coefficient between each of the plurality of healthcare related recommendations and the selected healthcare trend model, wherein the correlation coefficient indicates a likelihood that the plurality of healthcare related recommendations reduces resource consumption of information technology infrastructure by reducing an occurrence of denied transactions;
selecting, by the server based on a rank of each correlation coefficient, a highest ranking healthcare related recommendation of the plurality of healthcare related recommendations configured to reduce resource consumption of information technology infrastructure by reducing the occurrence of denied transactions;
retrieving, by the server responsive to selecting the highest ranking healthcare related recommendation, a notification template from a notification template data structure that maps to the highest ranking healthcare related recommendation;
configuring, by the server, a notification engine with the notification template to generate a notification corresponding to the highest ranking healthcare related recommendation and configured to reduce a likelihood of future occurrences of the healthcare transaction event;
generating, by the notification engine of the server, a request to deliver the notification corresponding to the highest ranking healthcare related recommendation at a destination address of a computing device of the participant; and
transmitting, by the server to the computing device via a communication channel established between the server and the computing device, responsive to the request, the notification to the computing device of the participant to reduce a likelihood of future occurrences of the healthcare transaction event.

### Claim 12 (depends on 11)

The method of claim 11, comprising:
retrieving a denial healthcare trend model responsive to the healthcare transaction event including the denial;
selecting, based on the denial healthcare trend model, a denial recommendation comprising a recommended processing configuration responsive to a processing configuration that resulted in the denial healthcare transaction event.

### Claim 13 (depends on 11)

The method of claim 11, comprising:
retrieving a denial healthcare trend model responsive to the healthcare transaction event including the denial; and
selecting, based on the denial healthcare trend model, a denial recommendation comprising a recommended resource allocation responsive to determining that an insufficient amount of resources resulted in the denial healthcare transaction event.

### Claim 14 (depends on 11)

The method of claim 11, comprising:
retrieving a denial healthcare trend model responsive to the healthcare transaction event including a partial denial; and
selecting, based on the denial healthcare trend model, a denial recommendation comprising an ordered list including at least one qualifying item and at least one non-qualifying item responsive to determining that the denial healthcare transaction event resulted from a transaction including one or more qualifying items and one or more non-qualifying items.

### Claim 15 (depends on 11)

The method of claim 11, comprising:
categorizing the healthcare transaction event into a first category selected from a plurality of categories;
determining, from the healthcare trend model, that a metric of the first category meets or exceeds a threshold for the first category; and
selecting, responsive to determining the metric meeting or exceeding the threshold, the highest ranking healthcare related recommendation.

### Claim 16 (depends on 11)

The method of claim 11, comprising:
generating, by the server, a first vector based on the healthcare transaction event and one or more healthcare transaction events of the participant;
identifying, by the server, a second vector for each of a plurality of healthcare transaction trend models;
determining, by the server, for each of the plurality of healthcare transaction trend models, a distance between the first vector and the second vector;
identifying, by the server, a minimum distance from the determined distance for each of the plurality of healthcare transaction trend models; and
selecting, by the server, the healthcare trend model corresponding to the minimum distance.

### Claim 17 (depends on 11)

The method of claim 11, comprising:
categorizing the healthcare transaction event into a first category selected from a plurality of categories;
determining, from the healthcare trend model, that a metric of the first category falls below a threshold; and
selecting, responsive to determining that the metric falls below the threshold, the highest ranking healthcare related recommendation.

### Claim 18 (depends on 11)

The method of claim 11, comprising:
receiving, by the healthcare management platform, electronic healthcare transactions;
processing, by the healthcare management platform, the electronic healthcare transactions to cause healthcare transaction events; and
storing, by the healthcare management platform, in a database, the healthcare transaction events.

### Claim 19 (depends on 11)

The method of claim 11, wherein the healthcare transaction events include one or more of a claim payment, a card denial, a password change, or a received deposit.

### Claim 20 (depends on 11)

The method of claim 11, comprising:
receiving the previously received data packets from a device of an administrator remote from the server via an administrator interface rendered by the server on the device of the administrator.