IP Library Granted Patent US 12,040,066
Granted Patent B1
US 12,040,066 · App. 16/895,157 · Granted Jul 16, 2024

Cloud-based methods and systems for providing adaptive prescription reminders

Inventors: Benjamin Weiss (Chicago, IL); Ankur Jain (Chicago, IL); Kate Louise Paduchowski (Hamtramck, MI)
Assignee: WALGREEN CO.
G16H20/13G06F9/4418G16H10/60G16H20/10G16H10/00
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Quick Facts
Patent No.
US 12,040,066
App. No.
16/895,157
Granted
Jul 16, 2024
Kind
B1
Abstract

A computing system for adaptive prescription reminders includes a processor and a memory storing instructions that, when executed by the processor, cause the system to receive a fill event, generate an initial schedule, receive an medication consumption indication, generate an updated schedule using a trained machine learning model, cause the updated schedule to be displayed, and receive a patient confirmation. A computer-implemented method includes receiving a fill event, generating an initial schedule, receiving an medication consumption indication, generating an updated schedule using a trained machine learning model, causing the updated schedule to be displayed, and receiving a patient confirmation. A non-transitory computer readable medium includes program instructions that when executed, cause a computer to: receive a fill event, generate an initial schedule, receive an medication consumption indication, generate an updated schedule using a trained machine learning model, cause the updated schedule to be displayed, and receive a patient confirmation.

Claims (81)

1. A regional pharmacy cloud computing system for facilitating an adaptive reminder of a pharmacy prescription, the regional pharmacy cloud computing system comprising:

one or more processors;

a retail pharmacy computing system layer communicatively connected to the one or more processors;

a patient computing device layer communicatively connected to the one or more processors; and

a memory storing instructions that, when executed by the one or more processors, cause the regional pharmacy cloud computing system to:

receive, from the retail pharmacy computing system layer, one or both of (i) a prescription refill event, and (ii) a prescription fill event corresponding to the pharmacy prescription,

analyze the event corresponding to the pharmacy prescription to generate an initial prescription schedule,

receive, from the patient computing device layer, one or more indications of the patient's consumption of a medication corresponding to the pharmacy prescription,

analyze the one or more indications using an artificial neural network to generate an updated prescription schedule,

wherein the artificial neural network is iteratively trained by processing historical prescription consumption information to determine scheduling patterns,

wherein the artificial neural network comprises a multi-layered network architecture, each layer in the multi-layered network architecture being associated with one or more of: (i) an activation function, (ii) a loss function, or (iii) an optimization function, and

wherein training the artificial neural network produces one or more weights derived from the historical prescription consumption information, values of the weights being used to iteratively train the trained artificial neural network,

cause the updated prescription schedule to be displayed in a graphical user interface of an application on the patient computing device layer, and

receive an indication of confirmation with respect to the updated prescription schedule,

wherein:

the regional pharmacy cloud computing system comprises (i) a first regional pharmacy cloud computing system implemented at a first geographical cloud computing data center corresponding to a first region and (ii) a second regional pharmacy cloud computing system implemented at a second geographical cloud computing data center corresponding to a second region, and

the first regional pharmacy cloud computing system is configured independently from the second regional pharmacy cloud computing system.

2. The regional pharmacy cloud computing system of claim 1 , the memory storing further instructions that, when executed by the one or more processors, cause the regional pharmacy cloud computing system to:

receive the event corresponding to the pharmacy prescription by analyzing an input sig code.

3. The regional pharmacy cloud computing system of claim 1 , the memory storing further instructions that, when executed by the one or more processors, cause the regional pharmacy cloud computing system to:

receive the one or more indications of the patient's consumption of the medication corresponding to the pharmacy prescription from a connected pharmacy device.

4. The regional pharmacy cloud computing system of claim 1 , the memory storing further instructions that, when executed by the one or more processors, cause the regional pharmacy cloud computing system to:

receive one or both of (i) a delegation of permission, and (ii) a revocation of permission with respect to one or more caregivers.

5. The regional pharmacy cloud computing system of claim 1 , the memory storing further instructions that, when executed by the one or more processors, cause the regional pharmacy cloud computing system to:

generate one or more awards by analyzing the indications of the patient's consumption of the medication corresponding to the pharmacy prescription; and

transmit the one or more awards to the patient computing device layer.

6. The regional pharmacy cloud computing system of claim 1 , the memory storing further instructions that, when executed by the one or more processors, cause the regional pharmacy cloud computing system to:

receive a snooze indication corresponding to the medication corresponding to the pharmacy prescription.

7. The regional pharmacy cloud computing system of claim 1 , the memory storing further instructions that, when executed by the one or more processors, cause the regional pharmacy cloud computing system to:

receive existing patient profile information from a legacy computing application of the patient computing device layer; and

display the patient profile information in the graphical user interface of the application on the patient computing device layer.

8. A computer-implemented method for facilitating an adaptive reminder of a pharmacy prescription, comprising:

receiving, from a retail pharmacy computing system layer of a regional pharmacy cloud computing system, one or both of (i) a prescription refill event, and (ii) a prescription fill event corresponding to the pharmacy prescription;

analyzing the event corresponding to the pharmacy prescription to generate an initial prescription schedule;

receiving, from a patient computing device layer of the regional pharmacy cloud computing system, one or more indications of the patient's consumption of a medication corresponding to the pharmacy prescription;

analyzing the one or more indications using an artificial neural network to generate an updated prescription schedule,

wherein the artificial neural network is iteratively trained by processing historical prescription consumption information to determine scheduling patterns,

wherein the artificial neural network comprises a multi-layered network architecture, each layer in the multi-layered network architecture being associated with one or more of: (i) an activation function, (ii) a loss function, or (iii) an optimization function, and

wherein training the artificial neural network produces one or more weights derived from the historical prescription consumption information, values of the weights being used to iteratively train the trained artificial neural network;

causing the updated prescription schedule to be displayed in a graphical user interface of an application on the patient computing device layer; and

receiving an indication of confirmation with respect to the updated prescription schedule,

wherein:

the regional pharmacy cloud computing system comprises at least (i) a first regional pharmacy cloud computing system implemented at a first geographical cloud computing data center corresponding to a first region and (ii) a second regional pharmacy cloud computing system implemented at a second geographical cloud computing data center corresponding to a second region, and

the first regional pharmacy cloud computing system is configured independently from the second regional pharmacy cloud computing system.

9. The computer-implemented method of claim 8 , further comprising:

receiving the event corresponding to the pharmacy prescription by analyzing an input sig code.

10. The computer-implemented method of claim 8 , further comprising:

receiving the one or more indications of the patient's consumption of the medication corresponding to the pharmacy prescription from a pharmacy connected device.

11. The computer-implemented method of claim 8 , further comprising:

receiving one or both of (i) a delegation of permission, and (ii) a revocation of permission with respect to one or more caregivers.

12. The computer-implemented method of claim 8 , further comprising:

generating one or more awards by analyzing the indications of the patient's consumption of the medication corresponding to the pharmacy prescription; and

transmitting the one or more awards to the patient computing device layer.

13. The computer-implemented method of claim 8 , further comprising:

receiving a snooze indication corresponding to the medication corresponding to the pharmacy prescription.

14. The computer-implemented method of claim 8 , further comprising:

receiving existing patient profile information from a legacy computing application of the patient computing device layer; and

displaying the patient profile information in the graphical user interface of the application on the patient computing device layer.

15. A non-transitory computer readable medium containing program instructions that when executed, cause a computer to:

receive, from a retail pharmacy computing system layer of a regional cloud computing system, one or both of (i) a prescription refill event, and (ii) a prescription fill event corresponding to the pharmacy prescription;

analyze the event corresponding to the pharmacy prescription to generate an initial prescription schedule;

receive, from a patient computing device layer of the regional cloud computing system, one or more indications of the patient's consumption of a medication corresponding to the pharmacy prescription;

analyze the one or more indications using an artificial neural network to generate an updated prescription schedule,

wherein the artificial neural network is iteratively trained by processing historical prescription consumption information to determine scheduling patterns,

wherein the artificial neural network comprises a multi-layered network architecture, each layer in the multi-layered network architecture being associated with one or more of: (i) an activation function, (ii) a loss function, or (iii) an optimization function, and

wherein training the artificial neural network produces one or more weights derived from the historical prescription consumption information, values of the weights being used to iteratively train the trained artificial neural network;

cause the updated prescription schedule to be displayed in a graphical user interface of an application on the patient computing device layer; and

receive an indication of confirmation with respect to the updated prescription schedule,

wherein:

the regional pharmacy cloud computing system comprises at least (i) a first regional pharmacy cloud computing system implemented at a first geographical cloud computing data center corresponding to a first region and (ii) a second regional pharmacy cloud computing system implemented at a second geographical cloud computing data center corresponding to a second region, and

the first regional pharmacy cloud computing system is configured independently from the second regional pharmacy cloud computing system.

16. The non-transitory computer readable medium of claim 15 containing further program instructions that when executed, cause a computer to:

receive the event corresponding to the pharmacy prescription by analyzing an input sig code.

17. The non-transitory computer readable medium of claim 15 containing further program instructions that when executed, cause a computer to:

receive the one or more indications of the patient's consumption of the medication corresponding to the pharmacy prescription from a connected pharmacy device.

18. The non-transitory computer readable medium of claim 15 containing further program instructions that when executed, cause a computer to:

receive one or both of (i) a delegation of permission, and (ii) a revocation of permission with respect to one or more caregivers.

19. The non-transitory computer readable medium of claim 15 containing further program instructions that when executed, cause a computer to:

generate one or more awards by analyzing the indications of the patient's consumption of the medication corresponding to the pharmacy prescription; and transmit the one or more awards to a mobile computing device of the patient.

20. The non-transitory computer readable medium of claim 15 containing further program instructions that when executed, cause a computer to:

receive a snooze indication corresponding to the medication corresponding to the pharmacy prescription.

Assignments (3)
INTELLECTUAL PROPERTY SECURITY AGREEMENT Recorded Aug 28, 2025
From: WALGREEN CO.
To: SIXTH STREET LENDING PARTNERS, AS COLLATERAL AGENT
Reel/Frame 072606/0878 →
SECURITY INTEREST Recorded Aug 28, 2025
From: WALGREEN CO.; DUANE READE; WALGREENS SPECIALTY PHARMACY LLC; WALGREENS BOOTS ALLIANCE, INC.
To: WELLS FARGO BANK, NATIONAL ASSOCIATION, AS COLLATERAL AGENT
Reel/Frame 072679/0926 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 8, 2020
From: WEISS, BENJAMIN; JAIN, ANKUR; PADUCHOWSKI, KATE LOUISE
To: WALGREEN CO.
Reel/Frame 052868/0227 →
Cited By (1)
US 12,205,719