Granted Patent B2

US 12,437,862 · App. 17/763,622 · Granted Oct 7, 2025

Inventors: Cynthia Yamaga (Oceanside, CA); Hien-Hoa Vu (Pearland, TX); Abhikesh Nag (San Diego, CA); Satya Varaprasad Allumallu (San Diego, CA); Dennis Tribble (Ormond Beach, FL)

Assignee: CareFusion 303, Inc.

G16H40/20G16H20/10

Abstract

Claims (34)

1. A system, comprising:

at least one data processor; and

at least one memory storing instructions which, when executed by the at least one data processor, result in operations comprising:

identifying an activity pattern associated with a first clinician as being an infrequent activity pattern that occurs below a threshold frequency, wherein the infrequent activity pattern is identified based at least on a signal-to-noise ratio associated with the infrequent activity pattern being below a threshold value;

determining, based at least on one or more data models, whether the infrequent activity pattern corresponds to an anomalous behavior;

triggering an investigative workflow in response to the infrequent activity pattern being determined to correspond to the anomalous behavior; and

causing a wasting station to provide a separate receptacle for unused medication from the first clinician, wherein the separate receptacle isolates the unused medication that the first clinician disposes of at the wasting station from a shared receptacle that comingles unused medication disposed by multiple clinicians.

2. The system of claim 1 , wherein the activity pattern includes a plurality of transaction records generated in response to the first clinician interacting with one or more data systems, and wherein the one or more data systems include an access control system, a dispensing system, an infusion system, a compounding system, and/or an electronic medical record system.

3. The system of claim 2 , wherein the plurality of transaction records include one or more transaction values corresponding to a timestamp, a patient identifier, a device identifier, a clinician identifier, a medication identifier, a prescription order identifier, an inventory information, a patient status, a shift identifier, a location tracking identifier, an infusion information, a compounding information, an administration information, a working off clock indicator, and/or an electronic health record identifier.

4. The system of claim 1 , wherein the one or more data models are generated based on a series of transaction records known to be associated with one or more types of anomalous behavior that are indicative of diversion.

5. The system of claim 4 , wherein each of the one or more data models include a combination of reference transaction values representative of a corresponding type of anomalous behavior, and wherein the combination of reference transaction values include one or more reference transaction values for the timestamp, the patient identifier, the device identifier, the clinician identifier, the medication identifier, the prescription order identifier, the inventory information, the patient status, the shift identifier, the location tracking identifier, the infusion information, the compounding information, the administration information, the working off clock indicator, and/or the electronic health record identifier.

6. The system of claim 1 , wherein the anomalous behavior includes the first clinician routinely selecting a second clinician to witness a wasting of medication while the second clinician also serves as a witness for a third clinician wasting medication.

7. The system of claim 1 , wherein the anomalous behavior includes the first clinician routinely selecting a second clinician to witness a wasting of medication and the second clinician routinely selecting the first clinician to witness the wasting of medication.

8. The system of claim 1 , wherein the anomalous behavior includes the first clinician withdrawing a medication for a deceased patient and/or a discharged patient.

9. The system of claim 1 , wherein the anomalous behavior includes the first clinician routinely accessing a medical management device within a threshold quantity of time after another clinician.

10. The system of claim 1 , wherein the anomalous behavior includes a paired cancellation of transactions, an unexpected forced opening of a medication management device, a clinician interacting with the medication management device when the clinician not scheduled to work, the clinician interacting with the medication management device when the clinician is not clocked in to for work, and/or the clinician interacting with the medication management device at an abnormal time.

11. The system of claim 1 , wherein the investigative workflow includes sending, to a client device, an alert indicating the first clinician as exhibiting the anomalous behavior.

12. The system of claim 1 , wherein the investigative workflow includes activating one or more surveillance devices in response to the first clinician interacting with a medical management device and/or isolating a medication accessed by the first clinician.

13. The system of claim 1 , wherein the infrequent activity pattern is determined to correspond to the anomalous behavior in response to a match between a first plurality of transaction values forming the infrequent activity pattern and a second plurality of reference transaction values included in a data model of the anomalous behavior being above a threshold value.

14. The system of claim 13 , wherein the threshold value is adjusted in response to a misidentification of more than a threshold quantity of infrequent activity patterns.

15. A computer-implemented method, comprising:

identifying an activity pattern associated with a first clinician as being an infrequent activity pattern that occurs below a threshold frequency, wherein the infrequent activity pattern is identified based at least on a signal-to-noise ratio associated with the infrequent activity pattern being below a threshold value;

determining, based at least on one or more data models, whether the infrequent activity pattern corresponds to an anomalous behavior;

triggering an investigative workflow in response to the infrequent activity pattern being determined to correspond to the anomalous behavior; and

causing a wasting station to provide a separate receptacle for unused medication from the first clinician, wherein the separate receptacle isolates the unused medication that the first clinician disposes of at the wasting station from a shared receptacle that comingles unused medication disposed by multiple clinicians.

16. The method of claim 15 , wherein the activity pattern includes a plurality of transaction records generated in response to the first clinician interacting with one or more data systems, and wherein the one or more data systems include an access control system, a dispensing system, an infusion system, a compounding system, and/or an electronic medical record system.

17. The method of claim 16 , wherein the plurality of transaction records include one or more transaction values corresponding to a timestamp, a patient identifier, a device identifier, a clinician identifier, a medication identifier, a prescription order identifier, an inventory information, a patient status, a shift identifier, a location tracking identifier, an infusion information, a compounding information, an administration information, a working off clock indicator, and/or an electronic health record identifier.

18. The method of claim 15 , wherein the one or more data models are generated based on a series of transaction records known to be associated with one or more types of anomalous behavior that are indicative of diversion.

19. The method of claim 18 , wherein each of the one or more data models include a combination of reference transaction values representative of a corresponding type of anomalous behavior, and wherein the combination of reference transaction values include one or more reference transaction values for the timestamp, the patient identifier, the device identifier, the clinician identifier, the medication identifier, the prescription order identifier, the inventory information, the patient status, the shift identifier, the location tracking identifier, the infusion information, the compounding information, the administration information, the working off clock indicator, and/or the electronic health record identifier.

20. A non-transitory computer readable medium storing instructions, which when executed by at least one data processor, result in operations comprising:

identifying an activity pattern associated with a clinician as being an infrequent activity pattern that occurs below a threshold frequency, wherein the infrequent activity pattern is identified based at least on a signal-to-noise ratio associated with the infrequent activity pattern being below a threshold value;

determining, based at least on one or more data models, whether the infrequent activity pattern corresponds to an anomalous behavior;

triggering an investigative workflow in response to the infrequent activity pattern being determined to correspond to the anomalous behavior; and

causing a wasting station to provide a separate receptacle for unused medication from the first clinician, wherein the separate receptacle isolates the unused medication that the first clinician disposes of at the wasting station from a shared receptacle that comingles unused medication disposed by multiple clinicians.

Assignments (1)

Continuity (2)

References Cited (206)