Peer community based anomalous behavior detection

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 a first peer community in a peer network by at least applying a machine-learning model trained to identify one or more peer communities present in the peer network, the peer network including a plurality of clinicians, and the first peer community including a first clinician and a second clinician from the plurality of clinicians based at least on the first clinician and the second clinician sharing at least one common attribute;
• comparing a first activity pattern of the first clinician to a second activity pattern of the second clinician;
• determining, based at least on the comparison between the first activity pattern of the first clinician and the second activity pattern of the second clinician, that the first clinician exhibits anomalous behavior;
• and
• in response to determining that the first clinician exhibits anomalous behavior, isolating at least one medication accessed by the first clinician.

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

• identifying a first peer community in a first peer network by at least applying a machine-learning model trained to identify one or more peer communities present in the peer network, the peer network including a plurality of clinicians, and the first peer community including a first clinician and a second clinician from the plurality of clinicians based at least on the first clinician and the second clinician sharing at least one common attribute;
• and
• comparing a first activity pattern of the first clinician to a second activity pattern of the second clinician;
• determining, based at least on the comparison between the first activity pattern of the first clinician and the second activity pattern of the second clinician, that the first clinician exhibits anomalous behavior;
• and
• in response to determining that the first clinician exhibits anomalous behavior, isolating at least one medication accessed by the first clinician.

An apparatus, comprising:

• a storage container;
• 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:
• receiving an indication identifying a first clinician as exhibiting anomalous behavior, the first clinician being part of a peer community in a peer network including a plurality of clinicians, the peer community being identified by at least applying a machine-learning model trained to identify one or more peer communities present in the peer network, and the first clinician being identified as exhibiting anomalous behavior based at least on a comparison between a first activity pattern of the first clinician and a second activity pattern of a second clinician in the peer community;
• and
• in response to the indication, restricting access to the storage container by the first clinician to isolate at least one medication stored in the storage container.