Data processing for making predictive determinations
In some examples, structured and unstructured data is evaluated using one or more predictive models to determine whether a dependent user is at risk for a certain condition. In other examples, structured and unstructured data is evaluated using one or more predictive models to determine a contact plan for contacting dependent users regarding follow-up appointments related to release of the dependent user.
1. A system comprising:
a memory comprising computer-executable instructions; and
a processor configured to access the memory to execute the computer-executable instructions to collectively at least:
monitor a data stream comprising a plurality of messages to detect a conclusion event associated with a particular message of the plurality of messages, the particular message being a standard message type for carrying information relating to the conclusion event;
determine, based on the conclusion event, that a dependent user has been released from a facility and that care related to presence of the dependent user at the facility has concluded;
access, based on the particular message, a release summary associated with a record of the dependent user, at least a portion of the release summary comprising unstructured data prepared by an authorized user who responded to conditions of the dependent user while the dependent user was present at the facility;
identify, based on the release summary, one or more related reports generated in connection with the care related to the presence of the dependent user at the facility or other care unrelated to the presence of the dependent user at the facility, the one or more related reports comprising other unstructured data;
evaluate at least one of the unstructured data of the release summary or the other unstructured data of the one or more related reports using a natural-language processing model to generate a list of potential follow-up tasks; and
generate a follow-up plan for execution of the list of potential follow-up tasks, the follow-up plan comprising:
a ranking of the list of potential follow-up tasks according to prioritization of medical necessity; and
a contact plan for contacting the dependent user to schedule one or more follow-up appointments corresponding to at least one potential follow-up task of the list of potential follow-up tasks.
2. The system of claim 1 , wherein the release summary comprises:
a release diagnosis identified by the authorized user;
a care instruction to be performed at home by the dependent user as part of treating a condition associated with the release diagnosis; and
an ancillary finding identified by the authorized user or by another authorized user.
3. The system of claim 2 , wherein the list of potential follow-up tasks comprises at least one release follow-up task associated with the release diagnosis and at least one ancillary follow-up task associated with the ancillary finding.
4. The system of claim 1 , wherein the natural-language processing model is based on a corpus of release summaries prepared by other authorized users.
5. The system of claim 1 , wherein the processor is further configured to access the memory to execute the computer-executable instructions to collectively at least provide a portion of the follow-up plan for presentation on a user interface of a user device.
6. The system of claim 1 , wherein the particular message is an admit, discharge, transfer (ADT) message.
7. The system of claim 1 , wherein evaluating at least one of the unstructured data of the release summary or the other unstructured data of the one or more related reports using the natural-language processing model is based at least in part on a first known format of the release summary or second one or more known formats of the one or more related reports.
8. A computer-implemented method comprising:
monitoring a data stream comprising a plurality of messages to detect a conclusion event associated with a particular message of the plurality of messages, the particular message being a standard message type for carrying information relating to the conclusion event;
determining, based on the conclusion event, that a dependent user has been released from a facility and that care related to presence of the dependent user at the facility has concluded;
accessing, based on the particular message, a release summary associated with a record of the dependent user, at least a portion of the release summary comprising unstructured data prepared by an authorized user who responded to conditions of the dependent user while the dependent user was present at the facility;
identifying, based on the release summary, one or more related reports generated in connection with the care related to the presence of the dependent user at the facility or other care unrelated to the presence of the dependent user at the facility, the one or more related reports comprising other unstructured data;
evaluating at least one of the unstructured data of the release summary or the other unstructured data of the one or more related reports using a natural-language processing model to generate a list of potential follow-up tasks; and
generating a follow-up plan for execution of the list of potential follow-up tasks, the follow-up plan comprising:
a ranking of the list of potential follow-up tasks according to prioritization of medical necessity; and
a contact plan for contacting the dependent user to schedule one or more follow-up appointments corresponding to at least one potential follow-up task of the list of potential follow-up tasks.
9. The computer-implemented method of claim 8 , wherein the release summary comprises:
a release diagnosis identified by the authorized user;
a care instruction to be performed at home by the dependent user as part of treating a condition associated with the release diagnosis; and
an ancillary finding identified by the authorized user or by another authorized user.
10. The computer-implemented method of claim 9 , wherein the list of potential follow-up tasks comprises at least one release follow-up task associated with the release diagnosis and at least one ancillary follow-up task associated with the ancillary finding.
11. The computer-implemented method of claim 8 , wherein the natural-language processing model is based on a corpus of release summaries prepared by other authorized users.
12. The computer-implemented method of claim 8 , further comprising providing a portion of the follow-up plan for presentation on a user interface of a user device.
13. The computer-implemented method of claim 8 , wherein the particular message is an admit, discharge, transfer (ADT) message.
14. The computer-implemented method of claim 8 , wherein evaluating at least one of the unstructured data of the release summary or the other unstructured data of the one or more related reports using the natural-language processing model is based at least in part on a first known format of the release summary or second one or more known formats of the one or more related reports.
15. One or more non-transitory, computer-readable storage media comprising computer-executable instructions that, when executed by one or more computer systems, cause the one or more computer systems to perform operations comprising:
monitoring a data stream comprising a plurality of messages to detect a conclusion event associated with a particular message of the plurality of messages, the particular message being a standard message type for carrying information relating to the conclusion event;
determining, based on the conclusion event, that a dependent user has been released from a facility and that care related to presence of the dependent user at the facility has concluded;
accessing, based on the particular message, a release summary associated with a record of the dependent user, at least a portion of the release summary comprising unstructured data prepared by an authorized user who responded to conditions of the dependent user while the dependent user was present at the facility;
identifying, based on the release summary, one or more related reports generated in connection with the care related to the presence of the dependent user at the facility or other care unrelated to the presence of the dependent user at the facility, the one or more related reports comprising other unstructured data;
evaluating at least one of the unstructured data of the release summary or the other unstructured data of the one or more related reports using a natural-language processing model to generate a list of potential follow-up tasks; and
generating a follow-up plan for execution of the list of potential follow-up tasks, the follow-up plan comprising:
a ranking of the list of potential follow-up tasks according to prioritization of medical necessity; and
a contact plan for contacting the dependent user to schedule one or more follow-up appointments corresponding to at least one potential follow-up task of the list of potential follow-up tasks.
16. The one or more non-transitory, computer-readable storage media of claim 15 , wherein the release summary comprises:
a release diagnosis identified by the authorized user;
a care instruction to be performed at home by the dependent user as part of treating a condition associated with the release diagnosis; and
an ancillary finding identified by the authorized user or by another authorized user.
17. The one or more non-transitory, computer-readable storage media of claim 16 , wherein the list of potential follow-up tasks comprises at least one release follow-up task associated with the release diagnosis and at least one ancillary follow-up task associated with the ancillary finding.
18. The one or more non-transitory, computer-readable storage media of claim 15 , wherein the natural-language processing model is based on a corpus of release summaries prepared by other authorized users.
19. The one or more non-transitory, computer-readable storage media of claim 15 , further comprising providing a portion of the follow-up plan for presentation on a user interface of a user device.
20. The one or more non-transitory, computer-readable storage media of claim 15 , wherein evaluating at least one of the unstructured data of the release summary or the other unstructured data of the one or more related reports using the natural-language processing model is based at least in part on a first known format of the release summary or second one or more known formats of the one or more related reports.