U.S. patent application number 15/627213 was filed with the patent office on 2017-11-30 for event management architecture.
The applicant listed for this patent is Resources Connection, Inc.. Invention is credited to Radgia Cook, Todd Fletcher, Gary Lee.
Application Number | 20170344405 15/627213 |
Document ID | / |
Family ID | 59034194 |
Filed Date | 2017-11-30 |
United States Patent
Application |
20170344405 |
Kind Code |
A1 |
Cook; Radgia ; et
al. |
November 30, 2017 |
EVENT MANAGEMENT ARCHITECTURE
Abstract
Generally described, aspects of the present disclosure relate to
the management of event data. In one aspect, an event management
service obtains information related to one or more events and
implements steps related to the collection of event data. In
another aspect, based on the collected information, the event
management service can implement one or more event data management
protocols. For example, the event management service can track the
progression of data analysis related to the event data, such as
implementing various error analysis tools or methodologies. In
another example, the event management service can implementing
tracking methodologies that can determine when to implement various
escalations or follow up actions based on the processing of event
data. In still a further aspect, the event management service can
implement various reporting or auditing related to the collection
of the event data, the processing of the event data or both.
Inventors: |
Cook; Radgia; (San Rafael,
CA) ; Fletcher; Todd; (New Orleans, LA) ; Lee;
Gary; (Cary, NC) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Resources Connection, Inc. |
Irvine |
CA |
US |
|
|
Family ID: |
59034194 |
Appl. No.: |
15/627213 |
Filed: |
June 19, 2017 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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14180290 |
Feb 13, 2014 |
9684549 |
|
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15627213 |
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61921879 |
Dec 30, 2013 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F 11/3093 20130101;
G06F 11/3006 20130101; G06F 11/3072 20130101 |
International
Class: |
G06F 9/54 20060101
G06F009/54 |
Claims
1. A computer-implemented method comprising: obtaining information
indicative of an event; obtaining a data collection template
associated with the event, wherein the data collection template
specifies a set of user inputs to collect regarding the event;
determining one or more data collection workflows based at least in
part on the data collection template; causing implementation of the
one or more data collection workflows to collect event data
corresponding to the set of user inputs, wherein the event data is
collected via one or more user interfaces; causing implementation
of one or more data processing methodologies on the event data;
determining, based at least in part on the implementation of the
one or more data processing methodologies, an attribute of the
event; and transmitting a result that is determined based at least
in part on the attribute of the event.
2. The computer-implemented method of claim 1, wherein the
attribute of the event comprises a cause of the event.
3. The computer-implemented method of claim 1, wherein the result
comprises a determination that a follow-up action associated with
the event has not been completed.
4. The computer-implemented method of claim 3 further comprising,
in response to the determination that the follow-up action
associated with the event has not been completed, transmitting a
notification to escalate the event.
5. The computer-implemented method of claim 1, wherein obtaining
the data collection template comprises obtaining a selection from a
set of available data collection templates.
6. The computer-implemented method of claim 1, wherein obtaining
the data collection template comprises determining the data
collection template based at least in part on the event.
7. A system comprising: a data store configured to store event
data, data collection templates, and computer-executable
instructions; and a processor in communication with the data store,
wherein the computer-executable instructions, when executed by the
processor, configure the processor to: obtain information
indicative of an event; obtain, from the data store, a data
collection template associated with the event, wherein the data
collection template specifies a set of event data to collect;
determine one or more data collection workflows based at least in
part on the data collection template; cause implementation of the
one or more data collection workflows to obtain the set of event
data; determine an attribute of the event based at least in part on
implementation of one or more data processing methodologies on the
set of event data; and transmit a result based at least in part on
the attribute of the event.
8. The system of claim 7, wherein the processor is further
configured to cause the implementation of the one or more data
processing methodologies.
9. The system of claim 7, wherein the event comprises a medical
prescription error.
10. The system of claim 7, wherein the attribute of the event is
determined based at least in part on previously determined behavior
patterns.
11. The system of claim 7, wherein the processor is further
configured to: determine, based at least in part on the attribute
of the event, an additional data collection workflow; and cause
implementation of the additional data collection workflow to obtain
additional event data.
12. The system of claim 7, wherein the attribute of the event
comprises an indication of whether the event is completed.
13. The system of claim 7, wherein the one or more data processing
methodologies include at least one of the London Protocol, the VA
Protocol, the SRX System protocol, and the Mayo Protocol.
14. The system of claim 7, wherein the processor is further
configured to identify the data collection template associated with
the event.
15. A computer-implemented method comprising: obtaining a data
collection template associated with an event, wherein the data
collection template specifies a set of event data to collect;
determining one or more data collection workflows based at least in
part on the data collection template; causing implementation of the
one or more data collection workflows to collect the set of event
data via one or more user interfaces; determining an attribute of
the event based at least in part on implementation of one or more
data processing methodologies on the set of event data; and
transmitting a result based at least in part on the attribute of
the event.
16. The computer-implemented method of claim 15, wherein the data
collection template is obtained based at least in part on a
selection from a set of available data collection templates.
17. The computer-implemented method of claim 15, wherein the set of
event data is defined according to aspects of performance of a
health care service provider.
18. The computer-implemented method of claim 15 further comprising
obtaining information indicative of the event.
19. The computer-implemented method of claim 18, wherein the
information indicative of the event comprises at least one of a
request for a service associated with the event, communication with
a person or entity associated with the event, or a request to
collect the set of event data.
20. The computer-implemented method of claim 15 further comprising
determining a priority for individual workflows of the one or more
data collection workflows, wherein the implementation of the one or
more data collection workflows is caused in accordance with the
priority.
Description
CROSS-REFERENCE TO RELATED APPLICATION
[0001] This application is a continuation of U.S. application Ser.
No. 14/180,290, entitled EVENT MANAGEMENT ARCHITECTURE, and filed
Feb. 13, 2014, which claims the benefit of U.S. Provisional Patent
Application No. 61/921,879, entitled EVENT MANAGEMENT ARCHITECTURE,
and filed Dec. 30, 2013, the entirety of each of which is
incorporated herein by reference.
BACKGROUND
[0002] Generally described, healthcare organizations are required
to implement event management protocols related to tracking and
managing events. Often, aspects of event management protocols may
be specified by various governmental or management authorities with
regard to the type of information collected as part of an event or
as to how event information is processed. Additionally, an
organization may utilize different methodologies for analyzing
event data, which may require different event data or different
forms of collected event data.
[0003] Many approaches to event management relate to the individual
collection and processing of event data. In some instances, a
healthcare organization may be required to collect event data
multiple times depending on the implementation of different event
management protocols or even utilizing different analysis tools as
part of the same event management protocol. Such methodologies may
be inefficient and subject to data entry errors.
BRIEF DESCRIPTION OF THE DRAWINGS
[0004] The foregoing aspects and many of the attendant advantages
of this disclosure will become more readily appreciated as the same
become better understood by reference to the following detailed
description, when taken in conjunction with the accompanying
drawings, wherein:
[0005] FIG. 1 is a block diagram illustrating an embodiment of a
virtual network having physical computing devices including hosted
virtual machine instances and a migration management service;
[0006] FIGS. 2A-2B are simplified block diagram of the network of
FIG. 1 illustrating the configuration of data collection workflows
and data processing methodologies based on data collection
templates;
[0007] FIG. 3 is a simplified block diagram of the network of FIG.
1 illustrating the collection and processing of event data by an
event management service; and
[0008] FIG. 4 is a flow-diagram illustrating an event data
processing routine implemented by an event management service.
DETAILED DESCRIPTION
[0009] Generally described, aspects of the present disclosure
relate to the management of event data. Specifically, systems and
methods are disclosed which the collection of event data related to
operation of an organization, such as healthcare organizations. In
one aspect, an event management service obtains information related
to one or more events and implements steps related to the
collection of event data. In another aspect, based on the collected
information, the event management service can implement one or more
event data management protocols. For example, the event management
service can track the progression of data analysis related to the
event data, such as implementing various error analysis tools or
methodologies. In another example, the event management service can
implement tracking methodologies that can determine when to
implement various escalations or follow up actions based on the
processing of event data. In still a further aspect, the event
management service can implement various reporting or auditing
related to the collection of the event data, the processing of the
event data or both.
[0010] Although the present application will be described with
regard to the management of event data related to healthcare
organizations, including several illustrative healthcare event data
management protocols, one skilled in the relevant art will
appreciate that the disclosed examples are illustrative in nature
and should not be construed as limiting.
[0011] FIG. 1 is a block diagram illustrating an embodiment 100 of
a network including an event management service 106. As will be
described in greater detail below, the event management service 106
includes a variety of computing devices, implementing functionality
associated with the event management service. In one aspect, the
event management service 106 functions to configure and collect
event data. Illustratively, event data corresponds to various
information associated with an identified event. By way of example,
event data can correspond to incident data associated with services
provided by a healthcare organization. Accordingly, in this
illustrative embodiment, the event management service 106 functions
to configure and collect event data related to incidents associated
with healthcare organizations. Still further, in this illustrative
embodiment, the event management service 106 can collect event data
to facilitate the processing of the event data by more than one
data processing methodology. In another aspect, the event
management service 106 functions to process the collected event
data. Illustratively, the processing of the collected event data
can include the application of various data processing
methodologies. Additionally, the processing of the collected data
can include the implementation of feedback or escalation
methodologies for additional implementation. In still a further
aspect, the event management service 106 can function to transmits
or otherwise publish the processing event data.
[0012] With continued reference to FIG. 1, various components of
the migration event management service 106 will be described.
Illustratively, the event management service 106 may be associated
with computing resources such as central processing units and
architectures, memory (e.g., RAM), mass storage or persistent
memory, graphics processing units, communication network
availability and bandwidth, etc. Generally, however, the event
management service 106 may include one or more hardware processing
units, such as one or more CPUs having logical circuitry for
executing computer-executable commands. The event management
service 106 may also include system memory, which may correspond to
any combination of volatile and/or non-volatile storage mechanisms.
The system memory may store information that provides an operating
system component, various program modules, program data, or other
components. The event management service 106 performs functions by
using the processing unit(s) to execute instructions provided by
the system memory. The event management service 106 may also
include one or more types of removable storage and one or more
types of non-removable storage. Still further, the event management
service 106 can include communication components for facilitating
communication via wired and wireless communication networks, such
as communication network 104.
[0013] Illustratively, the event management service 106 can include
or provide, among other hardware or software components, a data
collection service 108, a task/workflow service 110, and a security
service 112. In one aspect, the data collection service 108 is
operable, at least in part, to implement data collection workflows
for the collection of event data. As previously described, in one
embodiment, the data collection service 108 can facilitate the
collection of event data in a manner to support multiple data
processing methodologies that would be applied subsequent to the
collection of the event data. In another aspect, the task/workflow
service 110 is operable, at least in part, to implement data
processing methodologies for processing collected event. In still a
further aspect, the security service 112 is operable, at least in
part, to implement various security protocols related to the
collection of event data, processing of event data or maintenance
of event data on the event management service 106.
[0014] The event management service 106 can further include a data
collection workflow data store 114 for maintaining information
related to the implementation of data collection workflows. The
event management service 106 can also include an event information
data store 116 for maintain collected and processed event data.
Although the data collection workflow data store 114 and the event
information data store 116 are depicted in FIG. 1 as single data
stores, one skilled in the relevant art will appreciate that the
each of the data stores may be implemented by any number of
computing devices having data maintenance functionality.
Additionally, the data stores may distributed in a manner to be
remote from other computing devices associated with the event
management service 106. Accordingly, the depiction of the data
stores is illustrative and logical in nature.
[0015] In communication with the event management service 106 via a
communication network 104 are one or more client computing devices
102. Illustratively, the client computing devices 102 correspond to
any one of a variety of computing devices, such as desktop
computing devices, mobile devices, tablet devices, embedded devise,
and the like, that are configured to interact with one or more of
the hosted virtual machine instances via the communication network
104. By way of example, the communication network 104 may be, for
instance, a wide area network (WAN), a local area network (LAN), or
a global communications network.
[0016] With reference now to FIGS. 2A-2B, simplified block diagrams
are shown illustrating the process of configuring the event
management service 106 for the collection of event data. As
illustrated in FIG. 2A, at (1), a client computing device 102 can
specify event collection by selection of an event data collection
template. Illustratively, the event data template can identify
various types of event data that will be collected by selection of
an event type. The event data template can also identify one or
more data collection workflows that will be used by the event
management service 106 to collect information from client computing
devices 102. For example, the data collection workflows can define
logical steps utilized by the event management service 106 to
identify event data of interest. The event data template can also
specify the data processing methodologies that will be implemented
by the event management service 106 on the collected data and the
timing associated with the implementation of the data processing
methodologies. In one embodiment, a user may select from a set of
predefined data collection templates. For example, a user may be
presented with a graphical user interface that presents a data
collection template or data processing methodology to a user, such
as a list view, drop down menu, and the like. In another
embodiment, a user may be able to configure a data collection
template or modify pre-existing data collection templates.
[0017] At (2), the event management service 106 determines one or
more data collection workflows based on the selected data
collection template. The event management service 106 can utilize a
specified data collection workflow identified in the data
collection template. In another embodiment, the event management
service 106 can identify the event data that is to be collected and
generate data collection workflows based on the identified event
data to be collected. For example, in this embodiment, the event
management service 106 can identify how many data processing
methodologies will be supported and instantiate the collection of
the event data corresponding to the determination. In still a
further embodiment, the selection of the data collection template
can include declarative information that can be used as the basis
for generating the data collection workflows. At (3), the event
management service 106 stores the identified or generated data
collection workflows for subsequent implementation.
[0018] Turning now to FIG. 2B, in some embodiments, previously
specified data collection templates may be updated or modified. As
illustrated in FIG. 2B, at (1), a client computing device 102 can
specify a modification to a previously configured event collection
by selection of an updated event data collection template. As
previously described, the event data template can identify various
types of event data that will be collected by selection of an event
type. The event data template can also identify one or more data
collection workflows that will be used by the event management
service 106 to collect information from client computing devices
102. For example, the data collection workflows can define logical
steps utilized by the event management service 106 to identify
event data of interest. The event data template can also specify
the data processing methodologies that will be implemented by the
event management service 106 on the collected data and the timing
associated with the implementation of the data processing
methodologies. Illustratively, the user can specify new or
additional aspects of the data collection template.
[0019] At (2), the event management service 106 determines one or
more data collection workflows based on the selected and updated
data collection template. The event management service 106 can
utilize a specified data collection workflow identified in the data
collection template. In another embodiment, the event management
service 106 can identify the event data that is to be collected and
generate data collection workflows based on the identified event
data to be collected. In still a further embodiment, the selection
of the data collection template can include declarative information
that can be used as the basis for generating the data collection
workflows. At (3), the event management service 106 then modifies
the selected data collection workflow based on the updated data
collection template information. For example, the event management
service 106 can update logic or replace logic implemented by the
data collection workflow. At (4), the event management service 106
stores the identified or generated data collection workflows for
subsequent implementation.
[0020] With reference now to FIG. 3, a simplified block diagram are
shown illustrating the process of implementing the collection and
processing of event data by the event management service 106. At
(1), a client computing device 102 can request event collection by
transmission of a request to collect event data or request to
process an event. At (2), the event management service 106
determines, or identifies, a data collection workflow specified for
the event request.
[0021] At (3), the event management service 106 implements, or
causes to be implemented, the data collection workflow. As
previously described, illustratively, the implementation of the
data collection workflow can include the execution of data logic
for the purpose of collecting data that will be utilized in data
processing methodologies. The data collection workflow can be
characterized as a set of logic steps that may be modified or
edited based on the type of event data or changes in specified data
processing methodologies. In one embodiment, the execution of the
data collection workflow can be implemented in the presentation of
various questions or prompts presented on the client computing
device 102. Based on the information provided at each step, the
event management service 106 can utilize the logic steps to
determine whether additional information is required or if
previously submitted information should be modified.
[0022] In some embodiments, various data processing methodologies
may be implemented based on an event. In these embodiments, the
data collection workflow may include combined logic to collect
information for all the anticipated or possible data processing
methodologies. In these embodiments, the combined logic may allow
for a single collection of event data or a reduced number of
collections for the event data. Still further, in some embodiments,
the data collection workflow may be modified or updated during the
collection of the event data. In these embodiments, the logic steps
for the collection of event data can be updated or implemented in a
way to achieve the update.
[0023] With continued reference to FIG. 3, at (4), the event
management service 106 identifies one or more applicable data
processing methodologies to apply to the collected data. In one
illustrative embodiment, the event management service 106 can
implement established methodologies for determining information
about event, such as root cause analysis data processing
methodologies. In the context of health care organizations managing
event data, illustrative examples of such root cause analysis data
processing methodologies include, but are not limited to, the
London Protocol, VA Protocol, SRX System protocol, and Mayo
Protocol. In another embodiment, the event management service 106
may be configured to blend multiple data processing methodologies
or implement multiple data processing methodologies in
parallel.
[0024] Still further, the event management service 106 may be
configured to implement various pattern matching or statistical
processing methodologies to provide qualitative analysis of the
collected event data. For example, the event management service 106
can utilize previously determined behavior patterns to identify
specific event data of interest or to characterize the quality of
event data. In this example, the event management service 106 can
be trained or configured with behavior data that identifies
specific attributes, patterns, etc. indicative of quality, etc.
[0025] In another aspect, the event management service 106 can
implement the data processing methodologies to determine when an
event should be considered complete or finished. By way of example,
regulations or procedures may specify how specific events (e.g.,
such as a medical prescription error) should be handled. In this
example, the data collection workflow may attempt to collect
information about the initial event and any follow up that has
occurred (or will occur). Accordingly, the data processing
methodology may be configured to not only determine whether the
event occurred or factors related to the event, but to determine
whether the appropriate follow up actions have been completed. If
so, the event management service 106 can determine the event to be
"completed." Additionally, if an event is not completed, the data
processing methodologies can also specify actions that the event
management service 106 can subsequently implement to escalate the
event. For example, the event management service 106 can transmit
notifications or collect additional information in the situation
that an event cannot be closed or is not closed within a specified
time.
[0026] With reference now to FIG. 4, an illustrative flow-diagram
depicting a routine 400 for the management of event data is
depicted. This routine may be carried out by, for example, by one
or more services associated with the event management service 106
of FIG. 1. At block 402, the event management service 106 obtains a
request for event collection by transmission of a request to
collect event data or request to process an event. Illustratively,
the request for event collection may be transmitted by the client
computing device 102. Alternatively, the request for event
collection may be transmitted by a third party service, such as a
government agency or management service. Still further, in other
embodiments, the request for event collection may be determined
inferentially based on information obtained by the event management
service 106. For example, the event management service 106 can
obtain information indicative of an event, such as requests for
identified services (e.g., emergency personnel), communications to
specific individuals or entities (e.g., safety officers, insurance
companies), and the like.
[0027] At block 404, the event management service 106 determines,
or identifies, a data collection workflow specified for the event
request. As previously described, the data collection workflow may
be previously configured by a user or system administrator based on
a determine data collection template. In other embodiments, the
data workflow may be defined as part of the request and not
previously configured.
[0028] At block 406, the event management service 106 implements,
or causes to be implemented, the data collection workflow. As
previously described, the implementation of the data collection
workflow can include the execution of data logic for the purpose of
collecting data that will be utilized in data processing
methodologies. In some embodiments, the event management service
106 may be configured to collect event data corresponding to more
than one data processing methodology. In other embodiments, the
event management service may also prioritize portions of the data
collection workflow to prioritize portions of the event data that
are collected.
[0029] The data collection workflow can characterized as a set of
logic steps that may be modified or edited based on the type of
event data or changes in specified data processing methodologies.
In one embodiment, the execution of the data collection workflow
can be implemented in the presentation of various questions or
prompts presented on the client computing device 102. Based on the
information provided at each step, the event management service 106
can utilize the logic steps to determine whether additional
information is required or if previously submitted information
should be modified. Although block 406 is described with regard to
a single implementation of a data collection workflow, one skilled
in the relevant art will appreciate that the implementation of the
data collection workflow may be implemented in discrete portions.
Additionally, the implementation of such portions of the data
collection workflow may be defined according to previous portions
or according to time restrictions. Such definitions can control how
the event information is obtained.
[0030] At block 408, the event management service 106 identifies
one or more applicable data processing methodologies to implement
to the collected data and implements the identified data processing
methodologies at block 410. In one illustrative embodiment, the
event management service 106 can implement established
methodologies for determining information about one or more events,
such as root cause analysis data processing methodologies. In
another embodiment, the event management service 106 may be
configured to blend multiple data processing methodologies or
implement multiple data processing methodologies in parallel. As
previously described, the event management service 106 may also be
configured to implement various pattern matching or statistical
processing methodologies to provide qualitative analysis of the
collected event data.
[0031] In another aspect, the event management service 106 can
implement the data processing methodologies to determine when an
event should be considered complete or finished. By way of example,
regulations or procedures may specify how specific events (e.g.,
such as a medical prescription error) should be handled. In this
example, the data collection workflow may attempt to collect
information about the initial event and any follow up that has
occurred (or will occur). Accordingly, the data processing
methodology may be configured to not only determine whether the
event occurred or factors related to the event, but to determine
whether the appropriate follow up actions have been completed. If
so, the event management service 106 can determine the event to be
"completed." Additionally, in the event that an event is not
completed, the data processing methodologies can also specify
actions that the event management service 106 can subsequently
implement to escalate the event. For example, the event management
service 106 can transmit notifications or collect additional
information in the situation that an event cannot be closed or is
not closed within a specified time.
[0032] At block 412, the event management service 106 can then
transmit results of the processing of the collected event data. In
one aspect, the transmission of the results of the processed
collected event data can include notification to one or more users
related to the determined attributes, such as causes, related to
the events. In another aspect, the transmission of the results can
include notification to one or more users related to an escalation
or request for additional information. In still a further aspect,
the transmission of the results can include controls for requesting
audits, etc. At block 414, the routine 400 terminates.
[0033] Conditional language, such as, among others, "can," "could,"
"might," or "may," unless specifically stated otherwise, or
otherwise understood within the context as used, is generally
intended to convey that certain embodiments include, while other
embodiments do not include, certain features, elements, and/or
steps. Thus, such conditional language is not generally intended to
imply that features, elements and/or steps are in any way required
for one or more embodiments or that one or more embodiments
necessarily include logic for deciding, with or without user input
or prompting, whether these features, elements and/or steps are
included or are to be performed in any particular embodiment.
[0034] Any process descriptions, elements, or blocks in the flow
diagrams described herein and/or depicted in the attached figures
should be understood as potentially representing modules, segments,
or portions of code which include one or more executable
instructions for implementing specific logical functions or steps
in the process. Alternate implementations are included within the
scope of the embodiments described herein in which elements or
functions may be deleted, executed out of order from that shown or
discussed, including substantially concurrently or in reverse
order, depending on the functionality involved, as would be
understood by those skilled in the art. It will further be
appreciated that the data and/or components described above may be
stored on a computer-readable medium and loaded into memory of the
computing device using a drive mechanism associated with a computer
readable storing the computer executable components such as a
CD-ROM, DVD-ROM, or network interface further, the component and/or
data can be included in a single device or distributed in any
manner. Accordingly, general purpose computing devices may be
configured to implement the processes, algorithms, and methodology
of the present disclosure with the processing and/or execution of
the various data and/or components described above.
[0035] It should be emphasized that many variations and
modifications may be made to the above-described embodiments, the
elements of which are to be understood as being among other
acceptable examples. All such modifications and variations are
intended to be included herein within the scope of this disclosure
and protected by the following claims.
* * * * *