Note: Descriptions are shown in the official language in which they were submitted.
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METHODS AND SYSTEMS FOR MONITORING PATIENT SUPPORT
EXITING AND INITIATING RESPONSE
BACKGROUND OF THE INVENTION
1. Field of the Invention
The invention is in the field of patient monitoring systems and methods for
assessing and ensuring a level of quality and performance provided by a
healthcare
facility. The invention more particularly relates to ensuring that a
healthcare facility is
able to increase quality and performance based on patient specific attributes
and needs
embodied in individualized patient profiles, initiating appropriate responses
to the
patients' needs based on such profiles, and refining the patient profiles
based on
information gathered over time for each patient.
2. Relevant Technology
Healthcare facilities provide clinical and/or wellness health care for
patients
and/or residents (hereinafter collectively referred to as "patients") at such
facilities.
Hospitals and medical clinics provide clinical health care. Assisted living
and nursing
homes focus primarily on wellness health care. Most facilities provide at
least some
monitoring and supervision of patients to ensure they are receiving proper
nutrition and
medicines, are kept clean, and are protected from physical injury. A central
station (e.g.,
a nursing station) typically functions as a primary gathering and dispatch
location for
caregivers. At specified intervals, or in response to a patient or resident
request, a
caregiver can move from the central station to a patient's location (e.g.,
room) and
monitor or provide appropriate care.
There are often tradeoffs between ensuring that every patient at a facility
receives
a required level of basic care while also providing individualized care and
initiating
appropriate responses based on a patient's specific behaviors, attributes and
needs. Even
though all patients may receive the same basic level of care, some may receive
too much
care and others not enough care due to discrepancies between the basic
standards of care
and a patient's actual needs. The result is an inefficient allocation of
resources that
compromises the overall quality and performance of a facility and individual
staff
members.
There may be similar imbalances in interpreting patient behavior and
fashioning
appropriate responses. Not every patient behaves in the same manner, has the
same
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health problems and issues, or requires intervention upon the occurrence of
similar
behaviors or events. Behavior or events that may be perfectly safe for some
patients
might constitute high risk to others. For example, an elderly person at a rest
home who is
ambulatory, requires no assistance to walk, and is known to safely walk up and
down
stairs without falling should not trigger caregiver intervention when
approaching stairs.
In contrast, caregiver intervention may be appropriate when a person who is
bound to a
wheel chair, who can only safely walk with assistance, or who has difficulty
in perceiving
or evaluating danger approaches a staircase.
One specific area of concern involves unassisted bed exiting, wheelchair
exiting,
wheelchair to bed transfer, or other support exiting. Unassisted support
exiting by
invalids or the elderly is a significant cause of injury and liability. Falls
often occur due
to the inability of health care facilities to provide continuous, direct
supervision of
patients. Unfortunately, it is typically not feasible to provide round the
clock supervision
of every patient due to financial and/or logistical restraints. Nevertheless,
without
continuous direct supervision and/or a reliable system of early notification,
there may be
no way for a health care provider to know when a particular patient may be
engaging in
support exiting or other behavior which places them at high risk for falling.
Other measurements of quality and performance involve maintaining patients
within defined safety or security zones, tracking and analyzing patient gait
or daily
ambulation to diagnose potential injury or health issues, tracking patient
contacts with
assigned caregivers and/or third parties, monitoring patient socialization,
initiating patient
surveillance upon the occurrence of a triggering event, tracking staff
movements and
activities, tracking visitor movements and activities, responding to patient
initiated calls
or alerts, tracking assets used to provide patient care (e.g., medical
devices, walkers,
dentures, etc.), verifying the occurrence of prescribed treatments for each
patient, and the
like.
Notwithstanding the need to monitor and supervise patients to ensure an
adequate
level of quality and performance and prevent patient injury, the United
States, Europe,
Japan and other parts of the world are currently experiencing a serious
shortage of nurses,
nursing assistants, doctors, and other caregivers. Such shortage will only
worsen with
continued aging of the population. As the patient to caregiver ratio at a
facility increases,
the ability to provide adequate patient care and protection are likely to
decrease as more
patients are left unattended. There is therefore an acute need for new methods
and
systems that can better safeguard patients and improve the quality and
performance of
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care delivery at a facility while also reducing facility liability, enhancing
caregiver
productivity, and lowering operational expenses.
Although automated patient monitoring systems have been proposed, they
typically lack feasibility and have not been implemented on a wide scale. The
problem
with conventional patient monitoring systems is their inability to interpret
and distinguish
between safe or appropriate patient behaviors or conditions and those that are
potentially
dangerous or inappropriate as among different patients. Standard limits and
alarm levels
may be too tight or too loose depending on the patient. The result can be a
high
incidence of false positives in the case where limits and alarm levels are too
tight and
false negatives in the case where limits and alarm levels are too loose. A
high rate of
false positives can become like the boy crying wolf and might be ignored by
overworked
caregivers. False negatives provide no early warning of potential patient
harm.
For example, one type of patient monitoring system utilizes sensors to detect
patient bed exiting. A common problem that leads to a high level of false
positives and
false negatives is a "one size fits all" approach to detecting and
interpreting patient
movements. Although people often have uniquely personal ways of getting out of
bed,
no attempt is made in conventional monitoring systems to understand the
specific
movements and habits of a particular patient when bed exiting. For example,
one patient
might typically grasp the left handrail when commencing to bed exit while
another might
slide towards the foot of the bed. Persons who are left handed might exit
their beds
oppositely from right handed persons. Certain medical conditions might
determine or
alter bed exiting behavior (e.g., a person with a newly formed incision might
protect
against harm or pain by avoiding movements that would apply stress to the
incision, even
if such movements were previously used to bed exit when the patient was
healthy).
In view of the foregoing, it would be an advancement in the art to provide
methods and systems for monitoring patient, staff and visitor activities that
can more
accurately detect and interpret individual behaviors and conditions as they
pertain to the
overall quality and performance by a facility in delivering health care to its
patients.
Reducing the incidence of false positives and false negatives when detecting
actionable
events would be expected to increase the ability of a healthcare facility to
provide an
appropriate response thereto, intervene when necessary to prevent harm to a
patient, and
increase the overall quality and performance of the facility in providing for
the specific
needs of a patient as among a plurality of different patients.
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SUMMARY OF THE INVENTION
The present invention relates to patient monitoring methods and systems used
to
ensure an appropriate level of quality provided to the patients and
performance by staff
and visitors at a healthcare facility. Real time data regarding the locations,
movements
and/or behaviors of each of a plurality of patients, caregivers, visitors and
assets is
obtained from multiple sources and analyzed by a computer system (e.g.,
facility master).
The computer system meaningfully interprets the data through the use of
individualized
patient specific profiles in order to interpret the overall quality of service
provided to
each patient at a healthcare facility. In addition, the individual performance
by staff and
visitors, as they relate to the overall performance of the facility, can be
evaluated through
the use of staff and visitor specific profiles. When a patient, staff or
visitor specific limit
is approached or breeched, the computer system may initiate an appropriate
response to
prevent or mitigate patient harm, unauthorized access to restricted zones, or
other
inappropriate or harmful actions.
Data regarding the location, movements and/or behaviors of patients, staff,
visitors and assets throughout or outside a facility can be gathered using any
detection
means known in the art including, but not limited to, RFID devices, an RFID
detection
grid, GPS devices, cameras, motion detectors, light beam detectors, image
analysis
systems and the like. In-room surveillance cameras can be used to generate a
data stream
that is interpreted by a local computer system (e.g., in room controller),
such as to detect
movements or behaviors that may lead to unassisted support exiting by a
patient. Motion
and light beam detectors may also be used to detect patient, staff or visitor
movements
and generate data that can be analyzed by the computer system.
When a limit or alarm level is reached, a video feed from a surveillance
camera
may be sent to a nursing station for verification or denial by staff that a
triggering event
actually occurred and that a response is required to prevent or mitigate
patient harm or
prevent inappropriate activity. The verification or denial by staff forms an
information
feedback loop that can be used to refine patient, staff or visitor profiles to
tighten or
loosen limits or alarm levels as appropriate to more accurately identify the
occurrence of
triggering events in the future. Profiles can also be updated to reflect the
occurrence of
non-occurrence of prescribed activities, as may be automatically determined by
tracking
the locations of patients, staff, assets and visitors at a facility. The
refinement of profiles
over time allows the system to "learn" and store individualized data regarding
the
specific behaviors, attributes and performance of patients, staff or visitors
at the facility.
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This reduces the instances of false positives and false negatives as it
relates to detecting
triggering events.
Examples of quality and performance criteria (e.g., care and wellness)
include,
but are not limited to, ensuring the general safety of patients (e.g.,
preventing and/or
5 intervening in the case of unassisted support exiting, maintaining patients
within
prescribed geographic zones within or without a facility, responding to
patient
emergencies or alerts, and the like), assessing the status of prescribed
actions (e.g., which
involve caregivers, assets, patient-initiated behaviors, and the like), and
assessing the
status of patient's general health and well being (e.g., patient nutrition,
ambulation
tracking, denture use, use of walking aids, socialization, privacy, pain
level, rollovers to
prevent bed sores, and the like).
Many quality, performance, care and wellness parameters can be measured by
tracking the location of each patient relative to the locations of caregivers,
other patients,
visitors, assets and/or fixed objects or locations. Certain care regimens or
activities
involve interactions between patients and assigned caregivers and/or assets at
specified
locations, often for specific durations or time intervals. Other aspects of
quality and
performance involve the movement of patients between certain specified
locations
throughout a facility, often at defined time periods. Yet others may involve
interactions
between multiple patients and/or patients and visitors. Individualized care
and wellness
parameters can be established, verified and refined through the use of
specific patient
profiles, sometimes in conjunction with staff and/or visitor profiles. By
refining patient
specific profiles based on gathered data relating to the specific behaviors
and needs of
each patient, the inventive systems and methods are able to interpret
behaviors,
conditions and events in a highly individualized manner as among different
patients at a
healthcare facility. Appropriate alarms, limits and prescriptions may be set
for each
patient as appropriate based on data contained in the patient specific
profiles.
A typical patient profile includes both static and dynamic data relating to a
plurality of specific care and wellness parameters. These may include, for
example,
limits or alarm levels relating to one or more of support exiting behavior and
occurrence,
patient ambulation, the use of ambulation devices, patient gait behavior,
sound of patient
breathing, dietary restrictions, prescribed levels of caregiver assistance for
one or more
activities, trips to cafeteria, assisted and/or unassisted bed turning, social
interactions,
prescribed patient care regimens, in-room therapy, required therapeutic
devices, denture
use and cleaning, bathroom time duration, facility access or movement
privileges, facility
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exiting privileges, flight risk level, facility restricted areas, emergency
call button usage,
pet therapy contact, patient treatment by movement of, e.g., facility assets
and/or
personnel, critical medical history, and/or emergency contact information.
When a patient first enters a facility, a general patient profile of common or
known patient specific behaviors may be utilized before specific information
is learned
about the patient through the information feedback loop. As the profile is
periodically
refined based on verified and/or rejected patient behaviors relative to a
specific risk or
activity, it becomes more accurately predictive of actual risk or behavior by
the patient.
That reduces the incidence of false positives and false negatives and allows
for earlier
intervention into the risk sequence. According to one embodiment, patient
profiles
having initially coarse granularity due to the lack of known patient behaviors
and
attributes may have increasingly fine granularity as the profiles are refines
over time.
Increasing profile granularity may account for idiosyncratic movements or
behaviors that
are entirely unique to a particular patient in addition to the commonly
observed
movements or behaviors common to many patients.
Profile data can be uploaded to networked or peripheral computers as needed to
carry out a desired patient monitoring activity. An information feedback loop
can be
used to update each patient profile, which may occur automatically or manually
as
directed by patient and/or staff actions, in order to create and maintain a
current database
of patient status, attributes and needs. Actions that might be used to refine
patient
specific profile data include, for example, patient movements that precede
support
exiting, changes in patient gait, social interactions, recursive events,
patient wandering or
flight, use of emergency call button, sound of patient breathing, patient
eating habits,
observations by caregivers regarding patient behavior or condition, and
patient treatment
by movement of, e.g., facility assets and/or personnel. Information may be
gathered for
analysis by the computer system by means of RFID devices carried by patients,
staff,
assets, and visitors, RFID detection grids, still shot cameras, video cameras,
audio
recording devices, GPS devices, etc.
In the case where a triggering event is detected and verified, an alert for
direct
physical intervention may be sent to a staff member assigned to a particular
patient or
who is close to the patient and not otherwise occupied. The alert may be sent
to a
personal data assistant carried by each caregiver. The alerted staff member
can send
verification that intervention was successful. The RFID device carried by the
responder
can also be tracked automatically to verify that intervention has occurred.
Examples of
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triggering events include preventing unassisted support exiting, preventing
patient
wandering into unauthorized zones, preventing patient flight from the
facility, and
preventing patient abuse by caregivers, other patients or visitors.
An example of using a patient specific profile to improve patient wellness
involves detecting and then preventing or mitigating potential harm caused by
unassisted
patient support exiting. The inventive methods and systems can be used to
monitor a
patient resting on a bed (e.g., standard hospital bed with side rails),
wheelchair, gurney,
couch, chair, or recliner, to which the patient may be confined and detect
movements or
behaviors that are predictive of support exiting. Monitoring may be performed
by one or
more cameras, motion sensors, small zone RFID, and/or light beam detectors. A
computer system analyzes a data stream and detects movements or behaviors that
are
predictive of support exiting. The use of patient specific profiles helps the
computer
system distinguish between movements that are predictive of support exiting
and
movements that are not.
If behavior predictive of support exiting by a patient is detected, an
appropriate
response is triggered, examples of which include one or more of alerting
staff,
establishing two-way audio-video communication between staff and the patient,
sending
prerecorded audio and/or video warnings to the patient's room, direct
intervention by a
staff member, and automated functions, such as bed lowering, raising a
bedrail, turning
on a light, or actuation of a patient restraint device. Similar algorithms
involving analysis
of video data streams can be used to detect other movements by a patient such
as patient
rollover (e.g., to prevent skin damage), movements indicative of disease,
movements
consistent with prescribed behaviors, and the like.
An information feedback loop provided by a system of cameras and monitors
permits human inspection and verification of patient support exiting before
initiating
audio, visual and/or physical intervention. A video feed of the patient is
sent to a monitor
at a central station (e.g., nursing station) subsequent to a visual and/or
aural alert to both
the nursing station and the patient's room. A staff member views the live
video stream
from the patient's room to determine if the patient is actually attempting to
exit the
support. If so, verification is provided to the computer system by the staff
member and
appropriate intervention to prevent or assist support exiting is initiated. If
not, rejection is
provided to the computer system. If no response to the alert is given within a
prescribe
time period, an automated response may be initiated, such as sending a pre-
recorded
message or warning to the patient and/or alerting nearby staff for direct
physical
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intervention.
The information feedback loop can also be used to update a patient profile to
better predict future support exiting. The action of verifying or rejecting an
automated
support exiting alert based on actual patient movements and behavior can be
recorded by
the computer system and used to refine the patient profile (e.g., tightening
or loosening
limits) in order to better predict future support existing. The information
feedback loop
can also be used to refine other limits or data in the patient profile. For
example, if the
monitoring system detects patient movements that may be indicative of flight
from the
facility, wandering into unauthorized zones, or substantial changes in patient
gait, an alert
may be triggered and a video feed of the patient sent to a central nurse's
station. Two-
way communication can also be established to determine the patient's actual
intentions or
needs. Based on actual patient behavior, limits can be tightened or loosened
to better
predict patient flight risk, wandering, or health issues relating to gait.
In the case where a video data stream is generated by a surveillance camera,
such
as to detect support exiting or other high risk patient behavior, it is
typically deleted on an
ongoing basis to protect patient privacy. If the video stream is made
available for
viewing (e.g., by being sent to a nursing station), an alert is sent to the
patient to notify of
potential third party viewing to protect privacy (e.g., by means of a chime,
recording,
visual display of words, etc.). In some cases, the video data stream may be
optionally
archived (e.g., recorded on a non-volatile recording medium) for later viewing
and
analysis of an event. The archived video can be used to assess the overall
quality and
performance of a healthcare facility. Events that might trigger video
archiving include
entry into the patient's room or personal space by staff, visitors or other
patients, manual
alerts or distress signals sent by a patient, detection of other dangerous
conditions (e.g.,
alterations of vital signs), and requested archiving by visiting relatives,
friends, doctors or
other health care providers.
The location of patients can be continuously tracked by means of an assigned
RFID device worn or carried by each patient that emits a signal that can be
detected and
traced to a specific location by an RFID sensor grid. The RFID device may
include an
alert device that can be activated in case of emergency of other urgent need.
Because the
RFID device also provides means for locating the patient, assistance can be
provided
quickly even if the patient cannot communicate. Two-way audio-visual
communication
may be initiated via a camera, video monitor, microphone and speaker. The
alerting
system may access the patient's profile in order to tailor the response to
specific patient
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needs. Patient usage of the alert feature can be tracked, analyzed and used to
update the
patient's profile. For example, a patient profile may include data relating to
proper
and/or improper usage of the patient alert button.
In summary, computer controlled methods and systems can be used for
monitoring the location and/or activities of patients, staff, assets and
visitors and as they
relate to prescribed care and wellness, responding to actionable events,
verifying wellness
events, maintaining and updating patient, staff and visitor profiles,
preventing or
mitigating patient injury, locating and assisting patients in need of
assistance, and
monitoring and archiving video information relating to potentially dangerous
activities.
These and other advantages and features of the present invention will become
more fully apparent from the following description and appended claims, or may
be
learned by the practice of the invention as set forth hereinafter.
BRIEF DESCRIPTION OF THE DRAWINGS
In order to describe the manner in which the above-recited and other
advantages
and features of the invention can be obtained, a more particular description
of the
invention briefly described above will be rendered by reference to specific
embodiments
thereof which are illustrated in the appended drawings. Understanding that
these
drawings depict only typical embodiments of the invention and are not
therefore to be
considered to be limiting of its scope, the invention will be described and
explained with
additional specificity and detail through the use of the accompanying
drawings, in which:
Figure 1 schematically illustrates various exemplary computer-client network
protocols that can be used to facilitate communication between a facility
master computer
system and peripheral clients;
Figure 2 schematically illustrates an exemplary facility monitoring master
system;
Figure 3 schematically illustrates exemplary computer architecture that
facilitates
facility, patient, staff and/or asset monitoring and event response
management;
Figure 4 is a flow chart that illustrates an exemplary method for managing a
response to an actionable event in a healthcare facility;
Figure 5 is a flow chart that illustrates an exemplary method for maintaining
alarm levels in a patient risk profile for a patient of a healthcare facility;
Figure 6 is a flow chart that illustrates an exemplary method for determining
patient care and wellness using individualized patient profiles;
Figure 7 schematically illustrates the interrelationship of various data
gathering
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and analysis modules used to maintain and refine a patient profile;
Figure 8 is a flow chart that illustrates an exemplary method for maintaining
stored profiles for a plurality of patients at a healthcare facility;
Figure 9 schematically illustrates an exemplary system for patient monitoring,
5 alert and response;
Figures 1OA and l OB schematically illustrate exemplary configurations of
patient
rooms at a healthcare facility equipped for patient monitoring and response to
support
exiting;
Figure IlA and 11B schematically illustrate alternative patient support
exiting
10 detection systems;
Figure 12 is a flow chart that illustrates an exemplary method for monitoring
a
patient on a support, detecting possible support exiting, and initiating a
response to
prevent or mitigate patient harm;
Figures 13A-13E schematically depict a patient in various exemplary positions
on
a bed relative to known bed exiting behaviors;
Figure 14 is a flow chart that illustrates an exemplary method for generating
and
updating a patient profile that contains data relating to support exiting
behavior of that
patient;
Figure 15 is a flow chart that illustrates an exemplary method for responding
to a
computer predicted support exiting event;
Figure 16 is a decision chart that illustrates an exemplary decision sequence
for
responding to an alert of predicted bed exiting;
Figure 17 is a flow chart that illustrates an exemplary method for providing
an
automated response to a patient initiated alert; and
Figure 18 is a flow chart that illustrates an exemplary method for selective
archiving of a video data stream of a patient in response to a triggering
event.
DETAILED DESCRIPTION OF THE PREFFERED EMBODIMENTS
1. INTRODUCTION
Embodiments of the present invention extend to methods, systems, and computer
program products for managing quality of care and performance by staff and
visitors at a
healthcare facility. The invention more particularly relates to computer-
controlled
methods and systems for monitoring a plurality of patients, staff, assets and
visitors at the
facility using electronic devices, computers, patient profiles, staff
profiles, visitor
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profiles, algorithms, human verification of triggering events, and direct
human
intervention to provide improved quality of care and performance based on each
patient's
general and individualized needs.
Patient specific data can be collected for each patient to create a database
of
generalized and personalized knowledge. Healthcare facilities and providers
can use the
database of knowledge to better understand risks associated with various
activities for
each patient and/or for each type of activity. Predictive modeling and
artificial
intelligence can be applied to collected data patterns to identify, process,
categorize,
alarm, and rectify risks based on patient information, such as, for example,
patient type,
patient activity, patient medications, patient physical therapy process,
patient location,
and other variables.
The quality and performance monitoring systems and methods of the invention
assist caregivers at a facility in ensuring and verifying that each patient at
the facility
receives a prescribed level of care and also helps ensure wellness for each of
a plurality
of patients based on one or more predetermined wellness criteria. To be sure,
there are
general aspects and levels of patient care and wellness that may be
substantially similar
for some or all patients, including the need for adequate rest, nutrition,
cleanliness, safety,
privacy, and the like. On the other hand, some or all patients may require
specialized
care and have different wellness criteria based on individual patient needs
(e.g., based on
age, physical capacity, mental capacity, and the like).
The quality and performance systems and methods of the invention monitor care
and wellness for each patient by means of automated tracking of patients,
caregivers and
assets used to deliver care, and visitors. The inventive methods and systems
track patient
location, activities, condition, and regimen completion, as well as assigned
caregiver and
asset location, activities and regimen completion. Care and wellness are
measured in
relation to individual patient profiles which are maintained and periodically
refined for
each patient. The quality and performance of staff and visitors can also be
monitored and
assessed using staff and visitor profiles. According to one embodiment, the
methods and
system initiate responses to pre-determined triggering events to prevent or
mitigate
patient harm.
The methods and systems are implemented using a computer-controlled electronic
patient monitoring system that receives and analyzes data generated by a
network of
electronic data generating devices. A profile maintenance and refinement sub-
system and
method is used to periodically update and refine patient, staff and visitor
profiles as data
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is received and analyzed for individual patients, staff and visitors. The care
and wellness
of a patient, as well as the performance of staff and visitors, can be
analyzed and
improved through the use of individually refined profiles.
The term "patient profile" shall refer to stored data that is associated with
a
specific patient at a health facility. Patient profiles typically include
static data and
dynamic data. Dynamic data refers to limits and alarms that are continuously
or
periodically updated or refined based on information learned about the patient
and/or
changing patient needs or requirements. Dynamic data can be automatically
updated in
response to events or it may be manually updated by staff after an event.
The terms "care" and "wellness" shall be broadly understood to cover every
aspect of a patient's life and well being that are relevant to care and
treatment at a health
facility. Care more particularly relates to treatments, activities and
regimens that are
provided to the patient in order to ensure a prescribed or minimum level of
general health
and well-being. Wellness is a measure of the general health and well-being of
the
patient. Care and wellness affect the overall quality and performance of a
healthcare
facility.
The term "patient fall" shall be broadly understood to include falling to the
ground or floor, falling into stationary or moving objects, falling back onto
a support, or
any other falling motion caused at least in part by gravity that may
potentially cause
physical injury and/or mental or emotional trauma.
The terms "rest" and "resting" as it relates to a patient resting on a support
shall
be broadly understood as any situation where the support provides at least
some counter
action to the force of gravity. Thus, a patient may "rest" on a support while
lying still,
sitting up, moving, lying down, or otherwise positioned relative to the
support so long as
the support acts in some way to separate a patient from the floor or surface
upon which
the support is itself positioned.
The terms "continuous monitoring" and "continuous video data stream" include
taking a series of images that may be spaced apart by any appropriate time
interval so
long as the time interval is sufficiently short that the system is not unduly
hampered from
initiating a response in time to prevent or mitigate a potentially dangerous
event.
The terms "receiving" and "inputting" in the context of a patient profile
broadly
includes any action by which a complete or partial patient profile, or any
component
thereof, is stored or entered into a computer system. This includes, but is
not limited to,
creating a profile and then storing or entering it into a computer, entering
data which is
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used by the computer to generate a new patient profile, and/or storing or
entering data
used by a computer for updating a pre-existing patient profile already in the
computer.
Those skilled in the art will appreciate that the invention may be practiced
in
network computing environments with many types of computer system and
electronic
device configurations, including, personal computers, desktop computers,
laptop
computers, hand-held devices, multi-processor systems, microprocessor-based or
programmable consumer electronics, network PCs, minicomputers, mainframe
computers, mobile telephones, PDAs, one-way and two-way pagers, Radio
Frequency
Identification ("RFID") devices (e.g., bracelets, tags, etc.), global position
("GPS")
devices, and the like. The invention may also be practiced in distributed
system
environments where local and remote computer systems, which are linked (either
by
hardwired data links, wireless data links, or by a combination of hardwired
and wireless
data links) through a network, both perform tasks. In a distributed system
environment,
program modules may be located in both local and remote memory storage
devices.
Embodiments of the present invention may comprise or utilize a special purpose
or general-purpose computer including computer hardware, as discussed in
greater detail
below. Embodiments within the scope of the present invention also include
physical and
other computer-readable media for carrying or having computer-executable
instructions
or data structures stored thereon. Such computer-readable media can be any
available
media that can be accessed by a general purpose or special purpose computer.
By way of
example, and not limitation, physical computer-readable media can comprise
computer-
readable storage media, such as, RAM, ROM, EEPROM, CD-ROM or other optical
disk
storage, magnetic disk storage or other magnetic storage devices, or any other
medium
which can be used to store desired program code means in the form of computer-
executable instructions or data structures and which can be accessed by a
general purpose
or special purpose computer.
A "network" is defined as one or more data links that enable the transport of
electronic data between computer systems and/or modules and/or other
electronic
devices. When information is transferred or provided over a network or another
communications connection (either hardwired, wireless, or a combination of
hardwired or
wireless) to a computer, the computer properly views the connection as a
computer-
readable medium. Thus, by way of example, and not limitation, computer-
readable media
can comprise a network or data links which can be used to carry or store
desired program
code means in the form of computer-executable instructions or data structures
and which
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can be accessed by a general purpose or special purpose computer.
Computer-executable instructions comprise, for example, instructions and data
which cause a general purpose computer, special purpose computer, or special
purpose
processing device to perform a certain function or group of functions. The
computer
executable instructions may be, for example, binaries, intermediate format
instructions
such as assembly language, or even source code. Although the subject matter
has been
described in language specific to structural features and/or methodological
acts, it is to be
understood that the subject matter defined in the appended claims is not
necessarily
limited to the described features or acts described above. Rather, the
described features
and acts are disclosed as example forms of implementing the claims.
H. COMPUTER-IMPLEMENTED ELECTRONIC PATIENT MONITORING
SYSTEM AND METHOD FOR MEASURING AND VERIFYING
QUALITY AND PERFORMANCE
A. Exemplary System Architecture
According to one currently preferred embodiment, the quality and performance
monitoring systems and methods of the inventions are implemented by means of a
computer system. The computer system may include one or more centralized
computers,
referred to as a "facility master", and one or more localized computers,
exemplified by
one or more "in room controllers". The various computers within the overall
computer
system divide up the task of receiving and analyzing data gathered from the
overall
patient monitoring system. Figure 1 schematically illustrates the relationship
between
various components of an exemplary computerized system that can assist in
monitoring
the location, behavior and attributes of a plurality of patients, staff,
assets and visitors at a
healthcare facility.
As seen in Figure 1, a facility master computer system 101 receives data
regarding patients, staff, visitors and assets from a variety of data
collection clients 102
within and outside a facility. These include, for example, in room controller
clients 102a,
room associated clients 102b, support exiting monitoring clients 102c, care
giver system
clients 102d, facility patient, staff, visitor and asset tracking and location
clients 102e,
external facility patient, staff and asset tracking clients 102f, facility
audio/visual clients
102g, external facility audio/visual clients 102h, and nursing station clients
102i. The
data gathered or generated by the data collection clients 102 is sent to the
facility master
computer system 101 by means of communication pathways 103 for analysis,
response,
and report. In some cases, a localized computer, such as an in room controller
client
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and/or nursing station client 102i, may perform its own analysis of gathered
data in order
to compartmentalize or bifurcate the tasks provided by the various computers
of the
computer system in order to more efficiently use the computer system resources
and
reduce bottle necks.
5 The communication pathways 103 used to communicate gathered data from
clients 102 to facility master computer 101 are exemplified by satellite 103a,
paging
network 103b, PLC/BPL 103c, infrared network 103d, cable/telephone network
103e,
cellular/PCS/UWB system 103f, IEEE 802.xx wireless 103g (e.g., Wi-Fi, Wi-Max,
Zigbee, etc.), RF1D/GPS 103h, wireless and wired broadback internet 103i, and
10 public/private frame relay network 103j (e.g., MPLS). According to one
embodiment,
data from facility master computer 101 can be periodically archived and/or
analyzed at a
backup facility monitoring master system 104 (e.g., via network 105).
Figure 2 schematically illustrates an exemplary facility master computer
system
200 that can be used to control and implement quality and performance
monitoring
15 systems and methods according to the invention. Communications interface
and protocol
converter 201 can receive communications in accordance with one of the various
protocols of Figure 1 and can convert the communication so as to be compatible
with a
processing system 202. Storage 203 can store data used and produced by the
processing
system 202, examples of which include archived audio/video data 204a (e.g.,
archived in
response to detection of an actionable event), profile data 204b (e.g.,
patient, staff and
visitor data), and algorithms 204c used to process data and initiate
appropriate responses
and reports. Memory 205 can be used to buffer and quickly access short term
data used
or generated by the processing system 201.
The facility master computer system 200 includes exemplary system components
206, which are modules or applications that process data gathered by data
collection and
processing devices (e.g., clients 102 of Figure 1). Some of these modules or
applications
can also be run, at least in part, by local computers, such as in room
controller clients (not
shown). These include audio/video management 206a, in room client management
206b,
care giver systems management 206c, facility personnel location management
206d,
facility asset tracking and location management 206e, external facility asset
and
personnel tracking management 206f, external facility audio/video management
206g,
patient care interface and protocol management 206h, system security manager
206i,
report generator manager 206j, remote application interface 206k, data
modeling
subsystem 2061, alarm manager/generator 206m, and asset management subsystem
206n.
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Figure 3 illustrates an exemplary computer-implement monitoring system 300
that monitors patients, staff, assets and visitors, assesses quality and
performance, and
manages event responses at a healthcare facility. Monitoring system 300
includes a
networked computer system 301, which is composed of a main computer system
301a
(e.g., facility master) located in a data center 302, first peripheral
computer system 301b
(e.g., in room controller client) at patient location 303, and second
peripheral computer
system 301c at a central station (e.g., nurse's station). The use of an in
room controller
computer to analyze data regarding a patient within a patient room is more
particularly
illustrated in Figures IOA and IOB, which are discussed more fully below. Each
computer system 301a-c can be connected to a network, such as, for example, a
Local
Area Network ("LAN"), a Wide Area Network ("WAN"), or even the Internet. The
various components can receive and send data to each other, as well as other
components
connected to the network. Networked computer systems constitute a "computer
system"
for purposes of this disclosure.
Networks facilitating communication between computer systems and other
electronic devices can utilize any of a wide range of (potentially
interoperating) protocols
including, but not limited to, the IEEE 802 suite of wireless protocols, Radio
Frequency
Identification ("RFID") protocols, infrared protocols, cellular protocols, one-
way and
two-way wireless paging protocols, Global Positioning System ("GPS")
protocols, wired
and wireless broadband protocols, ultra-wideband "mesh" protocols, etc.
Accordingly,
computer systems and other devices can create message related data and
exchange
message related data (e.g., Internet Protocol ("IP") datagrams and other
higher layer
protocols that utilize IP datagrams, such as, Transmission Control Protocol
("TCP"),
Remote Desktop Protocol ("RDP"), Hypertext Transfer Protocol ("HTTP"), Simple
Mail
Transfer Protocol ("SMTP"), etc.) over the network.
In some embodiments, a multi-platform, multi-network, multi-protocol, wireless
and wired network architecture is utilized to monitor patient, staff, visitor,
and asset
locations and movements within a facility. Computer systems and electronic
devices
may be configured to utilize protocols that are appropriate based on
corresponding
computer system and electronic device on functionality. For example, an
electronic
device that is to send small amounts of data a short distance within a
patient's room can
be configured to use Infrared protocols. On the other hand, a computer system
configured to transmit and receive large database records can be configured to
use an
802.11 protocol. Components within the architecture can be configured to
convert
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between various protocols to facilitate compatible communication. Computer
systems
and electronic devices may be configured with multiple protocols and use
different
protocols to implement different functionality. For example, an in room
controller or
other computer system 301b at patient location 303 can receive patient data
via infrared
from a biometric monitor and then forward the patient data via fast Ethernet
to computer
system 301a at data center 302 for processing.
Computer system 301c can be physically located at a central station 304 of a
healthcare facility, e.g., a nursing station. Provider 305 (a nurse or other
healthcare
worker) can be physically located near computer system 301c such that provider
305 can
access electronic communications (e.g., alarm 320, video feeds, A/V
communications)
presented at computer system 301c. Acknowledgment 321 can be sent to other
computer
systems 301a, 301b as appropriate to verify that alarm 320 was considered by
provider
305. Other healthcare providers, such as providers 306 and 307, can be
physically
located in other parts of a healthcare facility. Healthcare providers can move
between
different locations (e.g., central station 304, patient rooms, hallways,
outside the building,
etc.). Accordingly, healthcare providers 306, 307 can also carry mobile
computer
systems (e.g., laptop computers or PDAs 308 and 309) and other types of mobile
devices,
(e.g., pagers, mobile phones, GPS devices, or RFID devices). As providers 306,
307
move about a healthcare facility they can still access electronic messages
(e.g., alarms)
and send messages.
Computer system 301b, storage device 310, sensors 312, and UO devices 313 can
be physically located at patient location 303, such as patient rooms, common
areas,
hallways, and other appropriate locations throughout or outside a healthcare
facility. For
example, patient location 303 can be a room of a patient 314. Sensors 312 can
include
various types of sensors, such as, for example, video cameras, still cameras,
microphones,
motion sensors, pain scale sensors, pressure sensors, acoustic sensors,
temperature
sensors, heart rate monitors, conductivity sensors, RFID detectors, global
positioning
sensors ("GPS"), manual assistance switches/buttons, bed sensors, handrail
sensors,
mattress sensors, location sensors, oxygen tank sensors, support location
sensors, call
buttons, etc. Although depicted separately, I/O devices 313 can also be
sensors. Sensors
and 1/0 devices can also send data to any appropriate computer system for
processing and
event detection, including either or both of computer systems 301a and 301c.
Some sensors 312 can be stationary (e.g., mounted at patient location 303)
such
that the sensors sense patient, staff, asset or visitor characteristics when
within a specified
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vicinity of the sensor 312. For example, characteristics of a patient's gait
can be
observed when the patient walks by a video camera or closely spaced apart
location
sensors. A patient's gait can be monitored by measuring the time it takes a
patient to
move between localized points or zones. Other sensors can be mobile and move
with a
patient, provider, asset or visitor as they move about a healthcare facility.
For example, a
heart rate monitor can be attached to a patient and move with the patient to
continuously
monitor the patient's heart rate. As a patient, provider, asset or visitor
moves about a
healthcare facility, different combinations of stationary and mobile sensors
can monitor
the patient, provider, asset or visitor at different locations and/or times.
Each of sensors 312 can provide input to computer system 301b. Event detection
module 316 can monitor and process inputs from sensors 312 to detect if a
combination
of inputs indicates the occurrence of a potentially actionable event 317.
Detecting the
occurrence of event 317 can trigger the transfer of various electronic
messages from
computer system 301b to other networked computers of the monitoring system
300. For
example, electronic messages (alarm messages 320 regarding event 317) can be
transferred to computer system 301c and/or mobile devices to alert health care
providers
of an actionable event 317. Alternatively or in addition, electronic messages
including
patient data 322 can be transferred to other computer systems, such as
computer system
301a, that process the patient data 322 (e.g., for refining patient profiles
324 stored in
storage 326). Alarm levels 325 can be sent to computer system 301b for use in
determining whether an event 317 is actionable.
One or more of sensors 312 can be used to detect patient conditions or
performance, such as support exiting, ambulation, changes in gait, social
interaction,
breathing, etc. RFID zones separated by specified distances can be used to
measure total
ambulation distances and monitor speed or interruptions in speed as a patient
walks.
Image analysis can determine the manner of a patient's walk and/or support
exiting.
Computer system 301b can buffer sensor input at storage device 310 for some
amount of
time before discarding the input (e.g., video data). In response to detecting
the
occurrence of an event 317, computer system 301b can locally archive sensor
input or
data from I/O devices 908 at storage device 310 (e.g., A/V data 328). Buffered
and/or
archived sensor input can provide the basis for patient data 322 that is
transferred to other
computer systems.
Event occurrences can be detected in accordance with a risk profile associated
with a monitored patient. Patient profiles 324, either accessed directly from
computer
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system 301a or stored locally in storage 310, can be used to analyze data from
sensors
312. Alternatively, alarm levels 325 can be used independently of a patient
profile 324
by local computer system 301b. Based on differing patient profiles 324 and/or
alarm
levels 325 for a plurality of patients, a combination of inputs detected as
the occurrence
of an (actionable) event 317 for one patient is not necessarily detected as
the occurrence
of an (actionable) event 317 for another patient, and vice versa. An
actionable event can
be detected when a specified alarm level for a given patient is satisfied. For
example, a
specified combination of risk behaviors and/or vital signs can cause an
actionable event
to be detected.
Computer system 301a and storage device 326 can be physically located at data
center 302. Storage device 326 can store profiles (e.g., profiles 324a and
324b) for
patients, staff and visitors. Profile manager 330 can receive patient data 322
sent to
computer system 301a (e.g., in response to a detected event) and refine a
corresponding
patient profile 324 in accordance with the patient data 322. As data related
to a patient
314 changes, the patient's profile 324 can be modified to indicate changed
risks, limits
and alarm levels for the patient 314. Risk profiles for a patient can be
iteratively refined
as patient data 322 for the patient 314 is received. Algorithms for refining
profiles can be
recursed on a per iteration basis.
Patients, providers, visitors and assets may carry RFID transmitting devices,
which are examples of a sensor 312, each having a unique signature such that
an RFID
transmitting device can be used to determine the location of a patient,
provider, visitor or
asset within a healthcare facility. RFID transmitting devices can be non-
removable, such
as a bracelet or an adhesively attached pad, or removable, such as an employee
badge.
B. Event Response
Appropriate responses to an alert or alarm of an event can be provided through
communication among and between computer systems. The difference between an
alert
and alarm is one of severity. If a trigger is minimally exceeded, an alert is
activated.
Typical alert responses include notification of event to the nursing station,
establishment
of A/V contact with patient, sounding of a tone, or verbally dispatching staff
to
investigate the situation. Significantly exceeding trigger value or ignored
alerts will
generate alarms, which typically activate an automatic PDA dispatching of
staff, A/V
contact and report generation.
Figure 4 illustrates a flow chart of a method 400 for managing a response to
an
actionable event in a healthcare facility. Method 400 will be described with
respect to the
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components and data in monitoring system 300 of Figure 3. Method 400 includes
an act
401 of accessing input from sensors monitoring a patient in accordance with a
patient risk
profile 324. Further discussion regarding patient profiles is set forth later.
Method 400 further includes an act 402 of detecting the occurrence of a
patient
5 related event. For example, event detection module 316 can detect the
occurrence of
event 317 for patient 314 (from the input of one or more of sensors 312).
Thereafter, an
act 403 involves determining whether the detected event is an actionable event
based on a
patient risk profile 324 and/or alarm level 325. Profile manager 330 can
create alarm
levels 325 which are sent to event detection module 316 of computer system
301b.
10 Alarm levels 325 can include one or more combinations of values for inputs
from sensors
312 that indicate an actionable event based on profile 324. When one or more
monitored
values satisfy an alarm level 325, an actionable event is detected.
Method 400 includes an act 404 of sending an alarm to an appropriate
healthcare
provider. For example, computer system 301b can send an alarm 320, including
event
15 317, to computer system 301c to communicate the occurrence of event 317 to
healthcare
provider 305. Thereafter, act 406 involves receiving an alarm indicating an
actionable
event has occurred for the patient. For example, computer system 301c can
receive alarm
320 indicating that event 317 (an actionable event) has occurred for patient
314 in
accordance with profile 324 and/or alarm level 325.
20 Method 400 includes an act 407 of initiating a pre-determined response for
assisting in the resolution of the actionable event. For example, computer
system 301c
can initiate a pre-determined response for assisting in resolution of event
317 in response
to receiving alarm 320. A response can include notifying an appropriate health
care
provider 306, 307 of the occurrence of the actionable event 317. For example,
in
response to receiving alarm 320, computer system 301 c can present an audio
and/or video
indication of event 317 at central station 304, such as by means of a video
display and
speakers. Alternately, or in addition, one or more of PDAs 308, 309 can
receive alarm
320 and present an audio and/or video indication of event 317 to providers
either or both
of providers 306, 307.
Initiating a response 407 can include acknowledging the alarm. For example,
computer system 301c can send acknowledgment 321 to either or both of computer
systems 301a, 301b. Sending acknowledgment 321 may result in establishing one
or
two-way communication between a healthcare provider and patient location 303
(e.g.,
using 1/0 devices 313). For example, provider 305 can input commands at
computer
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system 301c to open communication from central station 304 to patient location
303.
Similarly, providers 306, 307 can input commands at PDA's 308, 309 to open
communication from their locations to patient location 303. Communication can
be used
to send instructions to a patient, ascertain whether a patient is coherent,
responsive to
commands or instructions, etc.
A response 407 can also include a provider responding to the location of a
patient.
For example, in response to detecting that patient 314 has fallen, might fall,
or otherwise
requires assistance (e.g., by a patient controlled call device), provider 306
or 307 can
respond to patient location 303. RFID detectors at patient location 303 can
detect an
RFID transmitting device corresponding to provider 306 or 307 to verify
response by
provider 306 or 307 to a patient in need (e.g., comprising act 405 of method
400).
Expiration of a time interval can trigger some actionable events. For example,
movement of bed bound patients to prevent bed sores or administration of
medicine can
be required at specified intervals. Computer system 301b can send an alert to
computer
system 301c (or other appropriate computer systems) when a time interval
expires or is
about to expire.
C. Refining Patient Risk Profiles and Modifying Alarm Levels
In some embodiments, stored patient profiles include risk profiles that
include
recursively refined patient alarms levels indicative of actionable events
requiring a
response. Figure 5 is a flow chart that illustrates a computerized method 500
for
maintaining and refining patient risk profiles and associated alarms levels
for a patient at
a healthcare facility. Method 500 will be described with respect to the
components and
data in monitoring system 300. Method 500 includes an act 501 of receiving
collected
patient data 322 related to a detected event 317 for a patient 314. For
example, computer
system 301a can receive patient data 322 related to event 317 for patient 314.
As previously described, event 317 can be detected in accordance with a
recursively refined risk profile 324 based on previously collected patient
data for patient
314 (or on historical default data). Patient data 322 is collected from a
plurality of
sensors 312 monitoring the patient 314 for various conditions that, when
combined or
considered individually, indicate occurrence of an event 317. Although event
317 may
be an actionable event, embodiments of the invention can also receive data in
response to
non-actionable events 317. For example, some events 317 may trigger refinement
of a
patient risk profile 324 without triggering an alarm 320.
Method 500 includes an act 502 of refining the patient risk profile 324 based
on
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the collected patient data 322. For example, profile manager 330 can refine
patient risk
profile 324 based on patient data 322. Profile manager 330 can adjust events
317 that are
designated as actionable events for patient 314. Profile manager 330 can
iteratively
refine profile 324 through recursive application of profile refinement
algorithms.
Act 503 involves modifying alarm levels 325 for the patient 314 based on the
further refined patient risk profile 324 such that an appropriate health care
response can
be provided for alarms indicative of actionable events. For example, profile
manager 330
can adjust alarm levels 325 for patient 314 based on refinements resulting
from patient
data 322. Alarm levels 325 can cause an appropriate healthcare provider to be
notified
when actionable events related to patient 314 occur. Modified alarm levels can
differ
from previous alarm levels for patient 314 as a result of refinements to
profile 324 to
adjust risk. In some embodiments, an information feedback loop can be used to
periodically or continually update patient profiles to fine tune the
monitoring of patient
conditions. For example, monitoring for bed exiting can begin with common
preset
values that are updated over time to create unique or verified information for
each
patient.
A decision algorithm can be used to adjust parameter values that will cause an
actionable event. If an actionable event is appropriately detected (a
positive), parameters
can be made more restrictive such that the standard is lowered for detecting
the
actionable event in the future. For example, if a patient has fallen when
exiting a bed, the
values for detecting a bed exit can be made more restrictive. On the other
hand, if an
actionable event is inappropriately detected (a false positive), parameters
can be made
less restrictive such that the standard is raised for causing or detecting the
actionable
event in the future. When no actionable event is detected (a negative) for
some time
period, the parameters can also be made less restrictive such that the
standard is raised for
causing or detecting the actionable event in the future.
D. Measuring Care and Wellness
Patient care and wellness can be monitored in a variety of ways. According to
one embodiment, appropriate care and wellness according to certain parameters
can be
determined by monitoring the locations and/or movement of patients relative to
one or
more of caregivers, assets, visitors, other patients or fixed locations.
Figure 6 is a flow chart illustrating an exemplary method 600 for determining
patient care and wellness. Method 600 includes an act 601 of accessing stored
patient
profiles, which contain data that relate to one or more care or wellness
parameters. In
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most cases, the profile data will differ as between at least some of the
patients based on
the specific attributes and needs of each patient, which are rarely identical
for all patients.
Act 602 involves identifying one or more care or wellness parameters for each
of
a plurality of patients based on profile data contained in a corresponding
patient profile.
Examples of care or wellness parameters include, but are not limited to,
preventing
unassisted bed exiting, measuring total ambulation of a patient in a given
time period,
assessing the level of patient socialization with others, detecting changes in
patient gait,
verifying the completion of treatments, exercises or care regimes, ensuring
proper
denture use, identifying periodic bed rolling for bed bound patients to
prevent bed sores,
responding to patient initiating emergency calls, preventing or mitigating
patient harm,
wandering or flight, ensuring proper nutrition, detecting breathing sounds,
coughs,
choking, etc. that may be indicative of impaired respiratory function,
ensuring that patient
ambulation occurs in association with prescribed assistive devices, and the
like.
Act 603 includes determining one or more predetermined locations for each of a
plurality of patients relative to one or more predetermined locations for at
least one of a
caregiver, asset, visitor, other patient or fixed location within or without
the facility
which are consistent with or that confirm or verify the satisfaction of the
one or more care
or wellness parameters identified in 602. Many care and wellness parameters
involve
interactions between a patient and a caregiver, visitor, other patient or
asset. Tracking
location can also include determining a time duration at a location or between
multiple
locations. Tracking the locations of each roughly indicates whether such
interactions
have actually occurred as prescribed. A patient who is never in the same
location as the
assigned individual or asset is unlikely to have had the required interaction
for a care or
wellness parameter to have occurred. Tracking nutrition or preventing patient
wandering
or flight typically involves comparing patient movements (i.e., changing
locations)
relative to a fixed location in or out of a facility (e.g., cafeteria,
security zone, exit,
parking lot, etc.).
By way of example, patients, staff, assets and visitors can be assigned an
RFID
device that can be tracked throughout a facility by means of an RFID detection
system
comprising a plurality of RFID detectors throughout the facility. The location
of the
RFID detectors and assignment of RFID devices can be recorded and maintained
in a
computer system. As patients, staff, assets and visitors move throughout the
facility, the
RFID detectors notify the computer system of RFID devices that are currently
being
detected. This computer system can correlate the location of each RFID device,
as well
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as the duration of each RFID device at a specific location, and determine
whether
prescribed care and wellness routines or activities involving patients, staff,
assets and/or
visitors have been properly carried out.
In act 605 and 606, the actual locations of the patient, caregiver, asset,
visitor,
other patients and/or fixed location are compared with the one or more
predetermined
locations relating to the one or more care or wellness parameters selected in
602 to
determine if such care or wellness parameters have been satisfied. The
location,
movement and/or duration of a patient, caregiver, visitor, or other patient
can be
monitored to determine if prescribed duties or activities are actually carried
out as
prescribed (e.g., performed within predetermined time guidelines or in a
proper location,
such as bathing, assisted feeding, turning of bed ridden patients to prevent
bed sores,
etc.).
Measures can be taken to enhance patient care or wellness and/or prevent or
mitigate harm to a patient. Thus, act 607 includes optionally initiating a
response to
prevent or mitigate harm in the case of an actual event, refining a patient
profile and/or
generating a care or wellness report. By way of example, staff can be alerted
to prevent
or mitigate patient wandering into unauthorized or forbidden areas (e.g.,
other patient
rooms, facility exit, sensitive staff or equipment locations, etc.). Patient
wellness events
(e.g., social interactions, use of dentures, and proper nutrition) can be
chronicled and, if
necessary, improved through remedial action. Modification of patient profiles
can assist
in more accurately predicting patient's needs and limits. Generating a care
and wellness
report can assist providers or family members in ensuring enhanced care and
wellness of
the patient.
III. PROFILE MAINTENANCE AND REFINEMENT
An important aspect of the inventive monitoring systems and methods for
assessing and ensuring quality and performance is the use and refinement of
patient
specific profiles. Individual profiles permit the inventive patient monitoring
systems and
methods to more accurately assess the quality of cai-e and wellness of each
patient, as
among a plurality of patients having a variety of different attributes and
needs. Staff and
visitor profiles permit analysis of staff and visitor performance at a
healthcare facility.
Patient, staff and visitor profiles also permit the inventive systems and
methods to better
interpret conditions and actions of patients, staff and visitors that may lead
to an
actionable or triggering event. This reduces the incidence of false positives
and false
negatives and may reduce staff response times to critical clinical events.
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Figure 7 schematically illustrates an exemplary computer system 700 containing
networked computers and interrelated functional modules and peripheral data
gathering
systems for gathering information regarding a plurality of patients, staff and
visitors at a
healthcare facility and updating patient, staff and visitor profiles. Computer
system 700
5 more particularly includes a facility master 702 and in room controller 704.
Of course,
computer system 700 may include multiple in room controllers 704 and/or other
computers as desired. An RFID system interfaces directly with facility master
702 to
provide data regarding the location and movements of patients, staff, assets
and visitors.
An image analysis system 707 interfaces directly with in room controller 704
to provide
10 data regarding the location, behavior and/or condition of a patient in a
room. A detailed
discussion regarding detecting and responding to support exiting is set forth
below.
The exemplary modules within facility master 702 include denture tracker 708,
RFID zone security 710, contact tracker 712, ambulation tracker 714, emergency
response 716, socialization 718, surveillance controller 720, mobile call
button 722, and
15 exterior GPS integration 724. The in room controller 704 includes support
exit module
726, which interprets data from the image analysis system 707. It will be
appreciated that
additional modules and data generating peripherals may be included as required
to
generate and process other data types. The data that is processed by the
foregoing
modules shown in Figure 7 is used to update or refine patient profiles 730,
staff profiles
20 732, and visitor profiles 734. Each of the data processing modules as well
as exemplary
information contained within patient profiles 730, staff profiles 732 and
visitor profiles
734 will now be discussed in detail.
The following discussion of functional modules regarding profile maintenance
and refinement is also useful in understanding how the inventive methods and
systems
25 can be used to monitor and ensure a desired delivery of care and
maintenance of patient
wellness. They also assist in assessing the overall quality and performance of
and at a
healthcare facility. Thus, the following discussion of functional modules is
also
applicable to understanding how the methods and system help to monitor,
deliver and/or
ensure patient care and wellness as well as overall quality and performance.
A. Functional Modules
1. Support Exiting Module
As discussed above, the support exiting module 726 is typically located within
the
in room controller 704. The support exiting module 726 imports the most
recently
refined patient profile data relating to support exiting from facility master
702 so as to be
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26
locally stored at in room controller 704. Threshold issues include whether
patient bed
behavior is restricted and what time periods the restrictions are enforced. If
support
exiting behavior is not restricted for that patient or within a given time
period, support
exiting need not be monitored and responded to, at least within the given time
period
when the restriction is not in effect. Only if support exiting restrictions
apply within a
given time period does the support exiting module need to function to detect
support
exiting by the patient.
According to one embodiment, data from a plurality of data channels relating
to
various parts of the patients body are sampled with a frequency sufficiently
high to obtain
maximal event capture while minimizing unproductive hardware loads to populate
support exiting algorithms (e.g., at 0.25 second intervals). The data channels
contain
continuously flowing data regarding the locations and/or time durations at
specified
locations for the patient's head, arms, hands, legs and torso. The algorithms
for each
patient are based on specific support exiting behavior for that patient based
on the
patient's profile. Examples of profile data relating to support exiting
behavior and limits
is set forth in a later section below. The profile data includes or is used to
create specific
combinations of triggers relating to specific combinations of body part
movements and/or
time durations at specific locations, which are individually populated and
flagged if
satisfied. If the correct combination of triggers for that patient is met
simultaneously, an
actionable event is detected and a response is initiated.
For example, the following data channels A through H have been assigned to
measure the distance between a particular patient body part and a
corresponding or
related support (e.g., bed) zone and/or the time duration that a body part is
in contact or
proximity with the corresponding or related support zone.
Bed Exit Channels
A = head distance from head board (inches)
B* = B = head distance right (inches)
C* = C = head distance left (inches)
D engagement of right upper bed rail (consecutive seconds)
E engagement of left upper bed rail (consecutive seconds)
F leg within exit zone right (consecutive seconds)
G leg within exit zone left (consecutive seconds)
H head height of eleveation (inches)
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As discussed below, there are seven common bed exiting behaviors which are
consistent with specific combinations of behaviors corresponding to
information
measured by each of data channels A though H.
Trigger Combinations for Alerts
Bed slide A
Side rail roll right D and B
Side rail roll left E and C
Torso up / side rail roll right H and B*
Torso up / side rail roll left H and C*
Torso up / leg kick right H and F
Torso up / leg kick left H and G
When a distance or time duration matches information contained within a
patient's profile of support exiting behavior, that variable is flagged. When
all of the
variables for the specific support exiting behavior for a patient are
triggered, an alert or
alarm may be triggered and a response initiated. Different patients may have
different
trigger values for the various behaviors depending on known support exiting
behavior,
patient size, and other attributes.
Upon the occurrence of a predetermined combination of behaviors consistent
with
support exiting for a specific patient, an alarm may be triggered and a
response initiated.
An exemplary support exiting response includes: (1) initiating HIPAA
notification to the
patient of potential viewing of video feed of patient; (2) establishing an A/V
link to a
nursing station for nurse only viewing of the patient; (3) verifying nurse's
presence at the
nursing station within an established time response period by the nurse
verifying or
rejecting whether support exiting is actually occurring; (4) alternatively
initiating an
automatic response if nurse's presence not verified within time response
period; (5) if
nurse's response is "reject", with the option of mandatory staff approval,
modifying the
patient profile to loosen support exiting limits and notifying resident that
viewing is
concluded; (6) if nurse's response is "accept", establishing "video stall" A/V
link to delay
support exiting, sending message to assigned PDA and closest nurse PDA of
event,
beginning nurse floor response time timer (finish when nurse RFID enters
requested
room), and modifying patient profile to confirm or tighten support exiting
limits; and (7)
generating bed exit event report for each 24 hour period. A more detailed
description of
support exiting and response is set forth in a later section below.
2. RFID Zone Security Module
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As discussed above, the RFID zone security module 710 is typically located in
the
facility master 702. According to one embodiment, the RFID zone security
module 710
scans the RFID zone locations of patients, staff and visitors at a facility at
a frequency
sufficiently high to obtain maximal event capture while minimizing
unproductive
hardware loads (e.g., at 1.0 second intervals). Using profile data, the module
710
classifies individual locations as one of: (1) safe, (2) warning or (3)
violation. If the
location classification is safe, no alerts or alarms are initiated.
In the case where a patient's or visitor's location triggers a "warning", a
timer is
initiated. If the location of the individual at issue does not downgrade to
"safe" within a
prescribed timer interval (e.g., "X" seconds), an alert is sent to the nursing
station and a
staff response timer mode is initiated. The timer runs until the individual is
removed
from any restricted RFID zones. The amount of elapsed time can be used to
assess staff
performance.
If an individual's location triggers a "violation", an alert is sent to the
nursing
station and possibly security, and a staff response timer mode is initiated.
The timer runs
until the individual is removed from any restricted RFID zones. The amount of
elapsed
time can be used to assess staff performance. According to one embodiment,
nursing
station staff can visually and/or verbally instruct the patient or visitor to
vacate the
restricted area through the use of an A/V interface. A security zone report
can be
generated every 24 hours if requested.
In order to illustrate how an initial flight risk level for a given patient,
coupled
with monitored behavior, may trigger appropriate alerts and alarms in the case
of possible
building flight, the following example is given. The box below is a grid that
illustrates
various danger zone values surrounding a building exit, with the lower numbers
representing geographic zones that are farther away from the exit, and higher
numbers
representing geographic zones that are closer to the exit. The danger zone
values can be
used to calculate a present flight risk level for each of a plurality of
patients as they move
toward the exit, which is next to danger zone 8.
3 4 8 4 3
exit
2 3 5 3 2
1 1 2 1 1
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1 1 1 1 1
0 0 0 0 0
By way of example, a patient of known normal flight risk might be assigned an
initial flight risk score of 10. A patient having a known high flight risk
level might be
given an initial score of 5. The lower the score, the higher the flight risk.
Whenever a
patient enters a zone having a danger zone value that is equal to or greater
than the
danger value of preceding zone, the initial flight risk score is modified by
subtracting the
present danger zone value. Thus, if a patient with an initial flight risk
score of 10 enters a
flight zone with a danger zone value of 1, the patient's current flight risk
score is reduced
to 9. Entering danger zones of equal or greater value results in further
reductions in the
current flight risk score. An alert of possible flight risk and A/V
intervention may be
triggered, for example, if the flight risk score falls to below a
predetermined threshold
(e.g., below 4). An alarm is triggered if the flight risk score falls to 0 or
below (i.e., a
negative number) and direct intervention to prevent or mitigate actual flight
is initiated.
If, after entering a danger zone with a given value, the patient turns around
and enters a
danger zone having a lower value, the flight risk score can be increased to
reflect the
lessened flight risk.
3. Ambulation Tracker Module
As discussed above, the ambulation tracker module 714 is typically located in
the
facility master 702. According to one embodiment, the ambulation tracker
module 714
measures the total ambulation distance for each patient and staff member by
determining
the total number of RFID zones occupied by each individual during each 24 hour
period
and multiplying that value by the RFID zone size (e.g., 3 feet). Daily
ambulation values
are buffered to generate weekly averages. Alerts may be generated when daily
values
differ from the historical average by more than 50%. The overall trend for
weekly
averages can be monitored to determine the existence of increases or declines
in
ambulation. Ambulation reports and be generated for patients, staff and
visitors every 24
hours if requested. Patient health, staff performance and visitor behaviors
can be
assessed using ambulation values.
According to another embodiment, ambulation tracker module 714 polls patient
profiles to determine which patients require ambulation assistance devices
(e.g., walker,
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wheelchair or crutches). If so, the module 714 also tracks the location of any
assigned
devices for each patient using the associated RFID for the device. For the
subset of
patient requiring ambulation devices, determining whether any patient moves
between
RFID zones without detecting the presence of the assigned RFID tagged
ambulation
5 device. If separation of patient and ambulation device is determined,
initiating an alert to
the nursing station for possible intervention. Assistive ambulation device
reports can be
generated for patients every 24 hours if requested.
The ambulation tracker module 714 can also detect potentially dangerous
changes
in patient gait by noting the time it takes for a patient to move between
zones. For
lo example, for a patient who normally passes between RFID zones at a
particular pace,
detecting substantial slowing or unusual movement between zones may be an
indication
of a serious medical condition.
4. Contact Tracker Module
As discussed above, the contact tracker module 712 is typically located in the
15 facility master 702. The purpose is to determine and verify the existence
of prescribed
patient/staff contacts as they may relate to patient care and wellness and/or
staff
performance. According to one embodiment, the contact tracker module 712 polls
a
patient's profile for all elements that require patient/staff contact to be
performed and/or
delivered on a prescribed schedule. Examples include: (1) meals brought
directly to
20 rooms - denoted by RFID tagged meal tray; (2) special diet restrictions -
denoted by
RFID tagged meal tray; (3) assistance during mealtimes in room; (4) trips to
cafeteria
during meal times per day; (5) in-room therapy required without medical
device; (6) in-
room therapy required with one or more devices (i.e. assets) A; (7) in-
facility therapy /
physical therapy; (8) assisted facility exits.
25 The RFID system 706 is monitored to count each of these events and compare
to
prescribed standards set within each patient profile. The time period of
patient/staff
interaction should be measured and compared to pre-set minima and maxima.
Alerts and
alarms may be generated if an increasing degree of poor staff performance is
detected.
Data generated by the contact tracker module can be used to assess patient
care and
30 wellness and/or staff performance.
5. Socialization Module
As discussed above, the socialization module 718 is typically located in the
facility master 702. The purpose is to determine the degree of patient
socialization as it
may relate to patient care and wellness. The socialization module 718 analyzes
RFID
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monitored patient movements and behaviors and generates either a (+) or (-)
influence on
a numeric value that represents each patient's socialization factor (PSF). PSF
may
normally begin at a default value 5 and increase to a maximum of 10 and
decrease to a
minimum of I depending on patient activities. High, low or changing PSF are an
objective measure of patient wellness.
Exemplary patient activities that count as a possible (+) PSF influencing
element
include: (1) visitors visiting patient's room; (2) assisted exits of facility;
(3) other
patients to patient's room; (4) trips by patient to other patient's rooms; (5)
time in
common areas (e.g., cafeteria, courtyard, recreation rooms, etc.) when
occupied by
visitors other patients; (6) activation of "family plan" communication
elements; (7)
contact time with pets (e.g., "canine therapy"); and (8) time/trips to
facility courtyard
area.
Exemplary patient activities that count as a possible (-) PSF influencing
element
include: (1) consecutive hours in room alone; (2) missed meals; (3) repetitive
ambulation
behavior (e.g., walking back-and-forth or in circles); and (4) decreased
levels of daily
ambulation. Drastic decreases in PSF below previous values or an RSF below a
critical
minimal limit (e.g., 2) may result in the generation of alerts and alarms.
Periodic
socialization reports for each patient can be generated to assess patient
wellness and/or
staff or visitor performance (e.g., letters can be sent to relatives
requesting more visits).
6. Surveillance Controller Module
As discussed above, the surveillance controller module 720 is typically
located in
the facility master 702. According to one embodiment, the surveillance
controller
module 720 monitors RFID, motion detection, video cameras and/or door beam
tripping
data to detect the entrance of staff, patients, or visitors into a patient's
room or other
private zone. Upon authorized entry by individuals into a patient's room, as
detected
using assigned RFID devices, the surveillance controller module 720 initiates
A/V
monitoring of the patient's room and triggers HIPAA appropriate patient
notification.
Upon room clearing of RFID signals (other than those which assigned resident)
the the
surveillance controller module 720 terminates A/V monitoring.
Upon unauthorized entry by individuals into a patient's room, as detected by
image analysis of video data, motion detection and/or door beam tripping data
in the
absence of properly assigned RFID devices, the surveillance controller module
720
initiates an alarm at the nursing station, security is notified, and an event
response timer
is initiated. The event response timer is terminated when authorized staff
RFID enters
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the patient's room. The event response time can be used to assess staff
performance.
The surveillance controller module 720 time stamps and attaches a patient
identifier code
to A/V surveillance files, which are stored for a prescribed number of days
(e.g., 15
days).
7. Emergency Response Module
As discussed above, the emergency response module 716 is typically located in
the facility master 702. The purpose is to notify staff and patients of a
facility emergency
and initiate an appropriate response to prevent or mitigate patient harm. Upon
confirming the occurrence of a facility emergency (e.g., a fire), a qualified
staff member
inputs the location of the event into the system. The emergency response
module 716
causes the system to send messages to all patient rooms with evacuation
instructions.
The emergency response module 716 tracks the evacuation of all patients and
staff via
tracking the movements of assigned RFID devices for each patient and staff
member.
Laptop PC and network access at locations external to the building can be
provided for
administration and emergency response personnel.
8. Mobile Call Button Module
As discussed above, the mobile call button module 722 is typically located in
the
facility master 702. Patients and staff wear RFID bracelets that include a
manual call
button that allows for manual activation of a secondary RFID transmitter
during
emergency situations. When an emergency RFID is detected, the mobile call
button
module 722 determines who triggered the alert and where the individual is
located. The
mobile call button module 722 polls the assigned patient profile for a list of
most critical
medical conditions. The mobile call button module 722 transmits information
regarding
the call for help and any most critical medical conditions to the closest
staff PDA for
response and starts response timer mode. The mobile call button module 722
determines
if A/V communication is supported in the location of the emergency, and if so,
establishes an A/V link between the location and a nursing station. At the
conclusion of
the event, nursing station staff inputs whether or not an actual emergency
occurred and
the patient's profile is updated to note inappropriate emergency call button
usage (e.g.,
ordering room service, using it for social calls, horseplay, etc.).
9. External GPS Integration Module
As discussed above, the external GPS integration module 724 is typically
located
in the facility master 702. The external GPS integration module 724 allows for
hand off
of patient tracking from the RFID system 706 to GPS when residents travel into
an
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exterior courtyard region of the facility not equipped with RFID zone sensors
and/or in
cases of patient wandering or flight. Patient movement toward a courtyard can
be
determined by a patient assigned RFID device entering zones leading to the
courtyard.
The external GPS integration module 724 polls the patient profile for
privilege or
limit information, including: (1) courtyard privileges for the patient; (2)
courtyard time
of day restrictions; (3) courtyard time duration outside limits; (4) courtyard
maximum
outside temperature limits; (5) courtyard minimum outside temperature limits;
and (6) the
assigned GPS transmission code for that patient. If conditions are not met for
courtyard
access, the module 724 causes system to alert the nursing station and being a
response
timer. If conditions are met for courtyard access, then start courtyard
duration timer.
10. Denture Tracker Module
As discussed above, the denture tracker module 708 is typically located in the
facility master 702. According to one embodiment, the denture tracker module
708
ensures that prescribed denture cleaning schedules are maintained. By means of
denture
embedded RFID devices, track the time period between denture RFID occupying
RFID
zone dedicated to denture cleaning station. Cleaning dentures too often or too
infrequently can be noted in an appropriate report. Tracking proper cleaning
of dentures
is a measure of patient care and wellness.
According to another embodiment, the denture tracker module 708 ensures a
proper match between an upper denture, lower denture, and the patient. It does
so by
tracking the locations of patients and corresponding dentures. For example,
the denture
tracker module 708 may determine whether a denture RFID that is changing zones
(i.e.,
moving) belongs to the patient moving through equivalent RFID zones. If not,
the
module 708 sends an alert nursing station and generates a report.
Other assets can be tracked and matched with assigned patients in similar
fashion.
B. Exemplary Profiles
1. Patieiit Profile
The type of data contained in a patient profile can be selected, populated and
modified as required depending on any desired care and wellness criteria
and/or learned
information. The following patient profile is merely one example of a suitable
profile for
use in collecting and processing data by the modules described above. It is
given by way
of example, not by limitation. Each line represents an independent inquiry
that can be
analyzed using one or more computer-monitored data channels. Data may be
static or
dynamic. Dynamic data can either by altered automatically or manually.
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S = Static Parameter
AD = Automatically Dynamic Parameter
MD = Manually Dynamic Parameter
1. bed exit monitoring required - (y/n), S
2. evening bed bound initiation time - xx:xx, S
3. morning bed bound termination time - xx:xx, S
4. limit on head to head board distance - x inches, AD tighten, MD loosen
5. number of bed slide exit attempts -#, AD
6. limit on right hand bedrail loading - x seconds, AD tighten, MD loosen
7. number of right side bedrail exit attempts - #, AD
8. limit on left hand bedrail loading - x seconds, AD tighten, MD loosen
9, number of left side bedrail exit attempts -#, AD
10. limit on head elevation - x inches, AD tighten, MD loosen
11. number of torso up / bedrail roll exit attempts - #, AD
12. dietary restrictions - (y/n), S
13. diabetic food restrictions -(y/n), S
14. soft food restrictions -(y/n), S
15. in-room assistance required during eating -(y/n), S
16, number of trips to cafeteria during breakfast/lunch/dinner time periods
per
day - #, AD
17. assisted turning in bed per evening time block -#, AD
18, unassisted turns in bed per evening time block - #, AD
19. socialization counter - 1 to 10 scale, AD
20. hallway gait timer - x minutes, AD
21. total daily ambulation counter - x minutes and y distance, AD
22. weekly ambulation average - x minutes and y distance, AD
23, total daily (ambulation with assistive device) counter - x minutes and y
distance, AD
24. weekly (ambulation with assistive device) average - x minutes and y
distance, AD
25. in-room therapy without device -(y/n), S
26. in-room therapy with device -(y/n), S
27. staff presentations in room with device per day - #, AD
28, ambulation with device mandatory -(y/n), S
29. corresponding ambulation device or devices - RFID code, S
30. maxillary denture - RFID code, S
31. mandibular denture - RFID code, S
32. denture cleaning schedule counter - # per week, AD
33. bathroom time limit - x minutes, S
34. courtyard privileges - (y/n), S
35. courtyard time of day restrictions - xx:xx, S
36. courtyard duration outside limit - x minutes, S
37. courtyard maximum outside temperature - x F/C, S
38. courtyard minimum outside temperature - x F/C, S
39, unassisted facility exiting -(y/n), S
40. level of flight risk - #, AD tighten, MD loosen
41. number of authorized facility exits per month - #, AD
42, number of unauthorized facility exits or attempts per week - #, AD
43. facility restricted areas - RFID codes, S
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44. inappropriate emergency call button usages - #, AD
45. pet therapy contact -(y/n), S
46. critical medical history - [data], S
47. emergency call contact #1, S
5 48. emergency call contact #2, S
49. emergency call contact #3, S
2. Staff Profile
The type of data contained in a staff profile can be selected, populated and
10 modified as required depending on any desired quality or performance
criteria and/or
learned information. Staff performance will typically relate in some way to
providing
patient care and wellness and may differ based on specific attributes,
assignments and/or
rights of each staff member. The following staff profile is merely one example
of a
suitable profile for use in collecting and processing data by the modules
described above.
15 It is given by way of example, not by limitation. Each line represents an
independent
inquiry that can be analyzed using one or more computer-monitored data
channels. Data
may be static or dynamic. Dynamic data can either by altered automatically or
manually.
S = Static Parameter
AD = Automatically Dynamic Parameter
20 MD = Manually Dynamic Parameter
1. work schedule - day of week, time of day, S
2. restricted RFID zones - x,y,z, S
3. assigned resident rooms - x,y,z, S
4. total ambulation - time x and distance y, AD
25 5. most visited room - time x, AD
6. second most visited room - time x, AD
7. third most visited room - time x, AD
8. fourth most visited room - time x, AD
9. fifth most visited room - time x, AD
30 10. sixth most visited room - time x, AD
11. seventh most visited room - time x, AD
12. eighth most visited room - time x, AD
13. ninth most visited room - time x, AD
14. tenth most visited room - time x, AD
35 15. number of facility exits per day - #, AD
16. duration of facility exits - minutes x, AD
17. % of total work time spent with patients, AD
18. % of total work time spent with other staff, AD
19. % of total work time spent alone, AD
3. Visitor Profile
The type of data contained in a visitor profile can be selected, populated and
modified as required depending on any desired performance criteria and/or
learned
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information. Visitor performance may relate to attribute and rights of each
visitor and
also patient care and wellness. The following visitor profile is merely one
example of a
suitable profile for use in collecting and processing data by the modules
described above.
It is given by way of example, not by limitation. Each line represents an
independent
inquiry that can be analyzed using one or more computer-monitored data
channels. Data
may be static or dynamic. Dynamic data can either by altered automatically or
manually.
S = Static Parameter
AD = Automatically Dynamic Parameter
MD = Manually Dynamic Parameter
1. identification number (drivers license #) - xxxxxx, S
2. biometric scan data, S
3. time of day restriction for entrance - xx:xx, S
4. associated resident RFIDs - x,y,z, S
5. allowed resident room RFID zones - x,y,z, S
6. generic allowed RFID zones - x,y,z, S
7. generic restricted RFID zones - x,y,z, S
8. can patient leave facility with visitor assistance? (y/n), S
9. most visited room - x, AD
10. second most visited room - x, AD
11. third most visited room - x, AD
12. fourth most visited room - x, AD
13. fifth most visited room - x, AD
14. most commonly associated human RFID - x, AD
15. second most commonly associated human RFID - x, AD
16. third most commonly associated human RFID - x, AD
17. fourth most commonly associated human RFID - x, AD
C. Refinement of Profiles
Figure 8 illustrates a flow chart of a method 800 for maintaining and refining
stored profiles for patients, staff and visitors at a healthcare facility.
Method 800 includes
an act 801 of storing an initial profile for each of a plurality of patients,
staff or visitors at
a facility based on at least one of specific personalized information for each
patient, staff
or visitor, or general information common to more than one individual. The
patient
profiles may include at least one of an alarm level for use in triggering an
actionable
event, a treatment regimen for the patient, or wellness measurement for the
patient. The
staff and visitor profiles may include initial information relating to staff
and visitor
performance as it may relate to the care or wellness of patients.
Method 800 includes an act 802 of receiving collected data relating to each of
the
patients, staff or visitors at the facility. The data can be collected using
one or more
sensors, UO devices, cameras or computers positioned within the facility that
detect or
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provide data regarding movements by patients, staff, visitors and assets.
Act 803 involves refining the profile of a patient based on the collected data
in
order to modify at least one of an alarm level, care or wellness parameter, or
a treatment
regimen for the patient. The patient profile can be updated by way of an
information
feedback loop in which potentially actionable events are confirmed or denied
through
human intervention. In some embodiments, stored patient profiles are risk
profiles that
include recursively refined patient alarms levels indicative of actionable
events requiring
a response. Finally, method 800 includes an act 804 of refining staff and/or
visitor
profiles based on collected data relating to staff and/or visitor performance,
which will
typically relate in some way to ensuring or gauging patient care and wellness.
IV. SYSTEMS AND METHODS FOR MONITORING PATIENT SUPPORT
EXITING AND RESPONSE
Monitoring and responding to unassisted patient support exiting is an example
of
a specific care and wellness parameter. It helps increase the overall quality
and
performance of a facility. Potential support exiting can be monitored by
determining the
location of a patient, particularly the location and/or time duration of
specific body parts
relative to fixed locations. Detecting potential patient support exiting in
advance of
actual support exiting gives a caregiver the opportunity to intervene and
prevent support
exiting, assist support exiting, or mitigate patient harm.
Figure 9 is a diagram that schematically illustrates an exemplary computer-
controlled system 900 for patient monitoring, more particularly with respect
to potential
patient support exiting, detecting a position and/or movement of a patient
that is
predictive of support exiting, obtaining human verification of actual support
exiting, and
intervening if support exiting is confirmed. The patient monitoring system 900
includes a
patient room 902 containing a bed 904 or other support and a patient 906
resting thereon
at least some of the time. One or more overhead cameras 908 may be provided
that
provide an aerial view of patient 906 together with one or more side or
lateral view
cameras 910. The overhead camera 908 is especially useful in monitoring
lateral (i.e.,
side-to-side) and longitudinal (i.e., head-to-foot) patient movements,
although it may also
monitor other movements. The lateral view camera 910 is especially useful in
monitoring longitudinal and up and down movements, although it can monitor
other
movements. The lateral view camera 910 and/or other camera (not shown) can be
positioned to monitor and record a patient room door 912 or other access point
(e.g., to
detect and/or record entry and/or exit of personnel, other patients, or
visitors). The bed
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904 may include markings (e.g., decals) (not shown) that assist in properly
orienting the
cameras to fixed reference points. The markings may assist in determining the
distance
between a fixed point and body part.
The room 902 also includes an audio-video interface 914 that can be used to
initiate one-way and/or two-communication with the patient 906. According to
one
currently preferred embodiment, A/V interface 914 is mounted to a wall or
ceiling so as
to be seen by patient 906 (e.g., facing the patient's face, such as beyond the
foot of the
patient's bed). The A/V interface 914 may include any combination of a video
monitor
(e.g., flat panel screen), a camera mounted adjacent to the video monitor
(e.g., below),
one or more microphones, and one or more speakers. The A/V interface may form
part
of a local computer system (e.g., an "in room controller") that controls the
various
sensors and communication devices located in the patient room.
In order to analyze patient movements that may be predictive of support (e.g.,
bed) exiting, video data streams 916A and 918A are sent from cameras 908 and
910,
respectively, to a computer system 920 for analysis. According to one
currently preferred
embodiment, at least a portion of the computer system 920 is an in room
controller
associated with the patient room 902. In the case where each patient room has
its own in
room controller, patient monitoring and analysis of multiple patients can be
simultaneously performed in parallel by dedicated in room controller
computers.
Nevertheless, at least some of the tasks, information gathering, and
information flow may
be performed by a remote computer, such as a central facility master computer.
The
computer system 920 may therefore include multiple networked computers, such
an in
room controller, facility master, and other computers. The computer system 920
includes
or has access to a data storage module 922 that includes patient profiles 924
(e.g., stored
and updated centrally in the facility master and used locally by and/or
uploaded to the in
room controller).
A comparison module 926 of the computer system 920 analyzes the video streams
916A, 918A and, using one or more algorithms (e.g., that may be known in the
art or that
may be developed specifically for this system), determines the location and/or
any
movements and/or duration of body part action of patient 906. This information
is
compared to patient specific profile data 925 from a patient profile 924 that
corresponds
to patient 906. In the absence of predicted support exiting or other
triggering event,
video streams 916A and 918A are typically not viewed by any human but are
actively
deleted or simply not stored or archived. This helps protect patient privacy.
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When one or more locations, durations and/or movements of patient 906 match or
correlate with profile data 925 predictive of support exiting by patient 906,
the computer
system 920 sends an alert 928 to a central station 930 (e.g., nursing station)
that patient
906 may be attempting to exit support 904. In addition to the alert 928, at
least one of
video streams 916B, 918B from cameras 908, 910 and/or a modified video stream
(not
shown) from computer system 920 is sent to an A/V interface 934 at central
station 930
for human verification of actual patient support exiting. The patient 906 is
advantageously notified of potential active viewing by staff to satisfy HIPAA
regulations
(e.g., by a chime, prerecorded message, e.g., "camera is actively viewing", or
visual
indication, e.g., flashing or illuminated words, TV raster pattern). A
provider 932 views
the video stream(s) from patient room 902, determines whether the patient 906
is in fact
preparing to exit the bed 904 or other support, and provides verification
input 936 to an
appropriate interface device (not shown) at station 930, which sends
verification 938 to
the computer system 920. Verification 938 may either confirm or reject actual
patient
support exiting. When viewing is terminated, the patient may be notified of
this fact by,
e.g., a tone or pre-recorded message ("active viewing is terminated").
If the provider 932 determines and verifies that actual patient support
exiting is
occurring or about to occur, the in room controller, facility master, or other
appropriate
module or subsystem component within computer system 920 sends a notification
940 to
a responder 942 to assist the patient 906. Notification 940 may be sent by any
appropriate means, including an audio alert using a PA system, a text and/or
audio
message sent to a personal device carried by responder 942, a telephone alert,
and the
like. A tracking system 943 that interfaces or communicates with the computer
system
920 (e.g., the facility master) may be used to identify a caregiver 942 who is
assigned to
patient 906 and/or who is nearest to patient room 902. In this way, direct
physical
assistance to patient 906 who may be attempting to exit support 904 can be
provided
quickly and efficiently.
In addition to or instead of sending notification 940 to responder 942, one-
or
two-way A/V communication 944 can be established between provider 932 at
central
station 930 and patient 906 (e.g., by means of A/V interfaces 914 and 934).
This allows
provider 932 to talk to patient 906 in order to provide instructions or
warnings regarding
support exiting, possibly to distract patient 906 and delay or prevent support
exiting (e.g.,
"why are you getting out of bed?"). This may allow responder 942 to more
easily
intervene prior to actual support exiting so as to prevent or better mitigate
potential harm
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to patient 906. A pre-recorded audio and/or A/V message 946 may alternatively
be sent
to A/V interface 914 in patient room 902 instead of direct A/V communication
between
provider 932 and patient 906.
In the event a provider 932 is not present at central station 930 or otherwise
fails
5 to provide verification 938 regarding predicted support exiting within a
prescribed time
period, the computer system 920 may initiate an automated response in order to
prevent
or mitigate potential harm to patient 906. This may include one or both of
sending
notification 940 to a responder 942 regarding possible support exiting and/or
sending a
pre-recorded message 946.
10 Verification 938, whether confirmation or denial of actual support exiting,
can
also be used to update the patient profile 924 corresponding to patient 906.
Updated
profile data 948 based on one or more support exiting events can be input or
stored at
data storage module 922. If a particular behavior is found to accurately
predict support
exiting by patient 906, the patient profile 924 can be updated to confirm the
accuracy of
15 the initial profile 924. In some cases, limits within the patient profile
924 may be
tightened to be more sensitive to movements and/or durations of actions that
have been
confirmed to correlate with and accurately predict support exiting. This may
be done
manually by authorized personnel or automatically by the computer system 920.
If, on
the other hand, a particular behavior is determined to falsely predict support
exiting by
20 patient 906, the patient profile can be updated to note incidences of such
false positives.
Limits within the patient profile 924 can be loosened or eliminated relative
to movements
that have been found not to correlate with support exiting by patient 906. In
the event
support exiting by patient 906 occurs but is not detected by the computer 920,
limits
within the patient profile 924 can be established and/or tightened in an
effort to eliminate
25 false negatives of support exiting by patient 906. Updating the profile 924
of patient 906
to more accurately predict support exiting and reduce or eliminate false
positive and false
negatives substantially increases the reliability of the patient monitoring
system as
compared to conventional systems that do not distinguish between and among
support
exiting habits or behaviors of different patients. The foregoing is an example
of the use
30 of an information feedback loop to refine a patient profile.
In order to later view and/or analyze a triggering event as may be established
by a
facility, video data 950 that is the same as, or which may be derived from,
one or both of
video streams 916, 918 can be stored within an archive 952. Archive 952 may
comprise
any storage media known in the art of video recording and storage, examples of
which
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include hard drives, optical storage devices, magnetic tapes, memory devices,
and the
like. The triggering event need not be support exiting but may be entry into
the patient's
room by staff, other patients or visitors, or activation of the emergency call
button by the
patient.
Figures l0A and lOB schematically illustrate various embodiments of exemplary
patient room configurations used in monitoring a patient and providing one or
more
responses. In the embodiment of Figure 10A, an exemplary patient room 1000 is
illustrated which includes a patient 1002, a bed 1004 or other support upon
which the
patient 1002 rests at least some of the time. The patient 1002 may wear or
carry a mobile
electronic tracking device, such as an RFID bracelet or other device 1006.
This allows a
facility master computer and/or in room controller to identify and track the
location of
patient 1002 by means of electronic tracking systems known in the art. RFID
device
1006 is specially assigned to patient 1002 and provides verification when
patient 1002 is
located in room 1000. This facilitates using the correct patient profile when
interpreting
movements of patient 1002.
One or more overhead cameras 1008 are positioned above the bed 1004 and so as
to provide an aerial (e.g., bird's eye) view of patient 1002. One more side or
lateral view
cameras 1010 are positioned to the side of patient 1002 to provide a different
data stream
for determining the patient's position and/or movements. Camera 1010 may have
a direct
or peripheral view of a door 1018 or other entrance to room 1000. An in room
controller
computer (IRCC) 1012, which may be a local computer located in room 1000,
analyzes
video data streams generated by cameras 1008, 1010. A flat panel monitor 1014
(e.g.,
high definition), controller mounted camera 1016, and optionally other devices
such as
microphones and speakers (not shown) are interfaced with IRCC 1012.
The IRCC 1012 is used to determine the location of the patient's body,
including
specific body parts, by interpreting video data streams generated by one or
more of the
cameras 1008, 1010, 1016 and comparing relative distances between the
patient's body
and fixed locations (e.g., the patient's head and the headboard of the bed,
the patient's
arms and legs relative to respective left and right bedrails, the height of
the patient's torso
relative to the bed, etc.). A changing body part position indicates movement
of that body
part. The IRCC 1012 continuously or periodically compares the location and/or
any
movements of the patient's body or portion thereof with locations and
movements that
are predictive of patient bed exiting by that patient as contained in the
patient's profile of
bed exiting behaviors. Whenever the unique singular or combination of
positions,
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movements, and/or duration of positional actions is detected that is
consistent with a
unique bed exiting behavior, an appropriate response is initiated.
The flat panel video monitor 1014 can provide multiple functions, including
providing normal television programming, recorded programming requested by the
patient 1002, video feeds to remote locations (such as loved ones or staff who
wish to
communicate with patient 1002 remotely), emergency situation instructions and
special
messages (e.g., patient alerts). The controller mounted camera 1016 provides a
direct
facial view of the patient and, in combination with video monitor 1014,
facilitates two-
way A/V communication between patient 1002 and individuals outside room 1000.
As
shown, the camera 1016 may also have a direct view of door 1018 or other room
entrance
to monitor entry and exit of individuals (e.g., staff 1042, other patients or
visitors) from
room 1000. Camera 1016 may also have a view of bathroom door 1020 to monitor
movement of patient 1002 to and from the bathroom. A standard motion sensor
integrated with conventional video cameras (e.g., camera 1016) may provide
motion
detection means for detecting room entry or exiting activity. Video data from
room
viewing video cameras, such as camera 1016, or combinations of room based
video
cameras, may also be utilized by image analysis programs running within in-
room
controller 1012 to detect and count the number of individuals within the room.
When
combined with in-room counts of residents, staff and visitors from RFID data,
this
information can be used to detect unauthorized entry into patient's room and
therefore
positively impact patient wellness.
The room 1000 may include other auxiliary devices, such as bedside call button
1022, patient pain scale interface 1023, bathroom call button 1024,
microphones/speakers
1025, and bathroom motion sensor 1026. Call buttons 1022, 1024 may comprise
those
known in the art. The pain scale interface 1023 allows a patient to indicate
to the
monitoring system (e.g., IRCC 1012, facility master, and/or nursing station)
the patient's
current pain level (e.g., on a scale of 1 to 10, with 1 being the least and 10
being the most
pain). Motion sensor 1026 can be used, e.g., in combination with camera 1016,
call
button 1024 and/or microphones/speakers 1025, to determine whether a patient
1002
requires further assistance while in the bathroom. An RFID grid set up
throughout the
room can be used to monitor the position andlor movements of the patient 1002
when not
resting on the bed 1004 and also the position and/or movements of staff 1042,
other
persons such as patients, friends, family or other visitors, and assets (not
shown).
Figure lOB illustrates an exemplary patient room 1000 which includes a patient
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1002, a bed 1004 or other support upon which the patient 1002 rests at least
some of the
time, and various other devices used to monitor the patient and the patient's
room 1000.
The patient 1002 may wear or carry a mobile electronic tracking device, i.e.,
mobile
patient location client 1006. This allows a facility master computer to
identify and track
the location of the patient 1002 by means of electronic tracking systems known
in the art.
Patient location client 1006 may be a conventional RFID device (e.g.,
bracelet) and may
be equipped with a patient emergency call or panic button (not shown) as known
in the
art. Mobile patient location client 1006 is specially assigned (and attached)
to patient
1002 staying in patient room 1000. Client 1006 provides verification that
patient 1002 is
actually located in room 1000. This facilitates using the correct patient
profile when
interpreting movements of patient 1002 rather than those of another patient.
High risk motion clients 1008A and 1008B (e.g., which include one or more of
cameras, electronic motion sensors, electric eyes, RFID detectors, etc.) may
be positioned
on either side of bed 1004, thus providing two separate data streams for
interpretation of
the patient's position and/or movements. Side cameras 1010A and 1010B are
positioned
on either side of patient 1002 to provide additional data streams for
interpretation of the
patient's position and/or movements. At least one of cameras lOlOA and 1010B
may
have a direct or peripheral view of a door 1011 or other entrance to room
1000. An in
room controller client (IRCC) 1012, which can be a local computer located in
or near
room 1000, at least partially controls motion clients 1008A and 1008B, cameras
1010A
and 1010B, and other electronic devices in room 1000. IRCC 1012 also analyzes
video
data generated by cameras 1008, 1010 in order to identify behavior of patient
1002 that
may be predictive of support exiting.
Other electronic devices include an in-room A/V interface client 1014, which
can
be used to establish one- or two-way communication with patient 1002, patient
care client
1016, external A/V client 1018 (e.g., in a hallway), bathroom interface 1020
(e.g., call
button, microphone and/or speaker), and manual patient interface client 1022
(e.g., a call
button, pain scale dial, etc.). The room is shown having a chair 1024 or other
furniture
(e.g., wheel chair), upon which visitors or even the patient may rest at least
some of the
time. The monitoring system can be used to detect potential support exiting by
patient
1002 of chair/furniture 1024 in addition to bed 1004.
The IRCC 1012 and electronic devices in room 1000 can interoperate to
implement the principles of the present invention. High risk motion clients
1008A and
1008B, either alone or in combination with one or both of cameras 1010A and
1010B,
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can monitor a patient's movements in bed 1004 and/or chair or other furniture
1024.
Generally, a patient's movement on a bed or other support can be monitored
through a
grid monitoring system ("GMS") that identifies patient vertical and horizontal
movements that may be indicative of an attempt to exit the furniture. The time
a body
part is located within a critical zone and/or changes in position and/or
changes in speed
can all be determined. The GMS can also utilize pressure, temperature, and
other
distributed sensors located within a bed or other furniture or directly
attached to a patient.
Inputs from the various clients and sensors in room 1000 can be provided to
the IRCC
1012 and/or facility master (not shown). In addition, any of cameras 1010A,
1010B or
1020, as well as motion clients 1008A and 1008B, can monitor a patient's
position and/or
movements within room 1000 when the patient is not resting on a bed 1004,
chair 1024
or other support located in room 1000.
Upon activation of the GMS or other high risk motions clients, in room
controller
client 1012 and/or a facility master utilizes patient management software to
initiate and
establish responsive actions. For example, upon detecting activities that
predict an
unattended support exit, in room controller 1012 and/or a facility master can
establish a
real time A/V connection with a central station (e.g., nurse's) and/or one or
more mobile
caregiver clients (e.g., PDAs carried by responder caregivers). Further, in
room
controller client 1012 and/or a facility master can activate external A/V
client 1018 (e.g.,
an alarm in a hallway) and/or initiate archiving of data from one or more of
high risk
motion clients 1008A and 1008B, and cameras 1010A, 1010B and 1020 upon the
occurrence of a support exiting event or other pre-established triggering
event.
Figure lOB further depicts a provider location client 1026 (e.g., an RFID
device),
a provider PDA 1028, a provider ID tag 1030 (e.g., an RFID device), other
facility ID tag
1032 (e.g., an RFID device), and/or diagnostic equipment 1034 which have
entered room
1000. Each of these devices can communicate with IRCC 1012 and/or a system-
wide
tracking system that communicates direct to a facility master computer (not
shown) via
various appropriate protocols (e.g., RF, IEEE 802.11 group, IEEE 802.15.4,
etc.). IRCC
1012 can update pertinent patient information, such as, for example, provider
ID, other
personnel ID or diagnostic equipment and time of entry. Detecting the presence
of
personnel and devices inside room 1000 indicates that facility personnel
and/or assets
associated with these devices have likely entered room 1000, for example, in
response to
a predicted support exiting event, a patient initiated alarm, prescribed
patient activities,
and the like.
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According to one embodiment, patient room 1000 may be networked with other
components including, for example, subscription clients (e.g., subscription
A/V web
browser interface client 1040 and subscription A/V voice and video over IP
client 1042),
which are connected to in room controller client 1012 by means of network
1044.
5 Subscriber clients 1040 and 1042 can be located at or external to a
healthcare facility.
Thus, providers in diverse locations can be notified of actionable events
occurring inside
patient room 1000.
Figure 11A illustrates an alternative embodiment for detecting patient support
exiting behavior comprising a light beam matrix system 1101, which may be used
instead
10 of or in addition to one or more cameras used to determine patient position
and/or
movements. Exemplary light beam matrix system 1101 includes a patient 1102
resting
on a bed 1104 or other support. A plurality of light transmitters 1160 are
positioned at
one side of bed or other support 1104 and generate first beams of light 1162,
which are
detected by corresponding first light receivers 1164. A plurality of second
light
15 transmitters 1166 are positioned laterally relative to first light
transmitters 1160 and
generate second beams of light 1168, which are detected by corresponding
second light
receivers 1170. Beams of light 1162, 1168 may comprise IR, visible or UV
wavelengths.
First and second beams of light 1162, 1168 may be positioned above the patient
1102 and cross-cross to form a light beam matrix that is able to detect
patient location
20 and/or movement in multiple (e.g., three) dimensions. The closer together
the light
beams, the finer the detection of patient position and/or movement. According
to one
embodiment, the light beams are spaced apart at intervals ranging from six (6)
inches to
two (2) feet (e.g., at one (1) foot intervals). As long as the patient 1102
rests flat on the
bed or other support 1104 or is otherwise below the light beam matrix
comprising first
25 and second light beams 1162, 1168, no beams of light are blocked or
interrupted such
that no movement is detected. Interrupting and/or resuming one or more beams
of light
may be indicative up upward and/or downward movement(s). Sequentially
interrupting
and/or resuming one or more of first light beams 1162 may be indicative of
lateral
movement(s). Sequentially interrupting and/or resuming one or more of second
light
30 beams 1162 may be indicative of longitudinal movement(s).
A computer system (not shown) interprets data generated by the light beam
matrix. Continuous light detection by the light sensors may be interpreted as
a series of
1 s(or Os) in computer language. Any interruption or blocking of a light beam
corresponds to a series of Os (or Is) in computer language and is indicative
of a body part
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being positioned between one or more particular light transmitters and
detectors.
Because bed exiting, for example, involves at least some lifting of the
patient's body
(e.g., to get over bed rails or pass through a narrow passage in a bed rail),
actual lifting of
the patient's body will typically block or interrupt at least one light beam.
Depending on
which light beams are interrupted and/or the sequence of such interruption,
the computer
can determine which parts of the patient's body have raised and/or moved.
Sequentially
interrupting multiple beams typically indicates movement (i.e., lateral,
longitudinal,
upward and/or downward depending on which sequence of beams are interrupted).
The
patient's movements, as detected by the light beam matrix and interpreted by
the
computer system, are compared to a patient profile of positions and/or
movements that
are predictive of support exiting by that patient. If potential patient
support exiting is
detected, an appropriate response can be initiated.
Figure 11B illustrates an alternative embodiment for detecting patient support
exiting behavior comprising a small zone RFID grid system 1103, which may be
used
instead of or in addition to one or more cameras used to determine patient
position and/or
movements. Exemplary RFID grid system 1103 includes a patient 1102 resting on
a bed
1104 or other support. The patient's body may be equipped with any appropriate
number
of RFID devices that are located so as to detect patient positions and/or
movements
associated with support exiting (e.g., right RFID wrist device 1106A, left
RFID wrist
device 1106B, right RFID ankle device 1106C, left RFID ankle device 1106D, and
neck
RFID device 1106E). Each RFID device can be separately encoded to represent a
specific body part of the patient to distinguish between positions and
movements of the
different body parts.
The RFID grid system 1103 includes a three-dimensional grid of small, cube-
like
RFID zones defined by a plurality of RFID detectors positioned along lateral
zone
boundaries 1180, longitudinal zone boundaries 1182, and elevation zone
boundaries
1184. The closer together the RFID detectors, the finer the detection of
patient position
and/or movement. According to one embodiment, the RFID detectors are spaced
apart at
intervals ranging from six (6) inches to two (2) feet (e.g., at one (1) foot
intervals). The
grid of RFID zones is able to detect three-dimensional patient position and/or
movements
as approximated by the positions and/or movements of the RFID devices 1106
worn by
the patient in or through the RFID zones.
A computer system (not shown) interprets data generated by the small zone RFID
grid as it detects the position and/or movement of the RFID devices 1106
attached to the
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patient 1102. Depending on which RFID zone is occupied by a specific RFID
device
and/or which RFID device(s) may be moving between RFID zones, the computer can
determine the position and/or location of corresponding body parts of the
patient. If
potential patient support exiting is detected, an appropriate response can be
initiated.
Figure 12 is a flow chart that schematically illustrates an exemplary method
1200
of monitoring a patient in order to detect support exiting and initiate a
response in the
event of predicted support exiting. This method may be carried out at least in
part using
the exemplary patient monitoring systems illustrated in Figures 3, 9, 1 0A-B
and 11A-B
discussed above and/or systems illustrated or discussed elsewhere in this
disclosure
and/or systems or components known in the art. A first act or step 1201
involves creating
or obtaining a plurality of patient profiles, each containing personalized
information
relating to support exiting behavior for each patient.
Examples of known bed exiting behaviors that have been observed as being used
by one or more patients include, but are not limited to: (1) bed slide method
(e.g., sliding
down towards the bottom of the bed); (2) right side rail roll method; (3) left
side rail roll
method; (4) torso angle up and leg swing right method; (5) torso angle up and
leg swing
left method; (6) torso angle up and upper body roll right method; and (7)
torso angle up
and upper body roll left method. A given patient may utilize one or more of
the
foregoing methods or a variation thereof, but typically one will dominate.
Other support
exiting behaviors are possible and can be accounted for where relevant.
Reference is now made to Figures 13A-13E which illustrate exemplary patient
behaviors as they relate to normal resting and bed exiting. Figure 13A
schematically
illustrates a normal resting position of a patient lying flat on a bed.
Figures 13B-13E
schematically illustrate positions associated with various bed exiting
positions,
movements or behaviors. Figure 13B roughly depicts the position of a patient
that has
engaged in the bed slide method of bed exiting. A notable feature is the
distance between
the patient's head and the pillow or headboard. Figure 13C roughly depicts
left and right
side rail roll methods in which the patient's body moves to the side or left
side rail
preparatory to bed exiting. Figure 13D illustrates the torso up and leg swing
left method
of bed exiting, which is characterized by upward movement of the torso coupled
with
movement of the left leg toward the edge of the bed. The torso up and right
leg swing
method is simply the mirror image of that shown in Figure 13D. Figure 13E
illustrates
the torso up and upper body roll left method, which is characterized by the
patient's torso
moving upward and the patient's body rolling to the left. The torso up and
upper body
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roll right method would be the mirror image of that shown in Figure 13E.
Each patient profile contains one or more spatial parameters or limits
associated
with the one or more support exiting behaviors that are known for each
patient. The
spatial parameters or limits relating to bed exiting may include data points
pertaining to
one or more of the seven common bed exiting behaviors noted above. Image
parameters
relating to exiting of other supports can be tailored to behaviors that are
typical for
patients exiting such supports. Patient profiles may include idiosyncratic
information that
is specific to a particular individual (e.g., base on patient height, weight,
speed of
movement, length of limbs, number of operable limbs, and/or personal habits of
position
and/or movement while support exiting).
By way of example, as illustrated a spatial parameter that corresponds to the
bed
slide method of bed exiting is the distance from a head feature to the top of
the bed (e.g.,
headboard) (see Figure 13B). Spatial parameters corresponding to the side rail
roll
methods (left or right) for bed exiting include: (a) the torso positioned
primarily to the
right or left of the bed and (b) the hand and/or arm on or over (i.e.,
covering or blocking
the view of) the left or right bed rail for a given period of time (see Figure
13C). Spatial
parameters corresponding to the torso up and leg swing methods (left or right)
of bed
exiting include: (a) the head elevated from a flat position and (b) right or
left legs and/or
feet breaking a vertical bed edge plane (see Figure 13D). Spatial parameters
corresponding to the torso up and upper body roll methods (left or right) of
bed exiting
include: (a) the head elevated from a flat position; (b) torso positioned
primarily to the
right or left portion of the bed; and one or both of (cl) the left or right
hand and/or arm on
or over (i.e., covering or blocking the view of) the left or right bed rail
for a given period
of time and/or (c2) the head breaking a vertical plane of the left or right
side rail (see
Figure 13E). In addition to patient body position, time of duration of a limb
or body part
at a specified location relative to a critical region of the support may also
play a roll in
determining bed or other support exiting.
Referring back to Figure 12, a second act or step 1202 of method 1200 involves
associating a corresponding patient profile with the particular patient being
monitored.
The use of RFID or other patient identification and tracking devices may
assist in
identifying which patient profile corresponds to the patient being monitored.
For
example, if a patient moves from room to room over time, different monitoring
equipment in the various rooms can all monitor the same patient at different
times, while
comparing patient position and/or movements with specific profile data for
that patient,
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because the patient is associated with a patient identification and tracking
device that
emits a uniquely encoded signal. Such association may alternatively be made
(e.g.,
entered manually into a computer) by hospital staff whenever a patient
occupies a
particular room.
A third act or step 1203 of method 1200 involves continuously monitoring a
patient resting on a support by capturing a series of images of the patient
and
surroundings and sending a data stream (e.g., video feed) to a computer system
for
analysis. Since both motion video recording devices and still photo devices
are capable
of taking individual frames, the distinction between the two is simply the
speed with
which individual frames are taken (i.e., the time interval between frames).
Thus, both
motion video recording devices and still photo devices can be used to send a
continuous
data stream to the analyzing computer system.
A fourth act or step 1204 of method 1200 involves analyzing the data stream
(e.g.,
frames of video data) to determine patient position and/or movement and
comparing them
to patient profile data relating to the support exiting behavior of that
patient. As
discussed above, such computer-implemented analysis of position and/or
movement may
be carried out using a grid monitoring system (GMS), which compares the
relative
position of one or more body parts in relation to stationary background
objects, such as
critical or predefined support zones. The use of patient specific profiles
enables the
computer system to more accurately detect and distinguish between behaviors
that are
indicative or predictive of patient support exiting and those which are not as
compared to
methods that are not patient specific but utilize the same sets of analytical
limits for all
patients. In this way, the incidences of false positives and false negatives
are
significantly reduced or substantially eliminated.
In the event that behavior consistent with predicted support exiting is
detected, a
fifth act or step 1205 of method 1200 is triggered. Step 1205 includes
initiating an
appropriate response in an attempt to prevent or mitigate harm to the patient.
Exemplary
responses include sending an alarm and/or video feed to a nursing station,
alerting the
patient of potential viewing, establishing one- or two-way communication
between the
patient, sending a pre-recorded message to the patient, sending notification
to a nearby
caregiver who can provide direct physical intervention, sounding an alarm, and
the like.
It may even be appropriate in some cases to activate an automated restraint
device that is
able to keep the patient from exiting the support until a caregiver is able to
arrive and
provide assistance.
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The method optionally includes an act or step 1206 of refining the patient's
profile to adjust one or more alert triggers to reflect monitored bed exiting
behavior. In
this way, the profile may be progressively refined to reflect a patient's
historical support
exiting behavior as monitored over time. This would be expected to decrease
the overall
5 number of false positives and false negatives, which would tend to increase
the accuracy
and efficiency of responding to potential support exiting behaviors on the
part of the
patient.
Figure 14 is a flow chart that schematically illustrates an exemplary method
or
sub-routine 1400 of generating and updating a patient profile for support
exiting
10 behavior. A first act or step 1401 involves setting initial support exiting
limits based on
information learned from or about the patient (e.g., as a result of a patient
or relative
completed questionnaire, observation by a qualified provider, general
defaults, and the
like). It is understand that the initial limits are advantageously modified as
more
information is gathered over time regarding a patient's actual support exiting
habits while
15 at one or more facilities.
Accordingly, a second act or step 1402 includes actually monitoring a patient
while resting on a support as discussed above and then either confirming or
rejecting an
alert of predicted patient support exiting. From one or more confirmations or
rejections
of predicted bed exiting, additional information regarding the specific
support exiting
2o habits of the patient can be learned. Act or step 1402 may form part of an
information
feedback loop for recursively refining patient profile data.
A third act or step 1403 includes manually or automatically revising or
updating
previously set support exiting limits in order to more accurately predict
support exiting
behavior by patient in question. In some cases, the computer system may
appropriately
25 alter patient profile data and limits relating to bed exiting so long as it
does not
substantially increase the risk of unassisted support exiting. In other cases,
patient profile
data and limits relating to bed exiting may be altered manually by a qualified
individual
or committee who analyzes data generated during predicted support exiting
events.
Limits can be established initially, or pre-existing limits may be tightened
or loosened, in
30 response to incidences of false positives and/or false negatives relative
to support exiting.
Figure 15 is a flow chart that schematically illustrates an exemplary method
or
sub-routine 1500 of responding to predicted patient support exiting. In a
first act or step
1501, a computer system finds a correlation between a patient's location
and/or
movements and predetermined limits for that patient contained in or derived
from a
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patient specific profile. A second act or step 1502 involves a computer
initiating a
response by sending an alert to both the patient's room (to warn of a breech
in privacy)
and a nursing station along with a live (i.e., real time) video feed of the
patient's room to
the nursing station. In a third act or step 1503, a staff member at the
nursing station
confirms or rejects the predicted support exiting upon viewing the live video
feed of the
patient's room. In a fourth act or step 1504, if support exiting is confirmed,
a computer-
controlled tracking system locates an unoccupied staff member who is assigned
and/or
near the patient's room and instructs the staff member to assist the patient.
Figure 16 is a flow chart that schematically illustrates an exemplary
monitoring
and response decision chart 1600 relative to bed exiting. The patient is
continuously or
periodically monitored, and the patient's position and/or movements are
analyzed. As
long as positions and/or movements predictive of bed exiting are not detected,
monitoring
continues. Of course, monitoring may also continue even after bed exiting is
predicted in
order to send a live video feed to a central station and/or determine an
escalation of
events.
If predicted patient bed existing is detected by the analyzing computer
system, an
alert is sent to a nursing station as well as a live video feed of the patient
for verification
of actual bed exiting. Prior to or at the same time, an alert is sent to the
patient's room of
potential third party viewing of the patient (e.g., to protect patient
privacy). If no
verification (i.e., confirmation or denial) is sent to the computer system
within a
predetermined time period, an automated response is initiated. If verification
is sent, the
computer determines whether bed exiting is confirmed or denied. If bed exiting
is
denied, the computer system resumes normal patient monitoring. If bed exiting
is
confirmed, further intervention is initiated.
The escalation of intervention to assist a patient who is in the process of
bed
exiting may include establishing one- or two-way communication between the
confirming staff member and the patient. It may also include sending an alert
to a nearby
or assigned staff member for direct physical intervention. An RFID or other
tracking
device can be used to verify that physical intervention was carried out as
prescribed. The
assisting caregiver may press a confirm button on a patient care interface
device
connected to the computer system, or the caregiver may provide oral
confirmation to the
staff member at the nursing station. The staff member at the nursing station
may view
the live video feed from the patient's room to confirm successful
intervention. If
intervention is confirmed, the response is complete. If intervention is not
confirmed, the
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response may include sending one or more additional alerts to other nearby
staff
members for direct physical intervention.
V. EXAMPLES OF OTHER METHODS AND SYSTEMS FOR ENHANCING
QUALITY AND PERFORMANCE AT A FACILITY
A. Providing Patient Assistance
Figure 17 a flow chart which illustrates an exemplary method 1700 for
responding
to patient alerts and providing assistance for a patient in need thereof.
Method 1700 will
be described with respect to the components and data in system architecture
300 (Figure
3). Method 1700 includes an act 1701 of providing the patients of a facility
with RFID
devices, each of which is associated with a specific patient, emits a signal
that permits
tracking of the specific patient, and includes an alert button that, when
actuated, sends an
alert associated with the specific patient. For example, as previously
described, a patient
staying in a room at the facility can be provided with a mobile patient
location bracelet
specifically assigned to the patient.
Method 1700 includes an act 1702 of receiving one or more signals emitted by
one or more RFID devices so as to track the location of patients throughout
the facility.
For example, sensing devices 312 within the facility can receive an RFID
signal, an alarm
signal, etc. from each mobile patient location bracelet. Each patient can be
tracked and
located in patient rooms and also throughout hallways, other common areas, and
dangerous or otherwise restricted areas of a healthcare facility. Signals can
be detected
by RFID sensors throughout a facility and relayed to computer systems that
process the
signals to generate appropriate electronic messages and notifications.
Method 1700 includes an act 1703 that includes, in response to receiving an
alert
from an RFID device associated with a patient in need of assistance,
identifying the
location of the patient, accessing relevant information from the patient's
profile, and
initiating a response (e.g., a patient specific response that can optionally
be tailored based
on information in the patient's profile, such as the most critical medical
conditions of the
patient requesting help). For example, in response to receiving an alert from
a mobile
patient location bracelet, the location of an assigned or nearby caregiver can
be identified
and appropriate physical intervention can be initiated. The intervention may
be different
for different patients based on their respective profiles and medical
conditions. A
computer system that processes the signal (e.g., an in room controller client
or facility
master) can generate an electronic message or notification that is sent to one
or more
other electronic devices corresponding to assigned or nearby healthcare
providers (e.g., to
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computer system 301c, PDA 309, PDA 309, etc.)
In response to using the alert feature, patient profiles can be updated to
count the
number of times each patient has initiated an authorized alert (e.g., an
actual physical or
medical emergency) versus an unauthorized alert (e.g., ordering room service,
socializing, horseplay, etc.). In order to provide for the specific needs of a
patient, patient
profiles data can be accessed and a predetermined or specially tailored
response initiated
(e.g., in the case of patients with special needs).
B. Selectively Archiving Patient Video Recordings
Figure 18 is a flow chart that illustrates an exemplary method 1800 for
selectively
archiving a video recording of a patient in response to a triggering event.
Method 1800
will be described with respect to the components in a typical patient room
(e.g., room
1000 of Figures l0A and l OB).
Method 1800 includes an act 1801 of generating a video data stream of a
patient's
room at a healthcare facility, wherein the video data stream is continuously
buffered and
then deleted in the absence of a triggering event such that the buffered and
deleted video
recording is normally never viewed by an individual in order to protect
patient privacy.
For example, a computer system can use a circular buffer of a specified size
such that
after a prescribed amount of time (e.g., 3 to 5 minutes) older video data is
overwritten by
new video data within the buffer. By way of example, an in room controller
and/or
facility master can make a temporary or buffered video recording of received
video data
from one or more cameras positioned within a patient's room.
Method 1800 includes an act 1802 of selectively archiving the temporarily
buffered video data stream in response to a triggering event so as to permit
later viewing
of the archived video recording. Video archival data can be stored at a
healthcare facility
or offsite. The archived video recordings are typically merely a back-up that
helps verify
the occurrence of a prescribed event and do not constitute a "medical record"
within the
meaning of HIPAA or other applicable statutes. By way of example and not by
limitation, the triggering event may comprise at least one of:
(i) entry into the room of an authorized RFID device encoded with entry rights
associated with an authorized individual;
(ii) entry into the room of an unauthorized RFID device associated with an
unauthorized individual not having entry rights;
(iii) entry into the room of an individual not associated with any RFID
device;
(iv) an asset used for a prescribed treatment and associated with an RFID
device
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being located in the room; and/or
(v) any other prescribed triggering event created by a given healthcare
facility.
C. Monitoring Patient Bed Rolling
Image analysis used to monitoring patient support exiting can also be used to
monitor patient bed rolling behaviors. With bed-bound patients, skin
breakdown,
pressure sores and ulceration are important clinical concerns. To prevent
these
conditions from occurring, staff may be scheduled to relieve skin pressure
points on the
patient's body by manually turning the patient periodically (e.g., every 2, 3
or 4 hours as
prescribed). This turning schedule disturbs the patient's natural sleep
pattern, increases
the risk of injuring the patient during the process, and adds significantly to
staff
workload.
By utilizing the in-room image analysis system to detect, record, count and
report
patient roll-overs, it will be possible to alert staff as to which patients
require manual
rolling over for each time period and which do not. Benefits to the patient
include better
sleep quality and less opportunity for tissue injury due to manual turning.
Benefits to the
staff include reduced work load by only turning those patients who actually
require it. To
visually verify that a patient has self-turned adequately during a time
period, the system
may allow for accelerated viewing of the buffered or recorded time period with
real-
speed viewing of detected turning events.
D. Patient/Staff Contact Time Tracker
Beginning with each new day, contact between individual patients and
categories
of staff members can be monitored and the cumulative duration of contact time
for each
category recorded. Contact data may be drawn from data available via RFID, GPS
and/or
advanced image analysis systems deployed about a medical facility. Contact may
be
defined on a facility by facility basis and can vary from patient and staff
within the same
room to patient and staff within the same and/or adjacent RFID zone. Patient
profiles
may contain minimum requirements for contact hours per day for each staff
category. At
predetermined times during the day, alerts may be issued to the staff through
monitors at
a central nursing station that indicate which patients are proportionally in
deficit of their
mandated contact hours. Alarms may be issued when contact hour deficits reach
critical
limits. Reports may be generated to reflect the facility's compliance with
mandated
patient/staff contact time requirements.
VI. EXEMPLARY SYSTEM LOGIC
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By way of example only and not by limitation, the inventive systems and
methods
for patient, staff and visitor monitoring and response may employ the
following
exemplary logic:
Assigned Limit Variables
5 [A] - head distance from headboard; initial value = 30"
[B] - head elevation from flat/down position; initial value = 12"
[C] - space between body and bedrail; initial value = 5" - may need
Small/Med/Large Values to reflect Patient body size
[D] - hand on bedrail time; initial value = 5 seconds
10 [E] - bed bound/requires assist for exit; yes=1, no=0
[F] - patient room assignment for RFID
[G] - number of exit attempt for Torso Slide
[H] - number of exit attempt for Torso Up / Leg Sweep
[I] - number of exit attempt for Bedrail Roll
15 [J] - number of exit attempt for Unknown Method
[K] - family members video recorded; yes=1, no=0
[L] - other residents video recorded within room; yes=1, no=0
[M] - resident currently in facility; yes=1, no=O
[N] - requires movement assistance; yes=1, no=0
20 [0] - requires movement assistance every "X" hrs
[P] - does the resident require a special diet; yes=1, no=0
[Q] - does the resident require assistance during eating; yes=1, no=0
[R] - number of RFID presences in eating area during breakfast, lunch and
dinner times per day
25 [S] - status of resident social interactions, maximum=10, minimum=0
[T] - requires device specific therapy every "Y" hrs
[U] - valid mobile emergency call button usage per month
[V] - unwarranted mobile emergency call button usage per month
[W] - is resident limited to movement within the facility; yes=1, no=0
30 [X] - is resident limited to movement within their room; yes=1, no=0
Ima egAnalysis Outputs
(1) top of head to headboard distance (inches)
(2) head elevation from flat position (inches)
35 (3) leg in bed or out of bed (in/out)
(4) space between body and bedrail (inches)
(5) hand grasping bedrail duration (seconds)
(6) no body in bed (absent/present)
40 Alert Conditions For Bed Exiting
For all [E]=1
Torso Slide = (1) > [A]
Torso Up / Leg Sweep =(2)>[B] and (3) = out
45 Bedrail Ro11= (4)<[C] and (5) > [D]
Bed Exit Has Occurred = (6) is absent and RFID [F] is positive
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Action Taken For Positive Exit Alert
check RFID for Staff presence at Nursing Station
o if no - then send pre-recorded message, alarm sent to closest shell staff
RFID
PDA, document, and go to Patient Profile Update
o if yes - then request Alert Verification or Alert Rejection from staff
~ if neither Verify or Reject is given within 30 seconds then send pre-
recorded message, alarm sent to closest shell staffRFID PDA,
document and go to Patient Profile Update
o if yes and Alert Verification is Positive then
~ alarm sent to closest shell staffRFID PDA
~ Video/Audio link established with Nursing Station
~ Patient Profile is Updated
o if yes and Alert Rejection is Positive then
= Possible Patient Profile Update (loosen alert criteria)
Patient Profile Update For Bed Exiting
[A]=[A]-[G] until [A]=20" then [A]=[A]
[B]=[B]-[H] until [B]=6" then [B]=[B]
[C]=[C]+([I]/3) until [C]=9" then [C]=[C]
[D]=[D]-([I]/3) until [D]=2 seconds then [D]=[D]
In-Room Camera Record On/Off Control
Camera Record is OFF until triggered by one of the following Actions:
1. For [K]=yes and [L]=yes, the detection of an RFID that doesn't match with
[F]
2. For [K]= no and [L]=yes, the detection of an RFID that doesn't match with
[F]
and is not a Family RFID
3. For [K]= yes and [L]=no, the detection of an RFID that doesn't match with
[F]
and is not a Resident RFID
4. For [K]=no and [L]=no, the detection of an RFID that doesn't match with [F]
and
is not a Resident RFID or a Family RFID
5. Alternatively for 3. and 4., a numeric coded "CAMMERA OFF" control pad
could be accessible for each resident in each room then 3. and 4. would be
deleted
6. Door motion detector detects motion and no RFID is detected in the zone
immediately positioned by the door - Alert Security
7. Resident RFID [F] is detected but wide angle motion detector has not
detected
movement for over 12 hrs and [M]=1 -- Alert Nursing Station
An actively recording camera is STOPPED from further recording by one of the
following Actions:
1. The only detectable RFID signal is [F] and conditions (6) or (7) were not
the
source triggers
2. No RFID detection and no detected movement in the room for > .5 hrs
3. Manual over-ride from Nursing Station
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Bed Bound Movement Therapy
1. For [N]=l, NUM=number of Staff RFID visits to room per 24hrs
2. For [N]=1, INTV=time period since last exiting of Staff RFID from room
3. If INTV> 0.9*[O] then Alert Nursing Station
4. If INTV >1.3*[O] then Alarm Nursing Station and Document
Food / Nutrition Trackin~
1. If [M]=1, [N]=O and [R]=O then Alarm and document
2. If [M]=1, [N]=0 and [R]=1 then Alert and RR=RR+1
3. If [M]=1, [N]=O and RR>3 then Alarm and document
Resident Requires Assistance When Eating
1. If [M]=1 and [Q]=1 then For Count Staff RFID and Food Tray RFID in Patient
Room during meal times QQ=QQ+1 per day, reset QQ=O each night
2. If QQ<3 then Alert
3. If QQ<2 then Alarm and document
(NOTE: if facility moves residents to another area for assistance with eating
system will
miss event)
Social Interaction Tracking
1. If RFID detected in Occupied Common Areas, then SI=SI+1
2. If Resident RFID detected in Room ~[F], then SI=SI+1
3. If detection of Assigned RFID in [F] and other Resident RFID in [F], then
SI=SI+1
4. If detection of Family RFID in [F] while Assigned RFID is in [F], then
SI=SI+1
5. At end of day, If SI>4 then [S]=[S]+1
6. At end of day, If SI=4 then [S]=[S]
7. At end of day, If SI=3 then [S]=[S]-1
8. At end of day, If SI=2 then [S]=[S]-2
9. At end of day, If SI=1 then [S]=[S]-3 and Alert Nursing Station
10. At end of day, If S1=0 then [S]=[S]-4 and Alarm Nursing Station and
document
11. At end of day, If S<5 then Alert Nursing Station
12. At end of day, If S<1 then Alarm Nursing Station and Document
In-Room Therapy Requiring Special Equipment
1. Skip entire subroutine If [M]=0 or [T]=0
2. If Staff RFID and Device RFID are detected in [F], then TD=TD+1
3. If (current military time) >1.2*[T] and TD=O then Alarm Nursing Station and
document
4. If TD=1 then begin TDT=timer
5. If TDT>.9*[T] then Alert Nursing Station
6. If TDT>1.2*[T] then Alarm Nursing Station and document
7. If TD=2 then TDT = 0 and begin timer and TD=0
8. Loop back to 1.
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RFID Mobile Emergency Call Button
l. Unique Emergency RFID is detected
2. Individual Resident is Identified
3. Resident Location is Identified
4. Nursing Station is Alarmed
5. Location is compared to list of "wired" facility locations
6. If location is "wired", video/audio link is established with Nursing
Station
7. If RFID of Staff is present at Nursing Station and "wired" link existed,
then wait
30 seconds for (VERIFY / REJECT) from Nursing Station before Alarm is
lo transmitted to PDAs. Send Alarm immediately for VERIFY, no Alarm for
REJECT.
8. If VERIFY then [U]=[U]+1, reset to [U]=0 at first of month
9. If REJECT then [V]=[V]+1, reset to [V]=0 at first of month
10. If [U]> 1, document to staff "high risk resident"
11. If [V]>3, document to staff "resident requires counseling"
Resident Wandering Detection
1. If [W]=1 and solo Resident RFID (no associated Staff or Family RFID) is
detected approaching or at exit then
a. Alert Nursing Station
b. Wait 30 seconds for VERIFY/REJECT
c. If VERIFY then Establish Video/audio link if location is "wired"
d. If VERIFY then Alarm Staff/Security PDAs
e. Document Event
f. If 30 seconds elapse with no response from Nursing Station then d. & e.
2. If [X]=1 and solo Resident RFID (no associated Staff or Family RFID) is
detected outside room [F] then
a. Alert Nursing Station
b. Wait 30 seconds for VERIFY/REJECT
c. If VERIFY then Establish Video/audio link if location is "wired"
d. If VERIFY then Alarm Staff PDAs
e. Document Event
f. If 30 seconds elapse with no response from Nursing Station then d. & e.
3. If Resident RFID is detected in any Facility Area that is denoted
"Restricted"
without the presence of Staff RFID then
a. Alert Nursing Station
b. Wait 30 seconds for VERIFY/REJECT
c. If VERIFY then Establish Video/audio link if location is "wired"
d. If VERIFY then Alarm Staff/Security PDAs
e. Document Event
f If 30 seconds elapse with no response from Nursing Station then d. & e.
"Closest Staff Locator" / Shell Method
For a uniform grid of RFID zones measuring MM by NN and numbered from left to
right, starting in the upper left zone
Shell 0 = X (the present location of the Resident in need)
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Shell 1= X-1, X+1, X+MM, X-MM, X+MM+1, X+MM-1, X-MM+1, X-MM-1
Shel12 = X-2, X+2, X-2+MM, X-2-MM, X-2+2MM, X-2-2MM, X+2+MM,
X+2-MM, X+2+2MM, X+2-2MM, X-2MM, X-2MM+1, X-2MM-1,
X+2MM, X+2MM+ 1, X+2MM-1
The present invention may be embodied in other specific forms without
departing
from its spirit or essential characteristics. The described embodiments are to
be
considered in all respects only as illustrative and not restrictive. The scope
of the
invention is, therefore, indicated by the appended claims rather than by the
foregoing
description. All changes which come within the meaning and range of
equivalency of the
claims are to be embraced within their scope.
What is claimed is:
