Patent Publication Number: US-7911348-B2

Title: Methods for refining patient, staff and visitor profiles used in monitoring quality and performance at a healthcare facility

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application is a continuation-in-part of co-pending U.S. application Ser. No. 11/608,074, filed Dec. 7, 2006, which claims the benefit under 35 U.S.C. §119(e) of co-pending U.S. provisional application No. 60/748,376, filed Dec. 9, 2005, co-pending U.S. provisional application No. 60/799,041, filed May 10, 2006, co-pending U.S. provisional application No. 60/835,662, filed Aug. 4, 2006, and co-pending U.S. provisional application No. 60/826,634, filed Sep. 22, 2006. The disclosures of the foregoing applications are incorporated herein in their entirety. 
    
    
     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&#39; 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&#39;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&#39;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&#39;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 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 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. 
     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, ultrasound devices, an ultrasound 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. 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 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&#39;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 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 refined 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 and/or ultrasound devices carried by patients, staff, assets, and visitors, RFID and/or ultrasound 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 or ultrasound device carried by the responder can also be tracked automatically to verify that intervention has occurred. Examples of 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, ultrasound, 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&#39;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&#39;s room. A staff member views the live video stream from the patient&#39;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 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&#39;s station. Two-way communication can also be established to determine the patient&#39;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&#39;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 or ultrasound device worn or carried by each patient that emits a signal that can be detected and traced to a specific location by a corresponding RFID sensor grid or ultrasound sensor grid respectively. RFID devices and ultrasound devices may include an alert device that can be activated in case of emergency of other urgent need. Because an RFID device or ultrasound 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&#39;s profile in order to tailor the response to specific patient needs. Patient usage of the alert feature can be tracked, analyzed and used to update the patient&#39;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: 
         FIG. 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; 
         FIG. 2  schematically illustrates an exemplary facility monitoring master system; 
         FIG. 3  schematically illustrates exemplary computer architecture that facilitates facility, patient, staff and/or asset monitoring and event response management; 
         FIG. 4  is a flow chart that illustrates an exemplary method for managing a response to an actionable event in a healthcare facility; 
         FIG. 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; 
         FIG. 6  is a flow chart that illustrates an exemplary method for determining patient care and wellness using individualized patient profiles; 
         FIG. 7  schematically illustrates the interrelationship of various data gathering and analysis modules used to maintain and refine a patient profile; 
         FIG. 8  is a flow chart that illustrates an exemplary method for maintaining stored profiles for a plurality of patients at a healthcare facility; 
         FIG. 9  schematically illustrates an exemplary system for patient monitoring, alert and response; 
         FIGS. 10A and 10B  schematically illustrate exemplary configurations of patient rooms at a healthcare facility equipped for patient monitoring and response to support exiting; 
         FIGS. 11A and 11B  schematically illustrate alternative patient support exiting detection systems; 
         FIG. 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; 
         FIGS. 13A-13E  schematically depict a patient in various exemplary positions on a bed relative to known bed exiting behaviors; 
         FIG. 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; 
         FIG. 15  is a flow chart that illustrates an exemplary method for responding to a computer predicted support exiting event; 
         FIG. 16  is a decision chart that illustrates an exemplary decision sequence for responding to an alert of predicted bed exiting; 
         FIG. 17  is a flow chart that illustrates an exemplary method for providing an automated response to a patient initiated alert; and 
         FIG. 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 PREFERRED EMBODIMENTS 
     I. 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 profiles, algorithms, human verification of triggering events, and direct human intervention to provide improved quality of care and performance based on each patient&#39;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 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&#39;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 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.), ultrasound 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 system. Computer-readable media that store computer-executable instructions are physical storage media. Computer-readable media that carry computer-executable instructions are transmission media. Thus, by way of example, and not limitation, computer-readable media can comprise physical storage media or transmission media. 
     Physical 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 transmission medium. Transmissions 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 can be accessed by a general purpose or special purpose computer. Combinations of the above should also be included within the scope of computer-readable media. 
     Further, it should be understood, that upon reaching various computer system components program code means in the form of computer-executable instructions or data structures can be transferred automatically from transmission media to physical storage media. For example, computer-executable instructions or data structures received over a network or data link can be buffered in RAM within a network interface card, and then eventually transferred to computer system RAM and/or to less volatile physical storage media at a computer system. Thus, it should be understood that physical storage media can be included in computer system components that also (or even primarily) utilize transmission media. 
     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. 
     II. 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.  FIG. 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  FIG. 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  102   a , room associated clients  102   b , support exiting monitoring clients  102   c , care giver system clients  102   d , facility patient, staff, visitor and asset tracking and location clients  102   e , external facility patient, staff and asset tracking clients  102   f , facility audio/visual clients  102   g , external facility audio/visual clients  102   h , and nursing station clients  102   i . 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 and/or nursing station client  102   i , 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. 
     The communication pathways  103  used to communicate gathered data from clients  102  to facility master computer  101  are exemplified by satellite  103   a , paging network  103   b , PLC/BPL  103   c , infrared network  103   d , cable/telephone network  103   e , cellular/PCS/UWB system  103   f , IEEE 802.xx wireless  103   g  (e.g., Wi-Fi, Wi-Max, Zigbee, etc.), ultrasound  103   h , RFID/GPS  103   i , wireless and wired broadband Internet  103   j , and public/private frame relay network  103   k  (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 ). 
       FIG. 2  schematically illustrates an exemplary facility master computer system  200  that can be used to control and implement quality and performance monitoring 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  FIG. 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  204   a  (e.g., archived in response to detection of an actionable event), profile data  204   b  (e.g., patient, staff and visitor data), and algorithms  204   c  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  FIG. 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  206   a , in room client management  206   b , care giver systems management  206   c , facility personnel location management  206   d , facility asset tracking and location management  206   e , external facility asset and personnel tracking management  206   f , external facility audio/video management  206   g , patient care interface and protocol management  206   h , system security manager  206   i , report generator manager  206   j , remote application interface  206   k , data modeling subsystem  206   i , alarm manager/generator  206   m , and asset management subsystem  206   n.    
       FIG. 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  301   a  (e.g., facility master) located in a data center  302 , first peripheral computer system  301   b  (e.g., in room controller client) at patient location  303 , and second peripheral computer system  301   c  at a central station (e.g., nurse&#39;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  FIGS. 10A and 10B , which are discussed more fully below. Each computer system  301   a - 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, ultrasound 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&#39;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 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  301   b  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  301   a  at data center  302  for processing. 
     In some environments, ultrasound technologies, such as, for example, those developed by Sonitor Technologies, may be preferred for monitoring patient, staff, and asset locations, movements, and interactions within a facility. Ultrasound waves can be blocked by normal walls, are less likely to reflect off of metallic objects, and are less likely to interfere with sensate instruments. For example, ultrasound waves can be confined to a room (e.g., a patient room) where they originate. When using ultrasound receivers and detectors, various Digital Signal Processing (DSP) algorithms can be used to convert ultrasound waves into meaningful digital data (e.g., for transport on a wired network). The DSP algorithms can be configured to ensure that ultrasound detectors interpret ultrasound waves without risk of interference from any environmental noise or other signals nor interference with sensitive instruments. 
     However, in other environments the increased range of RFID may be preferred for monitoring patient, staff, and asset locations, movements, and interactions within a facility. For example, since RFID signals can pass through walls, RFID detection systems can be implemented with fewer detectors. 
     Computer system  301   c  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  301   c  such that provider  305  can access electronic communications (e.g., alarm  320 , video feeds, A/V communications) presented at computer system  301   c . Acknowledgment  321  can be sent to other computer systems  301   a ,  301   b  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, ultrasound, 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  301   b , storage device  310 , sensors  312 , and I/O 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, ultrasound 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 I/O devices can also send data to any appropriate computer system for processing and event detection, including either or both of computer systems  301   a  and  301   c.    
     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 vicinity of the sensor  312 . For example, characteristics of a patient&#39;s gait can be observed when the patient walks by a video camera or closely spaced apart location sensors. A patient&#39;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&#39;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  301   b . 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  301   b  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  301   c  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  301   a , 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  301   b  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 or ultrasound 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&#39;s walk and/or support exiting. Computer system  301   b  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  301   b  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 system  301   a  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  301   b . 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  301   a  and storage device  326  can be physically located at data center  302 . Storage device  326  can store profiles (e.g., profiles  324   a  and  324   b ) for patients, staff and visitors. Profile manager  330  can receive patient data  322  sent to computer system  301   a  (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&#39;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. 
     Alternately, patients, providers, and assets may carry ultrasound transmitting devices that can be used to determine patient, provider and asset locations within a healthcare facility. Transmitted ultrasound waves can be detected by ultrasound receivers. 
     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. 
       FIG. 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 components and data in monitoring system  300  of  FIG. 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 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  301   b . 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  301   b  can send an alarm  320 , including event  317 , to computer system  301   c  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  301   c  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 . 
     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  301   c  can initiate a predetermined 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  301   c  can send acknowledgment  321  to either or both of computer systems  301   a ,  301   b . Sending acknowledgment  321  may result in establishing one or two-way communication between a healthcare provider and patient location  303  (e.g., using I/O devices  313 ). For example, provider  305  can input commands at computer system  301   c  to open communication from central station  304  to patient location  303 . Similarly, providers  306 ,  307  can input commands at PDA&#39;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 and/or ultrasound detectors at patient location  303  can detect an RFID transmitting device and/or ultrasound transmitting device respectively 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  301   b  can send an alert to computer system  301   c  (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.  FIG. 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  301   a  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 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. 
       FIG. 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 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 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. 
     Alternately to or in combination with RFID, patients, staff, assets and visitors can be assigned an ultrasound device that can be tracked throughout a facility by means of an ultrasound detection system comprising a plurality of ultrasound detectors throughout the facility. The location of the ultrasound detectors and assignment of ultrasound devices can be recorded and maintained in a computer system. As patients, staff, assets and visitors move throughout the facility, the ultrasound detectors notify the computer system of ultrasound devices that are currently being detected. This computer system can correlate the location of each ultrasound device, as well as the duration of each ultrasound 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&#39;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 care 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. 
       FIG. 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  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 and/or ultrasound system  706  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 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/ultrasound zone security  710 , contact tracker  712 , ambulation tracker  714 , emergency response  716 , socialization  718 , surveillance controller  720 , mobile call button  722 , and 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  FIG. 7  is used to update or refine patient profiles  730 , staff profiles  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 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 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&#39;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&#39;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 elevation (inches) 
           
         
       
    
     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&#39;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&#39;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&#39;s presence not verified within time response period; (5) if nurse&#39;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&#39;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 or ultrasound 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/Ultrasound Zone Security Module 
     As discussed above, the RFID/Ultrasound zone security module  710  is typically located in the facility master  702 . According to one embodiment, the RFID/Ultrasound zone security module  710  scans the RFID zone locations and/or ultrasound 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&#39;s or visitor&#39;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 and/or ultrasound zones. The amount of elapsed time can be used to assess staff performance. 
     If an individual&#39;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 and/or ultrasound 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. 
     
       
         
           
               
               
               
               
               
             
               
                   
               
             
            
               
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     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&#39;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 and/or ultrasound zones occupied by each individual during each 24 hour period and multiplying that value by the (RFID and/or ultrasound) 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, wheelchair or crutches). If so, the module  714  also tracks the location of any assigned devices for each patient using the associated RFID or ultrasound for the device. For the subset of patient requiring ambulation devices, determining whether any patient moves between RFID and/or ultrasound zones without detecting the presence of the assigned RFID or ultrasound tagged ambulation 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 example, for a patient who normally passes between RFID and/or ultrasound 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 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&#39;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 rooms—denoted by RFID or ultrasound 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. 
     The RFID/ultrasound 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 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 and/or ultrasound monitored patient movements and behaviors and generates either a (+) or (−) influence on a numeric value that represents each patient&#39;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 1 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&#39;s room; (2) assisted exits of facility; (3) other patients to patient&#39;s room; (4) trips by patient to other patient&#39;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, ultrasound, motion detection, video cameras and/or door beam tripping data to detect the entrance of staff, patients, or visitors into a patient&#39;s room or other private zone. Upon authorized entry by individuals into a patient&#39;s room, as detected using assigned RFID and/or ultrasound devices, the surveillance controller module  720  initiates A/V monitoring of the patient&#39;s room and triggers HIPAA appropriate patient notification. Upon room clearing of RFID and/or ultrasound signals (other than those which assigned resident), surveillance controller module  720  terminates A/V monitoring. 
     Upon unauthorized entry by individuals into a patient&#39;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 and/or ultrasound 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 and/or ultrasound signal enters the patient&#39;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 and/or ultrasound 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 can wear RFID and/or ultrasound bracelets that include a manual call button that allows for manual activation of a secondary RFID transmitter or ultrasound transmitter during emergency situations. When an emergency RFID or ultrasound signal 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&#39;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/ultrasound system  706  to GPS when residents travel into an exterior courtyard region of the facility not equipped with RFID or ultrasound zone sensors and/or in cases of patient wandering or flight. Patient movement toward a courtyard can be determined by a patient assigned RFID or ultrasound 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 or ultrasound devices, track the time period between denture RFID or ultrasound signal occupying an RFID or ultrasound 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 or ultrasound signal that is changing zones (i.e., moving) belongs to the patient moving through equivalent RFID or ultrasound 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. Patient 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.
         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—H, 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—H, 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/ultrasound code, S   30. maxillary denture—RFID/ultrasound code, S   31. mandibular denture—RFID/utlrasound 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/ultrasound codes, S   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   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 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. 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. work schedule—day of week, time of day, S   2. restricted RFID/ultrasound zones—x,y,z, S   3. assigned resident rooms—x,y,z, S   4. total ambulation—time x and distance y, AD   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   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   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 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/ultrasound signals—x,y,z, S   5. allowed resident room RFID/ultrasound zones—x,y,z, S   6. generic allowed RFID/ultrasound zones—x,y,z, S   7. generic restricted RFID/ultrasound 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/ultrasound signal—x, AD   15. second most commonly associated human RFID/ultrasound signal—x, AD   16. third most commonly associated human RFID/ultrasound signal—x, AD   17. fourth most commonly associated human RFID/ultrasound signal—x, AD       

     C. Refinement of Profiles 
       FIG. 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, I/O devices, cameras or computers positioned within the facility that detect or 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. 
       FIG. 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  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&#39;s face, such as beyond the foot of the patient&#39;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  916 A and  918 A 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  916 A,  918 A 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  916 A and  918 A are typically not viewed by any human but are actively deleted or simply not stored or archived. This helps protect patient privacy. 
     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  916 B,  918 B 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 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 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 . 
     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 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 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 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 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 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&#39;s room by staff, other patients or visitors, or activation of the emergency call button by the patient. 
       FIGS. 10A and 10B  schematically illustrate various embodiments of exemplary patient room configurations used in monitoring a patient and providing one or more responses. In the embodiment of  FIG. 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  1006 , such as an RFID bracelet, ultrasound bracelet, or other device. 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. Tracking 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&#39;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&#39;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&#39;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&#39;s body and fixed locations (e.g., the patient&#39;s head and the headboard of the bed, the patient&#39;s arms and legs relative to respective left and right bedrails, the height of the patient&#39;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&#39;s body or portion thereof with locations and movements that are predictive of patient bed exiting by that patient as contained in the patient&#39;s profile of bed exiting behaviors. Whenever the unique singular or combination of positions, 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 and/or ultrasound data, this information can be used to detect unauthorized entry into patient&#39;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  1096 . 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&#39;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  1096  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 or ultrasound grid set up throughout the room can be used to monitor the position and/or 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). 
       FIG. 10B  illustrates an exemplary patient room  1000  which includes a patient  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&#39;s room  1000 . The patient  1002  may wear or carry a mobile electronic tracking device  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. Tracking device  1006  may be a conventional RFID or ultrasound device (e.g., bracelet) and may be equipped with a patient emergency call or panic button (not shown) as known in the art. Tracking device  1006  is specially assigned (and attached) to patient  1002  staying in patient room  1000 . Tracking device  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  1008 A and  1008 B (e.g., which include one or more of cameras, electronic motion sensors, electric eyes, RFID detectors, ultrasound detectors, etc.) may be positioned on either side of bed  1004 , thus providing two separate data streams for interpretation of the patient&#39;s position and/or movements. Side cameras  1010 A and  1010 B are positioned on either side of patient  1002  to provide additional data streams for interpretation of the patient&#39;s position and/or movements. At least one of cameras  1010 A and  1010 B 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  1008 A and  1008 B, cameras  1010 A and  1010 B, 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  1008 A and  1008 B, either alone or in combination with one or both of cameras  110 A and  1010 B, can monitor a patient&#39;s movements in bed  1004  and/or chair or other furniture  1024 . Generally, a patient&#39;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  1010 A,  1010 B or  1020 , as well as motion clients  1008 A and  1008 B, can monitor a patient&#39;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&#39;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  1008 A and  1008 B, and cameras  1010 A,  1010 B and  1020  upon the occurrence of a support exiting event or other pre-established triggering event. 
       FIG. 10B  further depicts a provider tracking device  1026  (e.g., an RFID or ultrasound device), a provider PDA  1028 , a provider ID tag  1030  (e.g., an RFID or ultrasound device), other facility ID tag  1032  (e.g., an RFID or ultrasound 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. 
     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 . 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 . 
       FIG. 11A  illustrates an alternative embodiment for detecting patient support exiting behavior comprising a light beam matrix system  1101 , which may be used instead 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 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 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 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 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 0 s) in computer language. Any interruption or blocking of a light beam corresponds to a series of 0 s (or 1 s) in computer language and is indicative of a body part being positioned between one or more particular light transmitters and detectors. Because bed exiting, for example, involves at least some lifting of the patient&#39;s body (e.g., to get over bed rails or pass through a narrow passage in a bed rail), actual lifting of the patient&#39;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&#39;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&#39;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. 
       FIG. 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&#39;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  1106 A, left RFID wrist device  1106 B, right RFID ankle device  1106 C, left RFID ankle device  1106 D, and neck RFID device  1106 E). 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 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. 
     A similarly configured ultrasound grid system can also be used to implement the functionality depicted in  FIG. 11B . A patient&#39;s body may be equipped with any appropriate number of ultrasound devices that are located so as to detect patient positions and/or movements associated with support exiting. Each ultrasound 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. 
     Thus, an ultrasound grid system can also include a three-dimensional grid of small, cube-like ultrasound zones defined by a plurality of ultrasound detectors positioned along lateral zone boundaries  1180 , longitudinal zone boundaries  1182 , and elevation zone boundaries  1184 . The closer together the ultrasound detectors, the finer the detection of patient position and/or movement. According to one embodiment, the ultrasound 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 ultrasound zones is able to detect three-dimensional patient position and/or movements as approximated by the positions and/or movements of the ultrasound devices worn by the patient in or through the ultrasound zones. 
     Accordingly, a computer system (not shown) can interpret data generated by the small zone ultrasound grid as it detects the position and/or movement of the ultrasound devices attached to the patient  1102 . Depending on which ultrasound zone is occupied by a specific ultrasound device and/or which ultrasound device(s) may be moving between ultrasound 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. 
       FIG. 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  FIGS. 3 ,  9 ,  10 A-B and  11 A-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  FIGS. 13A-13E  which illustrate exemplary patient behaviors as they relate to normal resting and bed exiting.  FIG. 13A  schematically illustrates a normal resting position of a patient lying flat on a bed.  FIGS. 13B-13E  schematically illustrate positions associated with various bed exiting positions, movements or behaviors.  FIG. 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&#39;s head and the pillow or headboard.  FIG. 13C  roughly depicts left and right side rail roll methods in which the patient&#39;s body moves to the side or left side rail preparatory to bed exiting.  FIG. 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  FIG. 13D .  FIG. 13E  illustrates the torso up and upper body roll left method, which is characterized by the patient&#39;s torso moving upward and the patient&#39;s body rolling to the left. The torso up and upper body roll right method would be the mirror image of that shown in  FIG. 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  FIG. 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  FIG. 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  FIG. 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 (c 1 ) 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 (c 2 ) the head breaking a vertical plane of the left or right side rail (see  FIG. 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  FIG. 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, ultrasound, 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, 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. 
     The method optionally includes an act or step  1206  of refining the patient&#39;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&#39;s historical support exiting behavior as monitored over time. This would be expected to decrease the overall 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. 
       FIG. 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 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&#39;s actual support exiting habits while 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 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 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 response to incidences of false positives and/or false negatives relative to support exiting. 
       FIG. 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&#39;s location and/or movements and predetermined limits for that patient contained in or derived from a patient specific profile. A second act or step  1502  involves a computer initiating a response by sending an alert to both the patient&#39;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&#39;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&#39;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&#39;s room and instructs the staff member to assist the patient. 
       FIG. 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&#39;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&#39;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, ultrasound, 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&#39;s room to confirm successful intervention. If intervention is confirmed, the response is complete. If intervention is not confirmed, the 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 
       FIG. 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  ( FIG. 3 ). Method  1700  includes an act  1701  of providing the patients of a facility with tracking 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. A tracking device can transmit any of a variety of different type signals, such as, for example, RFID signals or ultrasound signals. 
     Method  1700  includes an act  1702  of receiving one or more signals emitted by one or more tracking 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 ultrasound 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 and/or ultrasound 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 a tracking device associated with a patient in need of assistance, identifying the location of the patient, accessing relevant information from the patient&#39;s profile, and initiating a response (e.g., a patient specific response that can optionally be tailored based on information in the patient&#39;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 computer system  301   c , 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 
       FIG. 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  FIGS. 10A and 10B ). 
     Method  1800  includes an act  1801  of generating a video data stream of a patient&#39;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&#39;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 tracking device encoded with entry rights associated with an authorized individual;   (ii) entry into the room of an unauthorized tracking device associated with an unauthorized individual not having entry rights;   (iii) entry into the room of an individual not associated with any tracking device;   (iv) an asset used for a prescribed treatment and associated with an tracking device being located in the room; and/or   (v) any other prescribed triggering event created by a given healthcare facility.       

     A tracking device can transmit any of a variety of different type signals, such as, for example RFID signals or ultrasound signals 
     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&#39;s body by manually turning the patient periodically (e.g., every 2, 3 or 4 hours as prescribed). This turning schedule disturbs the patient&#39;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. 
     VI. Exemplary System Logic 
     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
         [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   [E]—bed bound/requires assist for exit; yes=1, no=0   [F]—patient room assignment for RFID/ultrasound   [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   [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=0   [N]—requires movement assistance; yes=1, no=0   [O]—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/ultrasound presences in eating area during breakfast, lunch and dinner times per day   [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   [X]—is resident limited to movement within their room; yes=1, no=0       

     Image Analysis Outputs
         (1) top of head to headboard distance (inches)   (2) head elevation from flat position (inches)   (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)       

     Alert Conditions For Bed Exiting 
     For all [E]=1 
     Torso Slide=(1)&gt;[A] 
     Torso Up/Leg Sweep=(2)&gt;[B] and (3)=out 
     Bedrail Roll=(4)&lt;[C] and (5)&gt;[D] 
     Bed Exit Has Occurred=(6) is absent and RFID/ultrasound [F] is positive 
     Action Taken For Positive Exit Alert 
     check RFID/ultrasound for Staff presence at Nursing Station
         if no—then send pre-recorded message, alarm sent to closest shell staff RFID/ultrasound PDA, document, and go to Patient Profile Update   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 staff RFID/ultrasound PDA, document and go to Patient Profile Update   
           if yes and Alert Verification is Positive then
           alarm sent to closest shell staff RFID/ultrasound PDA   Video/Audio link established with Nursing Station   Patient Profile is Updated   
           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/ultrasound that doesn&#39;t match with [F] 
             2. For [K]=no and [L]=yes, the detection of an RFID/ultrasound that doesn&#39;t match with [F] and is not a Family RFID/ultrasound 
             3. For [K]=yes and [L]=no, the detection of an RFID/ultrasound that doesn&#39;t match with [F] and is not a Resident RFID/ultrasound 
             4. For [K]=no and [L]=no, the detection of an RFID that doesn&#39;t match with [F] and is not a Resident RFID/ultrasound or a Family RFID/ultrasound 
             5. Alternatively for 3. and 4., a numeric coded “CAMERA 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/ultrasound is detected in the zone immediately positioned by the door—Alert Security 
             7. Resident RFID/ultrasound [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/ultrasound signal is [F] and conditions (6) or (7) were not the source triggers 
             2. No RFID/ultrasound detection and no detected movement in the room for &gt;0.5 hrs 
             3. Manual over-ride from Nursing Station 
           
         
       
    
     Bed Bound Movement Therapy
         1. For [N]=1, NUM=number of Staff RFID/ultrasound visits to room per 24 hrs   2. For [N]=1, INTV=time period since last exiting of Staff RFID/ultrasound from room   3. If INTV&gt;0.9*[O] then Alert Nursing Station   4. If INTV&gt;1.3*[O] then Alarm Nursing Station and Document       

     Food/Nutrition Tracking
         1. If [M]=1, [N]=0 and [R]=0 then Alarm and document   2. If [M]=1, [N]=0 and [R]=1 then Alert and RR=RR+1   3. If [M]=1, [N]=0 and RR&gt;3 then Alarm and document       

     Resident Requires Assistance When Eating
         1. If [M]=1 and [Q]=1 then For Count Staff RFID/ultrasound and Food Tray RFID/ultrasound in Patient Room during meal times QQ=QQ+1 per day, reset QQ=0 each night   2. If QQ&lt;3 then Alert   3. If QQ&lt;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/ultrasound detected in Occupied Common Areas, then SI=SI+1   2. If Resident RFID/ultrasound detected in Room≠[F], then SI=SI+1   3. If detection of Assigned RFID/ultrasound in [F] and other Resident RFID/ultrasound in [F], then SI=SI+1   4. If detection of Family RFID/ultrasound in [F] while Assigned RFID/ultrasound is in [F], then SI=SI+1   5. At end of day, If SI&gt;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 SI=0 then [S]=[S]−4 and Alarm Nursing Station and document   11. At end of day, If S&lt;5 then Alert Nursing Station   12. At end of day, If S&lt;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/ultrasound and Device RFID/ultrasound are detected in [F], then TD=TD+1   3. If (current military time)&gt;1.2*[T] and TD=0 then Alarm Nursing Station and document   4. If TD=1 then begin TDT=timer   5. If TDT&gt;0.9*[T] then Alert Nursing Station   6. If TDT&gt;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.       

     RFID/Ultrasound Mobile Emergency Call Button
         1. Unique Emergency RFID/ultrasound 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/ultrasound of Staff is present at Nursing Station and “wired” link existed, then wait 30 seconds for (VERIFY/REJECT) from Nursing Station before Alarm is 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]&gt;1, document to staff “high risk resident”   11. If [V]&gt;3, document to staff “resident requires counseling”       

     Resident Wandering Detection
         1. If [W]=1 and solo Resident RFID/ultrasound (no associated Staff or Family RFID/ultrasound) 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. &amp; e.   
           2. If [X]=1 and solo Resident RFID/ultrasound (no associated Staff or Family RFID/ultrasound) 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. &amp; e.   
           3. If Resident RFID/ultrasound is detected in any Facility Area that is denoted “Restricted” without the presence of Staff RFID/ultrasound 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. &amp; e.   
               

     “Closest Staff Locator”/Shell Method
         For a uniform grid of RFID/ultrasound 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)   Shell 1=X−1, X+1, X+MM, X−MM, X+MM+1, X+MM−1, X−MM+1, X−MM−1   Shell 2=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.