Patent Publication Number: US-2007106129-A1

Title: Dietary monitoring system for comprehensive patient management

Description:
TECHNICAL FIELD  
      The present invention generally relates to comprehensive patient management systems and, more specifically, to systems and methods for monitoring patient dietary conditions and communicating suggested dietary input for the patient.  
     BACKGROUND OF THE INVENTION  
      Management of patients with chronic disease consumes a significant proportion of the total health care expenditure in the United States. Many of these diseases are widely prevalent and have significant annual incidences as well. Heart failure prevalence alone is estimated at over 5.5 million patients in 2000 with incidence rates of over half a million additional patients annually, resulting in a total health care burden in excess of $20 billion. Heart failure, like many other chronic diseases such as asthma, COPD, chronic pain, and epilepsy, is event driven, where acute de-compensations result in hospitalization.  
      Hospitalizations consume a large portion of the total health care expenditure allocated to the treatment of heart failure. Hospitalization and treatment for an acute de-compensation typically occurs after the de-compensation event has occurred. However, most heart failure patients exhibit prior non-traumatic symptoms, such as steady weight gain, in the weeks or days prior to the de-compensation. If the caregiver is aware of these symptoms, it is possible to intervene before the event, at substantially less cost to the patient and the health care system.  
      Intervention is usually in the form of a re-titration of the patient&#39;s drug cocktail, reinforcement of the patient&#39;s compliance with the prescribed drug regimen, or acute changes to the patient&#39;s diet and exercise. Such intervention is usually effective in preventing the de-compensation episode and thus avoiding hospitalization. Patients with chronic heart disease can receive implantable cardiac devices such as pacemakers, implantable cardioverter defibrillators (ICDs), and heart failure cardiac resynchronization therapy (CRT) devices. Currently, the electrophysiologist that implants a pacemaker or ICD requires a patient to make clinic follow up visits periodically, usually once every three or four months, in order to verify that the their implanted device is working correctly and programmed optimally. Device follow-ups are usually performed by the nurse-staff assisted by the sales representative from the device manufacturers. Device follow-ups are labor intensive and typically require patients to make multiple clinic visits.  
      A significant number of heart failure hospitalizations occur due to noncompliance with a strict dietary regimen. Despite adequate counseling and training during hospitalization and clinic visits, management of food intake by the patient continues to be the cause of recovery delays and even hospitalization. One primary reason for patient noncompliance with prescribed nutritional intake is the lack of adequate and timely feedback concerning the patient&#39;s dietary condition.  
     SUMMARY OF THE INVENTION  
      The present invention generally relates to monitoring and communicating a patient&#39;s dietary conditions. The invention relates to systems and methods for measuring data associated with a patient&#39;s dietary conditions, and can include comparison of that data to an expected dietary model. Based on this comparison, one or more actions can be performed including, but not limited to, providing feedback (e.g., recommended nutritional intake, exercise, and drug therapy) to the patient related to their dietary condition, reporting to a physician, alarming, creation of new dietary models/algorithms, etc. While the patient&#39;s own input of dietary information into the system can be useful for the comparison or for verifying other sources of measured data, the system is configured to perform accurately even in the absence of patient input or the input of incorrect information by the patient.  
      In accordance with one aspect, the invention relates to an advanced patient management system that includes a device, an interactive display, a repeater unit, and a host. The device assesses at least one dietary condition of a patient. The interactive display receives patient input related to the patient&#39;s dietary conditions and communicates dietary feedback to the patient. The repeater unit collects information from the device and the interactive display. The device may be, for example, a patient&#39;s implanted medical device. The host communicates with the repeater through a network. The system provides dietary related feedback to the patient in response to the collected information. The system may also include at least one sensor configured to assess at least one dietary condition of the patient. Some example sensors include a sodium sensor, a weight measuring sensor, a blood pressure sensor, a heart rate sensor, an INR/Coumadin sensor, a glucose sensor, a respiration sensor, an insulin sensor, a temperature sensor, and a hydration sensor. The dietary feedback may include dietary advice, food and menu options, calorie information, sodium information, hydration conditions, pharmacological dosage recommendations, and patient input prompts.  
      A further aspect of the invention relates to a method of monitoring dietary conditions of a patient. The method includes providing an implanted device, a repeater, and a host in communication with each other, collecting dietary information from the patient with the implanted device, comparing the collected dietary information to expected dietary conditions of the patient stored by the repeater or the host, and communicating dietary information to the patient in response to the comparison. The method may further include providing an interactive display and collecting dietary information from the patient via the interactive display. The method may still further include providing at least one sensor configured to measure a dietary condition of the patient, and comparing the dietary condition to expected dietary conditions of the patient stored by the repeater or the host.  
      A still further aspect of the invention relates to a method of monitoring and communicating a patient&#39;s nutritional/dietary condition. The method includes collecting data associated with at least one dietary condition of a patient, communicating the data to a host, comparing the collected data to an expected dietary model, and communicating to the patient a recommended nutritional intake.  
      The above summary is not intended to describe each disclosed embodiment or every implementation of the present invention. Figures and the detailed description that follow more particularly exemplify embodiments of the invention. While certain embodiments will be illustrated and described, the invention is not limited to use in such embodiments. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
      The invention can be more completely understood in consideration of the following detailed description of various embodiments of the invention in connection with the accompanying drawings, in which:  
       FIG. 1  illustrates an example system made in accordance with the present invention;  
       FIG. 2  illustrates another example system made in accordance with the present invention;  
       FIG. 3  illustrates an example method for collection and analysis of a nutritional feedback system for a patient;  
       FIG. 4  illustrates an example advanced patient management system made in accordance with the present invention;  
       FIG. 5  illustrates an example interrogator/transceiver unit made in accordance with the present invention;  
       FIG. 6  illustrates an example interactive display for use with the example interrogator/transmitter unit of  FIG. 5 ;  
       FIG. 7  illustrates an example communication system made in accordance with the present invention; and  
       FIG. 8  illustrates an example method for monitoring patient compliance with and efficacy of a patient drug regimen. 
    
    
      While the invention is amenable to various modifications and alternative forms, specifics thereof have been shown by way of example in the drawings and will be described in detail. It should be understood, however, that the intention is not to limit the invention to the particular embodiments described. On the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.  
     DETAILED DESCRIPTION  
      The present invention generally relates to monitoring and communicating a patient&#39;s dietary conditions. More specifically, the present invention relates to systems and methods for measuring data associated with a patient&#39;s dietary conditions, and comparison of that data to expected dietary conditions. Based on this comparison, one or more actions can be performed including, but not limited to, providing feedback (e.g., recommended nutritional intake, exercise, and drug therapy) to the patient related to their dietary condition, reporting to a physician, issuing an alert, or creation of new dietary models/algorithms. While the patient&#39;s own input of dietary information into the system can be useful for the comparison or for verifying sources of measured data, the system is configured to perform accurately even in the absence of patient input or the input of incorrect information by the patient.  
      As used herein, the term “patient” is used to mean any individual from whom information is collected. The term “caregiver” is used herein to mean any provider of services, such as health care providers including, but not limited to, nurses, doctors, and other health care provider staff. The terms “dietary information” and “dietary condition” are used herein to describe any physiological condition or subjective response by a patient that relates to a patient&#39;s diet. Example physiological conditions related to a patient&#39;s diet include heart rate, glucose levels, sodium levels, electrolyte levels, blood pressure, respiration rates, temperature, and weight. Some example subjective responses by a patient related to their diet include feeling faint or dizzy, feeling thirsty, feeling bloated or gaseous, feeling nauseated, feeling heart burn, feeling weak and lethargic, and feeling tired. Other example subjective responses by a patient relate to their nutritional/dietary intake and their physical activity.  
      I. Monitoring and Therapy Enhancement Using Dietary Models  
      In the embodiments illustrated herein, nutritional/dietary monitoring and therapy for a patient can be enhanced using data collected by one or more devices associated with a patient. Specifically, one or more sensors are used to collect data associated with the dietary related conditions of the patient. Patient input related to their subjective physical conditions as well as their dietary intake and physical activity. The collected data is compared to an expected dietary model. An expected dietary model may be based upon one or more algorithms that generate different outcomes based on certain conditional inputs. The expected dietary model may be established based on, for example, the past dietary and physical history of the patient, target conditions established by a physician, industry standards and recommendations, or by patient preferences. Based on the comparison, one or more actions are performed including, but not limited to, reporting or alarming the patient, the patient&#39;s physician, or a third party, creation of new dietary model models, updating population databases, etc.  
      Referring now to  FIG. 1 , an example system  100  for collecting and analyzing patient data is illustrated. System  100  includes a device  102 , an interrogatory/transceiver unit (ITU) or repeater  108 , a communications system  110 , and a host  112 .  
      Device  102  is a sensor that can measure a pharmacological effect (e.g., physiological or subjective) of a drug on a patient. Device  102  can be configured in a manner similar to that of devices  104 ,  106 ,  602 ,  604 ,  606  described below. For example, device  102  can be an implanted medical device such as, for example, a cardiac rhythm management (CRM) device such as a pacemaker, a cardioverter defibrillator, or a heart failure cardiac resynchronization therapy device, or other devices such as an implantable loop recorder. Other example implanted devices include a variety of sensors such as sodium, glucose, temperature, electrolyte, hydration, respiratory, heart rate, cardiac output, and other sensors that provide information related to dietary conditions of the patient. The device  102  can also be a non-implanted device such as, for example and without limitation, a weight measuring device, a blood pressure cuff, blood content monitor (i.e., gases, glucose, creatinine, BNP), insulin sensor, or Holter or ECG devices. Device  102  can collect data associated with the patient including, but not limited to, activity level, weight, intracardiac or systemic blood pressure, heart rate, heart rate variability, thoracic impedance, or heart sounds.  
      Device  102  generally collects data associated with the patient and communicates the data to host  112 . In one embodiment, the device  102  communicates with host  112  through ITU  108  and communications system  110 . Other configurations are also possible. For example, in some embodiments, device  102  can communicate directly with communications system  110  and/or host  112 . In the illustrated embodiment, device  102  can upload collected data to ITU  108  in real-time, on a periodic (batch) basis, or manually such as when interrogated by the ITU  108 .  
      Referring now to  FIG. 2 , another example system  200  is illustrated. System  200  is similar to system  100  described above, except that system  200  also includes devices  104  and  106 . The devices  102 ,  104 ,  106  can be any combination of implanted and external devices as described above in the discussion of sensor  102 . In other embodiments, at least one of the devices  102 ,  104 ,  106  may be an interactive display or a handheld device.  
      The interactive display provides for patient input to the system  200  related to, for example, nutritional/dietary intake, subjective physical conditions, and physical activity (e.g., sleep and exercise). The interactive display may also provide for communication between the system  100  and the patient using, for example, text messages related to recommended nutritional/dietary intake, physical activity, and physical conditions (e.g., glucose and sodium count). In some embodiments, the interactive display may be integrated into the ITU  108  as described below with reference to  FIG. 5 .  
      Providing one of the devices  102 ,  104 ,  106  as a handheld device could provide additional mobility and user convenience for the system  200 . The ITU  108  is typically configured for use in the patient&#39;s living structure. The ITU  108  may be mobile, but is typically not convenient for carrying at all times or for use when traveling. A handheld device may be configured with some of the features of the ITU such as, for example, data collection from one of the other devices  102 ,  104 ,  106 , communication with the host  112  via the communications systems  110 , and analysis of some types of information, and interactive display for some patient input, dietary feedback, and sensor measurements.  
      Referring now to  FIG. 3 , a flow diagram  300  illustrates one example method for enhancing therapy for a patient. In operation  310 , data is collected about the patient using, for example, devices  102 ,  104 ,  106  (e.g., sensors, CRM device, patient input via interactive display) and information about the patient stored by the ITU  108  and host  112 .  
      Next, in operation  320 , the collected data is compared to an expected dietary model. The expected dietary model can be selected in various ways. For example, the model can be selected based on population statistics arranged, for example, according to age, race, national origin, and/or gender. In other examples, the model can be tailored according to the specific medical history of a patient. For example, an expected dietary model can be constructed based on previous data collected from the patient, dietary recommendations from a physician. Other methods for selecting an expected dietary model are also contemplated such as, for example, using individual patient genetic factors that impact a patient&#39;s blood pressure, sodium count, or cholesterol level. In yet further methods, the expected dietary model can be based upon or in some way influenced by regularly updated guidelines from such organizations as, for example, the American Hospital Association (AHA), the American Medical Association (AMA), the Heart Rhythm Society (HRS), and the Heart Failure Society of America (HFSA).  
      Example expected dietary models may use many parameters related to, for example, nutritional intake, physical parameters such as sodium and glucose levels, exercise, sleep, and drug regimes. A dietary model may relate to a specific parameter or to a plurality of parameters.  
      Referring back to  FIG. 3 , once the data collected from the patient is compared to the expected dietary model in operation  320 , control is then passed to operation  330  and a determination is made as to whether the collected data corresponds to the expected dietary model. In one embodiment, the comparison is made by computing deviations between the models. In another embodiment, parameters of the expected model (e.g., time of the step-wise change, delta increment) are computed in advance and stored in the system.  
      If the collected data corresponds to the expected dietary model, control is passed back to operation  310  and collection of data continues. If the collected data does not correspond to the expected dietary model, control is passed to operation  340 , and specific steps such as reporting and alarming can occur. In some embodiments, automatic steps can be initiated in response to the operation  330  such as therapy using the implanted device or altering of the patient&#39;s drug regimen.  
      In one example, the type and magnitude of deviation of the collected data from the expected dietary model can result in the generation various reports and alarms. In one embodiment, if the collected data indicates an adverse side effect to a given nutritional intake, a side-effect report is generated that is then forwarded to the patient via the interactive display or handheld device, and/or sent to the caregiver via, for example, the host and communications network. In yet another embodiment, if the collected data indicates noncompliance with a dietary schedule, a noncompliance report is generated that is then forwarded to the caregiver and/or patient. If the nature of the deviation from the expected dietary model is such that immediate action is desirable, alarms can be sent to the caregiver and/or to the patient to notify of the potential problem.  
      More than one device can also be used to measure multiple aspects of the patient&#39;s dietary condition. For example, multiple devices (or a single device with multiple capabilities) can be used to collect data related to multiple different physical effects such as, for example and without limitation, a patient&#39;s heart rate, blood pressure, temperature, sodium and glucose levels, etc. Further, in some embodiments, multiple expected dietary models can be compared to data collected with respect to the dietary condition of a patient during different activities, different times of the day or week, different dietary menus, different drug treatment, and different environmental conditions. Or, alternatively, a single expected dietary model can be used that accounts  30  for multiple conditions and inputs.  
      In addition, in some embodiments, not all of the collected data is forwarded to the host  112  for processing. For example, in some embodiments, the device  102  and/or the ITU  108  can conduct at least initial processing of the collected data to identify, for example, data that would indicate that immediate reporting is necessary.  
      Various advantages are associated with the use of systems configured in a manner similar to example systems  100  and  200  described above. For example, the collected data can be used to monitor dietary intake side effects, patient compliance, and time of nutritional intake. In addition, the data can be used to identify beneficial dietary intake in combination with certain physical activities and drug regimens. Beneficial dietary intake can be further substantiated when using the measured collect data with subjective data entered by the patient in response to system prompts for patient information.  
      II. Advanced Patient Management System  
      In some embodiments, the systems  100  and  200  described above are implemented as part of an advanced patient management (“APM”) system configured to collect patient-specific information, store and collate the information, and generate actionable recommendations to enable the predictive management of patients.  
      Embodiments of the APM system can be configured to monitor patient dietary conditions, determine and communicate recommended action related to the patient&#39;s dietary conditions, and develop and store a history of the patient&#39;s dietary conditions and the patient&#39;s response to the recommended action. The APM system can be configured to use dietary information and patient health history provided by at least one of a primary care giver (e.g., a doctor), a secondary caregiver database, and a population health information database in conjunction with patient physical indicators (measured or entered by the patient). The example APM systems disclosed herein can also be configured to produce reports related to a patient&#39;s current dietary conditions as well as compliance and side effects of, for example, certain dietary intake, physical activity, and drug regimens, and communicate those reports to various destinations, such as, for example, a primary caregiver, the patient, or a dietary related database.  
       FIG. 4  illustrates an example APM system  600  made in accordance with the present invention. APM system  600  generally includes the following components: devices  602 ,  604 , and  606 , an interrogator/transceiver units  608 , a communication system  610 , and a host  612 .  
      Each component of the APM system  600  can communicate using the communication system  610 . Some components can also communicate directly with one another. For example, devices  602  and  604  can be configured to communicate directly with one another and with the interrogator/transceiver units  608 . The various components of the example APM system  600  illustrated herein are described below.  
      a. Devices  
      Devices  602 ,  604 , and  606  can be implantable devices or external devices that can provide at least one of the following functions with respect to a patient in addition to other possible functions: (1) sensing/measuring, (2) data analysis, (3) therapy, (4) distribution of product, and (5) communication. For example, in one embodiment, devices  602 ,  604 , and  606  are either implanted or external devices used to sense or measure a variety of physiological, subjective, and environmental conditions of a patient using electrical, mechanical, and/or chemical means. In one embodiment, the device  602  is a handheld device, device  604  is an implanted medical device, and device  606  is an internal or external sensor.  
      The devices  602 ,  604 , and  606  can be configured to automatically gather data or can require manual intervention by the patient. The devices  602 ,  604 , and  606  can be devices that are positioned external and separated from the patient, positioned on an external surface of the patient, or positioned within the patient as an implanted device or sensor. The devices  602 ,  604 , and  606  can be configured to store data related to the physiological and/or subjective measurements and/or transmit the data to the communication system  610  using a variety of methods, described in detail below. Although three devices  602 ,  604 , and  606  are illustrated in the example embodiment shown, more or fewer devices can be used for a given patient.  
      The devices  602 ,  604 , and  606  can be configured to analyze the measured data and act upon the analyzed data. For example, the devices  602 ,  604 , and  606  are configured to modify therapy or provide alarm indications based on the analysis of the data.  
      In one embodiment, devices  602 ,  604 , and  606  also provide therapy. Therapy can be provided automatically or in response to an external communication. Devices  602 ,  604 , and  606  are programmable in that the characteristics of their sensing, therapy (e.g., duration and interval), or communication can be altered by communication between the devices  602 ,  604 , and  606  and other components of the APM system  600 . Devices  602 ,  604 , and  606  can also perform self-checks or be interrogated by the communication system  610  to verify that the devices are functioning properly.  
      In another embodiment, devices  602 ,  604 , and  606  also provide disbursement of product. Product disbursement can be provided automatically or in response to an external communication. Some example products that can be dispersed include pills/drugs that are part of a patient drug regimen and testing/sampling products for patient conducted tests or sampling bodily products.  
      The devices  602 ,  604 , and  606  can be configured to communicate with the patient and with other devices and features of the APM. For example, the devices  602 ,  604 , and  606  can communicate with a patient using sound or visual prompts to, for example, obtain answers to questions, remind the patient to perform certain tasks, and warn the patient about the presence of predetermined threshold trends and conditions that represent the patient&#39;s well-being. The devices  602 ,  604 , and  606  can also include user interface features such as a keypad, touch control screen, or other input device that facilitate communication between the patient and the devices  602 ,  604 , and  606 . Additional examples of different embodiments of the devices  602 ,  604 , and  606  are provided below.  
      Devices implanted within the body have the ability to sense and communicate as well as to provide therapy. Implantable devices can provide direct measurement of characteristics of the body, including, without limitation, electrical cardiac activity (e.g., a pacemaker, cardiac resynchronization management device, defibrillator, etc.), physical motion, temperature, heart rate, activity, blood pressure, breathing patterns, ejection fractions, blood viscosity, blood chemistry, blood glucose levels, and other patient-specific clinical physiological parameters, while minimizing the need for patient compliance.  
      Derived measurements can also be determined from the implantable device sensors. Examples of such derived measurements include, but are not limited to, a functional capacity indicator, autonomic tone indicator, sleep quality indicator, cough indicator, anxiety indicator, and cardiovascular wellness indicator for calculating a quality of life indicator quantifying a patient&#39;s overall health and well-being.  
      Devices  602 ,  604 , and  606  can also be external devices, or devices that are not implanted in the human body, that are used to measure physiological data. Such devices include a multitude of devices to measure data relating to the human body, such as temperature (e.g., a thermometer), blood pressure (e.g., a sphygmomanometer), blood characteristics (e.g., glucose levels), body weight, physical strength, mental acuity, diet, heart characteristics, and relative geographic position (e.g., a Global Positioning System (GPS)). The physiologic signals collected by external sensors could be uniquely associated with the patient by verifying device ID via a telemetry link.  
      Devices  602 ,  604 , and  606  can also be environmental sensors. The devices can be placed in a variety of geographic locations (in close proximity to patient or distributed throughout a population) and record nonpatient specific characteristics such as, but not limited to, temperature, air quality, humidity, carbon monoxide level, oxygen level, barometric pressure, light intensity, and sound.  
      One or more of the devices  602 ,  604 , and  606  (for example, device  606 ) can be external devices that measure subjective or perceptive data from the patient. Subjective data is information related to a patient&#39;s feelings, perceptions, and/or opinions, as opposed to objective physiological data. For example, the “subjective” devices can measure patient responses to inquiries such as “How do you feel?” and “How is your pain?” The device can prompt the patient and record subjective data from the patient using visual and/or audible cues.  
      The subjective data can be collected from the patient at set times, or, alternatively, collected whenever the patient feels like providing subjective data. The subjective data can also be collected substantially contemporaneously with physiological data to provide greater insight into overall patient conditions such as dietary related conditions. The subjective device can be any device that accepts input from a patient or other concerned individual and/or provides information in a format that is recognizable to the patient.  
      One or more of the devices  602 ,  604 , and  606  (e.g., device  602 ) can also include one or more remote peripheral devices. The remote peripheral device can include, for example and without limitation, cellular telephones, pagers, PDA devices, facsimiles, remote computers, printers, video and/or audio devices, etc. The remote peripheral device can communicate using wired or wireless technologies and can be used by the patient or caregiver to communicate with the interrogator/transmitter unit  608 , communication system  610 , and/or the host  612 . For example, the remote peripheral device can be used by the caregiver to receive alarms from the host  612  based on data collected from the patient and to send instructions from the caregiver to either the patient or other clinical staff. In another example, the remote peripheral device is used by the patient to receive periodic or real time updates and alarms regarding the patient&#39;s health and well-being.  
      b. Interrogator/Transceiver Unit  
      Referring now to  FIG. 5 , the example APM system  600  includes one or more interrogator/transceiver units (“ITUs”), such as ITU  608 . In illustrated embodiments, the ITU is configured in a manner similar to that disclosed in U.S. Published Patent Application No. US-2004-0127958-A1, filed Dec. 27, 2002, and entitled “Advanced Patient Management System Including Interrogator/Transceiver Unit,” which is hereby incorporated by reference in its entirety.  
      The ITU  608  can include an interrogator module  652  for sending and receiving data from a device, such as devices  602 ,  604 ,  606 , a memory module  654  for storing data, and a transceiver module  656  for sending and receiving data to and from other components of the APM system  600 . The transceiver module can also operate as an interrogator of the devices  602 ,  604 ,  606 . The ITU  608  also includes a power module  658  that provides power and an interactive display  660 . Example features of the interactive display  660  are described below with reference to  FIG. 6 .  
      The ITU  608  can perform one or more of the following functions: (1) data storage; (2) data analysis; (3) data forwarding; (4) patient interaction; (5) patient feedback; and (6) data communications. For example, the ITU  608  can facilitate communications between the devices  602 ,  604 ,  606  and the communication system  610 . The ITU  608  can, periodically or in real-time, interrogate and download into memory clinically relevant patient data from the devices  602 ,  604 ,  606 . This data includes, in the cardiac sensor context, for example, P and R-wave measurements, pacing, shocking events, lead impedances, pacing thresholds, battery voltage, capacitor charge times, ATR episodes with electrograms, tachycardia episodes with electrograms, histogram information, physiological conditions that represent efficacy and compliance of a drug regimen, and any other clinical information necessary to ensure patient health and proper device function. The data is sent to the ITU  608  by the devices  602 ,  604 ,  606  in real-time or periodically uploaded from buffers in the devices.  
      The ITU  608  can also allow patient interaction via the interactive display  660 . For example, the display  660  can include a patient interface and allow the patient to input subjective data. In addition, the ITU  608  can provide feedback to the patient via the display  660  based on the data that has been analyzed or based on information communicated by the communication system  610 .  
      In another embodiment, the ITU  608  includes a telemetry link from the devices to a network that forms the basis of a wireless LAN in the patient&#39;s home. The ITU  608  systematically uploads information from the devices  602 ,  604 ,  606  while the patient is sleeping, for example. The uploaded data is transmitted through the communication system  610  or directly to the host  612 . In addition, in one embodiment the ITU  608  functions in a hybrid form, utilizing wireless communication when available and defaulting to a local wireless portal or a wired connection when the wireless communication becomes unavailable.  
      When the interrogator  652  uses radio frequency to communicate with the devices  602 ,  604 ,  606 , the ITU  608  can be in the form of a small device that is placed in an inconspicuous place within the patient&#39;s residence. Alternatively, the ITU  608  can be implemented as part of a commonly used appliance in the patient&#39;s residence. For example, the ITU can be integrated with an alarm clock that is positioned near the patient&#39;s bed. In another embodiment, the ITU can be implemented as part of the patient&#39;s personal computer system. Other embodiments are also possible.  
      In another embodiment, the ITU  608  can comprise a hand-held device such as a PDA, cellular telephone, or other similar device that is in wireless communication with the devices  602 ,  604 ,  606 . The hand-held device can upload the data to the communication system  610  wirelessly. Alternatively, the hand-held device can periodically be placed in a cradle or other similar device that is configured to transmit the data to the communication system  610 .  
      If multiple devices, such as devices  602 ,  604 ,  606  and/or additional device, are provided for a given patient, each device can include its own means for communicating with the ITU  608  or communication system  610 . Alternatively, a single telemetry system can be implemented as part of one of the devices, or separate from the devices, and each device  602 ,  604 , and  606  can use this single telemetry system to communication with the ITU  608  or the communication system  610 .  
      In yet another embodiment, the devices  602 ,  604 , and  606  include wires or leads extending from devices  602 ,  604 , and  606  to an area external of the patient to provide a direct physical connection. The external leads can be connected, for example, to the ITU  608  or a similar device to provide communications between the devices  602 ,  604 ,  606  and the other components of the APM system  600 .  
      The APM system  600  can also involve a hybrid use of the ITU  608 . For example, the devices  602 ,  604 ,  606  can intelligently communicate via short-range telemetry with the ITU when the patient is located within the patient&#39;s home and communicate directly with the communication system  610  or host  612  when the patient is traveling. This can be advantageous, for example, to conserve battery power when the devices are located near an ITU.  
       FIG. 6  illustrates an example interactive display  660  for use either independently or integrated with the ITU  608 . The display  660  may include a plurality of input buttons  661 , a plurality counter indicators  663 ,  665 ,  667 , and a text display  669 . The buttons  661  may provide for input of information or selection of options presented on the text display. The indicators  663 ,  665 ,  667  may be used to illustrate the patient&#39;s physical conditions measured by a plurality of sensors either internal or external positioned. In some embodiments, the indicators  663 ,  665 ,  667  may be integrated into the text display  669 . The text display  669  may provide, for example, dietary advice, food/menu options, patient input questions, and nutritional content information.  
      The features of display  660  illustrated in  FIG. 6  are exemplary only. Numerous combinations of buttons, displays indicators and other features may be integrated into a display for use in system  600  in ways that provide improved user convenience and transfer of information between the patient and the system  600 .  
      c. Communication System  
      Communication system  610  provides for communications between and among the various components of the APM system  600 , such as between the devices  602 ,  604 ,  606  and ITU  608  and the host  612 .  FIG. 7  illustrates one embodiment for the communication system  610  made in accordance with the present invention. The communication system  610  includes a plurality of computer systems  804 ,  806 ,  808 , and  810 , as well as devices  602 ,  604 ,  606  and host  612 , connected to one another by a communication network  800 . The communication network  800  can be, for example, a local area network (LAN), wide area network (WAN), or the Internet. Communications among the various components, as described more fully below, can be implemented using wired or wireless technologies.  
      In the example embodiment illustrated, the host  612  includes server computers  818  and  822  that communicate with computers  804 ,  806 ,  808 , and  810  using a variety of communications protocols that are described more fully below. The server computers  818  and  822  store information in databases  816  and  820 . This information can also be stored in a distributed manner across one or more additional servers.  
      A variety of communication methods and protocols can be used to facilitate communication between devices  602 ,  604 ,  606 , ITU  608 , communication system  610 , host  612 , and remote peripheral device  609 . For example, wired and wireless communications methods can be used. Wired communication methods can include, for example and without limitation, traditional copper-line communications such as DSL, broadband technologies such as ISDN and cable modems, and fiber optics, while wireless communications can include cellular, satellite, radio frequency (RF), Infrared, etc.  
      d. Host  
      Referring again to  FIG. 4 , the example host  612  includes a database module  614 , an analysis module  616 , and a delivery module  618 . Host  612  preferably includes enough processing power to analyze and process large amounts of data collected from each patient, as well as to process statistics and perform analysis for large populations. For example, the host  612  can include a mainframe computer or multi-processor workstation. The host  612  can also include one or more personal computer systems containing sufficient computing power and memory. The host  612  can include storage medium (e.g., hard disks, optical data storage devices, etc.) sufficient to store the massive amount of high-resolution data that is collected from the patients and analyzed.  
      The host  612  can also include identification and contact information (e.g., IP addresses, telephone numbers, or a product serial number) for the various devices communicating with it, such as ITU  608  and one or more of devices  602 ,  604 ,  606 . For example, each ITU  608  is assigned a hard-coded or static identifier (e.g., IP address, telephone number, etc.), which allows the lost  612  to identify which patient&#39;s information the host  612  is receiving at a given instant. Alternatively, each device  602 ,  604 ,  606  can be assigned a unique identification number, or a unique patient identification number can be transmitted with each transmission of patient data.  
      Referring again to  FIG. 4 , the example database module  614  includes a patient database  630 , a population database  632 , a medical database  634 , and a general database  636 . The patient database  630  includes patient specific data, including data acquired by the devices  602 ,  604 , and  606 . The patient database  630  also includes a patient&#39;s medical records, the patient&#39;s current health information, targeted health information, and drug information. The patient database  630  can include pharmacogenomic information describing individual genetic differences that could impact drug metabolism. The patient database  630  can include historical information regarding the devices  602 ,  604 ,  606 . The information stored in the database  630  can be recorded at various times depending on the patient requirements or device requirements. For example, the database  630  is updated at periodic intervals that coincide with the patient downloading data from the device. Alternatively, data in the database  630  can be updated in real time. Typically, the sampling frequency depends on the health condition being monitored and the co-morbidities.  
      The population database  632  includes non-patient specific data, such as data relating to other patients and population trends. The population database  632  also records epidemic-class device statistics and patient statistics. The population database  632  also includes data relating to staffing by health care providers, environmental data, drugs, etc. In some cases, patient information from the patient database  630  can be added to the population database to supplement and maintain currency of the population database information and trends.  
      The example medical database  634  includes clinical data relating to the treatment of diseases. For example, the medical database  634  includes historical trend data for multiple patients in the form of a record of progression of their disease(s) along with markers of key events. The medical database could also include clinical study results.  
      The general database  636  includes non-medical data of interest to the patient. The general database  636  can include information relating to, for example, news, finances, shopping, technology, entertainment, and/or sports. The general database  636  can be customized to provide general information of specific interest to the patient. For example, stock information can be presented along with the latest health information as detected from the devices  602 ,  604 , and  606 .  
      In another embodiment, information is also provided from an external source, such as external database  620 . For example, the external database  620  can include external medical records related to other medical devices or medical conditions of the patient that are maintained separately and remotely from the host  612 . The remote database may include standards, recommendations, or guidelines provided by medical groups and associations such as, for example, the American Hospital Association (AHA), the American Medical Association (AMA), the Heart Rhythm Society (HRS), and the Heart Failure Society of America (HFSA).  
      The example analysis module  616  includes a patient analysis module  640 , device analysis module  642 , population analysis module  644 , and learning module  646 . Patient analysis module  640  can utilize information collected by the APM system  600 , as well as information from other relevant sources, to analyze data related to a patient and provide timely and predictive assessments of the patient&#39;s well-being. In performing this analysis, the patient device module  640  can utilize data collected from a variety of sources, include patient specific physiological and subjective data collected by the APM system  600 , medical and historical records (e.g., lab test results, histories of illnesses, etc., drugs currently and previously administered, etc.), as well as information related to population trends provided from sources external to the APM system  600 .  
      For example, in one embodiment, the patient analysis module  640  makes a predictive diagnosis of an oncoming event based on information stored in the database module  614 . For example, the data continuously gathered from a device of a given patient at a heightened risk for a chronic disease event (such as de-compensations in heart failure) is analyzed. Based on this analysis, therapy, typically device-based, dietary, or drug, can then be applied to the patient either through the device, via communications to the patient, or through clinician intervention.  
      In another example embodiment, the patient analysis module  640  provides a diagnosis of patient health status and predicted trend based on present and recent historical data collected from a device as interpreted by a system of expert knowledge derived from working practices within clinics. For example, the patient analysis module  640  performs probabilistic calculations using currently-collected information combined with regularly-collected historical information to predict patient health degradation.  
      In another example embodiment, the patient analysis module  640  can conduct pre-evaluation of the incoming data stream combined with patient historical information and information from patients with similar disease states. The pre-evaluation system is based on data derived from working clinical practices and the records of outcomes. The derived data is processed in an expert system (i.e., neural network, fuzzy logic system, or equivalent system) to reflect the clinical practice. Further, the patient analysis module  640  can also provide means for periodic processing of present and historical data to yield a multidimensional health state indication along with disease trend prediction, next phase of disease progression co- morbidities, and inferences about what other possible diseases can be involved. The patient analysis module  640  can also integrate data collected from internal and external devices with subjective data to optimize management of overall patient health.  
      Device analysis module  642  analyzes data from the devices  602 ,  604 ,  606  and ITU  608  to predict and determine device issues or failures. For example, if an implanted device  602  fails to communicate at an expected time, device analysis module  642  determines the source of the failure and takes action to restore the performance of the device  602 . The device analysis module  642  can also perform additional deterministic and probabilistic calculations. For example, the device analysis module  642  gathers data related to charge levels within a given device, such as an ICD, and provides analysis and alarming functions based on this information if, for example, the charge level reaches a point at which replacement of the device and/or battery is necessary. Similarly, early degradation or imminent failure of implanted devices or leads can be identified and proactively addressed, or at-risk devices can be closely monitored.  
      Population analysis module  644  uses the data collected in the database module  614  to manage the health of a population. For example, a clinic managing cardiac patients can access the APM system  600  and thereby obtain device-supplied advance information to predict and optimize resource allocation both as to immediate care and as a predictive metric for future need of practicing specialists. As another example, the spread of disease in remote populations can be localized and quarantined rapidly before further spread.  
      In one embodiment, population analysis module  644  trends the patient population therapy and management as recorded by the devices and directs health care resources to best satisfy the needs of the population. The resources can include people, facilities, supplies, and/or drugs. In other embodiments, the population analysis module detects epidemics and other events that affect large population groups. The population analysis module  644  can issue alarms that can initiate a population quarantine, redirect resources to balance size of staffing with number of presenting population, and predict future need of qualified specialists.  
      The population analysis module  644  can utilize a variety of characteristics to identify like-situated patients, such as, for example, sex, age, genetic makeup, etc. The population analysis module  644  can develop large amounts of data related to a given population based on the information collected by the APM system  600 . In addition, the population analysis module  644  can integrate information from a variety of other sources. For example, the population analysis module  644  can utilize data from public domain databases (e.g., the National Institute of Health), public and governmental and health agency databases, private insurance companies, medical societies (e.g., the American Heart Association), and genomic records (e.g., DNA sequences).  
      In one embodiment of the invention, the host  612  can be used as a “data clearinghouse,” to gather and integrate data collected from the devices  602 ,  604 ,  606 , as well as data from sources outside the APM system  600 , such as the external database  600 . The integrated data can be shared with other interested entities, subject to privacy restrictions, thereby increasing the quality and integration of data available.  
      Learning module  646  analyzes the data provided from the various information sources, including the data collected by the advanced patient system  600  and external information sources. For example, the learning module  646  analyzes historical symptoms, diagnoses, and outcomes along with time development of the diseases and co-morbidities. The learning module  646  can be implemented via an expert system.  
      The learning module  646  can be partially trained (i.e., the learning module  646  can be implemented with a given set of inference rules and then learn as the APM system functions) or untrained (i.e., the learning module  646  is initiated with no preset values and must learn from scratch as the APM system functions). In other alternative embodiments, the learning module  646  can continue to learn and adjust as the APM system functions (i.e., in real time), or the learning module  646  can remain at a given level of learning and only advanced to a higher level of understanding when manually allowed to do so.  
      In an expert system embodiment, new clinical information is presented to create new neural network coefficients that are distributed as an expert system knowledge upgrade. The learning module  646  can include a module for verifying the expert system conclusions for clinical accuracy and significance. The learning module can analyze a database of test cases, appropriate outcomes and relative occurrence of misidentification of the proper outcomes. In some embodiments, the learning module  646  can update the analysis module  616  when the analysis algorithms exceed a threshold level of acceptable misidentifications.  
      The example learning module  646  uses various algorithms and mathematical modeling such as, for example, trend and statistical analysis, data mining, pattern recognition, cluster analysis, neural networks and fuzzy logic. Learning module  646  can perform deterministic and probabilistic calculations. Deterministic calculations include algorithms for which a clear correlation is known between the data analyzed and a given outcome. For example, there can be a clear correlation between the energy left in a battery of an implantable device and the amount of time left before the battery must be replaced.  
      A probabilistic calculation involves the correlation between data and a given outcome that is less than 100 percent certain. Probabilistic determinations require an analysis of several possible outcomes and an assignment of probabilities for those outcomes (e.g., an increase in weight of a patient can, at a 25 percent probability, signal an impending de-compensation event and/or indicate that other tests are needed). The learning module  646  performs probabilistic calculations and selects a given response based on a highest probability. In doing so the module could use prior probability of an event derived from population or clinical study database. Further, as the learning module  646  “learns” for previous determinations (e.g., through a neural network configuration), the learning module  646  becomes more proficient at assigning probabilities for a given data pattern, thereby being able to more confidently select a given response. As the amount of data that has been analyzed by the learning module  646  grows, the learning module  646  becomes more and more accurate at assigning probabilities based on data patterns. A bifurcated analysis can be performed for diseases exhibiting similar symptoms. As progressive quantities of data are collected and the understanding of a given disease state advances, disease analysis is refined where a former singular classification can split into two or more sub-classes.  
      In addition, patient-specific clinical information can be stored and tracked for hundreds of thousands of individual patients, enabling a first- level electronic clinical analysis of the patient&#39;s clinical status and an intelligent estimate of the patient&#39;s short-term clinical prognosis. The learning module  646  is capable of tracking and forecasting a patient&#39;s clinical status with increasing levels of sophistication by measuring a number of interacting co-morbidities, all of which can serve individually or collectively to degrade the patient&#39;s health. This enables learning module  646 , as well as caregivers, to formulate a predictive medical response to oncoming acute events in the treatment of patients with chronic diseases such as heart failure, diabetes, renal dysfunction, cancer, and asthma/COPD, as well as possibly head-off acute catastrophic conditions such as MI and stroke.  
      Delivery module  618  coordinates the delivery of feedback based on the analysis performed by the host  612 . In response to the analysis module  616 , delivery module  618  can manage the devices  602 ,  604 ,  606 , perform diagnostic data recovery, program the devices, and otherwise deliver information as needed. In some embodiments, the delivery module  618  can manage a web interface that can be accessed by patients or caregivers. The information gathered by an implanted device or sensor, external sensor, or handheld device associated with system  600  can be periodically transmitted to a web site that is securely accessible to the caregiver and/or patient in a timely manner. In other embodiments, a patient accesses detailed health information with diagnostic recommendations based upon analysis algorithms derived from leading health care institutions.  
      For example, the caregiver and/or patient can access the data and analysis performed on the data by accessing one or more general content providers. In one example, the patient&#39;s health information is accessed through a general portal such as My Yahoo provided by Yahoo! Inc. of Sunnyvale, California, or Guidant patient personal web page provided by Guidant Corporation of Indianapolis, Indiana. For example, a patient can access his or her My Yahoo homepage or Guidant patient personal web page and receive information regarding current health and trends derived from the information gathered from the devices  602 ,  604 , and  606 , as well as other health information gathered from other sources. The patient can also access other information in addition to health information on the My Yahoo website, such as weather and stock market information. Other electronic delivery methods such as email, facsimile, etc. can also be used for alarm distribution.  
      In an alternative embodiment, the data collected and integrated by the advanced patient system  600 , as well as any analysis performed by the system  600 , is delivered by delivery module  618  to a caregiver&#39;s hospital computer system for access by the caregiver. A standard or custom interface facilitates communication between the APM system  600  and a legacy hospital system used by the caregiver so that the caregiver can access all relevant information using a system familiar to the caregiver.  
      The APM system  600  can also be configured so that various components of the system (e.g., ITU  608 , communication system  610 , and/or host  612 ) provide reporting to various individuals (e.g., patient and/or caregiver). For example, different levels of reporting can be provided by (1) the ITU  608  and (2) the host  612 . The ITU  608  can be configured to conduct rudimentary analysis of data gathered from devices  602 ,  604 ,  606 , and provide reporting should an acute situation be identified. For example, if the ITU  608  detects a significantly high or low level of certain nutritional parameters that relate to a patient&#39;s immediate wellbeing, the ITU  608  provides reporting to the patient in the form of an audible or visual alarm.  
      The host  612  can provide a more sophisticated reporting system. For example, the host  612  can provide exception-based reporting and alarms that categorize different reporting events based on importance. Some reporting events do not require caregiver intervention and therefore can be reported automatically. In other escalating situations, caregiver and/or emergency response personnel need to become involved. For example, based on the data collected by the APM system  600 , the delivery module  618  can communicate directly with the devices  602 ,  604 ,  606 , communicate with the patient via a display (e.g., an interactive display on the ITU  608 ), and/or contact  911  emergency response. In an alternative embodiment, the delivery module  618  and/or the patient can also establish a voice communication link between the patient and a caregiver, if warranted.  
      In addition to forms of reporting including visual and/or audible information, the APM system  600  can also communicate with and reconfigure one or more of the devices  602 ,  604 ,  606 . For example, if device  602  is part of a cardiac rhythm management system, the host  612  can communicate with the device  602  and reconfigure the therapy provided by the cardiac rhythm management system based on the data collected from one or more of the devices  602 ,  604 ,  606 . In another embodiment, the delivery module  618  can provide to the ITU  608  recorded data, an ideal range for the data, a conclusion based on the recorded data, and a recommended course of action. This information can be displayed on the ITU  608  for the patient to review or made available on the peripheral device  609  for the patient and/or clinician to review.  
      III. Example Methods of Using the Advanced Patient Management System  
      A method  950  of using an APM system according to principles of the present invention is further illustrated with reference to  FIG. 8 . The method includes input of different types of information from different sources and output of information related to a patient&#39;s dietary conditions. The method includes a step  952  of the physician entering information about a suggested dietary regimen (e.g., types of food/nutritional intake, interval, and amount), notification thresholds, and the patient health history into the APM system. Another step  954  includes entering of dietary information from dietary databases. Dietary databases may include, for example, nutritional and side-effects information about different types of food, relationships between foods and different types of activities, etc. A further step  956  includes patient inputs about nutritional intake and physical conditions. Another step  958  includes input from sensors related to measured patient conditions.  
      One or more outputs  960 ,  962 ,  964  result from one or more system inputs. One example output  960  includes a patient physical conditions report. Another example output  962  includes a displayed recommendation to the patient of nutritional intake and/or physical activity. A further example output  964  includes a compliance report related to a patient&#39;s adherence to a recommended nutritional intake schedule.  
      Another example method (not illustrated) may include a scenario generator. The system could provide for patient inputs that relate to a proposed nutritional intake and/or activity schedule for a given day. The system would then output estimated dietary and other health related conditions that would likely result if the patient actually undertook the proposed schedule. This output could provide valuable insight to the patient when making decisions concerning the patient&#39;s menu and activity selection. These and other methods could result from applying principles of the example disclosed above to meet other objectives of the patient or patient caregiver.  
      IV. Conclusion  
      One or more headings have been provided above to assist in describing the various embodiments disclosed herein. The use of headings, and the resulting division of the description by the headings, should not be construed as limiting in any way. The subject matter described under one heading can be combined with subject matter described under one or more of the other headings without limitation and as desired.  
      The systems and methods of the present disclosure can be implemented using a system as shown in the various Figures disclosed herein including various devices and/or programmers, including implantable or external devices. Accordingly, the methods of the present disclosure can be implemented: (1) as a sequence of computer implemented steps running on the system; and (2) as interconnected modules within the system. The implementation is a matter of choice dependent on the performance requirements of the system implementing the method of the present disclosure and the components selected by or utilized by the users of the method.  
      Accordingly, the logical operations making up the embodiments of the method of the present disclosure described herein can be referred to variously as operations, steps, or modules. It will be recognized by one of ordinary skill in the art that the operations, steps, and modules can be implemented in software, in firmware, in special purpose digital logic, analog circuits, and any combination thereof without deviating from the spirit and scope of the present invention as recited within the claims attached hereto.  
      The above specification, examples and data provide a complete description of the manufacture and use of the composition of the invention. Since many embodiments of the invention can be made without departing from the spirit and scope of the invention, the invention resides in the claims hereinafter appended.