Abstract:
A system and method for the optimization of scheduling visits by a clinician to a plurality of remotely located patients. A plurality of predefined or clinician specified risk factors are combined with patient data with a home visit interval algorithm to specify a visit interval for each patient. This interval is used with a calendar with other information regarding past and future scheduled visits to determine the optimal date for the next visit to the patient by the clinician. The patient risk factors may be weighted to place more emphasis on specific factors, thus allowing for the tailoring of the system to meet the needs of an individual patient.

Description:
FIELD OF THE INVENTION 
   The present invention relates to the field of health care management systems. More specifically, the invention relates to a system for monitoring and managing the need for a clinician to visit a patient at a remote site. 
   BACKGROUND OF THE INVENTION 
   The rising cost of health care is of increasing concern to many. One way to reduce the cost of medical treatment is to reduce the number of days that are spent in the hospital as there is a large fundamental cost that is associated with each night spent in a hospital bed. As a result, there has been a continued push towards home centered and/or remote offsite patient treatment and/or convalescence. This increased push for remote patient care presents its own significant challenges for health care providers due to the lack of personal contact that clinicians have with patients that are located at remote sites. While mobile communication systems and telemonitoring have greatly increased the quality of the care provided to patients that are being treated or are recovering at a location remote from the hospital, clinicians have found it useful to augment the care provided via these systems with remote site visits by the clinicians to check up on the patients in person. In-person visits may be particularly necessary where the remotely located patient experiences difficulty in making regularly scheduled visits to a medical care facility, perhaps due to mobility issues that are part of the patient&#39;s ailments or perhaps due to a lack of available transportation options or the patient&#39;s remote location. 
   Many types of patient conditions may lead to a situation where it is desirable for a clinician to periodically check up on the patient&#39;s condition with a visit to the remote site at which the patient is located. The patient&#39;s condition may be that of a chronic disease such as chronic obstructive pulmonary disease (COPD), congestive heart failure (CHF) or another manageable chronic disease such as diabetes. Other times, a patient&#39;s physical or mental disability may make periodic remote site checkups by the clinician desirable as well. 
   It is known in the field that in-person interaction between the clinician and the patient is advantageous to the treatment and/or recovery of the patient from his affliction. These clinician/patient interactions do, however, experience a diminishing rate of return as the interactions substantially increase in number. Therefore, in a system where a relatively smaller number of clinicians must provide care to a relatively larger number of patients, the interest of efficiency requires that clinician visits to remotely located patients must be scheduled in such a way as to maximize the quality of care given to each individual patient while minimizing the amount of time spent with that patient out of the pool of clinician time devoted to the treatment of all patients. 
   Various devices, systems, and methods have been developed to alleviate some of the above-noted issues regarding patient health care. In particular, U.S. Patent Application No. 2005/0131740 to Massenzio et al. describes a system and method for controlling home health care services. The &#39;740 application discloses a system by which the efficiency of remote care is improved by the transmission of remote patient alarm conditions. Health care providers are able to maximize their efficiency in providing emergency care to multiple remotely located patients by tracking the patient&#39;s locations using GPS and triaging the patients based upon the specific emergency conditions. However, this application does not address the scheduling and provision of non-emergency clinician visits or checkups. 
   U.S. Patent Application No. 2004/0249676 is directed to a system for the automatic scheduling of patients on waiting lists to receive medical treatments such as elective surgery, diagnostic services, clinic services and endoscopies. This system uses a calculated urgency score to calculate the target date for the patient&#39;s procedure based upon patient recorded physiological data and a ranked triage of patient procedure need. This system is limited in its application in that it only projects a date or schedule for a specific procedure and is not directed toward the scheduling of recurring clinician checkups or visits. Additionally, this disclosure does not contemplate the use of a wide variety of patient diagnostic data, but rather is limited to the evaluation of patient physiological data. 
   Therefore, it is desirable in the field of the provision of care to remotely located patients to provide an automated system by which clinician visits to remotely located patients are scheduled in an economical fashion. 
   Furthermore, it is desirable that the scheduling be based on a wide variety of diagnostic parameters such as clinician-observed or so-called “soft” parameters. 
   In a further embodiment of the present invention, it is desirable that the management system take into account other related data such as already scheduled clinician visits, patient requests for additional or fewer clinician visits, or remote patient locations with respect to the locations of other remotely located patients. 
   SUMMARY OF THE INVENTION 
   The present invention provides a system and method by which a plurality of patient risk factors are considered in determining the scheduling of a clinician visit to a remotely located patient. This system utilizes a variety of risk factors that are combined in a home visit interval algorithm to produce a determination of the date for the next home visit. 
   In an embodiment of the present invention, the risk factors comprise a variety of parameters including, but not limited to, physiological parameters, clinician-observed parameters, patient-initiated parameters, and patient history parameters. 
   In a still further embodiment of the present invention, each risk factor has an associated weight that may be developed by “learning” using a neural network or fuzzy logic methods or other type of weight optimization algorithm or technique. 
   In a still further embodiment of the present invention, the risk factors may trigger an alarm condition whereby emergency and/or immediate clinician intervention may be necessary. The system includes a means for notifying the clinician of this alarm condition. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
     The drawings illustrate the best mode presently contemplated of carrying out the invention. In the drawings: 
       FIG. 1  is a schematic diagram of the operation of the system of the present invention. 
       FIG. 2  is a schematic diagram of the operation of the remote health application of the present invention. 
   

   DETAILED DESCRIPTION OF THE INVENTION 
     FIG. 1  depicts a schematic diagram of a situation in which an embodiment of the present invention may be utilized. In  FIG. 1 , a plurality of remotely located patients  10  are each at a location that is different from each other and all are remote from the clinical institution  12 . The clinical institution  12  may be a regional hospital, local clinic, or any other provider of patient care. An on-line clinician  14  at a computer work station  16  within the clinical institution  12  monitors the scheduling of visits by a clinician (not depicted) to each remotely located patient  10 . The remote health application  18  of the present invention receives information from a variety of sources, such as patient data, risk factors, and scheduling information, for determining the proper schedule for clinician visits to the remotely located patients  10 . 
   The remote health application  18  uses risk factors from a risk database  20  and other institutionally determined controls  22  for operating the remote health application  18 . The risk factors  20  and institutional controls  22  may be supplemented or modified by the on-line clinician  14  to more specifically tailor the remote health application  18  to a specific patient depending upon that patient&#39;s diagnosis and treatment schedule. The remote health application  18  will use patient data provided to it via a patient database  24  as well as data received from a communications device  26  that is associated with each of the remotely located patients  10 . The communications device  26  may comprise but is not herein limited to internet communication, cellular communication, WIFI communication, or any other means with which the patient  10  may transmit a data or communications signal from the communications device  26  to the remote health application  18  and on-line clinician  14 . 
   The remote health application  18 , as will be described further herein, uses the data received from the patient database  24  as well as the data received directly from the patient  10  with the risk factors from the risk factor database  20  to determine the need for a visit by a clinician to the remotely located patient. Scheduling database  28  provides information regarding each patient&#39;s most recent clinician visit and next scheduled clinician visit to the remote health application  18 . This allows for the remote visit schedule to be modified based upon the determined patient need for a clinician visit in light of already scheduled out-patient visits. 
     FIG. 2  is a schematic diagram of the operation of the remote health application  18  of  FIG. 1 . As depicted in  FIG. 2 , a plurality of risk factors  30  are sent to home visit interval algorithm  32 . These risk factors  30  are used to analyze the patient data  34  that may be received from the variety of sources depicted in  FIG. 1 , such as the scheduling database  28 , the patient information database  24 , and/or the patient communications device  26 . The home visit interval algorithm  32  determines the current proper interval between home visits for that patient. The home visit interval algorithm  32  also determines whether the home visit interval  50  has been increasing over time, thereby showing an improvement in overall patient health, or whether the home visit interval  50  is decreasing over time, thereby indicating a general decline in overall patient health. 
   The home visit interval  50  is sent to the scheduling calendar  36  where the interval  50  is compared to additional scheduling information such as the last visit date  38 , a maximum interval duration that may apply to this patient&#39;s care  40 , or any already scheduled visit dates for this patient  42 . The last visit date  38  may comprise any clinician visits to the patient, but may also comprise any visits by the patient to the clinical institution  12 . The calendar  36  uses this information with the home visit interval  50  to set the date of the next home visit  44 . 
   The risk factors  30  that are supplied to the home visit interval algorithm  32  may comprise rules to interpret a variety of patient data that may be supplied to the algorithm  32  to determine the home visit interval  50 . The risk factors  30  may interpret patient data that is dynamic or static, continuous or discrete, and objective or subjective. The patient data  34  interpreted may compromise data from the patient database  24 , institutional controls  22 , and data from the scheduling database  28 . An exemplary listing of data that may be provided by the patient database  24  could include the patient&#39;s compliance level and/or compliance history with prescribed medications and treatments, the patient&#39;s medical history including current disease level and/or disease progression, the patient&#39;s psychological profile, and information pertaining to the number of people living with the patient at the remote location. Institutional controls  22  that may be used in determining the home visit interval  50  may be information regarding other remote patients in the local area and the dates of their next clinician visits, the GPS location of clinicians available to provide remote care, the existence of a contractual or regulatory requirement for visit frequency, or other institutionally determined clinical guidelines or pathways. Finally, relevant data that may be included from the scheduling database  28  may include the date of the last visit with a health care provider, length of time since the most recent home health visit or doctor&#39;s appointment, any appointments for physical specimen collection, any scheduled clinical events, the next scheduled doctor&#39;s appointment, or the next scheduled home health visit. 
   The risk factors  30  may also include factors relating to data that may be received from the communications device  26 , including data collected from the patient regarding transduced physiological parameters from the patient or patient initiated communications. Factors that may be received via the communications device  26  from the patient may include, but are not limited to: the patient&#39;s activity level, physiological data recorded by a telemetry system, voice analysis data, gait analysis data, a recorded log of patient visitors, the patient&#39;s answer to self-assessment questions, requests for an appointment by the patient, clinician, or doctor, and patient environmental data, such as the ambient temperature or relative humidity of the patient&#39;s home or remote location. 
   The home visit interval algorithm  32  combines the patient data  34  with the risk factors  30  to determine the proper interval between remote care clinician visits to the patient. In an embodiment of the present invention, each risk factor may include an associated weight whereby specific risk factors are given more consideration by the home visit interval algorithm than other risk factors. The patient data  34  and risk factors  30  may be combined in the form of if/then statements to produce the home visit interval result. The following examples of output statements are designed to be exemplary and not limiting upon the present invention:
         1) If a patient who had previously been very timely about collecting vital sign measurements suddenly stops taking his/her physiological measurements, then that patient becomes higher risk and in an embodiment of the present invention, may initiate some form of immediate intervention alarm.   2) If a person has other household members who participate in the care of that patient, then that patient has lower risk and the interval between home care visits can be increased.   3) If a patient&#39;s activity level is decreasing, then that patient becomes higher risk and the time to the next scheduled home visit is reduced.   4) If a patient has a doctor&#39;s office visit scheduled in the near future, then that patient has lower risk and the next home visit date is delayed.       

   Logical output statements such as the preceding exemplary statements are used by the home visit interval algorithm to determine a home visit interval  50  that is sent to the scheduling calendar  36 . In an embodiment of the present invention, the home visit interval  50  may be combined with other calendar data such as the patient&#39;s most recent clinician visit date  38 , a maximum visit interval  40  which may be a contractually, institutionally, professionally, or legally defined maximum visit interval, or other patient visit dates  42  already scheduled in the calendar  36 . The calculated home visit interval  50  is compared to any maximum visit interval  40  to determine if the interval should be modified to meet these constraints. 
   Next, the interval  50  is run from the most recent visit date  38  to determine the tentative next visit date. This tentative date is compared to any already scheduled visit dates  42  to create optimization of patient visits. Once the home visit interval  50  has been processed through the calendar  36 , the next home visit date  44  has been determined. The patient may then be notified of this next home visit date  44  via the communications device  26  or other notification means. 
   In an embodiment of the present invention, the associated weights for each risk factor may start as a default value, but may be modified later by a clinician to specifically tailor the home visit interval algorithm to the particular needs of an individual patient, or the associated weight of each risk factor may be developed by “learning” using a neural network or fuzzy logic method. This learning of the weight values for a risk factor may be done by observing patient data or by the entering of additional patient data by a clinician to form a pool of patient data from which the associated weights may be learned. 
   In a still further embodiment of the present invention, the detection of certain risk factors of specified weights may result in the triggering of an alarm condition which would result in an intervention prompt  46  to be displayed to the clinician. This intervention prompt  46  would notify a clinician of the emergency situation and as such enable the clinician to respond to the emergency situation accordingly. 
   This written description uses examples to disclose the invention, including the best mode, and also to enable any person skilled in the art to make and use the invention. The patentable scope of the invention is defined by the claims and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements of insubstantial difference from the literal language of the claims. 
   Various alternatives and embodiments are contemplated as being with in the scope of the following claims, particularly pointing out and distinctly claiming the subject matter regarded as the invention.