Abstract:
A computer-based system and method are provided for minimizing the overall cost of providing health care for a chronic disease. To do this, an operating point is selected on a ROC curve to classify patients in a defined population. Based on this classification, patients in the population are classified and placed on either of a pair of pathways for health care. One pathway involves relatively low-cost health care treatment, but potentially repetitive involvement with the patient. The other pathway involves relatively high-cost treatment, but only episodic involvement with the patient. Placement of each entity on a selected pathway is done to collectively minimize the overall cost of providing health care.

Description:
FIELD OF THE INVENTION 
       [0001]    The present invention pertains generally to systems and methods for minimizing the overall cost of health care services. More particularly, the present invention pertains to systems and methods which incorporate cost considerations (criteria) into a branching process that directs each entity in a population, onto either a pathway for proactive (i.e. preventative) care, which is relatively low cost but potentially repetitive, or onto a pathway for reactive (i.e. direct) care, which though not repetitive may be of relatively high cost. The present invention is particularly, but not exclusively, useful for systems and methods which require the selection of an operating point on a Receiver-Operating Characteristics (ROC) curve for implementing the branching process. 
       BACKGROUND OF THE INVENTION 
       [0002]    In any buyer-seller transaction, the cost for purchasing something (e.g. goods or services) is known and is determined directly by participants in the transaction. On the other hand, after purchase, the maintenance costs for taking care of whatever was purchased (i.e. an entity) is typically unknown or unpredictable. Moreover, maintenance costs can vary substantially from one entity to another, even though the entities may be the same or similarly situated. However, when a large population of similarly situated entities is considered in its totality, probabilities concerning maintenance costs come into play. Consequently, within the parameters of statistical probabilities, maintenance costs then become somewhat predictable and, therefore, more manageable. In this context, health care costs can be likened somewhat to maintenance costs. 
         [0003]    Of particular concern for the present invention are the costs that are associated with health care for chronic diseases. It happens that a useful analytical tool for evaluating the probabilities associated with chronic diseases is the Receiver-Operating Characteristics (ROC) curve. For a defined population of patients having a particular chronic disease, the ROC curve is characteristic of the disease and is essentially a plot of probable outcomes. For example, in the context of the present invention, patients with a chronic disease will require reactive health care only when treatment is needed on an episodic basis. Otherwise, they may be able to control the disease with less expensive proactive (i.e. preventive) health care. Not all patients, however, will similarly benefit from proactive health care; nor may they even actually require proactive health care. 
         [0004]    As an analytical tool, the ROC curve can be used to classify an individual (entity). Specifically, within a defined population, and based on test results only, each entity in the population can be divided into an affected subgroup (e.g. positive test result [+]) or an unaffected subgroup (e.g. negative test result [−]). Further, the ROC curve is able to account for such factors as false positives, and false negatives. For purposes of the present invention, the import here is that a population can be effectively and accurately bifurcated based on statistical probabilities. 
         [0005]    In light of the above, an object of the present invention is to provide a system and method for conducting an activity (e.g. health care) that uses the ROC curve to classify an entity from a defined population for placement onto a selected action pathway that will minimize the overall cost of conducting the activity. Another objective of the present invention is to effectively and accurately identify a smaller subpopulation of patients who will most likely benefit from lower cost proactive care; to then limit proactive care to this subpopulation; and to thereby reduce or minimize the overall cost of health care. Yet another object of the present invention is to provide a system and method for minimizing the overall cost of implementing a health care program for treating chronic diseases that is easy to use, is simple to implement and is cost effective. 
       SUMMARY OF THE INVENTION 
       [0006]    In accordance with the present invention, a system and method are provided for evaluating and classifying individuals in a population of patients according to health care cost requirements. The purpose here is to place each patient into an appropriate health care program that will minimize the overall health care costs for the entire population. In particular, the focus of the present invention is on patients with chronic diseases. With this in mind, the present invention is implemented with the understanding that statistical probabilities allow an entire population of patients, all having a same chronic disease, to be individually classified for health care treatment. In particular, the classification for each patient can be based on his/her test results. 
         [0007]    In use, the present invention is computer-based, and it relies on data that is pertinent to a particular chronic disease. With this stipulation in mind, a specific population of patients can be effectively defined. Data can then be collected from the population and subsequently organized and archived into a database. In particular, statistical data for a population of patients can be obtained from a plurality of tests that includes static patient data, physiological tests, laboratory tests, non-physiological parameters and multifactorial combinations of parameters. 
         [0008]    As envisioned for the present invention, collected data that is pertinent to a particular chronic disease can be used for several purposes. For one, the data can be used to associate health care costs with different treatment regimens. For another, the data can be used to assess the efficacy of a particular treatment regimen for an individual patient. Further, and most importantly, the collected data can be analytically used to classify patients. 
         [0009]    For purposes of the present invention, the data that is collected and organized for the database is used to define a pair of treatment (i.e. action) pathways. One of these pathways is specifically defined for proactive care and the other for reactive care. Typically, the proactive care will be routine, and it will be provided on an outpatient basis. Further, the proactive care pathway is designed for use by patients who are most likely to benefit from care that will prevent, or allay, the onset of an episodic event. Importantly, cost criteria for action on the proactive pathway will be considered when defining the parameters for assigning, and accepting, a patient onto the proactive care pathway. 
         [0010]    Along with the proactive care pathway, the present invention also requires a reactive care pathway. Specifically, this reactive care pathway is defined to accept acutely ill patients (i.e. patients in or near an episodic condition) who are in need of immediate and direct care. Treatment on the reactive care pathway has few, if any, options and it will most likely involve high health care costs. 
         [0011]    Importantly, the present invention relies on the construction of a compound test that is characterized by a ROC curve. In particular, this ROC curve is created in accordance with well-known techniques using data from the population database. More specifically, the ROC curve is based on treatment for a chronic disease and it will be determined by considerations such as the nature of the required proactive treatment regimen and the likelihood of a patient having a positive response to the proactive treatment. Further, like the proactive and reactive pathways, a use of the ROC curve is influenced by cost considerations. 
         [0012]    In an operation of the present invention, a population of patients having a same chronic disease is identified. Next, data from the population is collected, and a database is organized. A computerized ROC curve is then established using data from the database. For an operation of the present invention, an operating point selected on the ROC curve is chosen to classify patients. As noted above, it is an important aspect of the present invention that costing factors are incorporated into the creation and definition of the computer output pathways (i.e. the proactive health care pathway, and the reactive health care pathway). 
         [0013]    A consequence of the above interactive considerations is that test results for a patient can be provided as a computer input. These patient test results are then compared by the computer with a selected operating point on the ROC curve. The result of this comparison is that the patient is classified for assignment on either of the defined health care pathways for the purpose of collectively minimizing the overall cost of health care. 
         [0014]    As envisioned for the present invention, the database can be continuously updated. In this process, patients on either, or both, of the health care pathways can be retested and reclassified. Thus, an iterative process is established that effectively allows an entire population to be periodically reevaluated and reformed, in-whole or in-part. At any point, the reformed population can then be further subjected to a subsequent bifurcation for possible reclassification. 
         [0015]    To do the above, various testing procedures can be incorporated into the present invention. Further, the organization of data in the database and the implementation of cost criteria considerations into the data evaluations can be continuously revised and updated to provide for the most cost effective implementation of health care services. An important consequence here is that historical information developed during a continuous operation of the system can be used to refine the population. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0016]    The novel features of this invention, as well as the invention itself, both as to its structure and its operation, will be best understood from the accompanying drawings, taken in conjunction with the accompanying description, in which similar reference characters refer to similar parts, and in which: 
           [0017]      FIG. 1  is a schematic presentation of the computer components for a system of the present invention, showing essential inputs for an operation of the system; and 
           [0018]      FIG. 2  is a representative ROC curve that is pertinent to a specific chronic disease and is used in the methodology of the present invention to establish the relationship between the Probability of Detecting (PD) an episodic deterioration of the disease and the Probability of a False Alarm (PFA). 
       
    
    
     DESCRIPTION OF THE PREFERRED EMBODIMENTS 
       [0019]    Referring initially to  FIG. 1 , a schematic representation of a system in accordance with the present invention is shown and is generally designated  10 . In  FIG. 1  it will be seen that the system  10  includes a computer  12  which is provided with the various information inputs required for an operational set-up of the computer  12 . In detail, these inputs include data from a database  14 , and cost criteria  16  that are pertinent to relatively low cost health care regimens, as well as cost criteria  18  that are pertinent to relatively high cost health care regimens. Insofar as costs are concerned,  FIG. 1  also shows that generalized health care costs  20  are provided as input for the database  14 . 
         [0020]    With specific regard to the database  14  in  FIG. 1 , its input of generalized health care costs  20  is pertinent to a particular chronic disease (e.g. diabetes or heart disease) and this input will comprehensively include cost estimates for all aspects of the disease. On the other hand, the cost criteria  16  which are input for the computer  12  will be more focused in their estimations, and will be directed to the costs for regimens of health care treatment that are intended to be preventative (i.e. proactive) in nature. In particular, these cost criteria  16  will be relatively low, and will typically support outpatient care that is to be provided on a routine and, possibly, protracted basis. Similarly, the cost criteria  18  input for the computer  12  will also be focused in their estimations. In this case, however, the cost criteria  18  will be directed to the costs for regimens of health care treatment that are necessarily immediate and direct (i.e. reactive). For example, reactive health care is necessary for immediate response to an episodic presentation of the chronic disease. Consequently, cost criteria  18  will be relatively high, and will typically be driven by costs which are associated with emergency and surgical requirements. 
         [0021]    An important aspect of the present invention is the population  22  for whom the system  10  is operated. In detail, the population  22  will include all patients identified as having a same chronic disease. It is the population  22  that provides data for the database  14 . The data in this case comes from single tests  24  that include static patient data, physiological tests, laboratory tests and non-physiological parameters. Additionally, multifactorial tests  26 , involving combinations of various parameters, are included in this data. In accordance with the purposes of the present invention, these multifactorial tests  26  are pertinent to a chronic disease and, accordingly, are used to create a compound test that is ultimately characterized by a Receiver-Operating Characteristics (ROC) curve  28 . It is to be noted here that although the system  10  disclosed is primarily concerned with a same chronic disease, it is envisioned by the present invention that different systems  10 , pertaining to respectively different chronic diseases, can be operationally combined for cost management purposes. Moreover, different diseases can conceivably be considered and evaluated in the same system  10 . With this in mind, the operational flexibility of any system  10  will depend on how the population  22  is defined, and how the cost considerations (i.e. cost criteria  16 , cost criteria  18  and generalized costs  20 ) are employed. 
         [0022]      FIG. 1  shows that the computer  12  interacts directly with the database  14  to generate a plot for the Receiver-Operating Characteristic (ROC) curve  28 . As indicated in  FIG. 1 , the population  22 , the multifactorial tests  26 , and the generalized costs  20  all provide respectively appropriate inputs to the database  14  for this purpose. The computer  12  then uses these inputs to generate (i.e. plot) the ROC curve  28 . ROC curve  28  shown in  FIG. 2  is only exemplary. As shown and adapted for use with the present invention, the ROC curve  28  is based primarily on multifactorial tests  26 , and it pertains to the particular chronic disease associated with the population  22 . In essence, the ROC curve  28  is a plot of the Probability of Detection (PD) versus Probability of a False Alarm (PFA). The generation and plotting of ROC curves are well known in the pertinent art. As noted above, the specific purpose for generating the ROC curve  28  for use with the system  10  is to provide an analytical tool for classifying patients in the population  22 . 
         [0023]    With reference to  FIG. 2  it will be appreciated that a binary classifier  30  can be selected by the computer  12  to interact with the ROC curve  28 . Specifically, as directed by the computer  12 , the binary classifier  30  will identify an operating point (threshold)  32  on the ROC curve  28  that effectively bifurcates the population  22  into two subpopulations (i.e. subgroups). With this bifurcation, one subpopulation will be classified by the computer  12  with a positive result [+], and the other will be classified with a negative result [−]. 
         [0024]    Referring again to  FIG. 1 , it will be seen that system  10  of the present invention provides for both a proactive pathway  34  and a reactive pathway  36 . Together, this pair of pathways,  34  and  36 , is defined to provide health care services for the entire population  22 . In particular, patients with a positive screening result [+] are assigned to the proactive pathway  34 , while the remainder (i.e. those patients with negative screening results [−]) are assigned to the reactive pathway  36 . As indicated above, and shown in  FIG. 1 , the particular health care services that are provided on the proactive pathway  34  are characterized by the cost criteria  16 . On the other hand, the health care services provided on the reactive pathway  36  are characterized by the cost criteria  18 . In light of these respective cost considerations, the operating point  32  is selected by the computer  12  to identify patients, [+], who are most likely to benefit from an assignment to the proactive pathway  34  and, accordingly, to assign them to the proactive pathway  34  for health care. The remaining patients, [−], would therefore be assigned to the reactive pathway  36 . The objective here, of course, is to provide all necessary health care, and at the same time minimize the overall cost of health care for the population  22 . 
         [0025]    In an operation of the system  10 , a population  22  is defined. Statistical data pertinent to the defined population  22  is organized and archived in the database  14 . Next, the ROC curve  28  is established by the computer  12  using data from the database  14  (i.e. multifactorial tests  26 ). A pair of alternative action pathways (i.e. proactive pathway  34 , and reactive pathway  36 ) is defined with computer input for conducting a health care activity. Specifically, each defined pathway,  34  and  36 , has a respective cost associated with action on the pathway. A patient is then tested to obtain a test result  38  for the patient. This test result  38  is then evaluated using a screen  40  of the computer  12  to compare the test result  38  with the operating point  32  of the binary classifier  30  on the ROC curve  28 . With this comparison, the patient is classified, [+] or [−], according to a bifurcation determined by the binary classifier  30 . The patient is then directed, according to his/her classification, onto either the proactive pathway  34  or the reactive pathway  36  to minimize an overall cost for treating the chronic disease. As envisioned for the present invention, patients on the proactive pathway  34  and/or on the reactive pathway  36  can be periodically retested and rescreened to remain on the particular pathway, or for transfer to the other pathway. 
         [0026]    It is also an important aspect of the present invention that the system  10 , itself, is dynamic. In particular, during an operation of the system  10 , the population  22  can be selectively reevaluated and, possibly, reclassified. This can be done at any time, and can be repetitively accomplished in a manner determined by the operator of the system  10 . As envisioned for the present invention, this reevaluation can be done daily, weekly or monthly. 
         [0027]    As indicated in  FIG. 1 , the reevaluation and possible reclassification of the population  22  involves a manipulation of data by the computer  12 . Specifically, data pertaining to individuals (patients) on the proactive pathway  34  can be removed from the proactive pathway  34  and returned to the population  22  via a return line  42 . Similarly, data pertaining to individuals (patients) on the reactive pathway  36  can be removed from the reactive pathway  36  and returned to the population  22  via a return line  44 . In both instances, data for the individual (patient) reenters the population  22  for reprocessing and reformation of the population  22 . 
         [0028]    As envisioned for the present invention, an operation of the system  10  is iterative, and it can simultaneously involve both the proactive pathway  34  and the reactive pathway  36 . Alternatively, it may involve only one pathway at a time (i.e. proactive pathway  34  or reactive pathway  36 ). Further, the entire process can be repeated as necessary or desired. 
         [0029]    A consequential benefit of the iterative process described above is that the results of prior classifications (bifurcations) can be archived and organized in the database  14 . The results of these prior bifurcations are therefore dynamically available as direct or indirect input to the computer  12  in real time. Importantly, the availability of this information is useful for continuously updating and refining the ROC curve  28  and, if desired, a reselection of the operating point  32  on the ROC curve  28 . 
         [0030]    While the particular Systems and Methods for Lowering the Cost of Health Care as herein shown and disclosed in detail is fully capable of obtaining the objects and providing the advantages herein before stated, it is to be understood that it is merely illustrative of the presently preferred embodiments of the invention and that no limitations are intended to the details of construction or design herein shown other than as described in the appended claims.