Patent Abstract:
A non-transitory computer-readable storage medium storing a set of instructions executable by a processor, the set of instructions, when executed by the processor, causing the processor to perform operations including receiving a self-care assessment from a patient having a medical condition. The self-care assessment assesses the patient&#39;s level of ability for each of a plurality of determinants. The operations also include assigning a weight to each of the plurality of determinants. The operations also include creating an ordered list including the plurality of determinants. The determinants are ordered based on the corresponding weights. The operations also include determining a plurality of behavior-specific contributions. Each of the behavior-specific contributions corresponds to one of the determinants and to one of a plurality of self-care behaviors relevant to the medical condition.

Full Description:
BACKGROUND 
       [0001]    Patients suffering from chronic medical conditions may be required to perform self-care behaviors in order to manage their conditions and improve their clinical outcomes. However, individual patients may have varying determinants that influence their ability to comply with self-care behaviors, and it may be desirable to address and improve these determinants as part of a care plan in a patient-specific manner. Further, patients may not always understand the specific manner in which self-care behaviors affect their clinical outcomes, which may cause them not to comply with their self-care behaviors. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0002]      FIG. 1  schematically illustrates a system for generating a patient-specific ordered list of determinants according to an exemplary embodiment. 
           [0003]      FIG. 2  illustrates an exemplary method by which the system illustrated in  FIG. 1  may operate. 
           [0004]      FIG. 3  illustrates a table of self-care determinants that may be considered during the performance of the method of  FIG. 2 . 
           [0005]      FIG. 4A  illustrates an exemplary result of the performance of step  210  of the method of  FIG. 2 . 
           [0006]      FIG. 4B  illustrates an exemplary result of the performance of step  220  of the method of  FIG. 2 . 
           [0007]      FIG. 4C  illustrates an exemplary result of the performance of step  230  of the method of  FIG. 2 . 
           [0008]      FIG. 4D  illustrates an exemplary result of the performance of step  240  of the method of  FIG. 2 . 
           [0009]      FIG. 4E  illustrates an exemplary result of the performance of step  250  of the method of  FIG. 2 . 
           [0010]      FIG. 4F  illustrates an exemplary result of the performance of step  260  of the method of  FIG. 2 . 
           [0011]      FIG. 4G  illustrates an exemplary result of the performance of step  270  of the method of  FIG. 2 . 
           [0012]      FIG. 5  schematically illustrates an exemplary system for informing patients about the effects that performance of self-care behaviors may have on their health. 
           [0013]      FIG. 6  illustrates an exemplary method by which the system illustrated in  FIG. 5  may operate. 
           [0014]      FIG. 7  illustrates an exemplary patient profile that may be generated by the method of  FIG. 6 . 
           [0015]      FIG. 8  illustrates a portion of an exemplary database that may be used by the system of  FIG. 5  during the performance of the method of  FIG. 6 . 
           [0016]      FIG. 9  illustrates a table showing adjustment of the value of patient self-care behaviors according to patient&#39;s self-management abilities according to the method of  FIG. 6 . 
           [0017]      FIG. 10  illustrates a table showing adjustment of the value of patient self-care behaviors according to input parameters according to the method of  FIG. 6 . 
           [0018]      FIG. 11  illustrates an exemplary user interface display that may be generated by the system of  FIG. 5 . 
       
    
    
     DETAILED DESCRIPTION 
       [0019]    The exemplary embodiments may be further understood with reference to the following description and the related appended drawings, wherein like elements are provided with the same reference numerals. Specifically, the exemplary embodiments relate to methods and systems for prioritizing patient self-care behaviors and providing patients with support in choosing such behaviors. 
         [0020]    Increasing numbers of patients worldwide suffer from chronic conditions that are associated with poor outcomes such as diminished quality of life, frequent hospital readmissions, and early mortality. Self-care is useful for avoiding these poor outcomes, and, thus, is frequently recommended to patients as part of the treatment of chronic conditions. The effectiveness of such treatment relies on patients&#39; adherence to self-care behaviors such as taking medication, maintaining an appropriate level of physical activity, consuming appropriate types and quantities of foods and beverages, cessation of smoking, managing symptoms, etc. Non-adherence to self-care behaviors is a leading cause of exacerbation of chronic conditions and poor outcomes. Therefore, it is desirable to provide patients with proper interventions to enable effective adherence to self-care behaviors, and to demonstrate to patients the effects of adherence to self-care behaviors. 
         [0021]    Each patient will have various determinants that affect the patient&#39;s ability to adhere to self-care behaviors. Determinants may include factors such as disease burden, perceived control, self-efficacy, social support, ability to cope with problems, anxiety, depression, willingness to self-manage, comfort in a group, computer skills, etc. The patient&#39;s strength or weakness in each of the above determinants may help or hinder the patient&#39;s efforts to adhere to self-care behaviors such as those discussed above. Because this is the case, a patient&#39;s care plan (“CP”) may include efforts to address the patient&#39;s determinants and thereby improve the likelihood that the patient will adhere to self-care behaviors. For example, a patient coping with anxiety or depression may be instructed to undergo counseling; a patient with poor computer skills may not be offered an Internet-based behavior change program. 
         [0022]    Any given chronic condition may have corresponding weights for various self-care behaviors; for example, for a patient suffering from lung cancer, smoking cessation may be a pivotal factor, whereas the same self-care behavior may be less significant for a patient having a non-cardiopulmonary ailment. Further, any given patient will have some determinants that are areas of strength for the patient, and others that are areas of weakness. Additionally, there may typically be a limited amount of time available in which to address a given patient&#39;s determinants. Therefore, it may be desirable to have a patient-specific prioritized list of determinants in order to guide clinicians in designing a CP for the patient. The exemplary embodiments described herein may generate such a patient-specific prioritized list of determinants. 
         [0023]      FIG. 1  illustrates, schematically, an exemplary system  100  for generating a patient-specific ordered list of determinants. It will be apparent to those of skill in the art that the system  100  includes data processing elements that may be implemented through a combination of hardware (e.g., processor, memory, user interface, etc.) and software in a manner that will be understood by those of skill in the art. The operation of the system  100  will be described herein with reference to the exemplary method  200 . 
         [0024]    The system  100  may include a Triage element  110 . The Triage  110  may perform a first portion of the tasks performed by the system  100 . In step  210 , the Triage  100  may receive, as input, a clinician&#39;s choice of determinants  20  to be used in assessing the patient. The clinician may choose a subset of all possible determinants discussed above (e.g., disease burden, perceived control, self-efficacy, social support, coping with problems, willingness to self-manage) for use in assessing the patient. The choice may be based on clinical guidelines, results of clinical trials, the clinician&#39;s experience, etc. For example, a clinician may choose to exclude “computer skills” from consideration because a patient&#39;s low level of computer skills may indicate that a telehealth system may not be an efficient use of resources for the patient; those of skill in the art that this reason is only exemplary and that various other reasons for excluding a determinant for consideration may be possible. The subset of determinants retained for subsequent analysis will be referred to hereinafter as D mod , meaning modifiable determinants. 
         [0025]    In step  220 , the Triage  110  may also receive, as an input, data from a patient self-assessment  40 . The self-assessment  40  may be performed using a known assessment tool, such as Self-Management Assessment (“SeMaS”) or Patient Activation Measure (“PAM”) questionnaires. As a result of this self-assessment  40 , each determinant may be assigned a score which classifies a determinant as a facilitator or barrier of self-care behavior.  FIG. 3  illustrates a table  300  that shows, in a first column  310 , the list of determinants selected by the clinician as the applicable subset of determinants D mod , and, in a second column  320 , possible assessment scores for each selected determinant based on the patient self-assessment  40 . Based on these scores, each determinant may be classified as either a facilitator or a barrier; for example, high self-efficacy may be classified as a facilitator, whereas low self-efficacy may be classified as a barrier. 
         [0026]    Based on the scores for the determinants D mod  included in the table  300  of  FIG. 3 , in step  230  the Triage  110  assigns a weight to each determinant in the set D mod . Weights may be assigned according to the rule that a determinant with an assessment score indicating that the determinant is a facilitator of self-care behavior is assigned a low weight, while a determinant with an assessment score indicating that the determinant is a barrier to self-care behavior is assigned a high weight. This may indicate that it is more important for a CP to focus on barriers to self-care than on facilitators. The specific quantitative weights used in this step may vary among differing embodiments. 
         [0027]    Column  330  of table  300  illustrates generalized versions of weights that may be used herein. Column  340  of table  300  illustrates a first exemplary weighting that may be applied by the Triage  110 . In the first exemplary weighting, scores are given weights from 1 to 3, with facilitators scored a 1 and barriers scored a 3. Column  350  of table  300  illustrates a second exemplary weighting that may be applied by the Triage  110 . In the second exemplary weighting, facilitators are scored a 0 and barriers are scored a 2. It will be apparent to those of skill in the art that, by weighting facilitators a 0, they may be excluded from further consideration in the modification of self-care behavior. 
         [0028]    In step  240 , the Triage  110  creates an ordered list  120  of determinants of self-care behaviors based on the weights assigned in step  230 . This may involve ranking, by weight, the determinants D mod  that remain under consideration after any potential elimination from consideration of some of the determinants due to being assigned zero weight in step  230 . This ordered list  120  of self-care determinants may be the output generated by the Triage  110 . In step  250 , the ordered list  120  is passed, by the Triage, to Quantifier element  130  of the system  100 . 
         [0029]    In step  260 , the Quantifier  130  calculates a weight W D  of each determinant from step  240  across all determinants selected for inclusion in the CP for the patient by virtue of being selected in step  210  and not assigned zero weight in step  230 . The weight for W D  each determinant is calculated as: 
         [0000]    
       
         
           
             
               
                 
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         [0030]    In the above expression, “#D mod ” is the quantity of remaining determinants in the set D mod . In step  270 , the Quantifier  130  calculates the determines a contributions matrix  140 , in which the contribution c(i,j) of each determinant i from step  240  to the care plan for a particular self-care behavior j based on the weights W D  calculated in step  260  and known weights W B (j) for each behavior. The contributions c(i,j) may be calculated as: 
         [0000]        c ( i, j )= W   D ( D   mod ( i ))* W   B ( j ),  i= 1, . . . , # D   mod   ; j= 1, . . . , #Behaviors 
         [0031]    In the above expression, “#Behaviors” is the number of self-care behaviors under consideration. After step  270 , the method  200  is complete. The set of contributions c(i,j) of the contributions matrix  140  output by the Quantifier  130  in step  270  may be the output of method  200  performed by system  100 . The matrix  140  of contributions c(i,j) is patient-specific based on the patient&#39;s self-assessment  40 , and may then be used by a clinician in devising a CP to enable important determinants to be addressed, and, in turn, to enable the patient to adhere to important self-care behaviors. It will be apparent to those of skill in the art that the division of the functions of the Triage  110  and Quantifier  130  described herein may essentially be a logical construct. Thus, they may be integrated into a single element (e.g., a software application, combination of software and hardware, etc.) without departing from the broader scope of the functions described. 
         [0032]      FIGS. 4A-4G  illustrate the results of various phases of the application of method  200  to one exemplary patient. For the condition of the patient who is the subject of these figures, the behavior weight W B  for medication taking is 40%, W B  for symptom management is 30%, W B  for physical activity is 10%, W B  for nutrition is 10%, and W B  for smoking cessation is 10%, as indicated in  FIG. 4F .  FIG. 4A  illustrates a set of determinants D mod    410  that may be received from a clinician for the patient in step  210 . As noted above, this set of determinants may be selected by the clinician based on the patient&#39;s condition and various other factors.  FIG. 4B  illustrates the results of the patient&#39;s self-care assessment  420 . The results shown in  FIG. 4B  are formatted in accordance with the SeMaS assessment tool, and it will be apparent that similar information may be where the patient&#39;s self-care assessment has been made using a different technique. In  FIG. 4B , determinants with large dots are areas of strength for the patient, and will be termed facilitators of self-care, while determinants with small dots are areas of weakness and will be termed barriers. 
         [0033]      FIG. 4C  illustrates a weighted set of determinants D mod    430  that may be determined by the Triage  110  in step  230  based on the inputs shown in  FIGS. 4A and 4B . The determinants  430  are weighted as shown in column  350  of  FIG. 3 , described above.  FIG. 4D  illustrates an ordered list of determinants Dmod  120  that may be determined by the Triage  110  in step  240 , and may be the output of the Triage  110  to the Quantifier  130 . 
         [0034]      FIG. 4E  illustrates a set of weights W D    450  of each determinant from step  240  (e.g., shown in  FIG. 4D ), as divided in step  260  by the Quantifier  130  across all determinants selected for inclusion in the CP for the patient.  FIG. 4F  illustrates a table  460  showing the calculation of the contributions of the patient&#39;s determinants to the self-care behaviors appropriate for the patient&#39;s condition.  FIG. 4G  illustrates a contributions matrix  140  that may be determined by the Quantifier  130  in step  270  of the method  200 , based on the inputs described above with reference to  FIGS. 4A-4F . The contributions matrix  140  may be used by a clinician to determine a CP for the patient having these inputs. 
         [0035]    As described above, self-care behaviors are an important factor in controlling the progression of chronic diseases and supporting overall wellness. The exemplary embodiments described above with reference to  FIGS. 1, 2, 3 and 4A-4G  present techniques by which clinicians may evaluate a patient&#39;s determinants (e.g., factors that may influence the patient&#39;s ability to adhere to self-care behaviors), and use the evaluation of determinants to shape a care plan that may enable the patient&#39;s determinants to be addressed in a manner that may improve the likelihood that the patient will adhere to self-care behaviors. However, other applications for the patient&#39;s ordered list of determinants exist. The exemplary embodiments discussed hereinafter present exemplary embodiments providing another application therefor. 
         [0036]    One issue with self-care behaviors is that, although clinicians have a variety of ways of selecting an effective self-care behavior for a given patient, patients themselves may have difficulty integrating self-care behaviors into their daily lives. In part, this may be because it is difficult for patients to understand the level of effort that may be appropriate for a given self-care behavior, and the potential impact that such effort may have on their health. Because of this lack of understanding, patients may be discouraged from adopting new self-care behaviors into their lives. Further, a patient may find it too difficult to adopt a self-care behavior with parameters that are too challenging (e.g., an exercise regimen that is too long or performed too often). 
         [0037]      FIG. 5  illustrates schematically an exemplary system  500  that may enable patients to more clearly understand the effect that self-care behaviors have on their health. More specifically, the exemplary system  500  may apply patient-specific parameters to general information about a condition to provide a patient with an interactive tool that may enable the patient to understand how the patient&#39;s selected manner of performing self-care behaviors affect the patient&#39;s health. The system  500  may consist of logical elements performing different tasks, in the same manner as the system  100  described above, but those of skill in the art will understand that the functions of these elements may be grouped together in other embodiments. The operation of the system  500  will be described herein with reference to the exemplary method  600 . 
         [0038]    The system  500  may include a Profiler element  510 . In step  610 , the Profiler  510  retrieves available data about a specific patient. The data retrieved by the Profiler  510  may include results of assessment questionnaires about the patient&#39;s condition, data about the patient&#39;s self-management factors, data about the patient&#39;s communication style, data about the patient&#39;s previous clinical experiences, and data about the patient&#39;s personal preferences. It will be apparent to those of skill in the art that the specific data retrieved by the Profiler may vary among differing embodiments, and that the specific sources consulted may also vary. In one embodiment, a source of the data retrieved in step  610  may be the self-assessment  40  referred to above with reference to  FIG. 1 . 
         [0039]    Based on the data received in step  610 , in step  615  the Profiler  510  creates a profile  515  for the patient.  FIG. 7  illustrates an exemplary profile  700  that may be created in step  610 . The profile  700  of  FIG. 7  includes a profile element column  702  that describes the contents of each row, a value column  704  that contains the patient&#39;s value for the given row, and a type column  706  that describes the type of information contained in each row. The profile  700  includes conditions  710 , describing the conditions being experienced by the patient. The exemplary patient of the profile  700  suffers from heart failure and diabetes. The profile  700  also includes current performance  720 , describing current self-care behaviors of the patient. The exemplary patient of the profile  700  exercises once a week, skips medications once a week, and smokes five cigarettes per day. The profile  700  also includes social support  730 , describing the level of social support available to the patient. 
         [0040]    The profile  700  also includes locus of control  740 , describing the extent to which individuals believe they themselves can control events that affect their health (e.g., internal locus of control) or that others have the main control of events that affect the individual (e.g., external locus of control). The exemplary patient of the profile  700  has an external-others locus of control. The profile  700  also includes willingness to self-manage  750 , describing the patient&#39;s willingness to self-manage his/her condition. The exemplary patient of the profile  700  has low willingness to self-manage. The profile  700  also includes patient&#39;s prioritized outcome  760 , describing the patient&#39;s outcome priority. The prioritized outcome  760  of the exemplary patient of the profile  700  is extending lifespan. It will be apparent to those of skill in the art that the profile  700  is only exemplary. The specific rows shown in the profile  700  may vary among differing embodiments, and the specific values shown in the profile  700  are only one possible patient example. The profile  700  may be stored as a computer file in any format appropriate for subsequent use as will be described hereinafter. The profile  700  may also be exported in a computer-friendly format such as XML, or in a human-readable format for display, printing, etc. 
         [0041]    The system  500  also includes a Matcher component  520  in communication with the Profiler  510  and a Database  530 . The Database  530  stores self-care behaviors (e.g., physical activity, smoking cessation, etc.) indexed by various factors such as associated conditions, evidence of effectiveness, guidelines and recommended care plans, and population-generalized weights of the individual parameters of a behavior. In particular, the Database  530  may include, for each self-care behavior, a generalized (e.g., not patient-specific) ImpactScore for each medical condition, based only on known scientific evidence and expert opinion. 
         [0042]    An ImpactScore quantifies the effect that a self-care behavior has on a given medical condition; the effect that self-care behavior b has on medical condition m will be referred to herein as ImpactScore bm . All ImpactScores contained in the Database  530  may be represented on a common scale; in one exemplary embodiment, this scale may be from −100 to 100, but it will be apparent to those of skill in the art that the specific scale used may vary. For example, the physical activity self-care behavior may be associated with multiple medical conditions. For conditions for which scientific evidence and expert opinion have found to be impacted positively by physical activity, a high weight (e.g., an ImpactScore of 85 on a scale from −100 to 100) may be associated with them; for those with less evidence of positive impact, a lower weight (e.g., an ImpactScore of 30 on the same scale); for those conditions where a negative impact is found, a negative weight may be designed (e.g., an ImpactScore of −20 on the same scale). 
         [0043]    The Database  530  may also include a set of parameters describing how each self-care behavior is performed. For example, the self-care behavior or physical activity may have a parameter called “type” that may take on semantic values such as walking on a treadmill at home, attending a fitness class, walking at the mall, or following a fitness DVD at home. Another parameter may be “intensity,” which may take on semantic values such as low, moderate, or high. Another parameter may be “frequency,” which may take on values such as once per week, twice per month, three times a day, etc. It will be apparent to those of skill in the art that the specific parameters may vary for each self-care behavior contained in the Database  530 , depending on the nature of the self-care behavior. The Database  530  may also include a weight for each parameter (e.g., ranging from 0 to 1.0) describing the parameter&#39;s relative contribution to the effectiveness of the behavior, based on scientific evidence or expert opinion. The Database  530  may also include a recommended configuration of the parameters for each behavior and medical condition. 
         [0044]      FIG. 8  illustrates a portion of an exemplary database  800 . Though  FIG. 8  illustrates the contents of the entries in the database  800  for two self-care behaviors and one medical condition, it will be apparent to those of skill in the art that a real-world implementation of a database  800  may include a larger variety of both self-care behaviors and medical conditions. In the database  800 , entries for self-care behaviors  810  (in this example, taking medications) and  820  (in this example, physical activity) are provided for condition  840  (in this example, Heart Failure). 
         [0045]    For self-care behavior  810 , data included in the database includes ImpactScore  811 , parameter  812  (in this example, frequency), recommended value  813  corresponding to parameter  812  (in this example, 80% of prescribed episodes, weight  814  corresponding to parameter  812 , parameter  815  (in this example, type), recommended value  816  corresponding to parameter  815  (in this example, all), and weight  817  corresponding to parameter  815 . For self-care behavior  820  (in this example, physical activity), data included in the database includes ImpactScore  821 , parameter  822  (in this example, intensity), recommended value  823  corresponding to parameter  822  (in this example, moderate), weight  824  corresponding to parameter  822 , parameter  825  (in this example, frequency), recommended value  826  corresponding to parameter  825  (in this example, five times per week), weight  827  corresponding to parameter  825 , parameter  828  (in this example, type), recommended value  829  corresponding to parameter  828  (in this example, walking), and weight  830  corresponding to parameter  828 . It will be apparent to those of skill in the art that the specific examples shown in  FIG. 8  are only exemplary and that these may vary for differing embodiments of a database  800 . 
         [0046]    In step  620 , the Matcher  520  receives the patient profile from the Profiler  510  and data relevant to the patient&#39;s condition from the Database  530 . This may be prompted by action by a clinician or by the patient or in any other appropriate manner. In step  625 , the Matcher  520  generates an ordered list of self-care behaviors for the patient&#39;s medical condition. The ordered list may be ordered by the ImpactScore of the behaviors corresponding to the patient&#39;s condition. At this point in the method  600 , the ImpactScores are still generalized based on the assumption that the patient carries out self-care behaviors in the optimal manner prescribed by clinical guidelines, and are not specific to the patient; in subsequent steps, the Matcher  520  will calculate updated ImpactScores that are specific to the patient. 
         [0047]    In step  630 , the Matcher  520  scales the ImpactScores of the behaviors contained in the ordered list based on the patient&#39;s current level of performance and the corresponding parameters. In this step, an upper bound for each parameter is defined as the recommended level, as determined by clinical guidelines, and assigned a numeric value of 100. (It will be apparent to those of skill in the art that the scaling value of 100 used here is only exemplary and that the following may be performed in the same manner with a different scaling value.) A lower bound for each parameter is defined as non-performance and assigned a numeric value of zero. The patient&#39;s current level of performance is then mapped to this 0-100 scale. This process is performed for each parameter. Considering physical activity as an example, if the recommended level of physical activity is five times per week, this is defined as the upper bound and assigned a numeric value of 100. Zero times per week is identified as the lower bound and assigned a numeric value of zero. If the data received from the Profiler  510  indicates that the patient performs physical activity once per week, this may be determined to have a numeric value of 20. 
         [0048]    In step  635 , the Matcher  520  customizes the values of some or all of the parameters based on the patient profile received from the Profiler  510 . In particular, based on elements of the patient&#39;s self-care profile (e.g., as described in the self-assessment  40 ), certain types of behavior may be more or less effective. For example, physical activity can have many types, including walking on a treadmill at home, participating in a group exercise class, etc. A patient may choose one type of physical activity, and its associated value may be used in calculation of the ImpactScore for the physical activity. If each type of physical activity is effective as any other, then each may have the same numerical value. However, in some cases, one type of physical activity may be less effective than another due to the patient&#39;s self-care barriers; for example, a patient with a low level of social support or a low willingness to self-manage may be less effective at exercising at home than at exercising in a group exercise class where their exercise can be managed by an instructor and social support can be received from the instructor and classmates. Thus, in step  635 , the values of various types of physical activity (and other self-care behaviors) may be adjusted based on the patient&#39;s self-care profile. 
         [0049]      FIG. 9  illustrates a table  900  showing the adjustment of the value of patient self-care behaviors based on the patient&#39;s self-management abilities. Self-care behavior  910  (in this example, walking on a treadmill at home) receives an adjustment  912  of −25% due to rationale  914  of the patient&#39;s low willingness to self-manage, resulting in an adjusted value  916  of 75. Similarly, self-care behavior  920  (in this example, following a fitness DVD at home) receives an adjustment  922  of −50% due to rationale  924  of the patient&#39;s low willingness to self-manage, resulting in adjusted value  926  of 50. Conversely, self-care behaviors  930  and  940  are not impacted by the patient&#39;s willingness to self-manage and, thus, are not adjusted due to this rationale, resulting in corresponding adjusted values  932  and  942 , respectively, of 100. It will be apparent to those of skill in the art that the specific parameters used in such a table  900  may vary for different patients, different conditions, etc., and that the specific illustration of table  900  shown in  FIG. 9  is only exemplary. 
         [0050]    In step  640 , the Matcher  520  calculates adjusted, patient-specific ImpactScores for activities present in the ordered list. These revised ImpactScores are calculated so as to match the configuration and parameters specified by the patient and the patient&#39;s self-care profile. To do this calculation, a scaling factor is used. This scaling factor is calculated as: 
         [0000]      ScalingFactor bm =Σ(weight i ×parameter i )/100 ∀ i= 1, . . . , #parameters
 
         [0051]    The scaling factor is then used to calculate adjusted ImpactScores based on the following: 
         [0000]      ImpactScore′ bm =ScalingFactor bm *ImpactScore bm  
 
         [0052]    In the above formulas, ImpactScore bm  refers to the effect that self-care behavior b, when optimally configured, has on medical condition m; ImpactScore′ bm  refers to the updated effect that self-care behavior b, as configured by the patient, has on medical condition m; ScalingFactor bm  refers to the multiplier that scales the ImpactScore up or down based on the current configuration of the behavior b; parameter i  is the value of the ith parameter, on a range from zero to 100; and weight i  is a weight, ranging from 0 to 1, associated with the ith parameter, where the sum of all weights weight i  is equal to 1. 
         [0053]    Based on this model, the modification of a parameter value (equivalent to performing the corresponding self-care behavior more or less frequently, intensely, completely, etc.) will change the updated value ImpactScore′ by an amount proportional to the weight of the parameter. Separating the parameters while maintaining their relationship to the overall updated value ImpactScore′ is useful for helping the patient explore the relationship between the manner in which they carry out a self-care behavior and the effect the behavior will have on their clinical outcomes. 
         [0054]      FIG. 10  illustrates a table  1000  showing how an updated ImpactScore′ for a given self-care behavior is determined using patient-customized parameters. For self-care behavior  1010  (in this example, physical activity), the patient responds to parameters  1020 ,  1030  and  1040  with parameter values  1022 ,  1032  and  1042  (in this example, once a week, moderate intensity, and walking alone, respectively). The parameters  1020 ,  1030  and  1040  have corresponding unadjusted values  1024 ,  1034  and  1044  (in this example, 20, 100 and 100, respectively). Values  1024  and  1034  have unchanged adjusted values  1026  and  1036  (in this example, 20 and 100, respectively), but value  1044  has a changed adjusted value  1046  (in this example, 75), for the reasons discussed above with reference to  FIG. 9 . The parameters  1020 ,  1030  and  1040  also have corresponding parameter weights  1028 ,  1038  and  1048  (in this example, 0.60, 0.30 and 0.10, respectively). An updated ImpactScore′ value  1050  is then calculated as described above and as illustrated in table  1000 . It will be apparent to those of skill in the art that the specific values shown in table  1000  are only exemplary and that these may vary among different implementations, for different patients, for different medical conditions, etc. 
         [0055]    In step  645 , the Matcher  520  generates a patient-specific data model  540  for use by User Interface Application  550 . The data model  540  may include any data necessary for the User Interface Application  550  to receive, from a user (e.g., the patient) one or more changes to parameters of the patient&#39;s self-care behaviors, and calculate an updated version of the updated, patient-specific ImpactScore′ bm  based on those changes using the formulas described above. The data model  540  may contain only data relevant to the patient&#39;s self-care profile, medical condition, and relevant self-care behaviors and their corresponding parameters, in order to be provided to the user for interactive use through User Interface Application  550  in a comparatively small data footprint (e.g., as compared to the Database  530  containing data for a wide variety of medical conditions and the Matcher  520  capable of processing a larger quantity of data) that may be appropriate for use on an end user device such as a tablet, mobile phone, personal computer, notebook computer, desktop computer, etc. Thus, the User Interface Application  550  may use the data model  540  to calculate an updated ImpactScore for the patient without communication with other elements of the system  500 , such as the Matcher  520  or Database  530 . 
         [0056]    In step  650 , the User Interface Application  550  presents, to a user (e.g., the patient) a display showing the user&#39;s self-care activities and the corresponding parameters for the self-care activities in an interactive manner allowing the user to vary the parameters (e.g., using known interface elements such as dropdown menus, sliders, checkboxes, etc.).  FIG. 11  illustrates an exemplary User Interface Application  550 . In  FIG. 11 , the User Interface Application  550  provides a display  1100  on a tablet device  1105 , but other types of devices may execute the User Interface Application  550  and receive user input in a manner appropriate for the nature of the other devices. For example, for tablet device  1105  or a mobile phone, input may be received via a touchscreen; for a personal computer, input may be received with a mouse and/or keyboard; etc. 
         [0057]    For the patient corresponding to the User Interface Application  550  as shown in  FIG. 9 , the display  1100  includes three self-care behaviors  1110 ,  1120  and  1130 . In the display  1100  shown in  FIG. 9 , self-care behavior  1110  is physical activity, self-care behavior  1120  is taking medication, and self-care behavior  1130  is reducing smoking, but the specific self-care behaviors displayed by User Interface Application  550  may vary depending on the patient&#39;s medical condition. For each of the self-care behaviors  1110 ,  1120  and  1130 , the display  1100  includes interface elements for corresponding parameters. 
         [0058]    For self-care behavior  1110 , which is physical activity, the display  1100  includes a dropdown menu  1111  for the user to select a type of physical activity (e.g., walking outside, walking at the mall, group exercise class, etc.). The display  1100  also includes a slider  1112  for the user to select a frequency for performing the selected physical activity. The display  1100  also includes a slider  1113  for the user to select an intensity for the selected physical activity. The display  1100  also includes an ImpactScore  1114  describing the level of effectiveness of the physical activity based on the user inputs  1111 ,  1112  and  1113 , which may be determined as described above. It will be apparent to those of skill in the art that the ImpactScore  1114  and the other ImpactScores discussed hereinafter may be patient-specific adjusted ImpactScores determined as discussed above. 
         [0059]    For self-care behavior  1120 , which is taking medications, the display  1100  includes a slider  1121  for the user to select a number of episodes of missed medication per week. The display  1100  also includes checkboxes  1122 ,  1123 ,  1124  and  1125  for the user to select medications he/she is willing to take. The display  1100  also includes an ImpactScore  1126  describing the level of effectiveness of the user&#39;s medication based on the user inputs  1121 ,  1122 ,  1123 ,  1124  and  1125 , which may be determined as described above. 
         [0060]    For self-care behavior  1130 , which is reducing smoking, the display  1100  includes a slider  1131  for the user to select a number of cigarettes smoked. The display  1100  also includes a slider  1132  for the user to select a frequency time period during which the user will smoke the number of cigarettes indicated by the slider  1131 . The display  1100  also includes an ImpactScore  1133  describing the level of effectiveness of the user&#39;s smoking reduction based on the user inputs  1131  and  1132 , which may be determined as described above. In one exemplary embodiment, the ImpactScores  1114 ,  1126  and  1133  may be color-coded to more clearly indicate the level of effectiveness of the corresponding self-care behaviors  1110 ,  1120  and  1130 . For example, an ImpactScore of 0 to 35 may be colored red, an ImpactScore of 36 to 70 may be colored yellow, and an ImpactScore of 71 to 100 may be colored green. 
         [0061]    In step  655 , the User Interface Application  550  waits for changed input parameters from the user. As described above, changed input parameters may mean adjusting a dropdown menu, a slider, a checkbox, etc. If changed input parameters are received by the User Interface Application  550 , then, in step  660 , the User Interface Application  550  calculates updated ImpactScore values (e.g., ImpactScores  1114 ,  1126  and  1133  of  FIG. 11 ) based on the newly-received parameters and the data model  540 . After this, the method  600  returns to step  650 , where the display  1100  is updated and the new results are displayed to the user. If no new parameters are received in step  655 , then the method  600  proceeds to step  665 , where the results currently displayed may be considered to be final results for the user&#39;s selected parameters. Following step  665 , the method  600  terminates. 
         [0062]    The exemplary embodiments of  FIGS. 5-11  may provide users with the ability to visualize and dynamically modify parameters of their self-care behaviors, in order to understand the way those behaviors affect their clinical outcomes. This may be useful for patients across a wide spectrum of needs. In chronic disease management, where the trajectory of diseases is well established and the effects of self-care behaviors have been well-studied, this may be particularly useful. However, the same technique and interface may be equally applicable for choosing any health-related behavior. Some examples of this may include selection of exercise routines for general fitness purposes, selection of nutrition plans for dieting, selection of different medications, etc. 
         [0063]    Those of skill in the art will understand that the above-described exemplary embodiments may be implemented in any number of manners, including as a software module, as a combination of hardware and software, etc. For example, the exemplary methods  200  and  600  may be embodied in a program stored in a non-transitory storage medium and containing lines of code that, when compiled, may be executed by a processor. 
         [0064]    It will be apparent to those skilled in the art that various modifications may be made to the exemplary embodiments, without departing from the spirit or the scope of the invention. Thus, it is intended that the present invention cover modifications and variations of this invention provided they come within the scope of the appended claims and their equivalents.

Technology Classification (CPC): 6