Abstract:
Disclosed herein are technologies that may be used to determine the composition of service provider networks. Service providers may be compared based on a number of metrics related to the services they provide. As an example, medical service providers may be compared based on factors such as how quickly patients in their care recover from injuries, and how satisfied patients are with the care they receive. A service provider network may be defined as including only service providers with metrics that meet a given threshold. In the context of workers&#39; compensation insurance, the disclosed technologies may be used to direct injured workers to medical service providers that provide superior care, thereby achieving better outcomes for injured workers.

Description:
TECHNICAL FIELD 
       [0001]    The subject matter disclosed herein relates to computer systems, and particularly to the storage, processing, and display of data related to service provider networks. 
       BACKGROUND 
       [0002]    Workers&#39; compensation insurance is an insurance that provides benefits to workers that are injured in the course of their employment. Benefits that may be provided as part of workers&#39; compensation include disability benefits, rehabilitation services, and medical care. An employer may purchase a workers&#39; compensation insurance policy from an insurance provider. The policy may identify a network of service providers that treat the employees of the employer according to the policy. Service providers may include hospitals, doctors, and rehabilitation providers that administer care to injured workers. 
         [0003]    Service providers may vary in terms of the quality of care that they provide to injured workers. For example, a service provider may provide superior medical treatment versus other service providers, and workers that receive care from the superior service provider may consistently have better outcomes (i.e., may recover from injuries more quickly) than workers who are treated by other service providers. 
         [0004]    To provide the best care possible to injured workers, insurance providers and employers want the best possible service providers to be included in their service provider networks. However, it may be difficult for insurance providers and employers to determine who the best service providers are. Therefore, new technologies are required that may be used to assess the effectiveness of service providers, such that the best possible care may be provided to injured workers. 
       SUMMARY 
       [0005]    Disclosed herein are technologies that may be used to determine the composition of service provider networks. Service providers may be compared based on a number of metrics related to the services they provide. As an example, medical service providers may be compared based on factors such as how quickly patients in their care recover from injuries, and how satisfied patients are with the care they receive. A service provider network may be defined as including only service providers with metrics that meet a given threshold. In the context of workers&#39; compensation insurance, the disclosed technologies may be used to direct injured workers to medical service providers that provide superior care, thereby achieving better outcomes for injured workers. 
         [0006]    A system for determining a composition of a service provider network for providing services according to a workers&#39; compensation insurance plan may include a computer-readable storage medium, at least one processor, and a display device. The computer-readable storage medium may store claim information. The claim information may describe workers&#39; compensation claims and the medical service providers that provided medical services related to the workers&#39; compensation claims. The at least one processor may determine, for each of the medical service providers, a metric value for each of a number of service provider metrics. This may be based on the claim information, and/or other factors. The service provider metrics may include a metric that relates to an amount paid per claim or a percentage of claims that involved lost time. The at least one processor may adjust the metric values based on one or more metric values. Further, the at least one processor may assign scores to each of the medical service providers based on the adjusted metric values, and may determine averages for the assigned scores for each of the medical service providers. Further, the at least one processor may generate results data based on the determined averages of the assigned scores. The results data may indicate, for each of the medical service providers, whether the medical service provider is included in the service provider network. The display device may display the results data. 
         [0007]    A computer-implemented method for determining a composition of a service provider network may include a computer-readable storage storing claim information. The claim information may describe workers&#39; compensation claims and the medical service providers that provided medical services related to the workers&#39; compensation claims. At least one processor may determine, for each of the medical service providers, a metric value for each of a number of service provider metrics. This may be based on the claim information, and/or other factors. The service provider metrics may include a metric that relates to an amount paid per claim or a percentage of claims that involved lost time. The at least one processor may adjust the metric values based on one or more metric values, may assign scores to each of the medical service providers based on the adjusted metric values, and may determine averages for the assigned scores for each of the medical service providers. Further, the at least one processor may generate results data based on the determined averages of the assigned scores. The results data may indicate, for each of the medical service providers, whether the medical service provider is included in the service provider network. The results data may then be displayed by a display device. 
         [0008]    A computer-readable medium may store processor-executable instructions which, when executed by at least one processor, will cause the at least one processor to perform a method for determining a composition of a service provider network. The method may include the at least one processor receiving claim information. The claim information may describe workers&#39; compensation claims and the medical service providers that provided medical services related to the workers&#39; compensation claims. The at least one processor may determine, for each of the medical service providers, a metric value for each of a number of service provider metrics. This may be based on the claim information, and/or other factors. The service provider metrics may include a metric that relates to an amount paid per claim or a percentage of claims that involved lost time. The at least one processor may adjust the metric values based on one or more metric values, may assign scores to each of the medical service providers based on the adjusted metric values, and may determine averages for the assigned scores for each of the medical service providers. Further, the at least one processor may generate results data based on the determined averages of the assigned scores. The results data may indicate, for each of the medical service providers, whether the medical service provider is included in the service provider network. The at least one processor may then display the results data via a display device. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0009]    A more detailed understanding may be had from the following description, given by way of example in conjunction with the accompanying drawings wherein: 
           [0010]      FIG. 1  shows an example architecture  100  for determining the composition of a service provider network; 
           [0011]      FIG. 2  shows an example method for determining the composition of a service provider network; 
           [0012]      FIG. 3  shows an example graph that shows a function that may be used for normalizing data in the context of determining the composition of a service provider network; 
           [0013]      FIG. 4  shows a second example graph that may be used for normalizing data in the context of determining the composition of a service provider network; 
           [0014]      FIG. 5  shows an example user interface element that that may be used to display data that describes the composition of a service provider network; and 
           [0015]      FIG. 6  shows an example system that may be used to implement the features described herein with reference to  FIGS. 1-5 . 
       
    
    
     DETAILED DESCRIPTION 
       [0016]      FIG. 1  shows an example architecture  100  for determining the composition of a service provider network for use in the context of workers&#39; compensation insurance. As will be describe in further detail below, the example architecture  100  of  FIG. 1  may be used to determine if specific service providers should be included in a service provider network, and/or to determine how service providers within a network should be ranked or classified. 
         [0017]    The example architecture  100  includes a network determining module  110 , which is configured to analyze data and determine the composition of a service provider network. The example architecture  100  may also includes a claim information database  122 , claim information database module  120 , and a data input module  124 , which perform functionality related to the storage of data that describes services that have been provided to users by service providers. Further, the example architecture  100  may include a service provider search module  130 , service provider network database  132 , and a search client module  134 , which together provide data to users about medical services providers from which the users may receive services. 
         [0018]    The claim information database  122  may be stored on one or any number of computer-readable storage media (not depicted). The claim information database  122  may be or include, for example, a relational database, a hierarchical database, an object-oriented database, one or more flat files, one or more spreadsheets, and/or one or more structured files. The claim information database  122  may store information related to claims that have been filed and medical service providers that have provided services related to the claims. The claim information database  112  may include data related to service providers who are already included in one or more service provider networks, service providers who are not currently in a service provider network, and/or any combination thereof. For each claim, the claim information database  122  may include one or more parameters associated with the claim, such as: the amount paid by the insurance provider for the claim; the number of disability days for which the claimant missed work; whether the claim is associated with litigation or other legal activity; the number of days the claim has stayed open, which may also be referred to as the “age” or “maturity” of a claim; whether the claim settled; whether the compensability of the claim has been determined (in other words, whether a determination has been that the claim relates to an injury that should be compensated by workers&#39; compensation insurance, or whether investigation into this topic is still ongoing); the number of service provider office visits associated with the claim; whether surgery was associated with the claim; whether inpatient hospitalization was associated with the claim; the age of the claimant; a treatment delay time (i.e., the period of time that passed between the injury and when the claimant first sought treatment for the injury); a location where the injury and/or the treatment took place; a service provider that provided services associated with the claim; and/or other information. Further, the claim information database  122  may include information such as whether each claim involved lost time. Many jurisdictions define a waiting period that follows the onset of an injury. Work that is missed during this waiting period does not constitute lost time; however, work that is missed by an injured working after the waiting period is considered lost time. Alternatively or additionally, the claim information database  122  may store qualitative information related to the claims, such as: data that describes the satisfaction of the claimant with the care received; data that describes the satisfaction of a claims adjuster that handled the treatment associated with the claim with the service provider; and/or information that describes the satisfaction of the claimant&#39;s employer with how the service provider handled the treatment associated with the claim. A level of satisfaction may be represented using a numeric scale, with different values along the scale corresponding to different levels of satisfaction. As an example, a scale of zero to ten may be used, wherein zero represents the lowest level of satisfaction and ten represents the highest level of satisfaction). 
         [0019]    The claim information database module  120  may perform functionality such as adding data to, modifying data in, querying data from, and/or retrieving data from the claim information database  122 . The claim information database module  120  may be, for example, a database management system (DBMS), a database driver, a module that perform file input/output operations, and/or other type of module. The claim information database module  120  may be based on a technology such as Microsoft SQL Server, Microsoft Access, MySQL, PostgreSQL, Oracle Relational Database Management System (RDBMS), Microsoft Excel, a NoSQL database technology, and/or any other appropriate technology. 
         [0020]    The data input module  124  may perform functionality such as providing data to the claim information database module  120  for storage in the claim information database  122 . The data input module  124  may be, for example, a spreadsheet program, a database client application, a web browser, and/or any other type of application that may be used to provide data to the claim information database module  120 . 
         [0021]    The network determining module  110  may perform functionality such as determining the composition of a service provider network based on information stored in the claim information database  122 . The network determining module  110  may include an input module  112 , a network composition module  114 , and an output module  116 . The input module  112  may perform functionality such as obtaining data from the claim information database module  120  and providing the data to the network composition module  144 . The network composition module  114  may perform functionality such as analyzing the data provided by the input module  112  to determine the composition of the service provider network. This may include, for example, analyzing how well service providers perform in a number of parameters (such as those described above as stored in the claim information database  122 ), assigning scores to the service providers based on their performances, and ranking service providers based on their scores. The network composition module  114  may determine whether service providers should be included in a service provider network or not, based on the scores. Alternatively or additionally, the network composition module  114  may determine that service providers within a certain range of scores may be classified differently from service providers within other ranges. For example, service providers with scores above a threshold value should be classified as “preferred” providers within the network, while providers with lower scores may not. 
         [0022]    The output module  116  may obtain results determined by the network composition module  114  and may output the results in a number of ways. For example, the output module  116  may store the results in one or more computer-readable media (not depicted), and/or may send information related to the results to an output device (not depicted) such as a printer, display device, or network interface. Alternatively or additionally, the output module  116  may transmit and/or otherwise output its results for storage in the service provider network database  132 . Further details regarding functionality that may be performed by the network determining module  110  are provided below with reference to  FIG. 2 . 
         [0023]    The service provider network database  132  may store information that describes the composition of a service provider network. For example, the service provider network database  132  may include information that identifies service providers in the network, and may include contact information, specialty information, geographic information, information regarding how well service providers have been ranked by the network composition module  114  (for example, whether providers are “preferred” or not), and/or information associated with the service providers. The service provider network database  132  may be stored on one or any number of computer-readable storage media (not depicted). The claim information database  122  may be or include, for example, a relational database, a hierarchical database, an object-oriented database, one or more flat files, one or more spreadsheets, and/or one or more structured files. 
         [0024]    The service provider search module  130  may provide search functionality that allows users to search for service providers whose information is stored in the service provider network database  132 . A user may interact with the service provider search module  130  using the search client module  134 . The search client module  134  may provide a user interface that the user may use to enter information to search for a service provider. As an example, the search client module  134  may be a web browser or similar application. 
         [0025]    As an example, a user may wish to search for a medical service provider for a particular medical specialty that is geographically nearby to the user&#39;s location. The user may enter these search parameters into the user provided by the search client module  134 , which may transmit the search parameters to the service provider search module  130 . The search parameters may include, for example, an area of specialization, name, geographic location (such as a state, city, and/or zip code), and/or other parameters. The service provider search module  130  may then search for a service provider in the service provider database  132  that matches the parameters, and transmit search response information to the search client module  134 . The service provider search module  130  may generate the results based on information such as how the service providers have been ranked by the network composition module  114 . For example, the service provider search module  130  may generate results that will display preferred providers before providers with less favorable rankings are displayed. Alternatively or additionally, the service provider search module  130  may generate the search results to include only service providers within a certain range of scores. The search client module  134  may then display the search response information to the user via a display device (not depicted). The search response information may include contact information such as telephone numbers, addresses, and/or other information related to the medical service providers that match the search criteria. Using the contact information, the user may contact the service providers and initiate a visit to the service provider to begin medical treatment. 
         [0026]    Each or any combination of the modules  110 ,  112 ,  114 ,  116 ,  124 ,  120 ,  130 ,  134  may be implemented as software modules, specific-purpose processor elements, or as combinations thereof. A suitable software module may be or include, by way of example, one or more executable programs, one or more functions, one or more method calls, one or more procedures, one or more routines or sub-routines, one or more processor-executable instructions, and/or one or more objects or other data structures. 
         [0027]    The example architecture  100  of  FIG. 1  may be used in any number of different contexts. As one example, an insurance provider may control the data input module  124 , claim information database module  120 , claim information database  122 , and network determining module  110 . The insurance provider may use these modules  110 ,  120 ,  124  to determine the composition of a service provider network for use with a workers&#39; compensation policy. The insurance provider may provide the composition of the service provider network to a third party search vendor, which may control the service provider search module  130 . The insurance provider may provide the workers&#39; compensation policy to an employer. When employees of the employer are injured, the employees may search for medical service providers using the search client module  134 , thereby interacting with the service provider search module  130 . 
         [0028]    As an additional example, a third party administrator (TPA) of a self-funded workers&#39; compensation plan may control the data input module  124 , claim information database module  120 , claim information database  122 , and network determining module  110 . The TPA may use these modules  110 ,  120 ,  124  to determine the composition of a service provider network for use with the self-funded plan. The TPA and/or a third party search vendor may control the service provider search module  130 . 
         [0029]    Further, an insurance provider or TPA may interact with service providers differently based on the results generated by the network determining module  110 . For example, in an instance where the network determining module  110  classifies service providers, an insurance provider or TPA may perform claim management differently with service providers that are in the different classifications. For example, an insurance provider or TPA may reduce or completely remove claim management for service providers with favorable scores, while focusing additional energy and resources for claim management for providers with less favorable scores. 
         [0030]      FIG. 2  shows an example method  200  for determining the composition of a service provider network. The method  200  may begin with receiving data related to service providers and claims associated with services provided by the service providers (step  202 ). This may include, for example, reading the data from a computer-readable storage medium and/or receiving the data via a network interface. The data may be or include the information described above with reference to  FIG. 1  as stored in the claim information database  122 . 
         [0031]    Next, metrics for evaluating service providers may be selected (step  204 ). The metrics may include, for example, an average number of disability days experienced by workers that were treated by a service provider, or a percentage of claims that involved lost time. As further examples, the metrics may include: an average paid loss per claim; a percentage of claims that are associated with legal and/or litigation activity; an average claim duration; a percentage of claims that are open after twelve months; a percentage of claims for which compensability has not yet been determined; a percentage of claims that were settled; an average number of provider office visits for claims; a percentage of claims that involve surgery; a percentage of claims that involve inpatient hospitalization; an average number of lost work days per claim; average levels of satisfaction with provided services, as indicated by claimants, claims adjusters, and/or employers; and/or other metrics. While a number of example metrics are described above in terms of averages, the metrics may also include metrics that are based on other statistical functions such as means, modes, correlations, regressions, or standard deviations. 
         [0032]    Claims may then be filtered, based on a number of different parameters. (step  206 ). This may include removing data related to claims that have parameters that are far above or below the average for that parameter. For example, claims related to catastrophic injuries may have much higher associated costs, disability days, and/or higher values for other parameters, and data associated with these claims may be removed. As one example, claims that involved payment of more than a given threshold for a given type of expense within a given period of time may be removed. For example, claims that involved payment of more than $150,000 in medical expenses within the first six months of the filing of the claim may be removed. Alternatively or additionally, claims that involved a low total payment may be removed. For example, claims that involved a total payment of less than $50,000 may be filtered out of the received data. Alternatively or additionally, filtering may include removing data that is outside of a particular geographic area of interest. For example, if a particular zip code, state, or other geographic area is the region of interest, then claims that do not pertain to the geographic area may be removed. 
         [0033]    Then, for each metric, values may be determined for each of the service providers, based on the received data (step  208 ). This may include averaging and/or determining percentages for the data from the received data that is associated with claims handled by the service providers. For example, if a selected metric is an average satisfaction level for claimants, then the claimant satisfaction level values will be averaged for each service provider. Corresponding processing may be performed for each of the selected metrics. 
         [0034]    The metric values may then be adjusted to obtain metric values that are consistent values across service providers (step  210 ). Adjusting the metric values may include scaling and/or otherwise modifying the metric values, and may be based on a number of different factors. For example, metric values may be adjusted based on one or more adjustment parameters, such as the types of injuries a service provider has treated, the ages of claimants handled by a service provider, and/or the ages of claims handled by a service provider. 
         [0035]    To adjust metric values based on the type of injuries a service provider has treated (step  210 ), the following approach may be employed. First, claims may be grouped according to the type of injury (also referred to as the “Major Diagnostic Category (MDC)”) of the injury. Then, for each MDC, an average metric value for claims associated with that MDC may be determined. Then, the average metric values for each MDC may be compared, and values (“scaling factors”) may be determined for each of the MDCs. Scaling factors are values that may be used to multiply the average metric values to bring the average metric values onto a common scale. Finally, metric values may be multiplied by the scaling factors to obtain adjusted metric values. 
         [0036]    The following is an example of how metric values may be adjusted based on MDCs: A set of claims may relate to three example MDCs, “Injury One,” “Injury Two,” and “Injury Three.” The average paid loss for all claims for Injury One may be $5,000; the average paid loss for all claims for Injury Two may be $10,000; and the average paid loss for all claims for Injury Three may be $20,000. According to this example, the average paid loss is two times greater for Injury Three than for Injury Two, and four times greater for Injury Three than for Injury One. Therefore, all paid loss values for claims that are associated with Injury One may be adjusted by being multiplied by a scaling factor of four, and all paid loss values for claims that are associated with Injury Two may be adjusted by being multiplied by a scaling factor of two. By multiplying these paid loss values with these scaling factors, the average paid loss across all three of the MDCs will be the same and paid loss values across the different DMCs may be compared on a normalized scale. 
         [0037]    To adjust metric values based on the ages of claimants handled by a service provider (step  210 ), the following approach may be employed. Claims may be grouped according to the age of the claimants. Then, for each group, an average metric value for claims associated with the age may be determined. Then, a function may be derived from the averages. The function may take a claimant age range as an input, and generate a corresponding average metric value (such as, for example, an average number of disability days) as an output. Metric values may then be compared against values generated by the function, and be adjusted based on the difference between the metric values and the corresponding values generated by the function. 
         [0038]    Referring now to both  FIG. 2  and  FIG. 3 ,  FIG. 3  shows an example graph  300  that shows an example function  308  that may be used to adjust metric values based on the ages of claimants handled by a service provider (step  210 ). The graph  300  includes an X axis  302 , which corresponds to claimant ages, and a Y axis  304 , which corresponds to an average number of disability days. The graph  300  also includes a curve  306 , which is a graphical representation of the function  308 . The curve  306 , as shown in  FIG. 3 , shows correspondences between claimant age ranges (on the X axis  302 ) and average disability days (on the Y axis  304 ). 
         [0039]    Referring again to  FIG. 2 , to adjust metric values based on the ages of claims handled by a service provider (step  210 ), the following approach may be employed. Claims may be grouped according to the age (in months, or some other unit of time) of the claim. Then, for each group, an average metric value for claims associated with the age. Then, a function may be derived from the averages. The function may take a claim age as an input, and generate a corresponding average metric value (such as, for example, an average disability days) as an output. Metric values may then be compared against values generated by the function, and be adjusted based on the difference between the metric values and the corresponding values generated by the function. 
         [0040]    Referring now to both  FIG. 2  and  FIG. 4 ,  FIG. 4  shows an example graph  400  that shows an example function  408  that may be used to adjust metric values based on the ages of claims handled by a service provider (step  210 ). The graph  400  includes an X axis  402 , which corresponds to claim age ranges, and a Y axis  404 , which corresponds to an average number of disability days. The graph  400  also includes a curve  406 , which is a graphical representation of the function  408 . The curve  406 , as shown in  FIG. 4 , shows correspondences between claim age ranges (on the X axis  402 ) and average disability days (on the Y axis  404 ). 
         [0041]    Referring again to  FIG. 2 , after the metric values are adjusted (step  210 ), the adjusted metric values may be compared, and scores may be assigned to service providers based on the comparisons (step  212 ). Here, adjusted metric values for each metric may be sorted into ascending or descending order, and percentage range distributions for the sorted values may be determined. 
         [0042]    The following table (Table 1) shows examples of percentage range distributions for a number of example metrics: 
         [0000]    
       
         
               
               
               
               
               
               
             
               
               
               
               
               
               
             
           
               
                   
                 TABLE 1 
               
               
                   
                   
               
               
                   
                 Top 10% 
                 Top 25% 
                 Top 50% 
                 Top 75% 
                 Top 90% 
               
               
                   
                   
               
             
             
               
                   
               
             
          
           
               
                 Average 
                 7 
                 5 
                 3 
                 2 
                 1 
               
               
                 claimant 
               
               
                 satisfaction 
               
               
                 Average 
                 14 
                 30 
                 55 
                 90 
                 115 
               
               
                 disability 
               
               
                 days 
               
               
                 Average 
                 $2,000 
                 $5,000 
                 $15,000 
                 $30,000 
                 $40,000 
               
               
                 paid loss 
               
               
                   
               
             
          
         
       
     
         [0043]    In the example of Table 1, the metrics that are used are average claimant satisfaction, average disability days, and average paid loss. For average claimant satisfaction, values may be defined according to a scale of zero to ten, wherein zero represents the lowest level of satisfaction and ten represents the highest level of satisfaction. Table 1 is organized such that percentage ranges for qualitatively better values are on the left size of the table (e.g., a higher claimant satisfaction value is considered better than a lower claimant satisfaction value), while percentage ranges for qualitatively lesser values are on the right side of the table. 
         [0044]    Table 1 shows border values for the different percentage ranges for each of the average claimant satisfaction, average disability days, and average paid loss metrics. According to the example of Table 1, the top 10% of claimant satisfaction values were at seven or above; the next 15% of claimant satisfaction values were from five to six; the next 25% of values were from three to four; the next 25% of values were from one to two; and the next 15% of values were one. Similarly, the top 10% of values for the average number of disability days were less than fourteen; in the next percentage ranges for this metric, the average numbers of disability days were less than 30, 55, 90, and 155, respectively. Further, the top 10% of values for average paid loss were less than $2,000; in the next percentage ranges for this metric, the values for average paid loss were less than $5,000, $15,000, $30,000, and $40,000, respectively. After percentage range distributions are determined, each service provider may be assigned a score for each metric, based on which percentage range the service provider falls within for that metric. The following table (Table 2) shows example values that may be assigned based on percentage distributions: 
         [0000]    
       
         
               
               
               
             
           
               
                   
                 TABLE 2 
               
               
                   
                   
               
               
                   
                 Percentage 
                 Value to be 
               
               
                   
                 Range for Metric 
                 Assigned 
               
               
                   
                   
               
             
             
               
                   
                 Top 90%-100% 
                 5 
               
               
                   
                 75%-90% 
                 4 
               
               
                   
                 50%-75% 
                 3 
               
               
                   
                 25%-50% 
                 2 
               
               
                   
                 10%-25% 
                 1 
               
               
                   
                  0%-10% 
                 0 
               
               
                   
                   
               
             
          
         
       
     
         [0045]    As a further example that uses the examples of Table 1 and Table 2, a service provider may have the following values: an average claimant satisfaction value of seven; an average disability days value of fifty; and an average paid loss value of $35,000. For average claimant satisfaction, this service provider would fall within the top 90%-100% range, and so would be assigned a value of five; for average disability days, this service provider would fall within the 50%-75% range, and so would be assigned a value of three; and for average paid loss, this service provider would fall within the 10%-25% range, and so would be assigned a value of two. In summary, the service provider would be assigned the following scores: {5, 3, 1}. 
         [0046]    As shown in the above example, favorable percentage ranges correspond to higher values (e.g., the top 90%-100% range is associated with a value of five, the 75%-90% range is associated with a value of four, and so on.) In a variation on the above example, favorable percentage ranges may correspond to lower values and less favorable percentage ranges may correspond to higher values. According to this variation, the top 90%-100% range may correspond to a value of zero, the 75%-90% range may correspond to a value of one, the 50%-75% range may correspond to a value of three, and so on. 
         [0047]    Final scores for each service provider may then be determined by averaging the metric scores assigned to each service provider (step  214 ). Referring again to the above example, the service provider was assigned the following scores: {5, 3, 1}. Averaging these scores would result in a final score for the service provider of three. Alternatively or additionally, the final scores may be a weighted average. 
         [0048]    Then, the composition of the service provider network may be determined based on the final service provider scores (step  216 ). This may include, for example, determining that service providers with a final score below a threshold are not included in the service provider network, and that service providers with a final score above the threshold are included in the service provider network. As one example, a value of three may be used for the threshold; according to this example, service providers with a final score of three or above may be included in the service provider network, while those with a final score of one or two are not included in the service provider network. Alternatively or additionally, service providers within a certain range of scores may be classified differently from service providers within other ranges. For example, service providers with a final score above a threshold value may be considered to be “preferred” providers within the network, while providers with final scores below the threshold may be considered part of the network, but may not be designated with a preferred status. In a variation on the above, lower final scores may be considered better than higher local scores; in such an instance, determining the composition of the service provider network may include, as an example, determining that service providers with a final score above a threshold are not included in the service provider network and that service providers with a final score below the threshold are included in the service provider network. 
         [0049]    Once the composition of the service provider network is determined, the composition and/or other related information may then be output (step  218 ). This may include, for example, storing the results in one or more computer-readable media, displaying the results on a display device, printing the results via a printer, and/or communicating the results via a network interface. The other related information that may also be output may include any of the data or other parameter described above as used during steps  202  through  216 , and/or other parameters. 
         [0050]    Referring now to both  FIG. 2  and  FIG. 5 ,  FIG. 5  shows an example user interface element  500  that may be used to display data that describes the composition of an example service provider network on a display device (step  218 ). The example user interface element  500  includes a header row area  502 , a first row area  504 , a second row area  506 , and a third row area  508 . 
         [0051]    The user interface element  500  of  FIG. 5  shows service provider network composition data that relates to three example service providers, Provider One, Provider Two, and Provider Three. The first row area  504  shows data that relates to Provider One; Provider One has an average claimant satisfaction score of one, an average disability days score of zero, and an average paid loss score of three. These scores may be determined using the example parameters described above with reference to Table 1 and Table 2. These scores, when averaged, result in the final score of one, as shown in the first row area  504 . The second row area  506  and the third row area  508  show corresponding data for Provider Two and Provider Three, respectively. In this example, a threshold final value of three may have been used to determine whether a service provider should be included in the service provider network or not. According to this example, and as shown in the row areas  502 ,  504 ,  506  in the user interface element  500 , Provider One and Provider Three are included in the service provider network, while Provider Two is not included in the service provider network. 
         [0052]    Referring to both  FIG. 1  and  FIG. 2 , the method  200  of  FIG. 2  may be performed using the example architecture  100  of  FIG. 1 , or any other appropriate architecture. For example, the network determining module  110  of  FIG. 1  may perform the method  200  of  FIG. 2 . Alternatively or additionally, the input module  112  of  FIG. 1  may perform step  202  of the method  200  of  FIG. 2 , the network composition module  114  of  FIG. 1  may perform steps  204  through  216  of the method  200  of  FIG. 2 , and the output module  116  of  FIG. 1  may perform step  218  of the method  200  of  FIG. 2 . 
         [0053]      FIG. 6  shows an example system  600  that may be used to implement the example architecture  100  of  FIG. 1 , the method  200  of  FIG. 2 , and/or to display the user interface element  500  of  FIG. 5 . The example system  600  may include a data input computer  610 , a network determining computer  630 , a provider search server  650 , a search client device  670 , and one or more communication networks  690 . 
         [0054]    The data input device  610  may include a processor  618 , memory device  620 , communication interface  622 , input device interface  612 , display device interface  614 , and storage device  616 . The network determining device  630  may include a processor  638 , memory device  640 , communication interface  642 , input device interface  632 , display device interface  634 , and storage device  636 . The provider search server  650  may include a processor  658 , memory device  660 , communication interface  662 , input device interface  652 , display device interface  654 , and storage device  656 . The search client device  670  may include a processor  678 , memory device  680 , communication interface  682 , input device interface  672 , display device interface  674 , and storage device  676 . 
         [0055]    The data input device  610  may be configured to perform any feature or combination of features described above with reference to  FIGS. 1-5  as performed by the data input module  124 . The network determining device  630  may be configured to perform any feature or combination of features described above with reference to  FIGS. 1-5  as performed by the claim information database module  120  and/or the network determining module  110 . The provider search server  650  may be configured to perform any feature or combination of features described above with reference to  FIGS. 1-5  as performed by the service provider search module  130 . The search client device  670  may be configured to perform any feature or combination of features described above with reference to  FIGS. 1-5  as performed by the search client module  134 . The search client device  670  may be, for example, a desktop computer, a laptop computer, a netbook, a tablet computer, a personal digital assistant (PDA), a cellular phone, or any other appropriate device. 
         [0056]    Each or any of the memory devices  620 ,  640 ,  660 ,  680  may be or include a device such as a Dynamic Random Access Memory (D-RAM), Static RAM (S-RAM), or other RAM or a flash memory. Each or any of the storage devices  616 ,  636 ,  656 ,  676  may be or include a hard disk, a magneto-optical medium, an optical medium such as a CD-ROM, a digital versatile disk (DVDs), or Blu-Ray disc (BD), or other type of device for electronic data storage. 
         [0057]    Each or any of the communication interfaces  622 ,  642 ,  662 ,  682  may be, for example, a communications port, a wired transceiver, a wireless transceiver, and/or a network card. Each or any of the communication interfaces  622 ,  642 ,  662 ,  682  may be capable of communicating using technologies such as Ethernet, fiber optics, microwave, xDSL (Digital Subscriber Line), Wireless Local Area Network (WLAN) technology, wireless cellular technology, and/or any other appropriate technology. The communication interfaces  622 ,  642 ,  662 ,  682  may be used by the data input device  610 , the network determining device  630 , the provider search server  650 , and the search client device  670  to communicate via the one or more communication networks  690 . The one or more communication networks  690  may include one or more private Local Area Networks (LANs), and/or one or more public communication networks such as the Internet. The one or more communication networks  690  may be based on wired and/or wireless networking technologies. 
         [0058]    Each or any of the input device interfaces  612 ,  622 ,  652 ,  672  may an interface configured to receive input from an input device such as a keyboard, a mouse, a trackball, a scanner, a touch screen, a touch pad, a stylus pad, and/or other device. Each or any of the input device interfaces  612 ,  622 ,  652 ,  672  may operate using a technology such as Universal Serial Bus (USB), PS/2, Bluetooth, infrared, and/or other appropriate technology. 
         [0059]    Each or any of the display device interfaces  614 ,  634 ,  654 ,  674  may be an interface configured to communicate data to a display device. Each or any of the display device interfaces  614 ,  634 ,  654 ,  674  may operate using technology such as Video Graphics Array (VGA), Super VGA (S-VGA), Digital Visual Interface (DVI), High-Definition Multimedia Interface (HDMI), or other appropriate technology. 
         [0060]    The memory  620  and/or the storage device  616  of the data input device  610  may store instructions which, when executed by the processor  618 , cause the processor  618  to perform any feature or combination of features described above with reference to  FIGS. 1-5  as performed by the data input module  124 . The memory  640  and/or the storage device  636  of the network determining device  630  may store instructions which, when executed by the processor  638 , cause the processor  638  to perform any feature or combination of features described above with reference to  FIGS. 1-5  as performed by the claim information database module  120  and/or the network determining module  110 . The memory  660  and/or the storage device  656  in the provider search server  650  may store instructions which, when executed by the processor  658 , cause the processor  658  to perform any feature or combination of features described above with reference to  FIGS. 1-5  as performed by the provider search server  650 . The memory device  680  and/or the storage device  676  in the search client device  670  may store instructions which, when executed by the processor  678 , cause the processor  678  to perform any feature or combination of features described above with reference to  FIGS. 1-5  as performed by the search client module  134 . 
         [0061]    Although examples are described above in terms of workers&#39; compensation and medical service providers, the principles described above may be applied to any other appropriate context. For example, the principles described above may be applied, mutatis mutandis, to automobile insurance, property insurance, general liability insurance, and/or any other insurance-related or non-insurance-related context. 
         [0062]    When referred to herein, the term “display device” broadly refers to and is not limited to a monitor or television display, a plasma display, a liquid crystal display (LCD), and/or a display based on a technology such as front or rear projection, light emitting diodes (LEDs), organic light-emitting diodes (OLEDs), or Digital Light Processing (DLP). 
         [0063]    When referred to herein, the term “computer-readable storage medium” broadly refers to and is not limited to a register, a cache memory, a ROM, a semiconductor memory device (such as a D-RAM, S-RAM, or other RAM), a magnetic medium such as a flash memory, a hard disk, a magneto-optical medium, an optical medium such as a CD-ROM, a DVDs, or BD, or other device for electronic data storage. 
         [0064]    As used herein, the term “processor” broadly refers to and is not limited to a single- or multi-core general purpose processor, a special purpose processor, a conventional processor, a digital signal processor (DSP), a plurality of microprocessors, one or more microprocessors in association with a DSP core, a controller, a microcontroller, one or more Application Specific Integrated Circuits (ASICs), one or more Field Programmable Gate Array (FPGA) circuits, any other type of integrated circuit (IC), a system-on-a-chip (SOC), and/or a state machine. 
         [0065]    Although features and elements are described above in particular combinations, each feature or element can be used alone or in any combination with the other features and elements. For example, each feature or element described above with reference to any one or any combination of  FIGS. 1-6  may be used alone without the other features and elements or in various combinations with or without other features and elements described above with reference to any one or any combination of  FIGS. 1-6 . Sub-elements of the methods and features described above may be performed in any arbitrary order (including concurrently), in any combination or sub-combination.