Abstract:
Systems and methods utilize computing devices to generate diagnoses of medical conditions. The computing devices can incorporate algorithms based on predetermined relationships between the medical conditions and various symptoms or characteristics associated with the medical conditions. The computing devices can prompt an individual evaluating patient information to observe whether the characteristics or symptoms are present in the patient information. The individual can subsequently provide inputs to the computing device indicating whether the characteristics or symptoms are present in the patient information.

Description:
TECHNICAL FIELD  
       [0001]    The embodiments and methods disclosed herein relate to practice of medicine, and have particular relevance to generating diagnoses of medical conditions in the practice of telemedicine. 
       BACKGROUND  
       [0002]    Telemedicine involves the diagnosis and potential management of medical conditions by a physician or other individual remotely located from the patient, using information transmitted by electronic means. Achieving consistent, accurate diagnoses is of primary importance in telemedicine, and in the practice of medicine in general. In particular, it is desirable to minimize physician to physician variations in diagnoses generated using the same or similar information. It is also desirable to minimize variations in diagnoses generated by the same physician at different times based on the same or similar information. 
         [0003]    Achieving consistent, accurate diagnoses in the practice of telemedicine can be a challenge due to the lack of direct physical interaction between the patient and the physician. Moreover, the degree of inconsistency and inaccuracy in the diagnoses generated by a physician is generally higher when the physician does not have ready access to state of the art information and the current best practices in the physician&#39;s field of practice, a situation that can commonly occur in the practice of telemedicine. 
         [0004]    Another issue in the practice of medicine is the lack of specialized physicians. For example, the availability of physicians specializing in the diagnosis and treatment of ocular diseases is generally less than the demand for such physicians, particularly in areas located away from major population centers. 
         [0005]    Consequently, a need exists for systems and methods that can potentially enhance the consistency and accuracy of medical diagnoses, and that can help to maximize the efficiency of physicians or others in generating medical diagnoses. 
       SUMMARY  
       [0006]    Systems and methods utilize computing devices to generate diagnoses of medical conditions. The computing devices can incorporate algorithms based on predetermined relationships between the medical conditions and various symptoms or characteristics associated with the medical conditions. The computing devices can prompt an individual evaluating patient information to observe whether the characteristics or symptoms are present in the patient information. The individual can subsequently provide inputs to the computing device indicating whether the characteristics or symptoms are present in the patient information. 
         [0007]    Methods comprise receiving medical information relating to a first individual; prompting a second individual to evaluate the medical information using a predetermined criterion; and generating a diagnosis of a medical condition based on a predetermined relationship between the results of the evaluation and the medical condition using a computing device. 
         [0008]    Embodiments of computing devices comprise a processor, a memory communicatively coupled to the processor, and computer-executable instructions stored on the memory. The computing device receives medical information relating to a first individual; generates prompts for a second individual to evaluate the medical information using a predetermined criterion; and generates a diagnosis of a medical condition based on a predetermined relationship between the results of the evaluation and the medical condition. 
         [0009]    Embodiments of systems comprise an imaging station comprising a first computing device, and an imaging device communicatively coupled to the first computing device. The embodiments also comprise a reading station comprising a second computing device, and a central data processing system. The central data processing system comprises a third computing device communicatively coupled to the first and second computing devices. 
         [0010]    The third computing device receives images from the imaging station. The third computing device also generates prompts and sends the prompts and the images to the second computing device. The prompts prompt evaluation the images using a predetermined criterion. 
         [0011]    The third computing device also receives information from the second computing device relating to the evaluation of the images, and generates a diagnosis of a medical condition based on a predetermined relationship between the information relating to the evaluation of the images and the medical condition. 
     
    
     
       DRAWINGS  
         [0012]    The foregoing summary, as well as, the following detailed description of preferred embodiments, are better understood when read in conjunction with the appended diagrammatic drawings. The drawings are presented for illustrative purposes only, and the scope of the appended claims is not limited to the specific embodiments shown in the drawings. In the drawings: 
           [0013]      FIG. 1  is a diagrammatic illustration of a system for generating medical diagnoses; 
           [0014]      FIG. 2  is a block diagram depicting a server of the system shown in  Figure 1 ; 
           [0015]      FIG. 3  is a block diagram depicting a computing device of an imaging station of the system shown in  FIGS. 1 and 2 ; 
           [0016]      FIG. 4  is a block diagram depicting a computing device of a reading station of the system shown in  FIGS. 1-3 ; 
           [0017]      FIGS. 5A and 5B  are a flow diagram depicting a method for generating medical diagnoses; 
           [0018]      FIG. 6  depicts a web page generated by the system shown in  FIGS. 1-4 , the web page prompting the input of various information relating to a patient; 
           [0019]      FIG. 7  depicts another web page generated by the system shown in Figures  1 - 4 , the web page displaying various locations on a patient&#39;s retinas at which images are to be acquired; 
           [0020]      FIG. 8  depicts another web page generated by the system shown in Figures  1 - 4 , the web page displaying a list of patients and related information associated with a particular reading physician using the system; 
           [0021]      FIG. 9  depicts another web page generated by the system shown in Figures  1 - 4 , the web page displaying a previously-acquired retinal image of one of the patients associated with the reading physician, and various observations of the retinal images to be made by the reading physician; 
           [0022]      FIG. 10  depicts a web page generated by the system shown in  FIGS. 1-4 , the web page being capable of displaying a preliminary diagnostic report for review and approval of the reading physician; 
           [0023]      FIG. 11  depicts a final report form generated using the system and method depicted in  FIGS. 1-4 , the final report being capable containing a diagnosis and recommendations relating to the presence of absence of retinal disease in a patient; 
           [0024]      FIG. 12  depicts an algorithm for use in the system depicted in  FIGS. 1-4 , the algorithm being capable of generating diagnoses of diabetic retinopathy; and 
           [0025]      FIG. 13  depicts another algorithm for use in the system depicted in  FIGS. 1-4 , the algorithm being capable of generating diagnoses of retinopathy of prematurity. 
       
    
    
     DETAILED DESCRIPTION  
       [0026]      FIGS. 1 to 4  depict an embodiment of a system  10  for providing automated diagnoses of medical conditions. The system  10  comprises a central data processing system  12 , one or more imaging stations  14 , and one or more reading stations  16 . As discussed below, the data system  12  is configured to generate a diagnosis of a medical condition such as retinal disease. The diagnosis is generated based on images captured by the imaging stations  14 , and evaluations of the images made by a physician or other qualified individual at the reading stations  16 . 
         [0027]    The central data processing system  12 , imaging stations  14 , and reading stations  16  are depicted as being remotely located in relation to each other, i.e., as residing at different geographic locations. The central data processing system  12 , and some or all of the imaging stations  14  and reading stations  16  can reside at the same location in alternative embodiments. 
         [0028]    The use of the system  10  and the diagnostic methods described herein to diagnose various forms of retinal disease is described for exemplary purposes only. This particular application is disclosed for exemplary purposes only; the system  10  and the methods described herein can be adapted to diagnose other types of medical conditions, including medical conditions unrelated to the eyes. 
         [0029]    The central data processing system  12 , imaging stations  14 , and reading stations  16  can communicate by way of a suitable communications network  26 . The communications network  26  can be, for example, the internet, and the data processing system  12  can communicate with the imaging stations  14  and the reading stations  16  by way of a suitable protocol such as the hypertext transfer protocol (HTTP). The use of the internet as the communications network  26  is disclosed for exemplary purposes only; other suitable types of communications networks, such as a local area network, a wide area network, or an intranet, can be used in the alternative. 
         [0030]    The system  10  is depicted with three of the imaging stations  14  for exemplary purposes only. Alternative embodiments can include less, or more than three imaging stations  14 . The imaging stations  14  can each include an imaging device  20  suitable for acquiring images of the retina of a patient, as shown in  FIG. 1 . The imaging device  20  can be, for example, a digital camera such as a Nidek Fundus Camera. 
         [0031]    Each imaging station  14  can also including a computing device  22  communicatively coupled to the imaging device  20 . The computing device  22  can be any computing device, such as a desktop or notebook computer, capable of acquiring and storing digitized images from the imaging device  20 , and transmitting the digitized images to the data processing system  12  by way of the communications network  26 . 
         [0032]    The system  10  is depicted with two of the reading stations  16  for exemplary purposes only. Alternative embodiments can include less, or more than three reading stations  16 . Each reading station  16  can include a computing device  25  as shown in  FIG. 1 . Each computing device  25  is capable accessing the central data processing system  12  by way of the communications network  26 . The computing device  25  can be any computing device, such as a desktop or notebook computer, capable of providing a means for a physician or other individual to interface with the central data processing system  12  via web pages generated and served by the central data processing system  12 . 
         [0033]    The central data processing system  12  can include a suitable computing device such as a server  30 . The server  30  can comprise a processor such as a microprocessor  31 , and a bus  32  that facilitates communication between the microprocessor  31  and various other components of the computing device  22 , as shown in  FIG. 2 . 
         [0034]    The server  30  can also include memory  33 . The memory  33  can comprise a main memory  34  and a mass storage device  35 , each of which is communicatively coupled to the microprocessor  31  by way of the bus  32 . The main memory  34  can be, for example, random access memory. The mass storage device  35  can be, for example, a hard or optical disk. 
         [0035]    The server  30  can also include computer-executable instructions  35  stored on the memory  33 , as shown in  FIG. 2 . The computer-executable instructions  35 , as discussed below, can generate diagnoses of various retinal diseases based on inputs received from the imaging stations  14  and the readings stations  16 . Moreover, the computer-executable instructions  35  can include software that permits the server  30  to act as a web server. 
         [0036]    The server  30  can also include a user interface adapter  36  and a display adapter  37  communicatively coupled to the microprocessor  31  by way of the bus  32 . The server  30  can interface with the communications network  26  using a suitable communications device  52  such as a network card or modem. 
         [0037]    The central data processing system  12  can include suitable interface devices that allow operators, programmers, or other individuals to interact with the server  30 . For example, as shown in  FIG. 1 , the central data processing system  12  can include a keypad  38  and a mouse  40 , each of which is communicatively coupled to the user interface adapter  36  of the server  30 . The central data processing system  12  can also include a display device  42 , such as a liquid crystal display (LCD) screen or monitor, communicatively coupled to the display adapter  37  of the server  30 . 
         [0038]    Specific details of the server  30  are provided for exemplary purposes only. Computing devices having hardware and software architecture other than that described above can be used in lieu of the server  30 . 
         [0039]    The use of a single server  30  in the central data processing system  12  is specified for exemplary purposes only. Alternative embodiments can be configured with multiple servers. For example, alternative embodiments can include a first server that functions as a web server; a second server used for data storage; and a third server used for processing the inputs from the imaging stations  14  in the manner discussed below. 
         [0040]    Each computing device  22  of the imaging stations  14  can include a processor such as a microprocessor  61 , and a bus  62  that facilitates communication between the microprocessor  61 , various other components of the computing device  22 , and the imaging device  20  as shown in  FIG. 3 . 
         [0041]    The computing device  22  can also include memory  63 . The memory  63  can comprise a main memory  64  and a mass storage device  65 , each of which is communicatively coupled to the microprocessor  61  by way of the bus  62 . The main memory  64  can be, for example, random access memory. The mass storage device  65  can be, for example, a hard or optical disk. 
         [0042]    Each computing device  22  can also include a user interface adapter  66  and a display adapter  67  communicatively coupled to the microprocessor  61  by way of the bus  62 . The computing devices  22  can each interface with the communications network  26  and their corresponding imaging devices  20  using a suitable communications device  76  such as a network card or modem. 
         [0043]    Each imaging station  14  can also include suitable interface devices that permit the technician or other individual operating the imaging device  20  to interact with the associated computing device  22 . For example, as shown in  FIG. 1 , each imaging station  14  can include a keypad  68  and a mouse  70 , each of which is communicatively coupled to the user interface adapter  66 . The imaging stations  14  can each also include a display device  72 , such as an LCD screen or monitor, communicatively coupled to the display adapter  67  of the corresponding computing device  22 . 
         [0044]    Each computing device  25  can include computer-executable instructions  79  that are stored on the memory  63  and executed on the microprocessor  61 , as shown in  FIG. 3 . The computer-executable instructions  79  coordinate the display of the digital images and other information received from the imaging device  20 , and the transmission of the images and information to the central data processing system  12 . 
         [0045]    The computer-executable instructions  79  can also include web browser software that permits the technician or other individual operating the imaging device  20  to view the web pages served to the computing device  22  by the server  30 , and to initiate the transfer of the digital images and other information to the central data processing system  12 . 
         [0046]    Specific details of the computing devices  22  are provided for exemplary purposes only. Computing devices having hardware and software architecture other than that described above can be used in lieu of the computing devices  22 . 
         [0047]    Each computing device  25  of the reading stations  16  can include a processor such as a microprocessor  81 , and a bus  82  that facilitates communication between the microprocessor  81  and the various other components of the computing device  25  as shown in  FIG. 4 . 
         [0048]    The computing device  25  can also include memory  83 . The memory  83  can comprise a main memory  84  and a mass storage device  85 , each of which is communicatively coupled to the microprocessor  81  by way of the bus  82 . The main memory  84  can be, for example, random access memory. The mass storage device  85  can be, for example, a hard or optical disk. 
         [0049]    Each computing device  25  can also include a user interface adapter  86  and a display adapter  87  communicatively coupled to the microprocessor  81  by way of the bus  82 . Each computing device  25  can interface with the communications network  26  using a suitable communications device  76  such as a network card or modem. 
         [0050]    Each reading station  16  can also include suitable interface devices that permit the physician or other individual evaluating the images displayed on the reading station  16  to interact with the associated computing device  25 . For example, as shown in  FIG. 1 , each reading station  16  can include a keypad  88  and a mouse  90 , each of which is communicatively coupled to the user interface adapter  86  of the corresponding computing device  25 . The reading stations  16  can each also include a display device  92 , such as an LCD screen or monitor, communicatively coupled to the display adapter  87 . 
         [0051]    Each computing device  25  can include computer executable instructions  99  that are stored on the memory  83  and executed on the microprocessor  81 . The computer-executable instructions  99  can include web browser software  100  that permits the physician or other individual evaluating the retinal images to view the web pages served to the computing device  25  by the server  30  by the central data processing system  12 , and to provide inputs to the central data processing system  12  based on the evaluations. 
         [0052]    Specific details of the computing devices  25  are provided for exemplary purposes only. Computing devices having hardware and software architecture other than that described above can be used in lieu of the computing devices  25 . 
         [0053]    The system  10  can be used to diagnose retinal disease, such as diabetic retinopathy, in a patient in accordance with the exemplary method  200  depicted in  FIG. 5 . 
         [0054]    When performing the method  200 , one of the imaging stations  14  can be situated at a first location such as a mobile clinic or the office of a primary-care physician. The central data processing system  12  can be situated at a second location geographically remote from the first location. The reading station  16  can be situated at a third location, such as another physician&#39;s office, that is geographically remote from the first and second locations. The imaging station  14 , central data processing system  12 , and reading station  16  are described as being situated at three different locations for exemplary purposes only. The method  200  can be performed while the imaging station  14 , the central data processing system  12 , and/or the reading station  16  are co-located. 
         [0055]    Images of the patient&#39;s retina can be obtained by a technician or other individual capable of operating the imaging device  20 . 
         [0056]    The computer-executable instructions  79  stored on the server  30  of the central data processing system  30  can cause a main web page (not shown) to be displayed on the display device  72 . The main page can include an “Add Patient Information” prompt. The web page  250  depicted in  FIG. 6  can be served by the server  30  and displayed on the display device  72  when the technician responds to the prompt. The technician can input information concerning the patient&#39;s identity using prompts provided by this screen (step  202  of  FIG. 5 ). The technician can also enter information such as the type of diagnosis being made (such as diabetic retinopathy, macular degeneration, retinopathy of prematurity, etc.), and demographic and insurance-related information for the patient at this point. 
         [0057]    The technician can subsequently obtain medical data in the form of images of the patient&#39;s retina, such as ocular fundus images or scanning ocular images, using the imaging device  20  (step  204 ). The type and number of images acquired are dependent upon the type of diagnosis that will subsequently be performed using the images. For example, a total of fourteen images, seven for each eye, can be obtained when screening for diabetic retinopathy. A total of twelve images, six for each eye, can be obtained when a screening for hypertension, macular degeneration, and glaucoma is being conducted. A total to twenty-four images, twelve for each eye, can be obtained when a full diabetic retinal examination is being performed. Instructions concerning the type of examination can be provided to the technician by, for example, a physician who has referred the patient for the examination. 
         [0058]    The central data processing system  12  can provide guidance concerning the retinal images to be acquired by the technician. For example, the server  30  can serve the web page  251  shown in  FIG. 7  to the imaging station  14 . The web page  251  provides a graphical depiction of the specific locations at which retinal images are to be acquired for a screening for hypertension, macular degeneration, and glaucoma. 
         [0059]    The retinal images and corresponding patient information can be stored on a data base  71  residing in the memory  63  of the computing device  22  (step  206 ). The retinal images and patient information can subsequently be uploaded to the server  30  of the central data processing system  12  by way of the communications network  26 , using a suitable protocol such as file transfer protocol (FTP) (step  208 ). The information can be designated in the data base  71  as “uploaded” after the information has been successfully transmitted to the server  30 . 
         [0060]    The images and patient information can be uploaded at the end of each work day, along with images and information for other patients acquired during that day. The images and patient information can be uploaded at other times, e.g., immediately after the images have been acquired, in the alternative. The images and information can be deleted from the computing device  14 , for example, after a predetermined amount of time has elapsed, or when the memory storage space is subsequently needed for additional images and information. 
         [0061]    The retinal images and patient information transmitted to the central data processing system  14  from the computing device  22  can be stored in a data base  39  residing on the sever  30  of the central data processing system  14  (block  212 ). The images and patient information can subsequently be viewed and evaluated by an individual with sufficient training, such as a ophthalmologist (hereinafter referred to as a “reading physician”), using predetermined prompts and other guidance provided by the central data processing system  12 . 
         [0062]    The reading physician can be located at a location different than the location of the central data processing system  12 , and can access the central data processing system  12  via one of the reading stations  16  and the communications network  26  (step  213  of  FIG. 5 ). In particular, the reading physician can use the web browser of the computing device  25  of the reading station  16  to access the web site hosted by the server  30  of the central data processing system  12 . The reading physician can access an account stored on the data base  39  by, for example, inputting a user ID and a password in response to a prompt displayed on a home page (not shown) generated and served by the server  30 . 
         [0063]    The server  30  serves an initial web page  254  depicted in  FIG. 8  when the reading physician accesses his account (step  214 ). The initial web page  254  can include a list of all of the patients listed in the data base and associated with the reading physician. The initial web page  254  can also include information such as the name of the referring physician corresponding to each patient; the status (read or unread) of the data associated with each patient; the date on which the patient data was evaluated by the reading physician (if applicable); etc. The reading physician can view the initial web page  254  on the display device  92  of the reading station  16 , and can select a particular patient from the list of patients using the web browser of the computing device  25 . 
         [0064]    Upon selection of a particular patient by the reading physician, the server  30  serves the diagnostic web page  256  shown in  FIG. 9  (step  216 ). The diagnostic web page  256  includes one of the images of the patient&#39;s retinas acquired previously acquired and stored in the data base  39  on the server  30 . The diagnostic web page  256  also includes text that indicates various symptoms or conditions of the retina that should be evaluated by the reading physician when viewing the image, in view of the particular diagnosis that is being made. The computer-executable instructions  35  of the server  30  can be configured to automatically select and serve a particular set of diagnostic web pages corresponding to the particular diagnosis being made, based on the patient information sent to the reading station  16 . 
         [0065]    The symptoms and conditions associated with a particular diagnosis can be chosen, for example, based on state of the art and/or the current best practices in the relevant medical field, e.g., retinal opthamology. The symptoms and conditions can be chosen, for example, by one or more physicians or scientists considered to be an authority in the field. 
         [0066]    A box appears on the diagnostic web page  556  adjacent to the text denoting the symptoms or conditions that should be evaluated, as shown in  FIG. 9 . The reading physician can use the web browser of the computing device  25  to check the box if the condition or symptom described by the corresponding text is observed by the reading physician when viewing the retinal image being displayed (step  218 ). The text displayed on the diagnostic web page  256  thus prompts the reading physician to make certain observations regarding the image, and to provide inputs indicative of what the reading physician has observed by checking or not checking the corresponding boxes. 
         [0067]    For example, the diagnostic web page  256  depicted in  FIG. 9  prompts the reading physician to make observations relevant to a diagnosis of diabetic retinopathy. As indicated in  FIG. 9 , the physician is prompted to determine whether the following symptoms or conditions are visible in each image: microaneurism only (MA); microaneurism/hemorrhage (HMA); intraretinal microvascular abnormality (IRMA); venous beading (VB); hard exudate (HE); clinically significant macular edema (CSMA); neovascularization of disc (NVD&lt;10a, NVD&gt;10a); neovascularization elsewhere (NVE); preretinal hemorrhage (PRH); vitreous hemorrhage (VH); vitreous hemorrhage with no retinal details (DENSE VH); traction retinal detachment (TRD), etc. The reading physician checks a box located next to each symptom or condition if the reading physician observes the condition or symptom in the image. 
         [0068]    The particular conditions and symptoms listed on the diagnostic web page  256  are dependent upon, and will vary with the specific type of retinal disease or other medical condition being diagnosed. 
         [0069]    Once the reading physician has made each of the prompted observations and provided the corresponding inputs, the reading physician can advance to the next image in the set of retinal images for the patient by responding to an “advance” prompt on the initial web page  252  (step  220 ). Another diagnostic web page  256  containing the next image is served by the server  30  and appears on the display device  92  of the reading station  16  at this point. This diagnostic web page  256  also includes text prompting the reading physician to make various observations of the image, and boxes that the reading physician can check based on the observations. 
         [0070]    The above process can be repeated until the reading physician has observed and provided inputs concerning each of the images in the set of images for the patient (step  221 ). 
         [0071]    The reading physician can subsequently prompt the server  30  to generate a diagnosis and recommendations by using the web browser to click on a tab labeled “interpretation” on the web page containing the final image in the set. The diagnosis and recommendations are generated by algorithms incorporated into the computer-executable instructions  35  (step  222 ). The algorithms are capable of interpreting each possible combination of checked and unchecked boxes for the series of retinal images as corresponding to a particular diagnosis and an associated recommendation. 
         [0072]      FIG. 12  depicts an exemplary algorithm that can be used to generate diagnoses and corresponding recommendations relating to diabetic retinopathy, based on the observations prompted by the diagnostic web pages  256  corresponding to each of the seven images acquired for each eye.  FIG. 13  is an exemplary algorithm that can be used in the alternative to the algorithm depicted in  FIG. 12 , to generate diagnoses of retinopathy of prematurity based on observations prompted by an associated diagnostic web page (not shown). 
         [0073]    The algorithms, and the above-noted observations that are used as inputs to the algorithms, can be generated based on inputs from one or more physicians, scientists, or individuals considered to be authorities in the relevant field, and can be updated on an as-needed and/or periodic basis. This helps to ensure that the diagnoses produced using the algorithms reflect the state of the art and the current best practices in the corresponding medical field. 
         [0074]    The computer-executable instructions  35  can be configured to cause the server  30  to generate a series of web page  260  containing a preliminary report. A blank, i.e., not yet filled in, preliminary report is depicted in  FIG. 10 . The preliminary report contains the findings of the diagnostic process, the diagnosis, and the recommendations (step  223 ). The preliminary report can be accessed by the reading physician from the reading station  16 , and can be displayed on the display device  72 . The web pages  260  can be served automatically, immediately after the preliminary report is generated. Alternatively, the web pages  260  can be served in response to a prompt generated by the reading physician from the reading station  25 . 
         [0075]    The reading physician can review, edit, and approve the report (step  228  of  FIG. 5 ). The reading physician can approve the report by clicking on a tab on the report labeled “approve,” using the web browser of the computing device  25 . A final report  262  is subsequently generated and saved to the data base  39 , the corresponding patient data is marked as “read,” and the web page listing the patients associated with the reading physician and having unread data in the data base is once again displayed on the display device  92  (step  230 ). A blank final report is depicted in  FIG. 11 . 
         [0076]    The final report  262  can be sent to the referring physician in electronic or paper form (step  230 ). The final report  262  can sent on an automatic basis, immediately after being generated. Alternatively, a system administrator can send the final report  262  at a later time, e.g., at the end of the day together with other reports. The final report  262  can be sent using a suitable means such as e-mail, fax, regular mail, or overnight courier, pre-selected by the referring physician. 
         [0077]    The computer-executable instructions  35  can also be configured to cause the central data base  12  to send billing charges and information a third party billing system. The transmission of billing information can occur automatically, or upon an input of the system administrator. The billing information, including information relating to the patient&#39;s health insurance, can be stored in the data base  39 . 
         [0078]    The computer-executable instructions  35  can be configured to facilitate general maintenance of the system  10 , and to monitor the status of the server  30 , the health of the database  39 , and usage of the system  10 . These features can be implemented using, for example, MYSQL® open source software. 
         [0079]    The computer-executable instructions  35  of the server  30  can be configured to cause the server  30  to generate reminders for referring physicians and/or patients concerning follow up examinations; and reports relating to the frequency of use of the system  10  by each referring physician. The computer-executable instructions  35  can also be configured to cause the server  30  to generate summary reports for the reading physicians. These summary reports can include, for example, information relating to the transmission of the reports generated by the reading physician, the number of reports generated by the reading physician per session or per hour, and payments made to the reading physician. 
         [0080]    The computer-executable instructions  35  can also be configured to cause the server  30  to generate invoices for reading physicians, technicians, usage fees, etc. The reminders, reports, invoices, etc. can be sent electronically via e-mail or another suitable electronic medium; alternatively, hard copies can be generated and sent via regular mail or courier. 
         [0081]    The algorithms embedded in the computer-executable instructions  35 , as discussed above, can cause the server  30  to generate diagnoses of medical conditions by processing the observations in accordance with the state of the art and/or best practices in the relevant medical field. Moreover, the algorithms can be updated as the state of the art and/or best practices evolve or otherwise change. The diagnoses generated using the system  10  and method  200  can thus be based on the best, most up-to-date medical information available at the time the diagnoses are made. 
         [0082]    Moreover, diagnoses generated using the system  10  and the method  200  can have relatively high levels of accuracy, repeatability, and reliability due to the use of a pre-determined set of algorithms that (i) prompt the reading physician like a checklist to make specific observations concerning the medical data acquired from the patient, and (ii) generate diagnoses based on the observations. The algorithms can thus help to compensate for the lack of direct physical interaction between the reading physician and the patient. 
         [0083]    It is believed that the use of the system  10  and method  200  can make the diagnostic process more efficient by reducing the time and effort needed to generate diagnoses for each patient. A reading physician can thus generate diagnoses for a larger number of patients during a given time frame than would otherwise be possible. Moreover, by prompting observations and automatically generating diagnoses based on the observations, the system  10  and method  200  can potentially allow an individual with a comparatively low degree of education or training, e.g., a nurse or a physician&#39;s assistant, to generate diagnoses that would otherwise have to be generated by an individual with a higher degree of training, e.g., a physician. The use of the system  10  and method  200  can thus potentially increase the availability of medical care to patients that otherwise would not have access to such care. 
         [0084]    The foregoing description is provided for the purpose of explanation and is not to be construed as limiting the invention. Although the invention has been described with reference to preferred embodiments or preferred methods, it is understood that the words which have been used herein are words of description and illustration, rather than words of limitation. Furthermore, although the invention has been described herein with reference to particular structure, methods, and embodiments, the invention is not intended to be limited to the particulars disclosed herein, as the invention extends to all structures, methods and uses that are within the scope of the appended claims. Those skilled in the relevant art, having the benefit of the teachings of this specification, can make numerous modifications to the invention as described herein, and changes may be made without departing from the scope and spirit of the invention as defined by the appended claims.