EP1304956A4

EP1304956A4 - Online medical evaluation and treatment system, method and portal

Info

Publication number: EP1304956A4
Application number: EP01954984A
Authority: EP
Inventors: Jesse J Hade; Steven W Ainbinder; Bret M Schneider
Original assignee: HEALTHSHORE Inc
Current assignee: HEALTHSHORE Inc
Priority date: 2000-08-02
Filing date: 2001-07-25
Publication date: 2004-04-14
Also published as: AU7719501A; CA2389257A1; WO2002009580A1; EP1304956A1

Abstract

An online medical evaluation and treatment system (10) includes a patient interface (20), a physician interface (30) and diagnostic tools (52-58) to gather and sort information sent from the patient and automatically generate candidate diagnoses.

Description

ONLINE MEDICAL EVALUATION AND TREATMENT SYSTEM,

METHOD AND PORTAL

BACKGROUND OF THE INVENTION

1. Technical Field The present invention is directed to the field of medical software systems, methods and electronic portals. More specifically, the invention provides a comprehensive system for enabling evaluation and treatment of patients by certified medical personnel via a data network, such as the Internet.

2. Description of the Related Art Medical software system web sites are known in this field. These systems, however, suffer from many disadvantages that have limited their utility from the perspective of a patient, a physician (or other qualified caregiver) and also a healthcare management organization.

Example medical software systems use input from a doctor (or other medical personnel) to create a database entry that contains patient specific data. These medical software systems typically employ "smart agents" to suggest questions (or follow-up questions) based on answers to previous questions. Many of these "smart agents" are simply logic trees that branch to other questions based on the answer to a particular question. Once the system has traversed the logic tree, it then returns a diagnosis that is generally used as a check against the diagnosis the physician has independently determined.

Within these systems, any single question that is misunderstood will illicit an incorrect response and cause the system to diverge from the correct diagnosis.

Another known type of medical software system eases the process of inputting data into a centrally stored, universal database. The creation of a universal database for storing patient data from numerous treating physicians located at different medical facilities is a goal of the healthcare industry. Such a database would help physicians diagnose symptoms that are prevalent in a patient's medical history. The database structure also minimizes the physical space required for records storage since hard copy (paper) records can be saved digitally. These types of universal database systems are implemented either by directly scanning the paper records of patient folders into the database or by incorporating a digital assistant into patient visits by the physician or other medical personnel. The digital assistant could be, for example, a PDA, laptop computer, handheld computer, or digital voice recorder.

The digital assistants used with this type of system are easily configurable to accept input from a physician during an patient visit. Within this system, however, the doctor is still required to input the necessary patient information gathered during the visit. This makes the physicians job more difficult because he first must gather the information and then record it in a structured format. Thus, the physician must spend a longer period of time with each patient or use an assistant to record the data. Both of these solutions result in added cost to healthcare management organizations and ultimately the patient.

Another type of known medical software system connects patients to a physician's office or hospital through a network connection. The network connection can be a data network, such as the Internet, or a phone network where a patient places a telephone call to a central location. These systems are designed to access patients who are remotely located from medical care, but who have non-serious medical conditions. By using this type of telemedical service, the remote patient can receive a medical diagnosis from a medical professional that the patient otherwise could not access. Interaction between the medical personnel and the patient in these telemedical systems is typically accomplished through e-mail, instant chat, videoconferencing or Internet phone.

SUMMARY OF THE INVENTION

An online medical evaluation and treatment system includes a patient interface, a physician interface and diagnostic tools to gather information from the patient and to generate diagnoses for review by a treating physician. Using this system, the patient enters information about a medical condition through the patient interface. The diagnostic tools evaluate the information provided by the patient, generate further questions based on the answers to previous questions, and create a list of possible diagnoses, referred to as a differential diagnosis. A treating physician then enters the physician interface, after the patient has entered the pertinent medical information, to review a summary report within a patient file and then to diagnose the medical condition of the patient. Importantly, the physician does not have to be present as the data is gathered from the patient, freeing the physician from gathering and/or inputting information into the system, and, thus providing a more time- efficient system for delivering medical treatments.

The diagnostic tools first gather, sort and order the information from the patient. Then, the diagnostic tools search a knowledge base for medical conditions that reach a predetermined level of overlap of the known symptoms for the medical condition as reported in the database and the reported symptoms gathered from the patient. Once the list of medical conditions that meet this criteria are gathered, then any symptoms that are present in the medical conditions, but have not been addressed through questions to the patient, are gathered, presented to the patient, and then the patient's answers are recorded so that the diagnostic tools can determine a set of candidate diagnoses.

According to one aspect of the present invention, an online medical system comprises a patient interface, a physician interface and server applications. The patient interface is configured to display and record medical information of a patient. The physician interface is configured to display a summary of the medical information recorded from the patient interface. The server applications are configured to query the patient interface and evaluate the answers to the queries such that the summary includes a differential diagnosis. The data gathered during this process can then be sorted and stored in a resident program or exported to a third party medical record.

According to another aspect of the present invention, an online medical evaluation system comprises a patient interface, a physician interface, and a data drilling module. The data drilling module is configured to generate queries which are sent to the patient interface, and then summarize results of the queries in the physician interface. The queries include graphical medical data.

According to another aspect of the present invention, a method of treating a patient includes the steps of: (1) querying a patient interface for general health symptoms; (2) determining if any general health symptoms answered during the query are abnormal. (3)building a differential diagnosis based on the abnormal symptoms of the general health query; (4) displaying the differential diagnosis to a physician using a physician interface; (5) the physician determining a diagnosis and (6) receiving the diagnosis from the physician. A list of treatments is then displayed in response to the diagnosis. The physician determines a treatment which is then displayed to the patient via the patient interface.

It should be noted that these are just some of the many aspects of the present invention. Other aspects not specified will become apparent upon reading the detained description of the drawings set forth below.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a system diagram of an online medical evaluation and treatment system according to a preferred embodiment of the present invention;

FIG. 2 is a detailed diagram of certain software modules shown in FIG. 1; FIG. 3 is a logical flow chart setting forth the preferred steps enabled by the patient interface of the present invention;

FIG. 4 is a logical flow chart setting forth the preferred steps enabled by the physician interface of the present invention; FIG. 5 is a detailed diagram of the evaluation engine of FIG. 1 ;

FIG. 6 is a detailed diagram of the reference database of FIG. 1;

FIG. 7 is a logical flow chart setting forth the preferred steps enabled by the server applications of the present invention;

FIG. 8 is a graphical depiction showing an example layout of a differential diagnosis display generated by the server applications and viewed through the physician interface;

FIG. 9 is a graphical depiction showing an example layout of a possible treatments display generated by the server applications and viewed through the physician interface; and FIG. 10 is a graphical depiction showing an example of a physician report sent to a patient after a diagnosis and treatment regimen have been determined.

DETAILED DESCRIPTION OF DRAWINGS Turning now to the drawing figures, FIG. 1 is a system diagram of an online medical evaluation and treatment system 10 according to a preferred embodiment of the present invention. Through the system 10, an external user

(i.e., patient 20) can access a medical diagnosis and treatment system 10 that implements time leveraging strategies to minimize physician-patient interaction time. The patient first interacts with the system 10 to define a medical condition. A physician 30 can then interact with the patient 20 once the medical condition has been, at least partially, defined. Using the system

10, the physician 30 decides upon a diagnosis and prescribes a treatment.

Once the physician 30 has prescribed a treatment to the patient 20, then the treatment protocol can be sent to the patient 20 and also to a pharmacy system 34. The pharmacy system 34 can then fill any prescribed medication for the patient 20. Through the system 10, the pharmacy system 34 can fill a prescription for a patient 20 automatically or manually selected based upon the patient's location. In this manner, a patient 20 can begin treatment for an ailment without visiting a doctor's office.

The system 10 is connected to the patient 20, the physician 30, and the pharmacy 34 through a data communication network 12, such as the Internet. The system 10 is preferably implemented as an online web site for communicating information over the Internet. It should be understood, however, that the principles of the present invention are not limited to any particular technological implementation, and could be implemented over other types of communication networks.

The web site 10 includes an entry portal 40. The entry portal 40 is coupled to a pair of interfaces, a patient interface 42 and a physician interface 44. Each interface 42 and 44 includes software tools that the user operates to navigate the web site 10. The interfaces 42 and 44, in turn, are coupled to server applications 46. The patient interface 42 is coupled to a medical history database 48 and an evaluation engine 50. The medical history database 42 stores the medical history of patients. The evaluation engine 50 includes an intelligent data drilling (IDD) module 52, a diagnostic numbering and assessment module (D_XNA) 54, and a treatment module 56. These modules 52-56 support the physician in preparing a diagnosis by acquiring, sorting, flagging and presenting data to a physician 30 through the physician interface 44. The physician interface 44 is also supported by a reference database 58, which may include general medical research information, statistical samples, case studies of treatment regimens, physician practices, photographs and illustrations of normal and pathological anatomy, sound recordings, video recordings and relationships of symptoms to diseases. Information from the databases 48 and 58 are stored within the system 10, and are updated through external databases that are connected to the system 10 through external networking components 250-256.

A set of external networking components 250-256 are coupled to the databases 48, 58 for communicating information to facilities that could benefit from the information contained within the system 10. The external networking components 250-256 include a data record interpreter 250, an external recording system 252, a network 254 to transmit the data to the external recording system 252, and an aggregate database 256 to store the information gathered from the external recording system 252. The system 10 is preferably stored on a web server. The server preferably stores the software interfaces 42 and 44 as web pages accessible to users. The web pages of the interfaces 42 and 44 are communicated to users 20, 30 through standard Internet protocols for communicating web content, such as HTTP, TCP/IP, S-HTTP, SSL, etc. The users can thus interact with the system 10 by operating standard web browser software on their computers 20, 30, such as Microsoft's Internet Explorer ® or Netscape's Communicator ®.

A user 20 or 30 enters the system 10 through the entry portal 40, and is then directed to one of the distinct graphical user interface modules 42, 44, depending on whether the user is a patient or physician. This directional step is preferably accomplished by a graphical user interface that allows the user to select the user's class (e.g., patient or physician), and that then verifies the user's identity by querying for a user name and password. Alternatively, however, the directional step may be accomplished automatically, such as by reading information stored locally on the user's computer 20. For example, the system 10 may deposit a "cookie" on the user's computer during an initial registration process, where the "cookie" contains a profile of the user that includes information such as the user's class, identity and password. When the user accesses the system 10, the identity and password information are then automatically transferred to the system 10, thereby automating the login process and directing the user to the proper interface.

The physician interface 44 is the user interface (UI) that a physician navigates after he has passed through the entry portal 40. The physician interface 44 displays choices pertaining to the workload for the physician. For example, the physician may need to research a condition, interview a patient, review a patient's history, or make a patient diagnosis. The physician interface 44 displays a list of patients awaiting attention in a virtual waiting room and any other responsibilities the physician 30 needs to address. The physician 30 accomplishes these tasks through the physician interface 44 by using the tools of the reference database 58 and the evaluation engine 50 of the server applications 46. Once the research is completed, the physician 30 can then interact with a patient 20 who is using the patient interface 42 through the physician interface 44. The patient interface 42 is the UI that a patient navigates after he has passed through the entry portal 40. The patient interface 42 displays choices pertaining to the nature of the visit. For example, the patient 20 may visit the system 10 to update his personal medical history records, schedule an appointment or referral for a non-urgent concern, meet an appointment or referral that was previously scheduled, or seek immediate care for a medical problem. For each of these cases, the patient 20 inputs data into the system 10 prior to receiving consultation time with a physician, thereby allowing multiple patients of a single physician to actively seek consultation at the same time. Within both the physician interface 42 and the patient interface 44, links are formed to the server applications 46 that provide the functional interaction between the system 10 and the physician 30 or patient 20.

The server applications 46 are stored in the server as functional applications, such as the evaluation engine 50, and as data storage applications, such as the databases 48, 58. The server applications 46 generate the content that is sent to the users 20, 30 through the interfaces 42, 44. The content of the web pages is generated using coding schemes that may include HTML, XML, Java, Javascript, VBscript, ASP, or other standard web-based coding paradigms for displaying web content through a web browser and for communicating information back and forth to users 20, 30 and to the server applications 46.

The medical history database 48 stores medical information about a patient 20 within a patient record. The database 48 is organized hierarchically. The hierarchical structure means that a patient 20 can access only the data relevant to him. This is important because patient confidentiality is strictly kept within the site. For example, each patient might be identified by a certain code (i.e., a social security number, an e-mail account, or a sequentially generated number) that is assigned once the patient has chosen a user name and password. Whenever that patient enters the site 10 again, he will only have access to the information contained within the structure assigned to that code. By linking a medical history to a static data point, like SSN or e-mail account, a user re-entering the site having forgotten a username and password previously chosen can still access the correct medical history once the static data point is determined to be accurate. Data stored in the medical history database 48 is used in the evaluation engine 50 to generate questions to send to the patient interface 42.

The evaluation engine 50 retrieves the data record for the patient 20 from the medical history database 48. The evaluation engine 50 compiles the data record to determine pertinent questions that could be asked of the patient 20 through the LDD 52 and the D_XNA 54 modules. The IDD module 52 evaluates the answer to a question and determines if more questions should be asked via means such as branched chain logic. Within the D_XNA module 54, a set of diagnoses are coded in accordance with their respective symptom profiles. By checking symptoms documented by the IDD module 52 against the symptom profiles for different candidate diagnoses in the D_XNA module 54, an additional list of information to be gathered by the LDD module 52 is generated. The additional information can then be used in the D_XNA module 54 to validate or invalidate the candidate diagnoses. The D_XNA module 54 evaluates the answers to all the questions to determine what differential diagnosis can be made from the data gathered. For example, if the medical history database 48 contains information indicating that the patient 20 has had an appendectomy, the LDD module 52 will not question the patient 20 about problems and symptoms that are only applicable to appendicitis. Similarly, the D_XNA module 54 rules out appendicitis from the list of differential diagnoses. The information stored within the medical history database 48 provides a background for the IDD module 52 and the D_XNA module 54 to generate questions for the patient.

Once the physician 30 decides on a diagnosis from a list of differential diagnosis generated by the system 10, the treatment module 56 evaluates the pertinent data from the medical history database 48, as well as data from the reference database 58 to determine a proper treatment regimen. The treatment module 56 interprets data from the medical history database 48 to suggest possible treatments for the diagnosis selected by the physician 30. For example, a patient 20 that is allergic to penicillin should not be treated with penicillin, but may respond to ciproflaxacin. Once the diagnosis and treatment is made, a reference to the pertinent data gathered through the evaluation engine 50 for this particular patient visit is entered into the medical history database 48 and the reference database 58 for use in subsequent visits.

The reference database 58 stores medical data that is generally available to practicing physicians. In general, the reference database 58 is a compilation of reference material including statistical samples of patients, video clips, sound clips and photographs that is used to evaluate a patient's symptoms against typical symptoms stored within a symptom list for a specific disease. In this comparison, a physician can diagnose the patient 20 by evaluating how closely the symptoms match the symptom list. The database 58 can be built from known sources, such as MedLine or PubMed, and may also be built from data that is specific to the local region. For example, if a certain region has a current outbreak of the flu, for which a specific treatment is efficient at curing, the physician can find this information within the reference database 58. The reference database 58 varies from the medical history database 48 both in structure and in content. The medical history database 48 contains individual patient data that is hierarchically structured such that a patient can only access his own personal information. The reference database 58, by distinction, is structured such that a physician 30 can access data by searching any of a number of categories. The physician might search for a typical symptom or he might search for all symptoms associated with a certain disease. The physician is thus able to search for additional diagnoses if the diagnoses suggested by the evaluation engine 50 are too complex, or there are too many pertinent negatives (i.e., symptoms that suggest a diagnosis can not be correct) found within the diagnosis.

For example, if a patient is diagnosed with chicken pox because of hive-like bumps on the skin, but has previously had chicken pox the physician 30 might review the literature and photographs of skin lesions within the reference database 58 to possibly diagnose a more exotic disease, such as small pox. Such a disease might not be entered within the evaluation engine 50 since small pox is believed to be eradicated. Since the literature contained within the reference database 58 contains historical data, pertinent symptoms can be determined from examining the results of a query for small pox within the reference database 58. If the diagnosis then became small pox, this data could be stored in the reference database 58 as a recent diagnosis, and would also be stored in the medical history database 48 under the patient's record. In this manner, the medical history database 48 stores patient-specific data and the reference database 58 stores general medical information. Both of these databases 48 and 58, however, can be appended by actions taken by the physician 30 and the patient 20. Once the records in the databases 48 and 58 are stored within the system 10, it may be advantageous to export the records to external databases that are accessible at local hospitals, medical research facilities, or other treatment facilities. Exportation of the records is performed by the external networking components 250-256. The external networking components 250-256 are configured to isolate records for exporting, format the records into readable forms, and download information that could be useful for the physicians 30 into the system 10 or upload information from the system 10 to an external database. The external networking components 250-256 are configured to communicate with databases external to the system 10. This communication is implemented through the data record interpreter 250. The data record interpreter 250 takes the information from one database source (either the databases 48 or 58 or the aggregate database 256) and orders it so that it is similar in structure to the receiving database (the other of databases 48 or 58, or aggregate database 256).

For example, the system 10 may upload patient information to the aggregate database 256. The data record interpreter 250 may first remove personal information from the records from the medical history database 48 so that personal information is not shared unless necessary. The data record interpreter 250 sends the information from the database 48 through the network 254 to the external recording system 252. The external recording system can be an interface that detenriines if the information contained within the record is useful to users of the aggregate database 256. If the information is useful, then the record is stored in the aggregate database 256. The aggregate database 256 can then manipulate the record to include the record into statistics contained within the database, keep the record as a case study, or, in the case of the aggregate database 256 being hosted by a hospital, use the information as the background medical history when the same patient is taken to the hospital. The exportation of the medical information from the system 10 can save time when the patient's medical history does not need to be re entered at a hospital, serves as a research tool, and serves as a learning tool for other physicians looking for case studies.

The system 10 may also download information from the aggregate database 256. For example, if a patient 20 has recently undergone a surgery, 5 the system 10 may search for an aggregate database 256 (such as the database of the admitting hospital for the surgery) to retrieve the records from the surgery. The data record interpreter 250 would then generate a query to retrieve the information through the interface of the external recording system 252. The record would be retrieved through the aggregate database 256 and

L0 sent through the network 254 to the data record interpreter 250. The data record interpreter 250 then formats the record to comply with the database structure of the medical history database 48. The record of the surgery is then stored within the medical history database 48.

FIG. 2 is a detailed diagram of the patient interface 42, the physician

L5 interface 44, and the server applications 46 shown in FIG. 1. This figure shows the processes of data entry in the patient interface 42, data manipulation in the server applications 46, and data summary in the physician interface 44.

The patient interface 42 is initialized 60 when a patient 20 enters the patient interface 42. Data is then entered by the patient 20 through one of

20 three entry modes: (1) an unstructured data entry mode 62; (2) a graphical data entry mode 64; and (3) a structured data entry mode 66. The unstructured data entry mode 62 collects data that is not confined to predetermined answers. For example, the patient may be asked to generally describe the ailment in a few sentences. The graphical data entry mode 64 is presented

25 through a graphical interface that the patient 20 can manage to focus the diagnostic discussion to a particular body region. The graphical interface preferably includes figures representing regional body portions and figures that include very detailed schematics. The structured data entry mode 66 includes questions where the patient chooses from a list of predetermined 0 answers. For example, the patient 20 may be discussing his diet and may choose from a list that included: meats, vegetables and dairy; no red meat; vegetarian with dairy; vegetarian non dairy; or vegetarian with dairy and fish. The patient 20 may then describe his diet by choosing one of these predetermined categories. Each of these data entry modes 62-66 can query the patient 20 individually or combine certain aspects of different entry modes to query the patient.

After the patient passes through the entry portal 40, the patient interface 42 is initialized 60 by recalling the data that the patient previously entered into the site 10 and which is stored in the medical history database 48 and by configuring the interface 42 to match that data. For example, if the patient 20 is male, the system 10 would load male figures into the graphical entry mode 64. Similarly, other graphical displays that depict specific figures that are appropriate for the specific patient 20 can be displayed, such as wheel- chaired figures or figures having certain disabilities. The system 10 also loads the patient data from the medical history database 48 during initialization so that questions will not be redundant. If this visit is the first visit of the patient 20, then the initialization step 60 queries the patient 20 for family history and personal medical history information. In subsequent visits, these background queries are not repeated. The interactive patient interface 42 then proceeds to query the patient regarding the specific medical reason for the visit using the entry modes 62-66 to collect data.

Initially, the system 10 presents symptomatic questions that broadly define the problem and then narrowly focus in on the particular medical illness. For example, when a patient enters the site because of an illness, the unstructured data entry mode 62 may first ask the patient 20 to describe the illness in a brief one or two sentence statement. The graphical data entry mode 64 may then display a picture of a body that the patient can manipulate in order to pinpoint the particular area of the body which may be causing pain. Finally, a set of structured questions presented through the structured data entry mode 66 can focus the inquiry on the types of pain, frequency and how long the pain lasts. Other questions could arise such as changes in daily routine, medications taken, tone and color of the affected region, etc. The use of the structured data entry mode 66 enables very detailed questions.

The structured data entry mode 66 queries the patient 20 for information by providing a structured list of answers to a question. The structured list may contain choices for yes and no, or a series of choices where the patient 20 chooses at least one answer. For example, a patient 20 who complains of difficulty breathing might be asked, "Is your cough productive (produce sputum)?" Possible answers are "yes", "no" or "I don't know." If the answer is "yes," then the next question could be, "What color is the sputum?" Answers for this question could be: yellow, white, clear, red with blood, or pink and frothy. Most likely, this question will also have a single answer. But a question such as "When does your shortness of breath occur?", may require the patient 20 to choose any or all of these answers: sleeping, active, resting. Since the structured questions may be answered with one or more answers from a list, the structured data entry mode 66 presents the choices in a manner consistent with the ability to choose just one, or many answers from the list. This structured list thus could be presented to the patient 20 through pull down boxes, radio buttons, check boxes or other structured means. The patient 20 then chooses the best answer from this structured list. The answer is then used to generate the next question, as shown above in the sputum questions. The question can either be on the same topic or on a different topic based on the previous answer. Through the use of the structured data entry mode 66 the patient 20 can choose an answer from a standardized list instead of trying to create his own descriptive terms.

Similar to structured data entry mode 66, the graphical data entry mode 64 can display a series of pictures as a structured list. The standardized choices and use of pictures to describe the question reduces vernacular terms that a patient 20 might use and replaces the vernacular terms with standardized terms that physicians use to describe symptoms and conditions. The graphical data entry mode 64 can be used to display pictures of ailments. For example, if a patient 20 is complaining of a skin rash, the graphical data entry mode 64 could include pictures of common types of rashes, as shown on other patients, or as a medical diagram. Similar to the structured data entry mode 66, the graphical data entry mode 64 thus can provide descriptive graphical data that the patient 20 can choose instead of asking a patient 20 for descriptive terms.

For example, a patient 20 may have a raised irritation on the skin. Possible diagnoses could be a cyst, a blister, or a pustule such as acne. By showing pictures of each of these skin ailments to the patient 20, the system 10 can differentiate the three ailments more quickly than a set of questions could. The patient 20 would then realize a cyst is an elevated, encapsulated lesion, a blister is a vesicle that can be greater than 1 cm in size and is generally filled with a clear liquid, and acne is similar to a blister but filled with a purulent fluid.

The unstructured data entry mode 62 includes questions that seek descriptive terms or phrases that a physician 30 can interpret. Most of the questions within the unstructured data entry mode 62 are used to validate the answers provided in the structured and graphical data entry modes 64 and 66. The unstructured answers are also searched for terms that can be used to suggest certain types of questions. For example, a patient 20 complaining of a rash would generally use words such as "skin," "rash," or "itchy" as terms in a short description of the ailment. The system 10 would interpret these words and then compile questions directed to the integumentary system. Another form of data that may be entered through the unstructured data entry mode 62 includes physiological data captured at the location of the patient. The physiological data can be gathered through the use of a remote medical diagnostic tool 68. The remote medical diagnostic tool 68 could be, for example, an EKG monitor that monitors the electrocardiographic signal of the heart. The output of the diagnostic tool 68 could be coupled to the computer of the patient 20 through a serial port, USB port, or any other type of connection. The EKG would represent raw data that could be used by the system 10 to diagnose a heart condition. The data could be examined and/or integrated by the system 10 in order to generate questions, or so that the raw data can be displayed to the physician. Finally, unstructured data can be input into the system 10 through the diagnostic tool 68 via a sound file. The patient 10 may record a cough, or some other sound, through a microphone that can then be entered into the site through the unstructured data entry mode 62. The data gathered through the data entry modes 62-66 is passed to the server applications 46 for examination and storage.

The server applications 46: (i) process and store the data passed from the patient interface 42; (ii) communicate back to the patient interface 42 with additional questions, and (iii) compile summary information for the physician interface 44. The server applications 46 include an interpretation module 70 configured to translate unstructured data from the patient interface 42 into structured data. The medical history database 48 and the reference database 58 store the data from the patient interface 42 and the interpretation module 70. The IDD module 52 and the DxNA module 54 process the information from the patient interface 42 and the databases 48 and 58. The IDD module 52 also queries the patient interface 42 with additional questions. The DxNA, IDD and medical history database modules are also responsible for generating the summary information for the physician interface 44. Finally, the treatment module 56 processes information from the databases 48, 58 to determine treatment protocols.

The medical history database 48 is structured to receive structured data from either the structured data entry mode 66 or the graphical data entry mode 64 from the patient interface 42. Unstructured data captured through the unstructured data entry mode 62 first passes through an interpretation module 70 which analyzes the unstructured data and reduces it to a structured data form that is fed into the medical history database 48. For example, if the patient is asked to describe the chief complaint for the visit, and the answer given is, "Something is wrong with my eyes, they water a lot," a structured entry to the medical history database 48 that corresponds to this unstructured input might be, "Complaint: Watery eyes." This structured entry can be both a title for the complaint, and a beginning point to start questioning the patient 20.

If the patient 20 also had a diagnostic tool 68 for measuring sensitivity of the eye to light, then the patient may also input his eye's response to light. This responsive input could be a video clip, such as an MPEG, of changes in iris size based on a known lumen source. The interpretation module 70 may then determine if the eye is not responding normally to the light source by examining and analyzing the data contained within the video clip. The structured information sent to the medical history database 48 in response to this unstructured input may then be "an abnormal response to light" instead of the raw data of the MPEG. In this manner the interpretation module 70 can process textual unstructured data as well as data from diagnostic tools 68. The structured data can then be saved in the medical history database 48 and passed to the IDD module 52 or the D_XNA module 54. Furthermore, it may be necessary to store the unstructured data. The database 48 can link to the files storing unstructured data, or cells within the database 48 may be configured to handle the unstructured data.

The IDD module 52 retrieves data from the medical history database 48 and the reference database 58 to determine pertinent questions for the patient 20. The information gathered from the medical history database 52 is primarily the background information entered during the initialization step 60, as well as information from any prior visits to the system 10 for medical treatment. The LDD module 52 begins with a set of general questions. These general questions seek to define, in the broadest sense, the health problem of the patient. For example, the IDD module 52 may initially generate questions to determine the frequency and magnitude of the health problem. Example general questions could be:

1. Is this the first time this problem has occurred? (Yes/No)

2. Did you receive medical treatment the last time it occurred? (Yes/No)

3. What was the treatment? (Pull down box of medications and treatments)

4. The onset of the problem began (hours/days/weeks/months) ago.

5. The problem occurred at: (Work/Home/Traveling)

6. Are your symptoms (Intermittent/Constant)

7. How frequently does this problem occur? Per (minute/hour/day/week/month)

8. Is there a variation in symptoms between attacks(yes/no)

Once the patient 20 answers question 1, then he is asked question 2 only if the answer to question 1 is "no." Similarly, question 3 is asked only if the answer to question 2 is "yes." If the answer to question 1 is "yes," or the answer to question 2 is "no," then the JDD module 52 generates question 4. If the answer to question 6 is "intermittent," then the IDD module 52 generates questions 7 and 8. This process of drilling down through questions may continue for a plurality of levels via means such as branched chain logic. The answers to these questions are stored in the medical history database 48 as the patient 20 answers them.

The answers provided in response to these levels of questions are stored in a similar structure as the structure that stores the questions within the LDD module 52. Thus the medical history database 48 is structured so that if the answer to question 1 is "-no," then a layer within the patient's database record is created to store the answer to question 2. Once the general questions are exhausted, the IDD module 52 begins reviewing physiological systems that are related to the problem. Such system questions include general system questions that determine the general, current, overall health of the patient 20, and specific system questions that determine the specific characteristics of systems such as skin, gastro-intestinal, or urological, based on the chief complaint.

The IDD module 52 generates general system questions regarding the general state of health of the patient prior to the current medical condition. These questions put the health of the patient 20 into context. For instance, it is important to know if a patient 20 has recently been exposed to infectious or contagious diseases, or has traveled abroad. Other general system questions that may be appropriate seek to define symptoms such as fever, chills, pain type, etc. These questions and corresponding provide information the system can use to answers begin to focus on the exact nature of the medical problem.

Once the general system questions are completed, the LDD module 52 then builds the specific system questions, for example, relating to the skin, the musculoskeletal system, the digestive system, or any other systems of the human body. These more specific questions are presented to the patient 20, and then further questions are built within the LDD module 52 based on the answers to these specific system questions in order to seek more detailed information regarding questions that are answered with an abnormal response. Abnormal responses are determined by checking the patient's answers against common answers contained in the reference database 58. The reference database 58 is thus used as a check against the answers of the patient, and as a knowledge base to generate further questions. Once the general and more specific system questions have been answered by the patient 20, then the DxNA module 54 assesses the information from these answers. The DxNA module 54 retrieves information stored within the medical history database 48 and generates a preliminary list of possible diagnoses based on the answers supplied to the LDD module 52. This list of possible diagnoses is referred to as the differential diagnosis. The DxNA module 54 weighs the symptoms presented within the answers to the questions from the LDD module 52, and then matches the magnitude and frequency of the symptoms presented against known characteristic symptoms of various medical conditions. The results are weighted consistent with the seriousness of individual symptoms. From the weighted results, the differential diagnosis is made. The differential diagnosis can include multiple diagnoses arranged based on the likelihood that a particular diagnosis is the correct diagnosis (i.e., based on the value of the cumulative weighted results of the symptoms expressed by the patient 20).

A threshold, either in the number of diagnoses kept or as a minimum of the weighted result for a possible diagnosis, is set to limit the number of diagnoses reported to the physician 30. The threshold is set so that a sufficient number of diagnoses are kept within the differential diagnosis. In this manner, a physician 30 examining the results can choose between a set of diagnoses and may generate other questions that may be important in making a proper diagnosis. The differential diagnosis is also used to determine if any more questions are necessary.

Once the preliminary differential diagnosis is generated, the DxNA module 54 then uses the information gathered through the LDD module 52 to determine if more questions should be asked by testing the diagnoses. These questions are based on information stored within the DxNA knowledge base 180, the LDD knowledge base 170, reference database 58 that pertains to the diagnoses included in the differential diagnosis. For example, a diagnosis that includes a urinary tract infection (UTI) may require additional answers to questions within the urological system. Some of these questions may have been skipped in the initial screening, but can be asked when the diagnosis is narrowed to a set of candidates. The additional information fills in the information necessary to further narrow the list of candidate diagnoses. Once the additional information suggested by the DxNA module 54 is gathered through the IDD module 52, then the DxNA module 54 again generates a refined differential diagnosis that may contain some of the same diagnoses as before and any new diagnoses that are possibilities based on the symptoms presented. This process of looping through the DxNA module 54 and the LDD module 52 may be continued until no new diagnoses are generated within the differential diagnosis, or until some predetermined number of loops have been executed. The final results are then prepared for the physician interface 44. The physician interface 44 retrieves information from the D NA module 54, IDD module 52, medical history database 48 and may also retrieve data from diagnostic tools 68 that record data from the patient 20. The information gathered from these sources is presented to the physician 30 on a physician summary screen 80. The physician 30 interacts with the physician summary screen 80 as follows. First, the physician 30 reviews the information in the physician's summary, then he determines a diagnosis and submits the diagnosis on a select diagnosis screen 82. The physician interface 44 receives the diagnosis, searches the treatment module 56 for treatments for the medical condition determined in the diagnosis, and then displays the treatment results in a possible treatments screen 84. The physician 30 may then choose the treatment protocol from the possible treatments screen 84, and then finally, the physician 30 may enter the treatment in a determine treatment screen 86.

An email posting to a secured web space 88, or other form of correspondence, may then be sent to the patient 20 once the treatment is determined. If the treatment requires a prescription, then an order for a prescription 90 can be verified by the physician 30 at a drug store through the pharmacy system 34. The physician/patient visit is then concluded. Any additional instructions for follow up visits or referrals to a specialist could be included in the correspondence 88. The physician summary screen 80 reduces all the collected information into the most pertinent information that the physician 30 then reviews to make a diagnosis. This screen 80 is generally the first introduction the physician 30 has to the patient 20. Prior to interacting with the patient, the system 10 has received and recorded the information via the interactions described above, compiled the information, and then prepared it for presentation to the physician in the summary screen 80. This is an important aspect of the system 10, because these patient interaction steps free the physician 30 from the data gathering portion of the visit. This allows the physician 30 time to treat more patients 20. The physician summary screen 80 also displays all the pertinent information that the system 10 has reviewed to make a differential diagnosis. This again saves the physician 30 time by removing any duplicate data or unimportant information and logically ordering the data into a structured summary. The physician 30 can review the material presented in the summary 80, ask for additional data from diagnostic tools 68, and review the patient's medical history stored in the medical history database 48. These functions are tools a physician 30 uses to interact with the patient 20. The content of the physician summary screen 80 is discussed in more detail with reference to FIG. 8A and 8B. The physician summary screen 80 also may include a case complexity indicator. The case complexity indicator, also discussed in Figs. 8A and 8B, is a measure of the complexity of the patient's medical problem. The complexity is measured by the systemic interruption of normal activity that the patient experiences. Once the physician has interpreted and clarified the results shown on the summary screen 80, the physician 30 advances to the select diagnosis screen 82.

The select diagnosis screen 82 is an interface where the physician chooses either one of the diagnoses suggested in the differential diagnosis or determines a diagnosis separate from those included in the differential diagnosis. Once the diagnosis is chosen, the system 10 sends the diagnosis to the medical histoiy database 48 to be stored in the patient's record and also to the reference database 58 as a possible case study for future diagnoses. Having selected a diagnosis from the select diagnosis screen 82, the physician then views possible treatments generated via the treatment display 84

The treatment module 56 processes the patient's record to check for allergies or other medical history pertinent to the treatment, and also reviews treatment protocols within the reference database 58. The treatment module 56 then sends possible treatments to the generate possible treatments screen 84.

The possible treatments 84 are displayed for the physician 30 within the physician interface 44. The possible treatments are checked for side effects and are also checked to see if they interfere with other drugs. The physician 30 then determines if the patient 20 is allergic to any particular drug or if a drug has produced bad side effects in the past. The treatment could also include a number of medications to which the physician 30 must assure himself that the patient 20 has the mental capacity to manage. Once the physician 30 is satisfied with a treatment, the treatment is entered on the determine treatment screen 86. Finally, the treatment choice and the accompanying instructions are communicated to the patient 20 via the e-mail 88 or other means of communication. The patient 20 may then send the order to a pharmacy 90, which may verify the medication through the physician 30.

Turning now to FIG. 3, a logical flow chart is set forth showing the preferred steps enabled by the patient interface 42 of the present invention.

These steps are implemented when a patient 20 seeks a medical consultation via the system 10. The process starts at step 100, when a patient 20 enters the site 10. The patient 20 then enters an ID and password at step 102. The system 10 then determines if the ID and password exist at step 104. If the ID/password combination does not exist, then the system 10 creates the ID and password at step 106, and then queries the patient 20 to create a medical history in step 108. If the ID and password exist, however, then the system 10 determines if the medical history of the patient 20 has been entered into the medical history database 48 in step 110. If the medical history does not exist, then the patient 20 is queried to create the medical history in step 108. Once the medical history is created, the patient 20 then inputs a chief complaint in step 112. The patient 20 then inputs the affected regions in step 114, and answers structured questions in step 116. Once the structured questions have been answered, the patient 20 awaits physician interaction 124. The physician 30 then diagnosis the patient 20 and prescribes a treatment in step 126. The patient exits the site 10 in step 130 after the treatment regimen has been received. Within these steps 100 through 130, the patient 20 does not generally proceed until information at any step is fully gathered. This process allows the physician 30 to see the patient's case entirely when he begins his consultation. Importantly, this saves the physician 30 time since the physician 30 is not required to gather data during the consultation. The physician 30 can, however, further inquire about the data that has been gathered by questioning the patient 20 as the diagnosis is being made in step 126.

For example, a first time patient enters the system 10 seeking a diagnosis for a cough. Since an ID and password do not exist yet, the system 10 creates the ID and password 106. At this point, the medical history database 48 is also appended to include a new record for this patient. The system 10 then queries the patient for a medical history, and saves the medical history information to the patient's record in the medical history database 48. The create medical history step 108 requests personal information, such as the patient's name, birth date, height, weight, sex and address, and medical information such as family history. Once these preliminary steps 100-110 are completed, the patient begins to enter his complaint into the system.

The patient begins with a simple explanation of the medical problem in step 112, such as, "I have a cough that has become painful and as a result I have lost my voice." The patient then uses a mouse or other pointing device associated with his computer to pick the throat and head region of the body using the graphical data entry means 64. Additional graphical diagrams may also be presented by the system 10 so that the patient can zoom in closer on the throat and head portions of the body in order to more precisely indicate the problem area. The choices made by the patient in interacting with these graphics serve to narrow the focus of the questioning that the IDD 52 presents to the patient in step 116.

The IDD 52 generates the questions that the patient answers in step 116. The patient continues to answer questions until the present iteration of questions from the LDD 52 is exhausted. It is important to note that the questioning steps 112-116 can be rearranged and revisited. The LDD 52 may find additional graphical material for the patient to answer after step 114 has been passed. Also, additional material such as a sound file of an exemplary cough might be requested at some point during the questioning steps 112-116. Once the questioning steps 112-116 are completed, the patient waits for a physician 124 in a virtual waiting room. While waiting in the virtual waiting room, the system 10 may present informational material for the patient to review, such as physician biographies, general medical information, links to goods and services that may interest the patient, or games to occupy time. Once the physician is ready to review the case, the system 10 notifies the patient in the virtual waiting room, and the patient then begins to receive the diagnosis and treatment for the ailment directly from the treating physician.

The consultation step 126 may include numerous interactive tools. For example, the physician 30 may e-mail the diagnosis and treatment, or the system 10 could engage a videoconference link between the physician and the patient, or the physician could engage the patient in a telephone conversation, or the physician could send an instant message to the patient through an online service such as AOL Instant Messenger, ICQ, Yahoo! Messenger. During this interaction, the physician 30 explains the diagnosis and the prescribed treatment.

The steps 100-130 in FIG. 3 generally describe a patient's visit to a physician via the system 10. It should be understood, however, that this flow chart may include other steps for other types of patients. For instance, a child who can not enter the necessary information into the site 10 can have a proxy, such as a parent, enter the appropriate information and otherwise interact with the system. Similarly, older patients, or handicapped individuals, may use the assistance of a caregiver to enter information into the site 10. In these instances, the LD and password are assigned for the patient and not the proxy. Importantly, the steps 100-130 for the patient 20 are similar to the experience of a visit to a physician's office. In this experience, the patient 20 first fills out a general history sheet, is then taken to a room for routine questioning, likely by a nurse, and is then questioned by a physician as to the specific reason for the visit. The physician then leaves to review the results of the questioning and finally diagnoses the condition and suggests a treatment which is explained to the patient. The system 10, however, uses the server applications 46 to leverage the time required to treat the patient, thereby enabling the physician to complete the diagnosis and treatment of a patient in a fraction of the time associated with the traditional office visit.

Turning now to FIG. 4, a logical flow chart is set forth showing the preferred steps enabled by the physician interface 44 of the present invention. When the physician 30 enters the system 10, he logs in at the entry portal 40 and is then directed to the physician interface 44, where a list of patients who have completed interacting with the data gathering modules is waiting. The physician selects a patient to exam, then begins the evaluation process at step 140. The physician 30 reviews the patient's medical history of the current case at step 142. The physician then reviews the current complaint at step 144 and clarifies the complaint in step 146. Once the physician is confident that he understands the problem, he then reviews the differential diagnosis made by the system 10 in step 148. In step 150, the physician then decides which diagnosis is correct, or, alternatively, he selects another diagnosis that is not included in the differential diagnosis. Once a diagnosis is chosen, the physician then reviews treatments for the diagnosis in step 152. A treatment is decided at step 154, and then infoπnation, instructions and prescriptions for the diagnosis are sent to the patient in step 156. The physician completes these steps and the process ends in step 160. FIG. 4 generally shows the steps a physician takes in diagnosing a patient. Importantly, these steps are carried out in such a way as to save time for the physician. The physician does not have to collect the information from the patient regarding his current medical condition because most of this information was previously collected from the patient during the initial patient interaction with the system 10. The system 10 leverages the physician's time to maximize the number of patients that can be consulted in a given time period. The physician's time is maximized by reducing the physician's work load to include the most crucial steps in diagnosing the ailment, and prescribing the treatment while automating the more basic data gathering steps.

The flow chart of FIG. 4 includes review steps 142-148, decision steps 150-154, and resulting step 156. The review steps 142-148 provide a process for the physician 30 to review the medical condition and other pertinent information from the patient's past medical history. The review steps 142-148 provide time saving tools since information that is not pertinent to the case, as determined through the interaction of the LDD module 52 and D NA module 54, is not presented to the physician 30 in the review steps 140 -148. The physician 30 may also interact with the patient as necessary in the review steps by communicating with a patient as described above with reference to step 126. Within these review steps 142-148, the physician 30 may revisit the medical history records he has previously searched. Thus, the physician 30 may begin by reviewing the patient's medical history, but may then return to the medical history once he has studied the current complaint and the differential diagnosis. The information provided within these steps is contained in the differential diagnosis display of FIG. 8 and is discussed further below.

Turning now to FIG. 5, a detailed diagram of the evaluation engine 50 of FIG. 1 is provided. The evaluation engine 50 includes the LDD module 52, the D_XNA module 54, and the treatment module 56. Each of these modules 52- 56 includes a knowledge base 170, 180, 190; a rule base 174, 184, 194; and an inference engine 178, 188, 198. Within the LDD module 52, the knowledge base 170, the rule base 174, and the inference engine 178 are configured to generate further questions based on previous answers and reference data. Within the DxNA module 54, the knowledge base 180, the rule base 184, and the inference engine 188 are configured to generate candidate diagnoses based on previous answers and reference data, and thereby, indicate what additional information should be gathered by the IDD module 52.. And within the treatment module 56, the knowledge base 190, the rule base 194, and the inference engine 198 are configured to generate treatments based on previous answers and reference data.

The knowledge base 170, 180, 190 comprises reference material from the reference database 58 and the medical history database 48 as well as specially structured data sets. The knowledge base 170, 180, 190 collects and stores relevant data regarding the health status of the patient as well as a library of questions corresponding to diseases and symptoms so that the evaluation engine 56 can generate further questions, diagnoses or treatments. The rule base 174, 184, 194 checks the data provided by the patient 20 against the reference data provided by the knowledge base 170, 180, 190 to determine conditional relationships between data points that would suggest a question, a diagnosis, or a treatment. Finally, the inference engine 178 188, 198 implements the conditional rules of the rule base 174, 184, 194 and the knowledge stored in the knowledge base 170, 180, 190 to generate additional questions, diagnoses, or treatments. The inference engine 178 of the IDD module 52 checks the conditions within the rule base 174 based on the information within the knowledge base 170 to determine the scope of further questions. For example, within the rule base 174, there may be a condition that states, "if patient has normal fluid intake and has diarrhea, check for psychogenic problems and other illnesses." The inference engine 178 sorts the relevant information gathered from the patient 20 that indicates the current problem is constipation. The inference engine 178 then searches and reviews the medical history through the knowledge base 170 and finds that the patient has normal fluid intake by examining the patient's fluid intake compared to the normal population. The inference engine 178 thus begins to search the knowledge base 170 for questions concerning psychogenic problems and other illnesses and may find the questions, "Is there more stress than usual in your life right now?" and "Have you recently been, or are you currently, sick?"

The DxNA module 54 interprets the data collected from the LDD module 52 to make a differential diagnosis of the patient 20. The inference engine 188 sorts answers that are similar to symptoms of a single diagnosis. The inference engine 188 retrieves the answers to the questions stored in the medical history database 48 through the knowledge base 180. By using the structured entries within the knowledge base 180 and comparing these structured entries to the reported symptoms using the rule base, the inference engine 188 can then determine if these answers suggest candidate diagnoses.

DxNA module 54 includes a list of diseases, which may be represented by their unique, numerically-coded profiles of characteristic symptoms. For example, a simplified version of the code for diabetes might be a numerical representation of the phrase, "history of diabetes, thirst, frequent urination, high blood sugar." The code assigned to each disease entity thus may contain the information necessary for the inference engine to generate diagnostic hypotheses, and to determine what information is missing with respect to these candidate diagnoses. For example, three different diagnoses for diarrhea exist; enteritis, psychogenic diarrhea, and ulcerative colitis. Each of these diagnoses has a set of pertinent symptoms found within the patient that include symptoms of diarrhea. Enteritis is generally caused by an infection in the intestinal tract by a virus or a bacteria, such as cholera. Psychogenic diarrhea is associated with nervous tension. Ulcerative colitis is a disease where the walls of the large intestine are inflamed. Little is known of ulcerative colitis except that it is generally heriditary, and family members may have had an ileostomy. Therefore, the rule base 184 of the D_XNA module 54 may contain rules such as, "if patient has diarrhea and is stressed, then psychogenic diarrhea is a possible diagnosis," "if patient has diarrhea and has recently had an infection, then enteritis is a possible diagnosis," and finally, "if patient has diarrhea and family member has/had an ileostomy, then ulcerative colitis is a possible diagnosis." The inference engine 188 reviews the medical history through the knowledge base to determine if these symptoms are present in the patient 20, and returns a differential diagnosis from the evaluation engine 50. If the information gathered through the knowledge base 184 is inconclusive, then additional questions are asked through the LDD module 52 as is further explained below with reference to FIGs. 7A and 7B. Once the differential diagnosis is reviewed and a diagnosis is made, the treatment module 56 then determines possible treatments.

The three components of the treatment module (the knowledge base 190, the rule base 194, and the inference engine 198) similarly interact to search chosen treatments for the selected diagnosis. For example, if the diagnosis is enteritis (diarrhea caused by virus or bacteria), the physician 30 may select from a number of diagnosis that vary in magnitude. These treatments are generated by examining the data entered by the patient. If the patient 20 exhibits no signs of dehydration, the physician 30 might simply prescribe an antibiotic and high intake of fluids rich in electrolytes, such as Gatorade. The choices of antibiotics is prescribed by the treatment module 54. If the patient 20 is allergic to a certain antibiotic, such as penicillin, then that antibiotic will not be included in the possible treatments. Also, if records show that a particular antibiotic has been ineffective for this patient, it may also be removed from the possible treatments list. If the patient 20 has begun to exhibit signs of dehydration, then the physician might chose a more invasive treatment, such as sending the patient to a hospital and receiving solutions of glucose and saline intravenously. In general, the treatment module 54 generates a range of treatments based on intensity so that the physician 30 can chose the appropriate level of treatment. The knowledge base 190 also includes instructional information that is matched to the prescriptions so that when a physician 30 chooses a treatment, he may also choose instructions to accompany the treatment. The output of the treatment module 56 is a report of possible treatments and an accompanying instruction set.

FIG. 6 is a detailed diagram of the reference database 58 shown in FIG. 1. The reference database 58 stores information that is used to interface with the evaluation engine 50, and it is also searchable through the physician interface 44. The reference database 58 includes a general medical reference 200, a graphical medical reference 202, and a general treatment reference 204. The references 200-204 include searchable database structures so that the evaluation engine 50 may search through the database structures using the structured queries of the knowledge bases 170, 180, and 190. The physician interface 44 is also configured so that a physician may generate queries for the database structures 200-204 based on his need for further information.

The general medical reference 200 includes information regarding symptoms, traumas, diseases, and other medical conditions. This information is stored such that any one of these categories can be searched. For example, a query can be generated to search for all diseases where vision is blurred. The general medical reference 200 is searched for diseases where blurry vision is a symptom. The general medical reference 200 then outputs a list of diseases. Another query may request the symptoms associated with meningitis. These queries are generated through the FDD and D_XNA modules 52 and 54 or through a physician's reference within the physician interface 44.

The graphical medical reference 202 includes graphical information that can be displayed in the patient interface 42 and the physician interface 44. The graphical information contained within the graphical medical reference 202 may include photographs, illustrations, 3-D models, radiological images, animations, etc. For example, a photograph may show skin lesions for which the patient 20 must pick the closest match. Or, in order to describe a source of pain in the hand, an illustration may label parts of the hand in cutaway view so that the patient 20 can use descriptive terms that the physician 30 can then interpret. An animation may rotate the knee joint so that the patient 20 can pin point the orientation of the knee when pain occurs. The graphical medical reference 202 is thus a tool that can help a patient 20 and a physician 30 better communicate the medical condition. The general treatment reference 204 includes information on treatments, instructions for implementing treatments, and the diseases for which the treatments are effective. The general treatment reference 204 is generally searchable by disease or by symptom, but a physician 30 may also search through prescriptions to see what similar treatments can be prescribed that have similar effects. For example, if the patient 20 is allergic to penicillin, but requires an antibiotic for a medical condition, then the treatment module 56 will query the treatment reference 204 for similar antibiotics that are listed as treatments for that medical condition. If a physician would rather not use a certain antibiotic, he may query the general treatment reference 204 for a list of similar antibiotics from the physician interface 44. The reference database 58 thus includes reference material from the population of patients that have been treated by physicians through the system 10.

Turning now to FIGs. 7A and 7B, a logical flow chart sets forth the preferred steps enabled by the server applications 46 of the present invention. The flow chart describes the process that is implemented via the IDD module 52 and the DxNA module 54 in questioning a patient and diagnosing the medical condition.

The process starts at step 210, which is after the patient 20 has generally described the current medical problem as set forth above. The system 10 then asks general health questions in step 212. The answers to these questions are checked against normal answers stored in the reference database 58 in step 214. If any of the answers are abnormal, then the knowledge base 170 of the IDD module 52 determines if specific questions about the abnormality exist in step 216. If more specific questions exist, then in step 218 the LDD module 52 asks these specific questions through the patient interface 42. If no answers are abnormal, or no more specific questions about an abnormal answer exist, then the DxNA module 54 generates a list of diagnoses and assigns the number of diagnoses to a variable Dx in step 220. A counter, I, is initialized to 1 in step 222. In step 224, the DxNA module 54 determines if the Ith diagnosis suggests that more specific questions should be asked based on the symptoms that have been reported in the Ith diagnosis and the symptoms that are traditionally associated with the diagnosis that have not been ascertained from the previous questions presented in step 212. The DxNA module 54 generates a list of the data that is required to validate or invalidate a diagnosis, and then sends that information back to the IDD module 52. If more specific questions exist, then the IDD module 52 asks these specific questions in step 226. The answers to these questions are then checked against normal answers stored in the reference database 58 in step 228. If any of the answers are abnormal, then the knowledge base 170 of the IDD module 52 determines if additional specific questions about the abnormality exist in step 230. If additional specific questions exist, then in step 232 the LDD module 52 asks these questions through the patient interface 42. Once all the questions from steps 228 and 230 have been asked and answered, the counter I is then updated in step 234.

Step 236 determines if the counter, I, is less than or equal to Dx. If I is less than or equal to Dx (the number of diagnoses in the differential diagnosis), then the process returns to step 224 to determine if the next diagnosis suggests that additional questions should be asked of the patient 20. If, however, I is greater than Dχ₅ then in step 238 the DxNA module 54 determines if more diagnoses can be made. If more diagnoses can be made, then step 240 generates new possible diagnoses and Dx is reassigned to the new number of diagnoses. The previous diagnoses are kept for future reporting. The counter I is re-initialized to 1 at step 222 and the process of asking questions begins again at step 224. If no more diagnoses can be made at step 238, however, then the differential diagnosis report is generated at step 242 and the process ends at step 244.

FIGs. 7A and 7B generally show the recursive steps of the IDD module 52 and the D_XNA module 54 of FIG. 1. These steps 212-218 include the intelligent data drilling procedures of the IDD module 52. Once the LDD module 52 has fully drilled through the questions contained within the reference database 58 and gathered through the knowledge base 170, then the DxNA module 54 generates diagnoses as shown in step 220. The candidate diagnoses are evaluated to determine if other symptoms might be present in the patient that have not been ascertained because the patient has not been questioned about those symptoms. The DxNA module 52 then passes the symptoms and diagnoses to the IDD module 52 so that the LDD module 52 can present the more specific questions to the patient as shown in steps 226-232. This process repeats until all of the relevant questions are asked that are related to any of the diagnoses from the candidate diagnosis list. The process will also repeat until internal data point conflicts are resolved to a predetermined level of congruency. Alternatively, the system 10 may only cycle a predetermined number of times, regardless of conflicts or additional questions. The flow chart of FIG. 7 thus reduces a very broad search of medical conditions to a few likely candidate diagnoses and builds a differential diagnosis as shown in FIG. 8A and 8B

FIGs. 8A and 8B set forth a graphical depiction showing the layout of a differential diagnosis display generated by the server applications 46 and viewed through the physician interface 44. The differential diagnosis display includes a general description of the patient 260, a chart 270, a systemic scale 272, a differential diagnosis 274, a text box 276 and a submit button 278 to enter a diagnosis. The general description 260 includes pertinent data 262 from the medical history database record of the patient, a current complaint 264, and graphical displays 266. The pertinent history includes allergies, current medications, significant medical history, social history, etc. The graphical displays 266 include the pictures and/or 3D models that the patient 20 manipulated or selected when interacting with the patient interface 42. These pictures and or 3D models could include a general body view where the patient 20 chose an affected region, a display of the affected region, and a close-up of the affected region.

From step 242 of FIG 7B, the chart 270 of the patient's complaint is generated, and includes the affected systems, differential diagnosis and pertinent positives and negatives regarding the current complaint. The pertinent positives and negatives are based on the answers to the questions generated by the IDD module 52 as they pertain to the differential diagnosis list. The chart 270 is organized by system, such as urinary, digestive, pulmonary, integumentary, and nervous systems. A general category is included for symptoms that do not exactly fall into one of the system categories. Furthermore, any one condition can affect multiple systems. A pulmonary problem may create a sluggish feeling and also make body parts tingle because oxygen does not reach outer body parts. This type of condition can cause many systems to have symptoms that suggests a more serious condition that may require immediate medical help. The systemic scale 272 is a measure of how complicated a diagnosis is to make and helps determine if either immediate help or a doctor's visit, where lab work can be taken, is required. The systemic scale reflects how many systems are affected by the reported symptoms.

The systemic scale 272 of the differential diagnosis display measures the level of interaction of a condition on multiple systems. The systemic scale 272 measures the likelihood that a condition may be more complicated than a simple verbal exam with minimal tests can determine. While some tests may be available at the remote location of the patient 20, the patient 20 will not generally have access to tools to process blood samples, urine samples, stool samples, etc. If the condition elicits a response on the systemic scale that is above a particular threshold, then the physician 30 interviewing the patient 20 can suggest an immediate visit to a local specialist to have tests drawn.

Furthermore, a validity scale may be separately shown. The validity scale reflects the internal consistency of the data set. The validity scale may be represented by a strict pass/fail guideline or by a multilevel, continuous scale similar to the systemic scale.

The systemic scale 272 is also a measure of the likelihood that all of the relevant questions have been asked. When more systems are involved in the diagnosis, it is more difficult to ensure complete coverage of questions, and thus the systemic scale 272 can serve as a warning to the physician 30 that certain information may not have been gathered. The physician 30 may then engage the patient 20 to determine the information needed, or the physician may suggest that the patient visit a local specialist to obtain specific laboratory tests or radiological tests.

Using this interface screen, the physician can then review the suggested differential diagnosis 274. The suggested differential diagnosis 274 is a list of the possible diagnoses generated by the DxNA module 54. The differential diagnosis 274 maybe ordered based on the likelihood that a particular diagnosis is the best diagnosis given the symptoms of the current condition. The differential diagnosis display also contains suggested laboratory tests or radiological tests to order for uncomphcated cases. In these tests, the patient 20 may be able to take the data at home and mail in a sample, or may be able to go to any local clinic to have the test taken. Finally, once the physician has convinced himself of a diagnosis, the physician enters the diagnosis in the text box 276 or selects the diagnosis from the differential diagnosis list. The physician 30 then clicks the submit button 278 to begin the treatment module 56.

For example, the patient depicted in FIG. 8 is a 34 year old female. She is complaining of pain and burning when she urinates. The graphical data presented to her may have been a full body picture on which she highlighted the pelvic region. Within the affected region she may have chosen the lower pelvic region, and finally chosen the exact region of burning within the close up diagram of the affected region. The pertinent medical history includes information as to the patient's sexual behavior, current medications and any ongoing medical treatments such as for depression. It is also noted that she is allergic to penicillin so that other antibiotics should be chosen should she need that type of medication.

Her system chart shows pertinent negatives in the general, digestive, and genital tract systems. This suggests that these systems are not affected by the condition. While the urinary tract shows several pertinent negatives, these pertinent negatives more fully define what the diagnosis should be by eliminating other possible diagnosis. The pertinent positives of the chart, such as burning, urgency and frequency of urination suggest the diagnosis includes a problem within the urinary tract. The systemic scale suggests the diagnosis is uncomplicated.

The physician 30 then reviews the suggested differential diagnosis. In order of likelihood, the diagnoses are uncomplicated cystitis- bacterial, uncomplicated cystitis- non-bacterial, and pylonephritis. The differential diagnosis display suggests a simple urine analysis test to check for the presence of a bacteria within the sample. The physician 30 can choose one of the diagnoses from the differential diagnosis or make a diagnosis outside of the differential diagnosis and enter that diagnosis on the differential diagnosis display and then proceed to generate a treatment using the treatment display of FIG. 9. FIG. 9 is a graphical depiction showing the layout of a possible treatments display generated by the server applications 46 and viewed through the physician interface 44. The treatment display is split into two sides. The right side includes the suggested treatments 300 and suggested instructions 310 for the chosen diagnosis. The left side includes the selected treatments 300 and the selected instructions 312 from the right side of the treatment display. The physician 30 selected from the types of medication that are possible treatments 300. The physician may also prescribe an adjunctive medication which is used to treat effects such as pain or swelling or to counteract a side effect of the medication. The physician 30 may add or delete medications from the selected treatment 302 until he has found the combination of prescriptions that he believes to be the most effective. The physician 30 may also include instructions 302 for the patient 20. These instructions include how to take the medication (such as frequency, length, take with food, etc.) and other instructions for daily activities. These prescribed treatments 302 and instructions 312 are submitted to the system 10 and a physician report is generated to send to the patient 20 as shown in FIG. 10.

FIG. 10 is a graphical depiction showing an example of a physician report sent to a patient after a diagnosis and treatment regimen have been determined. The physician report includes the medications that are prescribe and the directions for the medication use 320, and a list of instructions for the patient 324. The physician report also includes secure, authorized, and verifiable links to wire the prescription to the pharmacy system 330, print the prescription 332, print the instructions 334 or print the entire report 336. Other links (that can be included in hyperlinks) allow the patient 20 to review the medical condition for a description of prescribed drugs, the disease or any other terms that are not commonly known. Once the patient 20 has received the physician report, the consultation is complete and the patient 20 may begin treating the condition. The example shown within FIGs. 9 and 10 is the treatment display and physician report of the woman complaining of pain when urinating shown in FIG. 8. Here, the physician 30 selected the diagnosis of uncomplicated cystitis- bacterial. The physician 30 then proceeds to the treatment display of FIG. 9. The suggested treatment includes an antibiotic and pain medication. The choice of antibiotics include Bactrim DS, Ciproflaxacin, and Keflex while the adjunctive medication for pain includes Pyridium and Motrin. The physician 30 selects an antibiotic and an adjunctive medication and adds each to the left hand side of the treatment display. The physician 30 also adds a number of instructions for daily habits that should help rid the patient 20 of the infection. Once these choices are made, the physician 30 sends the physician report of FIG. 10 to the patient 20. The physician report includes the list of medications the physician chose along with the chosen instruction set. The physician report includes details that were not seen on the physician report such as side effects (i.e., the medication will turn your urine orange) and a general description of the condition. The treatment and condition are then added to the database record of the patient 20 so that the physician 30 may review this treatment the next time the patient 20 visits the site 10.

The preferred embodiments described with reference to the attached drawing figures are presented only to demonstrate certain examples of the invention. Other elements, steps, methods, and techniques that are insubstantially different from those described above and/or in the appended claims are also intended to be within the scope of the invention.

Claims

The following is claimed:

1. An online medical system, comprising: a patient interface configured to display and record medical information of a patient; a physician interface configured to display a summary of the medical information recorded from the patient interface; and server applications configured to send queries to the patient interface and to evaluate the answers to the queries such that the summary of the medical information displayed in the physician interface includes a differential diagnosis.

2. The system of claim 1, wherein the server applications comprise: a data drilling module configured to generate the queries; and a diagnostic module configured to generate the differential diagnosis such that the differential diagnosis is based on the answers to the queries generated in the data drilling module.

3 The system of claim 2, wherein the differential diagnosis is interpreted by the data drilling module and additional queries are generated based on the differential diagnosis.

4. The system of claim 1, wherein the medical information is recorded to a medical history database.

5. The system of claim 4 wherein the medical history database is resident within the online medical system.

6. The system of claim 4, wherein a record in the medical history database is assigned to a patient, the record being accessible by the patient and medical personnel.

7. The system of claim 1, wherein the server applications comprise a reference database having graphical reference material that is accessible through the patient interface and the physician interface.

8. The system of claim 1, wherein the server applications comprise a reference database having sound reference material that is accessible through the patient interface and the physician interface.

9. The system of claim 1, wherein the server applications further comprise a treatment module configured to receive a diagnosis from the physician interface and generate possible treatments based on the diagnosis.

10. The system of claim 9, wherein the treatment module receives a chosen treatment from the physician interface and sends the chosen treatment to the patient interface.

11. The system of claim 10, wherein the system further comprises a prescription system configured to receive the chosen treatment and fill the prescription.

12. An online medical evaluation system, comprising: a patient interface; a physician interface; and a data drilling module configured to generate queries sent to the patient interface and summarize results of the queries in the physician interface; wherein the queries include graphical medical data.

13. The system of claim 12, wherein the results of the queries include graphical medical data.

14. The system of claim 12, wherein the results of the queries include aural medical data.

15. A method of gathering medical data from a sick patient, comprising the steps of: initializing a patient interface; generating queries to be sent to the patient interface; retrieving the answers to the queries; storing the answers in a database record; and rewarding the patient for entering answers by diagnosing a medical condition from the answers.

16. The method of claim 15, wherein the answer is entered through at least one of structured data entry, unstructured data entry, or graphical data entry.

17. The method of claim 16, wherein the structured data entry includes at least one of a pull down box, a radio button or a check box.

18. ^• The method of claim 15 further comprising the step of exporting the medical data to a third party.

19. The method of claim 15, wherein the initializing step includes retrieving an ID and password from the patient.

20. A method for diagnosing a health condition in a patient, comprising the steps of:

A) querying a patient interface for general health symptoms;

B) determining if any general health symptoms are abnormal; C) generating possible diagnoses based on the abnormal symptoms; D) for each diagnosis:

Dl) generating specific symptoms; and D2) querying the patient interface for existence of the specific symptoms; and E) building a differential diagnosis based on the abnormal symptoms.

21. The method of claim 20, wherein step D is repeated such that the specific symptoms generate additional possible diagnoses.

22. A method of treating a patient, comprising the steps of:

A) querying a patient interface for general health symptoms;

B) determining if any general health symptoms are abnormal;

C) building a differential diagnosis based on the abnormal symptoms;

D) displaying the differential diagnosis to a physician; E) receiving a diagnosis from the physician;

F) displaying a list of treatments in response to the diagnosis;

G) receiving a chosen treatment from the physician; and H) displaying the treatment at the patient interface.

23. The method of claim 22, further comprising the step:

El) building a list of treatments in response to the diagnosis.

24. The method of claim 22, further comprising the step of: I) forwarding the treatment to a pharmacy system.

25. the method of claim 22, further comprising the step of: I) forwarding a test request to the patient; J) referring the patient to a medical facility.

26. The method of claim 22 wherein the medical facility is a primary care center.

27. The method of claim 25 wherein the test comprises a diagnostic image.

28. The method of claim 25 wherein the diagnostic image is a radiological image.