Method and Apparatus for an Algorithmic Approach to Patient-Driven Computer-Assisted Diagnosis

• US 20080091631A1
• Filed: 10/09/2007
• Published: 04/17/2008
• Est. Priority Date: 10/11/2006
• Status: Abandoned Application

• Current Assignee: Henry Joseph Legere, Nicholas Aaron Solter
• Original Assignee: Henry Joseph Legere, Nicholas Aaron Solter
• Inventors: Solter, Nicholas Aaron, Legere, Henry Joseph
• Application Number:
  US11/869,292
• Publication Number:
  US 20080091631A1
• Time in Patent Office: Days
• US Class Current: 706/46
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

One embodiment of the present invention provides a computer software medical diagnosis system with which users can interact over the Internet using a web browser in order to obtain a medical diagnosis or recommendation. The user interacts with the diagnosis system by first identifying his or her chief complaint, and then answering a series of questions about his or her current symptoms, medical history, identification (age, sex, race), and the like. Then the diagnosis system presents him or her with a diagnosis or recommendation.

Claims

1. A method for computer-assisted diagnosis, the method comprising:

encoding medical diagnosis algorithms as diagnosis decision trees (“

diagnosis algorithms”

), each comprising;

one chief complaint;

one or more decision points comprising zero or more questions; and

one or more termination points;

a user initiating the diagnosis by identifying a chief complaint;

the user traversing the diagnosis algorithm for that chief complaint, wherein the user answers a series of questions; and

the user receiving a diagnosis, conclusion, or recommendation.

2. The method of claim 1, further comprising the lack of interaction, either directly or indirectly, of the user with a live physician.

3. The method of claim 1, further comprising diagnosis algorithm questions on the subjects of current symptoms, medical history, and identification (age, sex, race).

4. The method of claim 1, further comprising diagnosis algorithm decision points based on age, symptom presence, symptom duration, medical history, physical finding, general history, symptom details, and family history.

5. The method of claim 1, further comprising diagnosis algorithm termination points for diagnoses, recommendations for home treatment, recommendations to see a physician, and recommendations to visit an emergency room.

6. The method of claim 1, wherein a diagnosis algorithm for one chief complaint may reference a diagnosis algorithm for a different chief complaint such that the user traversing the first algorithm at a certain decision point automatically begins traversing the second.

7. The method of claim 1, wherein the answers to user questions can be “

auto-filled”

from previous stored user answers or from the user'"'"'s associated electronic medical record.

8. An apparatus for computer-assisted diagnosis, the apparatus comprising:

medical diagnosis algorithms encoded in computer-readable media as diagnosis decision trees (“

diagnosis algorithms”

) each comprising;

one chief complaint;

one or more decision points comprising zero or more questions; and

one or more termination points;

an interface for a user to initiate a diagnosis by identifying a chief complaint;

an interface for the user to traverse the diagnosis algorithm for that chief complaint, wherein the user answers a series of questions; and

an interface for the user to receive a diagnosis, conclusion, or recommendation.

9. The apparatus of claim 8, wherein the user interacts with the system over the Internet by using a web browser.

10. The apparatus of claim 8, wherein the diagnosis algorithms are stored as XML-structured text in a relational database.

11. The apparatus of claim 8, wherein the diagnosis algorithms and diagnosis traversal logic are implemented in an object-oriented programming language, further comprising:

distinctly separate object abstractions for the decision points of the diagnosis algorithms and the questions asked at those decision points;

the question abstraction handling the details of formatting a question and response, and processing the user'"'"'s answer; and

the decision node abstraction handling the logic of the decision points, each of which may depend on the answers to zero or more questions.

12. The apparatus of claim 11, further comprising:

a Question superclass, whose interface is comprised of methods to generate a question and response in the proper format, to parse the user'"'"'s answer, and to translate the answer into a result that the rest of the diagnosis program can use; and

subclasses (subtypes) of the Question superclass comprising abstractions for asking the user'"'"'s age, displaying a non-terminal statement, displaying a diagnosis, asking about multiple symptoms/diseases/diseases history being present, displaying a terminal statement, and displaying a severe terminal statement (warning).

13. The apparatus of claim 12, further comprising;

a DecisionNode superclass to represent the decision points in the diagnosis algorithms in which each DecisionNode has zero branches (terminal), one branch (unary), two branches (binary), or more than two branches (n-ary);

each branch of a DecisionNode points to one or more DecisionNodes;

each DecisionNode object is associated with one or more Questions;

subclasses (subtypes) of the DecisionNode superclass comprise abstractions for age decision points, conjunction (“

and”

) decision points, disjunction (“

or”

) decision points, disjunction decision points pointing to multiple decision points to be taken sequentially, binary decision points, and terminal decision points;

each algorithm is a directed acyclic graph (DAG) of DecisionNode objects; and

each algorithm contains one root node.

14. The apparatus of claim 13, further comprising;

a “

to-visit”

stack of decision nodes;

a “

diagnosis”

queue of decision nodes;

initiating the algorithm by pushing the root node for that algorithm on the to-visit stack;

a “

diagnosis engine”

that runs a depth-first traversal of the diagnosis algorithm by popping and executing the top node in the to-visit stack;

executing a decision node results in zero or more decision nodes being pushed on the to-visit stack and zero or more decision nodes being pushed on the diagnosis queue;

the diagnosis engine terminates if it comes across a terminal decision node; and

when the to-visit stack is empty, the diagnosis engine terminates and displays the diagnosis nodes in the diagnosis queue.

15. The apparatus of claim 14, further comprising a “

visited”

stack of decision nodes to allow the diagnosis engine to work in reverse to give the user to option to back up and answer a question differently.

16. The apparatus of claim 14, further comprising “

auto-filling”

answers to questions from previous stored user answers or from user'"'"'s associated electronic medical record.

17. The apparatus of claim 14, further comprising triggers that are independent of the diagnosis algorithms, and that are checked by the diagnosis engine based on the answers to user questions.