METHOD OF ANTICIPATING AN EPIDEMIC IN A POPULATION, AND A SYSTEM THEREOF

• US 20110125525A1
• Filed: 11/20/2009
• Published: 05/26/2011
• Est. Priority Date: 11/20/2009
• Status: Abandoned Application

• Current Assignee: LX1 Technology Limited
• Original Assignee: LX1 Technology Limited
• Inventors: LEE, Ka Yin Ken, LUNG, Ka Kui Francois, TANG, Wai Choi
• Application Number:
  US12/623,339
• Publication Number:
  US 20110125525A1
• Time in Patent Office: Days
• US Class Current: 705/3
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 50/80 for detecting, monitoring or modelling epidemics or pandemics, e.g. flu
• CPC Class Codes: G16H 70/60 relating to pathologies
• CPC Class Codes: Y02A 90/10 Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

A monitoring system is described comprising client computers 103 distributed in different location and a host computer 101. The system is capable of recording clinical symptoms of patients recorded via the client computers 103, and compiling the clinical symptoms to note any sudden increase of clinical symptom or specific combination of clinical symptoms. Thus, a trend may be observed before diagnosis and statistics can confirm infection outbreak allowing doctors to anticipate an infection outbreak, or epidemic.

Claims

1. A system for anticipating an epidemic, comprising

a host computer;

a plurality client computers having an interface for users to record clinical symptoms of patients;

the plurality of client computers having a communication link to the host computer;

the plurality of client computers each containing a set of rules;

the set of rules indicating at least one clinical symptom;

when the clinical symptoms of a patient is recorded into one of the plurality of client computers, the one of the plurality of client computers compares the clinical symptoms of the patient with the at least one clinical symptom in the set of rules;

if clinical symptom of the patient matches the at least one clinical symptom in the set of rules, data on the condition of patient is sent to the host computer;

wherein

the host computer compiles the data on the condition of patients from the plurality of client computers.

2. A system for anticipating an epidemic as claimed in claim 1, wherein

the plurality of client computers is capable of polling the host computer at pre-determined intervals to download an updated set of rules.

3. A system for anticipating an epidemic, comprising

a host computer,

a plurality client computers having an interface for users to record clinical symptoms of patients,

the plurality of client computers having a communication link to the host computer to upload the records of clinical symptoms of patients to the host computer,

the host computer storing a predetermined threshold value,

the host computer having capability for identifying at least one of the clinical symptoms with an occurrence above the threshold value,

the host computer having a communication link to the client computers for triggering an alert in the client computers to the at least one clinical symptoms with an occurrence above the threshold value.

4. A system for anticipating an epidemic as claimed in claim 3, wherein,

the threshold value is an alert-frequency.

5. A system for anticipating an epidemic as claimed in claim 3, wherein,

the threshold value is a percentage based on historical data.

6. A system for anticipating an epidemic as claimed in claim 3, wherein,

the threshold value is a pre-determined rate of increase of the frequency of occurrence.

7. A system for anticipating an epidemic as claimed in claim 3, wherein

the clinical symptoms are monitored for specific combinations of the clinical symptoms in each patient.

13. A system for anticipating an epidemic as claimed in claim 4, wherein the clinical symptoms are monitored for specific combinations of the clinical symptoms in each patient.

14. A system for anticipating an epidemic as claimed in claim 5, wherein the clinical symptoms are monitored for specific combinations of the clinical symptoms in each patient.

15. A system for anticipating an epidemic as claimed in claim 6, wherein the clinical symptoms are monitored for specific combinations of the clinical symptoms in each patient.

8. A method of anticipating an epidemic, comprising the steps of

recording clinical symptoms of patients at interface provided in a plurality of client computers,

uploading the records of clinical symptoms of patients to a host computer,

compiling the records of clinical symptoms of patients to the host computer,

identifying at least one clinical symptom from among the records of clinical symptoms that have a number of occurrences over a pre-determined threshold,

triggering an alert in the client computers to the at least one clinical symptom.

9. A method of anticipating an epidemic as claimed in claim 8, wherein the step of

identifying at least one clinical symptom from among the records of clinical symptoms comprises

identifying a combination of clinical symptoms from among each patient'"'"'s record, and

the threshold value is pre-determined for the combination of clinical symptoms.

10. A method of anticipating an epidemic as claimed in claim 8, wherein, the threshold value is an alert-frequency.

11. A method of anticipating an epidemic as claimed in claim 8, wherein, the threshold value is a percentage based on historical data.

12. A method of anticipating an epidemic as claimed in claim 8, wherein, the threshold value is a pre-determined rate of increase of the frequency of occurrence.

16. A method of anticipating an epidemic as claimed in claim 9, wherein, the threshold value is an alert-frequency.

17. A method of anticipating an epidemic as claimed in claim 9, wherein, the threshold value is a percentage based on historical data.

18. A method of anticipating an epidemic as claimed in claim 9, wherein, the threshold value is a pre-determined rate of increase of the frequency of occurrence.