HIGH PERFORMANCE AND INTEGRATED NOSOCOMIAL INFECTION SURVEILLANCE AND EARLY DETECTION SYSTEM AND METHOD THEREOF

• US 20120179491A1
• Filed: 01/06/2012
• Published: 07/12/2012
• Est. Priority Date: 01/07/2011
• Status: Abandoned Application

• Current Assignee: Taipei Medical University WAN Fan Hospital (Government of The Republic of China)
• Original Assignee: Taipei Medical University WAN Fan Hospital (Government of The Republic of China)
• Inventors: LIU, CHIEN-TSAI, LO, YU-SHENG
• Application Number:
  US13/344,992
• Publication Number:
  US 20120179491A1
• Time in Patent Office: Days
• US Class Current: 705/3
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 50/80 for detecting, monitoring or modelling epidemics or pandemics, e.g. flu
• 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 high performance and integrated nosocomial infection control surveillance and detection system includes a patient database having a patient information, a clinical database having a patient clinical information, a nosocomial infection surveillance model with capability to detect suspected cases, an infection monitoring dashboard presenting an integrated view of a patient information and infection conditions in the clinical database for each patient. The patient database, clinical database, nosocomial infection surveillance model and the infection monitoring dashboard are built in different network servers or a network server to meet the optimum efficiency for a user to conduct infection control and early detection of infected cases through his/her account.

Claims

1. An integrated nosocomial infection surveillance and detection method through the internet, said method integrating the patient information and various clinical information in the hospital to achieve the high performance nosocomial infection control and surveillance, comprising:

(1) providing a patient database;

(2) providing an clinical database;

(3) providing an infection monitoring dashboard integrating the information from the patient database and the clinical database based on the index column information of hospitalized patients into a set of related infection information for individual patient;

(4) providing a nosocomial infection surveillance model computing the infection information of the hospitalized patient to identify whether the patient is a suspected case; and

(5) allowing a user to access and browse the infection monitoring dashboard so that the user can further determine whether the patient is an infected case through the internet.

2. The method of claim 1, wherein the patient database comprises index column information of hospitalized patients, patient basic information, date of hospitalization, primary care physician, hospital bed number, and related medical information.

3. The method of claim 1, wherein the clinical database comprises clinical examination data, records of medication, records of surgery and invasive devices, and records of radiographic images.

4. The method of claim 1, wherein the infection monitoring dashboard provides a quick browsing interface comprising the whole patients sub-area, the suspected patients sub-area, the infected patients sub-area, and geographic information of the suspected infection patients according to the hospital wards and beds.

5. The method of claim 4, wherein the interface further show detailed medical records for users to browse.

6. The method of claim 5, wherein the detailed medical records comprise the medication records with respect to oral administration and injection of antibiotic, positive bacteria records, surgery and invasive devices records, white blood cell (WBC) records, leukocyte esterase records, nitrite records, drug-resistant bacteria report records and image reports.

7. The method of claim 1, wherein the model computing in step (4) is performed through a discriminant analysis to identify whether the patient is suspected of having nosocomial infections.

8. The method of claim 7, wherein the discriminant analysis builds a linear function:

L=c+b₁X₁+b₂X₂+ . . . +b_nX_n, n is a positive integer;

where n is the discriminant series, c is a constant, b₁ to b_n are discriminant coefficients, and X₁ to X_n are factor variables or predictor variables.

9. The method of claim 1, further comprising an infection information analysis mechanism to identify if the patient has infection risk in light of the infection information, wherein the mechanism comprises the steps:

(1) providing an infection knowledge database comprising knowledge factors of infections; and

(2) providing a risk analysis model which is used in combination with the infection controlling knowledge of the infection knowledge database to perform risk analysis, and eventually, the results are fed back to the infection monitoring dashboard.

10. The method of claim 9, wherein the knowledge factors of infections comprise the behavior pattern of antibiotic medication prescribed by doctors for suspected patients, the records with respect to oral administration and injection of antibiotic, reference values of positive bacteria results, codes related to surgery and invasive devices shown as health insurance codes, WBC risk values, leukocyte esterase abnormal values, and nitrite abnormal values.

11. An integrated nosocomial infection surveillance and detection system through the internet, said system integrating the patient information and various clinical information in the hospital, comprising:

a patient database;

a clinical database;

an infection monitoring dashboard integrating the information in the patient database and the clinical database into a set of related infection information for individual patient, and providing a quick browsing interface comprising the whole patients sub-area, the suspected patients sub-area, the infected patients sub-area, and the geographic information of the suspected infection patients on the basis of the hospital wards and beds; and

a nosocomial infection surveillance model for computing the infection information of the hospitalized patients to identify whether the patient is a suspected nosocomial infection case and feed back the results to the infection monitoring dashboard;

wherein the patient database, the clinical database, the infection surveillance model and the infection monitoring dashboard are built in a network server or in different network servers to meet the optimum efficiency for a user to conduct infection control and early detection of infected cases through his/her account.

12. The system of claim 11, wherein the patient database comprises index column information of hospitalized patients, patient basic information, date of hospitalization, primary care physician, hospital bed number, and related medical information.

13. The system of claim 11, wherein the clinical database comprises clinical examination data, records of medication, records of surgery and invasive devices, and records of radiographic images.

14. The system of claim 11, wherein the nosocomial infection surveillance model comprising a discriminant analysis algorithm.

15. The system of claim 14, wherein the discriminant analysis builds a linear function:

L=c+b₁X₁+b₂X₂+ . . . +b_nX_n, n is a positive integer;

where n is the discriminant series, c is a constant, b₁ to b_n are discriminant coefficients, and X′

to X_n are factor variables or predictor variables.

16. The system of claim 11, further comprising:

an infection knowledge database comprising knowledge factors of infections; and

a risk analysis model which is used in combination with the infection controlling knowledge of the infection knowledge database to perform risk analysis and eventually to feed back the results to the infection monitoring dashboard.

17. The system of claim 16, wherein the knowledge factors of infections comprise the behavior pattern of antibiotic medication prescribed by doctors for suspected patients, the records with respect to oral administration and injection of antibiotic, reference values of positive bacteria results, codes related to surgery and invasive devices shown as health insurance codes, WBC risk values, leukocyte esterase abnormal values, and nitrite abnormal values.

18. The system of claim 16, wherein the quick browsing interface shows the infection level of each infection item of patients in different colors.

19. The system of claim 11, wherein the quick browsing interface shows the detailed medical records of patients for users to browse.

20. The system of claim 19, wherein the detailed medical records comprise the medication records with respect to oral administration and injection of antibiotic, positive bacteria records, surgery and invasive devices records, WBC records, leukocyte esterase records, nitrite records, drug-resistant bacteria reports and image reports.