Automated advanced resuscitation training generation system and method therefor

• US 10,296,529 B2
• Filed: 09/13/2013
• Issued: 05/21/2019
• Est. Priority Date: 09/13/2012
• Status: Active Grant

• Current Assignee: Regents of the University of California (University of California)
• Original Assignee: Regents of the University of California (University of California)
• Inventors: Davis, Daniel P.
• Primary Examiner(s): Bullington, Robert P
• Application Number:
  US14/427,439
• Publication Number:
  US 20150242498A1
• Time in Patent Office: 2,076 Days
• Field of Search: 434365
• CPC Class Codes: G06F 16/3331 Query processing
• CPC Class Codes: G06F 16/35 Clustering; Classification
• CPC Class Codes: G09B 19/003 Repetitive work cycles; Sequence of movements
• CPC Class Codes: G09B 5/00 Electrically-operated educational appliances working with questions and answers G09B7/00; simulators G09B9/00; advertising or displaying in general G09F
• CPC Class Codes: G16H 40/00 ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
• CPC Class Codes: G16H 70/60 relating to pathologies

Abstract

A resuscitation training program generation system and method are provided. The system includes an acquisition section that acquires resuscitation event data on a cardiac arrest of a patient; an event categorization section that acquires a categorization of the cardiac arrest into one or more categories of a taxonomy of etiologies of cardiac arrest; an afferent data generator that generates afferent data based on afferent pathways associated with the one or more categories, and updates the resuscitation event data with the generated afferent data; and an efferent data generator that generates a training program for each of the one or more categories based on efferent pathways corresponding to the category and training materials corresponding to the category.

Claims

1. A resuscitation training program generation system comprising:

(a) at least one sensor configured to collect patient data; and

(b) a database server in communication with the at least one sensor and comprising at least one microprocessor, wherein the at least one microprocessor is configured to execute;

an acquisition section that acquires resuscitation event data on a cardiac arrest of a patient in an institution from the collected patient data and acquires resuscitation event data of other patients in the same institution from a resuscitation event data storage;

an event categorization section that analyzes matrix data from a matrix data storage that comprises a taxonomy of etiologies of resuscitation, acquires a categorization of the cardiac arrest from one or more categories within the taxonomy of etiologies of resuscitation based on the matrix data, and creates an acquired categorization;

an afferent data generator configured to read a plurality of afferent pathways based on the acquired categorization, combine the collected patient data with the resuscitation event data of other patients to form updated resuscitation event data, and create generated afferent data using the plurality of afferent pathways and the updated resuscitation event data;

an efferent data generator configured to read a plurality of efferent pathways from an efferent category storage based on the acquired categorization to create generated efferent data, acquire training materials from a training materials storage based on the acquired categorization, and organize and modify the acquired training materials to address resuscitation roles and patient units in the institution; and

generate a training program based on the generated efferent data, the generated afferent data, the updated resuscitation event data, and the organized and modified training materials.

2. The resuscitation training program generation system of claim 1, wherein the taxonomy of etiologies of resuscitation is arranged into a plurality of hierarchical levels, and the acquired categorization comprises categories from more than one of the plurality of hierarchical levels.

3. The resuscitation training program generation system of claim 1, wherein the efferent data generator further generates summary data specific to the patient and a summary response based on the summary data.

4. The resuscitation training program generation system of claim 3, wherein the case-specific response comprises one or more of structured debriefing, feedback data, a risk management response, or institutional response data.

5. The resuscitation training program generation system of claim 3, wherein the summary response comprises one or more of new policies, new procedures, new protocols, a launch of targeted initiatives, purchase a new equipment, implementation of new equipment, specific training, or institutional special projects.

6. The resuscitation training program generation system of claim 3, wherein the event categorization section acquires the categorization by transmitting graphical user interface (GUI) data for displaying the matrix data in a hierarchical series of windows to a workstation and receiving a selection of the acquired categorization using the GUI data from the workstation.

12. The resuscitation training program generation system of claim 1, wherein the afferent data generator further reads general afferent pathways that are unrelated to the acquired categorization, and generates both related and general afferent data.

13. The resuscitation training program generation system of claim 1, further comprising a display in communication with the database server, wherein the efferent data generator controls the display in presenting the efferent data.

14. The resuscitation training program generation system of claim 4, wherein the training program is directed to the one or more of the structured debriefing, the feedback data, the risk management response, or the institutional response data of the case-specific response.

15. The resuscitation training program generation system of claim 5, wherein the training program is directed to the one or more of the new policies, the new procedures, the new protocols, the launch of targeted initiatives, the purchase of new equipment, the implementation of new equipment, the specific training, or the institutional special projects of the summary response.

7. A method of generating a resuscitation training program, the method comprising:

acquiring patient data using at least one sensor in communication with at least one microprocessor configured to detect and record the patient data, wherein the acquired patient data comprises resuscitation event data on a cardiac arrest of a patient in an institution;

combining the acquired patient data with resuscitation data of other patients in the same institution to form updated resuscitation event data using the at least one microprocessor;

providing a plurality of afferent pathways and efferent pathways to make up a resuscitation training continuous quality improvement (CQI) matrix based on the acquired patient data and the updated resuscitation event data, wherein the using the at least one microprocessor;

hierarchically categorizing resuscitation events into one or more hierarchical categories within the resuscitation training CQI matrix using the at least one microprocessor;

linking the one or more hierarchical categories of the resuscitation training CQI matrix with at least one of training materials, treatment algorithms, and special initiatives programs, using the at least one microprocessor; and

organizing and modifying the at least one training materials, treatment algorithms, and special initiatives programs to generate the resuscitation training program using the at least one microprocessor.

8. The method of claim 7, wherein the plurality of afferent pathways comprise collected data associated with events leading up to an instance of a cardiopulmonary arrest.

9. The method of claim 7, wherein the plurality of efferent pathways comprise efferent pathways associated with reactions to data included within the CQI matrix.

10. The method of claim 9, wherein the reactions occur in response to one of a specific event including at least one of a debriefing event and dashboard feedback, and summary data including at least one of changes to training, new special initiatives programs, and modifications to the treatment algorithms.

11. The method of claim 7, wherein the step of hierarchically categorizing resuscitation events into one or more hierarchical categories within the resuscitation training CQI matrix comprises presenting a taxonomy for describing a plurality of etiologies of cardiopulmonary arrest.