HOLISTIC HOSPITAL PATIENT CARE AND MANAGEMENT SYSTEM AND METHOD FOR SITUATION ANALYSIS SIMULATION

• US 20150213223A1
• Filed: 04/09/2015
• Published: 07/30/2015
• Est. Priority Date: 09/13/2012
• Status: Abandoned Application

• Current Assignee: Pieces Technologies, Inc.
• Original Assignee: Parkland Center for Clinical Innovation
• Inventors: Amarasingham, Rubendran, Oliver, George R., Shah, Anand R., Siva, Vaidyanatha, Lucena, Brian O., Shah, Monal, Cherian, Praseetha, Ballard, Spencer, McGinn, Jason
• Application Number:
  US14/682,668
• Publication Number:
  US 20150213223A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

A holistic hospital patient care and management system comprises a data store to receive and store patient data including clinical and non-clinical data; a resource monitoring logic module to track real-time location and status of resources and supplies in a medical facility; a medical staff monitoring logic module to track real-time location and status of medical staff working at the medical facility; a patient monitoring logic module to track real-time location and status of patients admitted to the medical facility; a risk logic module to apply a predictive model to the clinical and non-clinical data, including patient, medical staff, and medical resource and supply location and status to determine at least one risk score associated with the patients; a situation simulation analysis logic module to determine a simulation result in response to a variable simulation parameter value and the real-time resource and supply, patient, and medical staff location and status.

Claims

1. A holistic hospital patient care and management system comprising:

a data store operable to receive and store data associated with a plurality of patients including clinical and non-clinical data, the clinical data are selected from at least one member of the group consisting of;

vital signs and other physiological data;

data associated with physical exams by a physician, nurse, or allied health professional;

medical history;

allergy and adverse medical reactions;

family medical information;

prior surgical information;

emergency room records;

medication administration records;

culture results;

dictated clinical notes and records;

gynecological and obstetric information;

mental status examination;

vaccination records;

radiological imaging exams;

invasive visualization procedures;

psychiatric treatment information;

prior histological specimens;

laboratory data;

genetic information;

physician'"'"'s and nurses'"'"' notes;

networked devices and monitors;

pharmaceutical and supplement intake information; and

focused genotype testing; and

the non-clinical data are selected from at least one member of the group consisting of;

social, behavioral, lifestyle, and economic data;

type and nature of employment data;

job history data;

medical insurance information;

hospital utilization patterns;

exercise information;

addictive substance use data;

occupational chemical exposure records;

frequency of physician or health system contact logs;

location and frequency of habitation change data;

predictive screening health questionnaires;

personality tests;

census and demographic data;

neighborhood environment data;

dietary data;

participation in food, housing, and utilities assistance registries;

gender;

marital status;

education data;

proximity and number of family or care-giving assistant data;

address data;

housing status data;

social media data;

educational level data; and

data entered by patients;

a resource and supply monitoring logic module configured to track real-time location and status of a plurality of medical resources and supplies in a medical facility;

a medical staff monitoring logic module configured to track real-time location and status of a plurality of medical staff working at the medical facility;

a patient monitoring logic module configured to track real-time location and status of the plurality of patients admitted to the medical facility;

at least one predictive model including a plurality of weighted risk variables and risk thresholds in consideration of the clinical and non-clinical data and configured to identify at least one medical condition associated with the plurality of patients;

a risk logic module configured to apply the at least one predictive model to the clinical and non-clinical data, including patient location and status, medical staff location and status, and medical resource and supply location and status, to determine at least one risk score associated with each of the plurality of patients, and to stratify the risks associated with the plurality of patients in response to the risk scores;

a situation simulation analysis logic module configured to accept a value for at least one variable simulation parameter and determine a simulation result in response to the variable simulation parameter value and the real-time resource and supply location and status, real-time patient location and status, real-time medical staff location and status, and the risk scores and medical conditions of the plurality of patients; and

a data presentation module configured to receive the value of the at least one variable simulation parameter and display the simulation results on a specified device.

2. The system of claim 1, wherein the specified device is selected from the group consisting of a mobile telephone, a laptop, a desktop computer, and a display monitor.

3. The system of claim 1, wherein the risk logic module further comprises a disease identification logic module configured to analyze the clinical and non-clinical data associated with a particular patient and identify the at least one medical condition associated with the patient.

4. The system of claim 1, wherein the risk logic module further comprises a natural language processing and generation logic module configured to process and analyze clinical and non-clinical data expressed in natural language, and to generate an output expressed in natural language.

5. The system of claim 1, wherein the risk logic module further comprises an artificial intelligence logic module configured to detect, analyze, and verify trends indicated in the clinical and non-clinical data and modify the plurality of weighted risk variables and risk thresholds in response to detected and verified trends indicated in the clinical and non-clinical data.

6. The system of claim 1, wherein the data presentation module is configured to display:

a list of medical resources and supplies, and status and location thereof;

a list of medical staff, and status and location thereof; and

a list of the plurality of patients, and status and location thereof.

7. The system of claim 1, wherein the medical resource and supply monitoring logic module is configured to determine the status of medical resources and supplies in response to the detected location thereof.

8. The system of claim 1, wherein the a situation simulation analysis logic module is configured to accept a value for at least one variable simulation parameter selected from the group consisting of number of beds available, number of medical staff available, number of patients admitted, amount of medical resources and supply available, number of medical equipment available, and simulation time period.

9. A holistic hospital patient care and management system, comprising:

a repository of patient data including clinical and non-clinical data associated with a plurality of patients updated and received from a plurality of clinical and social service organizations and data sources;

a plurality of presence detection sensors configured to detect a plurality of tags associated with a plurality of medical resources and supplies to enable real-time tracking location and status;

a plurality of presence detection sensors configured to detect a plurality of tags associated with medical staff to enable real-time tracking location and status;

a plurality of presence detection sensors configured to detect a plurality of tags associated with a plurality of patients to enable real-time tracking location and status;

at least one predictive model using clinical and social factors derived from the patient data to extract both explicitly encoded information and implicit information about the patient'"'"'s clinical and non-clinical data to identify at least one medical condition requiring medical care associated with the at least one patient;

a risk logic module configured to apply the at least one predictive model to the clinical and non-clinical data, including patient location and status, medical staff location and status, and medical resource and supply location and status, to determine at least one risk score associated with the at least one patient, and to stratify the patient'"'"'s risk associated with the at least one patient related to the at least one medical condition in response to the risk score;

a situation simulation analysis logic module configured to accept a value for at least one variable simulation parameter and determine a simulation result in response to the variable simulation parameter value and the real-time resource and supply location and status, real-time patient location and status, real-time medical staff location and status, and the risk scores and medical conditions of the plurality of patients; and

a data presentation module configured to receive as input the value of the at least one variable simulation parameter, and to display a simulation result on a specified device.

10. The system of claim 9, wherein the specified device is selected from the group consisting of a mobile telephone, a laptop, a desktop computer, and a display monitor.

11. The system of claim 9, wherein the risk logic module further comprises a disease identification logic module configured to analyze the clinical and non-clinical data associated with a particular patient and identify the at least one medical condition associated with the patient.

12. The system of claim 9, wherein the risk logic module further comprises a natural language processing and generation logic module configured to process and analyze clinical and non-clinical data expressed in natural language, and to generate an output expressed in natural language.

13. The system of claim 9, wherein the risk logic module further comprises an artificial intelligence logic module configured to detect, analyze, and verify trends indicated in the clinical and non-clinical data and modify the plurality of weighted risk variables and risk thresholds in response to detected and verified trends indicated in the clinical and non-clinical data.

14. The system of claim 9, wherein the data presentation module is configured to display a list of nurses, physicians, patients, medical resources, supplies, and equipment, and status and location of each entry in the list.

15. The system of claim 9, wherein the medical resource and supply monitoring logic module is configured to automatically determine the status of medical resources and supplies in response to the detected locations of the medical resources and supplies in relation to detected locations of the plurality of patients.

16. A holistic hospital patient care and management method, comprising:

receiving real-time patient data including clinical and non-clinical data associated with a plurality of patients admitted to a hospital;

applying a set of at least one predictive model using clinical and social factors derived from the patient data to extract and translate both structured and unstructured information about the patient'"'"'s clinical and non-clinical data to identify at least one patient having at least one medical condition requiring medical care;

receiving real-time location data from a plurality of RFID sensors configured to detect a plurality of RFID tags associated with a plurality of patients, medical staff, and medical resources and supplies;

accessing the patient data associated with the plurality of patients, pre-processing the patient data, including patient location, medical staff location, and medical resource and supply location, and applying a predictive model to analyze the patient data for at least one patient;

receiving a value for a variable simulation parameter and determine a simulation result in response to the real-time location and status of the patients, medical staff, and medical resources and supplies; and

presenting the simulation result on a specified device.

17. The method of claim 16, wherein presenting the simulation result on the specified device comprises presenting on a specified device selected from the group consisting of a mobile telephone, a laptop, a desktop computer, and a display monitor.

18. The method of claim 16, further comprising analyzing the clinical and non-clinical data associated with a particular patient and identifying the at least one medical condition associated with the patient.

19. The method of claim 16, further comprising processing and analyzing clinical and non-clinical data expressed in natural language, and to generate an output expressed in natural language.

20. The method of claim 16, comprising detecting, analyzing, and verifying trends indicated in the clinical and non-clinical data and modifying a plurality of weighted risk variables and risk thresholds used in the predictive model in response to detected and verified trends indicated in the clinical and non-clinical data.

21. The method of claim 16, wherein receiving a value for a variable simulation parameter comprises accepting a value for at least one variable simulation parameter selected from the group consisting of number of beds available, number of medical staff available, number of patients admitted, amount of medical resources and supply available, number of medical equipment available, and simulation time period.