Source: MAGIC MEDICAL SOLUTIONS, LLC submitted to NRP
COVID-19 RAPID RESPONSE: TELE CASE ASSESSMENT RESPONSE ENGINE ICU (TELECARE-ICU)
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
COMPLETE
Funding Source
SMALL BUSINESS GRANT
Reporting Frequency
Annual
Accession No.
1024024
Grant No.
2020-33610-32755
Cumulative Award Amt.
$99,000.00
Proposal No.
2020-06040
Multistate No.
(N/A)
Project Start Date
Sep 1, 2020
Project End Date
Apr 30, 2021
Grant Year
2020
Program Code
[8.6]- Rural & Community Development
Recipient Organization
MAGIC MEDICAL SOLUTIONS, LLC
100 RICE MINE ROAD LOOP STE 302
TUSCALOOSA,AL 354062416
Performing Department
(N/A)
Non Technical Summary
ProblemThe disaster that is the COVID 19 pandemic will leave large numbers of chronically ill patients requiring treatment for lung scarring, neurological conditions, mental health, etc. for many years to come. This will continue to place an enormous burden on our already overly stressed health care resources and personnel This is especially true for rural hospitals and clinics which have limited resources and expertise to deal with complex cases and critical care patients.There was already a critical shortage of ICU beds and healthcare specialists.The COVID-19 pandemic has exasperated this problem.SolutionProposal Magic Medical Solutions (proposes the TELE Case Assessment Response Engine ICU (TELECAREICU), which is an intelligent, mobile platform to provide comprehensive and automated ICU patient monitoring and assessment. It is a machine learning algorithm that takes inputs from standard monitoring devices and information from the patient's EHR, physical findings, and ancillary monitoring systems to provide automated assessments of their condition.Monitoring is continuous and the TELECARE ICU dynamically updates the patient's status on a dashboard in real-time to alert local healthcare workers and remote telemedicine consultants of changes in their condition. The solution also integrates with existing telehealth capabilities so that specialists can be teleconferenced in as needed.BenefitsThis effort will decrease the demand on existing hospital and healthcare services, reduce the cost of care, measure treatment adherence, identify disease worsening, improve accessibility to services, and extend the reach of services to remote locations. TELECARE ICU will also help create local and remote medical jobs, keep rural healthcare facilities operational, allow a precision medicine approach to complex medical management, and, as a byproduct, keep patients in their local hospitals.Market OpportunityOver the last decade, emergency department (EDs) visits increased by 26%. Meanwhile, the number of EDs declined 9% and hospitals closed 198,000 beds. The math is easy and very concerning. ED crowding was inevitable and has become highlighted with the COVID-19.Given these factors, there is an inherent need for intelligent monitoring, diagnostics, and intervention tools for the commercial market. This is true for pre-hospital transport, ED, ICU,and chronic care in rural hospitals.
Animal Health Component
25%
Research Effort Categories
Basic
(N/A)
Applied
25%
Developmental
75%
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
8057410110125%
8057410208075%
Knowledge Area
805 - Community Institutions, Health, and Social Services;

Subject Of Investigation
7410 - General technology;

Field Of Science
1101 - Virology; 2080 - Mathematics and computer sciences;
Goals / Objectives
The overall goal of this Phase I effort is to determine the feasibility of developing a mobile ICU for rural hospitals that can automatically monitor and manage COVID-19 patients along with other critical care patients.The first goal will be to develop and implement a prototype closed-loop BN machine learning patient monitoring model for COVID-19 for processing vital signs data, laboratory data, ventilator support data, patient history, bio-surveillance, and physical exam information.The development and evaluation of this model will be based on utilizingthe latest patient management protocols along with real/simulated data sets.The second goal is to develop an architecture that supports the integration and real-time processing of the various components for the automated ICU patient management solutions.This encompasses vital sign monitoring devices, BN models, multi-layer dashboards, HIPAA compliant database, and communications hierarchy for on-call consultant availability.
Project Methods
TELE Case Assessment Response Engine ICU (TELECAREICU), which is an intelligent, mobile platform to provide comprehensive and automated ICU patient monitoring and assessment. It is a Bayesian Network (BN) machine learning algorithm that takes inputs from standard monitoring devices and information from the patient's EHR, physical findings, and ancillary monitoring systems to provide automated assessments of their condition. Monitoring is continuous and the TELECARE-ICU dynamically updates the patient's status on a dashboard in real-time to alert local healthcare workers and remote telemedicine consultants of changes in their condition. The solution also integrates with existing telehealth capabilities so that specialists can be teleconferenced in as needed.

Progress 09/01/20 to 04/30/21

Outputs
Target Audience:TELECARE-ICU is a stand-alone solution integrated with an EHR, for the assessment and management of patients with infections (such as COVID or Sepsis) to overcome the lack of sub-specialty and critical care expertise for pre-hospital transport, ED, ICU, and chronic care in rural hospitals.The target audience is all healthcare workers involved in the management and care of critical care patients in rural hospitals.In addition, TELECARE-ICU can be used is hospitals in metropolitan areas that are dealing with the surge of critically ill patients. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided? Nothing Reported How have the results been disseminated to communities of interest?We will be publishing our results in the coming year. What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? During the Phase I effort, we developed several foundational components of the TELECARE-ICU system to demonstrate its feasibility.The key component was the Bayesian Network - Decision Support System (BN-DSS) algorithm that was able to successfully detect and diagnose several types of infections using an initial data set.The BN-DSS algorithm merges expert knowledge and experimental datasets. The framework provides for cause and effect associations between variables and trains them with probability that indicates the level in which one variable is likely to sway another. ?During Phase I we also developed initial healthcare dashboards and an initial design for the COVID-Somnia System.

Publications