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Smart Diagnostics Ecosystem for COVID-19 Disease Management

COVID-19 has had a severe and disruptive impact on nearly every segment of our society, but has had a disproportionate impact on the underserved and impoverished. As we enter the second wave of COVID-19, we can take advantage of real-time patient and community level information to drive improved diagnostic testing accuracy and severity information using point-of-care diagnostic tools with embedded artificial intelligence and cloud connected databases. We have assembled a world class team of partners with deep expertise and proven track records in mobile health apps, community clinic patient care, programmable diagnostic instrumentation, cloud connected database management, and regulatory expertise. Our team is positioned to nucleate the smart diagnostic ecosystem of the future. We have already developed an award-winning platform to digitize biology using sensors that learn. Further, this AI-linked universal diagnostic system has already been validated through a large series of clinical studies and has been used to identify signatures for early disease detection and disease severity, including COVID-19 within Brooklyn Family Health Center. This smart diagnostic ecosystem is positioned to provide the most comprehensive COVID-19 clinical decision support system. The COVID-19 decision support system covers numerous diagnostic/prognostic outcomes across several patient settings. A mobile application allows the user to input critical data and receive a severity score in real-time.

5 min Video of Capstone Project

Elevator Pitch

Cloud connected universal diagnostics platform, software, and FQHCs nucleate the most comprehensive COVID disease management system.

Challenge Goals

A smart diagnostics ecosystem has been established that links the award winning programmable medical microdevice technology to cloud-based databases alongside clinically validated decision support tools that are optimized for use in Federally Qualified Health Centers. These premarket capabilities through this HHS design-a-thon effort are now being linked to build digital solutions for data capture, harmonization, and reporting from COVID-19 diagnostic tests using both laboratory and non-laboratory data allowing for the secure transmission of results to local, state, and national public health authorities. The solution here developed greatly facilitates achievement of all the goals and outcomes set forth by the challenge.

 

Feasibility

Significant traction has been made on the point of need diagnostics, clinical implementation, and database linkage fronts. Commercial ready dx-platforms alongside cartridges, assay, and control software are in place. Several setting-specific COVID-19 severity scores have been developed and validated in major community clinics. These capabilities are documented in two recent high-profile peer review publications. This fully-integrated smart dx ecosystem takes into account patient demographics data from a self-reporting app as well as test diagnostic data from the dx device. Moving forward, there is strong potential to develop a minimum viable product that links these diagnostics to the various databases within 2 weeks of program onset.

Design

Smart diagnostic system is modular and scalable by design. Intuitive smartphone app and cloud based interfaces between EHR allows health data information to sync with HIPAA compliance. The data reporting module is designed with H-S specification for both Lab and Non-lab test data reporting. The device design is customizable as a point-of-care diagnostic tool that is suitable for the measurement of biomarkers use in determining severity of Covid19 patients. Deployment of system makes it accessible to an integrated test and scoring system for use at healthcare provider/test site and would help better triage patients allowing scarce healthcare resources for the patients most at risk. The entire system can be deployed at a very large scale.

Innovation

COVID-19 disease management including disease screening, patient exposure, and severity assessment requires clinical testing from multiple diagnostic platforms. The access to the complete diagnostic infrastructure required to manage this disease places extreme burden on care providers, especially with respect to logistics and data management. The ‘Smart Diagnostics Ecosystem for COVID-19 Disease Management’ introduces a universal platform to digitize biology as the front end of remote testing that allows for the early capture of disease from complex biomarker signatures for the first time. These signatures are linked to AI decision tools that transmit results to state and federal databases, transforming and simplifying disease management.

Flexibility & Scalability

This smart diagnostics ecosystem has a screening app for iPhone/Android, simplifying distribution to patients. The cloud-based interface for data management and distribution is highly scalable in HIPAA compliant servers on either Azure or Amazon Web Services. FHIR & HL7 based integration with EMR systems makes it compatible with almost all of the health systems nation-wide. This ecosystem can help health systems at the community-level to utilize the clinical decision support system for patient prognosis and provide relevant support. The impact of this point-of-care diagnostic platform, biomarker-based disease severity scores, and improved clinical decisions using Telehealth or in hospital admittance will be tremendous for the population.

Sustainability & Extensibility

This AI-linked universal diagnostic system has already been validated through a large series of clinical studies and has been used to identify signatures for early diagnosis and prognosis, including COVID-19 within Brooklyn Family Health Center. This smart diagnostic ecosystem is positioned to provide the most comprehensive COVID-19 clinical decision support system across standard EHR. The COVID-19 decision support system covers numerous diagnostic/prognostic outcomes across several patient settings. A mobile application allows the user to input critical data and receive a severity score in real-time. The team has started working on Lab & Non-Lab Data specifications being modeled for HHS data sharing with state and federal entities.

Team & Collaboration

A world class team has been assembled with deep expertise and proven track records in mobile health apps, patient care, programmable diagnostic instrumentation, cloud connected database management, and regulatory expertise. Importantly, the chosen team integrates leadership from one of largest Federally Qualified Health Centers that was involved in treatment of patients from a COVID-19 epicenter (i.e. Brooklyn, NY). Further, the organization includes participation from members that have strong regulatory experience in the area of in vitro diagnostics as well as digital health apps/devices. All team members have worked together closely previously and are, thus, in a position to move forward aggressively on this essential program.

Additional Comments

High-profile efforts of team have been covered through a series of recent news releases. Representative examples are listed below:

What Team(s) contributed to this Capstone Project?

New York University: Smart diagnostics platform recognized by largest award from American Association of Clinical Chemistry. Leadership in running large clinical studies to validate new biomarker panels

OraLiva: Strong IP coverage of the diagnostics platform, commercial experience in development, distribution of diagnostic devices and clinical services

Latham BioPharma Group: Strong experience in the facilitation, program management alongside deep regulatory experience to support public-private partnerships in bioscience

Brooklyn Family Health Center: One of largest Federally Qualified Health Centers in the US. Provides direct clinical experience in treating patients in rural settings

Mobisoft Infotech: Top digital health technology dev company

If you are using patient data, are you using real patient data or mock data? Please use MOCK patient data only

MOCK data

edited on Nov 28, 2020 by John T McDevitt
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John T McDevitt Dec 1, 2020

Thanks for your interest on our programs... See below link for more information: https://www.nyu.edu/about/news-publications/n...-score-app.html

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John T McDevitt Dec 1, 2020

Managing COVID-19 With a Clinical Decision Support Tool in a Community Health Network: Algorithm Development and Validation

https://www.jmir.org/2020/8/e22033/

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John T McDevitt Dec 3, 2020

Article describing use of clinical decision support tool in Federally Qualified Health Centers

https://www.newswise.com/coronavirus/app-dete...ticle_id=732579

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Below provided are the links to the various member entities of this program:

dental.nyu.edu/faculty/biomaterials/mcdevitt-research-group.html

https://nyulangone.org

https://www.lathambiopharm.com

https://nyulangone.org/locations/family-healt...-at-nyu-langone

https://mobisoft.co/

https://oraliva.com/

Reply 0

Shail Sinhasane Dec 4, 2020

Correct website for Mobisoft is https://mobisoftinfotech.com

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Sophia B Liu Dec 8, 2020

This idea has been advanced to the current phase

People's Choice Voting Extended

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Sophia B Liu Dec 8, 2020

This idea has been advanced to the next phase

People's Choice Voting Extended

Reply 0

Andrea Pitkus Dec 14, 2020

Trying to understand if there are preconditions met by other software. (In general) 1. How to collect AOEs, from ordering provider/patient/specimen collector 2. Integrate into app/LIS or other information source for patient to be married to results of IVD test device/system 3. All transmitted to public health (ELR) 4. All transmitted to HHS (may be met by 3).

Will your approach support all 4 or only portions of above for "tracking lab results"? (Looks like you may have capabilities for some of these)

Do you support LIS based reporting of ELR in HL7 v2.51 (per the MU IG)? For patient performed results are they routed to the physician who is required to report via electronic Case Reporting (eCR) by law? How would your approach support LISs or labs that don't have API functionality?

Are LOINC, SNOMED CT and other codes systems supported at the point of origin or downstream as in your diagram to meet requirements? How are test kit/system UDIs captured and reported

How are CLIA testing requirements met in your system?

Curious about how your approach would "automatically" collect patient performed test results like the recent Lucira EUA? How about for Antigen or Antibody card (like pregnancy tests). How are result values read and assigned appropriate LOINC and SNOMED CT codes depending on the results/values for appropriate transmission to the provider and public health? How are AOEs and other patient provided info collected and married with result values? How is it used in laboratories/Point of Care testing scenarios as in the Lucira EUA?

Looks like you have a great clinical decision support/AI predictor, but interested in the how you'd collect and manage the data in both traditional lab and non traditional testing (including patient performed) settings and report to providers and public health?

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