Joseph J. Frassica
Professor of the Practice
Title
Professor of the Practice, Institute for Medical Engineering and Science
Staff, Pediatric Critical Care, Massachusetts General Hospital
Photo: Joseph J. Frassica
Email
frassica [at] mit.edu
Phone
(617) 613-2395
Lab Phone
(617) 253-7818
Address

77 Main St.

Cambridge, MA 02142

Room
E-25
Joseph J. Frassica
Professor of the Practice
Title
Professor of the Practice, Institute for Medical Engineering and Science
Staff, Pediatric Critical Care, Massachusetts General Hospital

Degrees

  • MD in Medicine, Boston University
  • DDS in Dental Medicine, Case Western Reserve University
  • BA in Biology, University of Massachusetts, Boston

Residency

  • Boston Medical Center (Boston City Hospital)/Boston University – Anesthesiology
  • Boston Medical Center /Boston University – Pediatrics
  • Harvard University/Massachusetts General Hospital – Pediatric Critical Care

Bio

Joseph J. Frassica, MD serves as Professor of the Practice in the Institute for Medical Engineering and Science at MIT. He is also a member of the teaching and research staff of the Massachusetts General Hospital (Pediatric Critical Care) and serves as Pediatric Editor for the Journal of Intensive Care Medicine.

Dr. Frassica has served in multiple academic and industrial leadership roles. Most recently, Joe served as the Head of Philips Research for the Americas as well as Chief Medical Officer for Philips - North America. Prior to this appointment, Dr Frassica served as Chief Technology Officer, Chief Innovation Officer and Chief Medical Officer for Philips Connected Care and Healthcare Informatics Division. In these roles, Dr Frassica contributed significant clinical and technical insights to guide the advancement of highly distributed patient monitoring, alarm management and therapeutic devices including patient ventilators and defibrillators.  At Philips research, Dr Frassica and his Cambridge Lab team focused on the use of large-scale, high-resolution data to develop AI/ML-based predictive models, Clinical Decision Support, imaging analytics, interventional guidance and bacterial genomics. Under Dr. Frassica’s leadership the lab successfully leveraged several of these predictive models and algorithms into products including

  • A health system command center product aimed at improving health systems operational efficiency by incorporating real-time physiologic insight with operational awareness.  Multiple predictive algorithms underly the decision support that delivers this product’s operational insight
  • A real-time, cloud-based analytics platform.  This platform powers a real-time ICU CDS and visualization system and is now part of the Philips Reference Architecture
  • A molecular epidemiology system consisting of a platform combining bioinformatics and advanced genomic analysis with clinical informatics data.  This system is focused on detection and elimination of Hospital Acquired infection and antibiotic stewardship.

Dr. Frassica has also served in multiple leadership roles in academic medicine including: Chief Medical Officer at Holtz Children’s Hospital in Miami, Florida; Chief Medical Information Officer and Executive Medical Director of Aero-Medical Transport for Miami’s Jackson Health System; and Associate Chair for Clinical Affairs in the Department of Pediatrics and Professor of Clinical Pediatrics and Anesthesiology at the University of Miami, Miller School of Medicine; Chief of Pediatric Critical Care at UMASS/Memorial Medical Center and Associate Clinical Professor of Pediatrics and Anesthesiology at University of Massachusetts Medical School; Attending Pediatric Intensivist at Massachusetts General Hospital; Attending Anesthesiologist at the Massachusetts Eye and Ear Infirmary and Chief of Anesthesia at Franciscan Children’s Hospital in Boston.

Dr. Frassica received his Bachelor’s degree in Biology from the University of Massachusetts/Boston, his Doctor of Dental Surgery degree from Case Western Reserve University and his Medical Degree from the Boston University School of Medicine.  Dr. Frassica completed residencies in Anesthesiology and Pediatrics at the Boston Medical Center (Boston City Hospital)/Boston University and completed a Fellowship in Pediatric Critical Care at the Massachusetts General Hospital/Harvard Medical School.

Research Interests

Prof. Frassica’s work is focused is on these areas of special interest:

  • Development and distribution of large scale medical data sets as a resource for the creation of Healthcare AI
  • AI/ML based predictive analytics
  • Clinical informatics, genomics/bioinformatics, infectious disease
  • Medical ultrasound, interventional guidance, planning, and assessment

Some current projects center around:

  • Predictive algorithms for disease using high resolution clinical and physiologic data.
  • Clinical informatics and genomics to limit the spread of hospital acquired infections, multi-drug resistance and new pathogens within communities.
  • Development and distribution of AI/ML -based Ultrasound algorithms for diagnosis of traumatic injuries.
  • Examples of predictive models developed with multiple academic collaborators and his team at Philips include:

Dr. Frassica works closely with Prof. Roger Mark and the Laboratory of Computational Physiology on the ongoing MIMIC project as well as in the development of new high resolution data sources to support the use of data to create predictive algorithms and models.

Other Activities

  • Pediatric Editor, Journal of Intensive Care Medicine
  • Board of Directors,  Kendall Square Association

Selected Publications

Real-time infection prediction with wearable physiological monitoring and AI to aid military workforce readiness during COVID-19.

Conroy B, Silva I, Mehraei G, Damiano R, Gross B, Salvati E, Feng T, Schneider J, Olson N, Rizzo AG, Curtin CM, Frassica J, McFarlane DC.

Sci Rep. 2022 Mar 8;12(1):3797. doi: 10.1038/s41598-022-07764-6.

PMID: 35260671

Early prediction of hemodynamic interventions in the intensive care unit using machine learning.

Rahman A, Chang Y, Dong J, Conroy B, Natarajan A, Kinoshita T, Vicario F, Frassica J, Xu-Wilson M.

Crit Care. 2021 Nov 14;25(1):388. doi: 10.1186/s13054-021-03808-x.

PMID: 34775971

Utilizing machine learning to improve clinical trial design for acute respiratory distress syndrome.

Schwager E, Jansson K, Rahman A, Schiffer S, Chang Y, Boverman G, Gross B, Xu-Wilson M, Boehme P, Truebel H, Frassica JJ.

NPJ Digit Med. 2021 Sep 9;4(1):133. doi: 10.1038/s41746-021-00505-5.

PMID: 34504281

A rapidly deployable individualized system for augmenting ventilator capacity.

Srinivasan SS, Ramadi KB, Vicario F, Gwynne D, Hayward A, Lagier D, Langer R, Frassica JJ, Baron RM, Traverso G.

Sci Transl Med. 2020 Jun 24;12(549):eabb9401. doi: 10.1126/scitranslmed.abb9401. Epub 2020 May 18.

PMID: 32424018

A clinical prediction model to identify patients at high risk of hemodynamic instability in the pediatric intensive care unit.

Potes C, Conroy B, Xu-Wilson M, Newth C, Inwald D, Frassica J.

Crit Care. 2017 Nov 20;21(1):282. doi: 10.1186/s13054-017-1874-z.

PMID: 29151364

A practical algorithm to reduce false critical ECG alarms using arterial blood pressure and/or photoplethysmogram waveforms.

Zong W, Nielsen L, Gross B, Brea J, Frassica J.

Physiol Meas. 2016 Aug;37(8):1355-69. doi: 10.1088/0967-3334/37/8/1355. Epub 2016 Jul 25.

PMID: 27455375

Estimation of the patient monitor alarm rate for a quantitative analysis of new alarm settings.

de Waele S, Nielsen L, Frassica J.

Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:5727-30. doi: 10.1109/EMBC.2014.6944928

PMID: 25571296

Predicting respiratory instability in the ICU.

Ennett CM, Lee KP, Eshelman LJ, Gross B, Nielsen L, Frassica JJ, Saeed M.

Annu Int Conf IEEE Eng Med Biol Soc. 2008;2008:2848-51. doi: 10.1109/IEMBS.2008.4649796.

PMID: 19163299

Development and evaluation of predictive alerts for hemodynamic instability in ICU patients.

Eshelman LJ, Lee KP, Frassica JJ, Zong W, Nielsen L, Saeed M.

AMIA Annu Symp Proc. 2008 Nov 6;2008:379-83.

PMID: 18999006

A full list of Dr. Frassica’s publications can be found on PubMed.