Murray Pollack, MD, MBA
Short Bio: Murray M. Pollack, MD, MCCM
I am an outcomes researcher, pediatric critical care medicine specialist, a pioneer in this subspecialty, an experienced administrator, and mentor. My major focus has been measuring severity of illness and applying these methodologies to investigations of pediatric critical care, quality of care, emergency medicine, and neonatology. My major contributions include
the first pediatric demonstration that variability in crude mortality rates could be adjusted for severity of illness enabling the use of standardized morality ratios for quality assessment,
development of pediatric measures of severity of illness (PRISM, PRISM III, PRISM IV, PSI, PRISA), development of measures of ICU efficiency,
the first demonstration of the superiority of pediatric ICUs compared to adult ICUs for the care of children,
the investigation of quality factors for Pediatric ICUs including the first objective evidence that improved outcomes were associated with intensivists and worse outcomes with night-time resident-only coverage,
the investigation of quality factors in Pediatric Emergency Departments,
the development of a new and an increasingly utilized measure of morbidity, the Functional Status Scale (FSS) which has the potential to change the outcome paradigm for pediatric large-scale pediatric investigations.
simultaneously predicting multiple outcomes states - morbidity as well as mortality from critical care.
My current efforts major efforts are twofold. First, I am developing the first dynamic risk methodology suitable for bedside use in individual patients. Second, I am developing the conceptual framework for defining a new physiological state that could change the way we identify patients at risk for critical illness. Currently these efforts utilize existing electronic health record databases and artificial intelligence, as well as more routine bio-statistical methods. Most pertinent to this proposal, my team and I have developed a new conceptual framework for severity of illness pertinent to this era of electronic health records and artificial intelligence analytic methods. This method, the Criticality Index uses a new outcome, probability of receiving intensive care, as the relevant outcome for all hospitalized children. It uses measure of physiology, therapy, and intensity of care as core independent variables and machine learning. We are able to predict care needs up to 30 hours in the future.
I am currently at Children’s National Hospital.
Bibliography: https://www.ncbi.nlm.nih.gov/sites/myncbi/murray.pollack.1/bibliography/48189821/public/?sort=date&direction=descending
Financial relationships
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Type of financial relationship:There are no financial relationships to disclose.Date added:10/22/2024Date updated:10/22/2024