|Incorporating Learning Effects into Medical Device Active Safety Surveillance Methods|
NIH/NHLBI R01 HL149948-01Dec 1, 2019 - Nov 30, 2023
Role Description: This proposal seeks to extend the previously validated, open-source, active, prospective device safety surveillance tool, by developing and validating robust learning curve (LC) detection and quantification algorithms, designed to simultaneously account for the effects at the operator and institutional levels.
|Surveillance and prediction of post-acute kidney injury outcomes using digital phenotyping|
UCSD Academy of Clinician Scholars Oct 1, 2019 - Sep 30, 2020
Role Description: Acute Kidney Injury (AKI) occurs in 2 – 5% of hospitalized patients and nearly 70% of critically ill patients. AKI is associated with increased inpatient mortality, hospital length of stay, and post-discharge morbidity. Moreover, its effects may be long-lasting and are associated with cognitive dysfunction, frailty, and reduced quality of life. More real-time information is necessary from patients in the home setting post hospital discharge. This study leverages predictive modeling and digital phenotyping to track post-AKI cognitive and functional changes and their relationship to patient-centered outcomes. Digital phenotyping allows for unobtrusive, continuous monitoring thereby delivering actionable risk predictions conducive to tailored interventions.
|Diagnosing “Chemo Brain” Using Digital Phenotyping|
University of California San Diego Health Sciences Academic Senate GrantDec 1, 2018 - Dec 1, 2019
Role Description: The overall objective of this project is to develop methods of identifying chemotherapy related cognitive impairment. Up to 70% of patients have reported significant reduction in cognitive function, colloquially termed “chemo brain,” from chemotherapy. Studying these changes can be difficult within the clinical setting due to the resource requirements. We will evaluate the feasibility of using “digital phenotyping,” assessing the interaction between a patient’s health and their technology use, to diagnose chemotherapy related cognitive impairment. We will use multiple data streams from passive/wearable sensors to assess their daily cognitive status.
|Assessing Cognitive Status of Patients with Cirrhosis Using Digital Phenotyping|
University of California San Diego Health Sciences Academic Senate GrantMay 1, 2018 - May 1, 2019
Role Description: The overall objective of this project is to develop methods of identifying early hepatic encephalopathy before the patient requires hospitalization. More specifically we will evaluate the feasibility of using “digital phenotyping,” assessing the interaction between a patient’s health and their technology use, to diagnose hepatic encephalopathy. We will use multiple data streams from a FitBit and the patient’s routine interactions with their regular smartphone to assess their daily cognitive status.
|Assessing efficacy of passive and active forms of expressive art therapy in inpatient services|
University of California San Diego Health Sciences Academic Senate GrantJun 1, 2017 - May 31, 2018
|Automated Surveillance and Intervention among Patients with Liver Cirrhosis|
Department of Veterans Affairs HSR&D IIR 13-052Jun 1, 2014 - Jun 1, 2018
|San Diego Biomedical Informatics Education & Research (SABER)|
NIH T15LM011271Jul 1, 2012 - Jun 30, 2022
Role Description: Role Description: Director, Summer Internship Program