Global Health Informatics

Global Health Informatics
Dr. Christophe G. Lambert's Research Team
Contact Info
WebsitesIn August 2014 I became a faculty member in the University of New Mexico Center for Global Health, Division of Translational Informatics and Department of Internal Medicine. My research areas include clinical research informatics, bioinformatics, and systems thinking. My current research focus is analyzing longitudinal healthcare data for predictive and preventative medicine, in collaboration with other members of the Observational Health Data Sciences and Informatics program. The OHDSI/OMOP common data model has been adopted to represent over 680M patients' electronic health and/or administrative claims records worldwide, enabling the development of a broad set of tools for the analysis of human health on these massive datasets. I am currently developing statistical and computational tools to compare treatment options and obtain better estimates of expected health outcomes despite large biases and confounding in the data, with a focus on bipolar disorder. In July 2016 I received an NIH NLM R21 award to research methods for observational comparative effectiveness research, and a PCORI award to compare bipolar disorder treatments and outcomes in large scale administrative claims data. We are currently using a database of over 1 million bipolar disorder patients to answer questions about the safety and effectiveness of bipolar disorder therapies both short term and over many years of treatment. In 2020, I received an R56 award from the NIH NIMH to investigate undiagosed and/or unrecorded PTSD, TBI, and self-harm through machine learning to determine the degree to which this phenomenon exists and how patients
In addition I perform bioinformatic analyses of genomics datasets with current projects in pediatric Malaria in collaboration with Dr. DJ Perkins in the Center for Global Health, projects analyzing the genetics of pediatric developmental delay, including Autism, as well as clinical research informatics and bioinformatics of COVID-19.