The University of Rochester (UR) has a decades-long distinguished history in innovative clinical research education, enhanced substantially since 2006 with the establishment and focus of the University of Rochester Clinical and Translational Science Institute (UR-CTSI). Building historically on the groundbreaking concept of medical education based on the biopsychosocial model starting in the 1940s with Engel and Romano, the UR has continued to create paradigm-shifting educational reform integrating research and systematic evaluation with problem-based medical education, community engagement and population health, and mentored field experience. This culture of creativity and innovation in pre-doctoral research training supported through prior TL1 awards is embodied by an institutional focus on research training from molecules to populations. Through this and other means, the UR-CTSI has created an institution-wide focal point for multidisciplinary research training. Further, UR-TL1-supported students in the 50+ year-old UR MD/PhD training program (Medical Scientist Training Program (MSTP)) have taken advantage of the UR-CTSI's PhD program in Translational Biomedical Science and other multidisciplinary graduate training options. In addition, the UR-TL1-supported Academic Research Track (ART) further provides a pipeline of clinical and translational research-prepared academic physicians through a comprehensive research training and mentoring experience. Predoctoral training is a priority within Rochester's CTSI, is well-integrated, and has successfully generated productive, employed clinical researchers, both within and outside of academics. The vision for the UR-TL1 in the next era of UR-CTSI is inspired by several critical developments in the healthcare and institutional landscape of Rochester and the US more broadly, namely: 1) Implementation of national health care reform prioritizing evidence-based practice and population health, 2) rapid emergence of data science and ?Big Data? analytic opportunities and methodological approaches to healthcare and population health, and 3) emergence of precision medicine research and healthcare delivery using phenotype- genotype and biomarker-informed science. The goals for the coming five years include 1) to grow a pipeline of clinical and translational researchers able to address new and emerging scientific and methodological domains; 2) to enhance experiential and didactic learning through new training opportunities and partnerships that emphasize team science; 3) to stimulate creative and novel population health research that involves leveraging new tools and methods through establishing a University-wide Post-Doctoral Fellowship in Population Health; and 4) to rigorously evaluate the role of the UR-TL1 Training Program on the development of the clinical and translational research pipeline and disseminate learnings from the training program.
|Rosenberg, Alexander; Fucile, Christopher; White, Robert J et al. (2018) Visualizing nationwide variation in medicare Part D prescribing patterns. BMC Med Inform Decis Mak 18:103|
|Holland, Margaret L; Groth, Susan W; Smith, Joyce A et al. (2018) Low birthweight in second children after nurse home visiting. J Perinatol 38:1610-1619|
|Meng, Ying; Groth, Susan W (2018) Fathers Count: The Impact of Paternal Risk Factors on Birth Outcomes. Matern Child Health J 22:401-408|
|Meng, Ying; Groth, Susan W; Stewart, Patricia et al. (2018) An Exploration of the Determinants of Gestational Weight Gain in African American Women: Genetic Factors and Energy Expenditure. Biol Res Nurs 20:118-125|
|Selioutski, Olga; Grzesik, Katherine; Vasilyeva, Olga N et al. (2017) Evaluation of phenytoin serum levels following a loading dose in the acute hospital setting. Seizure 52:199-204|
|Piper, Keaton F; Tomlinson, Samuel B; Santangelo, Gabrielle et al. (2017) Risk factors for wound complications following spine surgery. Surg Neurol Int 8:269|
|Zand, Martin S; Trayhan, Melissa; Farooq, Samir A et al. (2017) Properties of healthcare teaming networks as a function of network construction algorithms. PLoS One 12:e0175876|