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Research Support Infrastructure: Implementing A Clinical Research Coordinating Center, Julio A. Ramirez, Paula Peyrani, William A. Mattingly, Forest W. Arnold, Timothy L. Wiemken, Robert R. Kelley, Leslie A. Wolf, Ruth M. Carrico, The Clinical Research Coordinating Center Team Apr 2018

Research Support Infrastructure: Implementing A Clinical Research Coordinating Center, Julio A. Ramirez, Paula Peyrani, William A. Mattingly, Forest W. Arnold, Timothy L. Wiemken, Robert R. Kelley, Leslie A. Wolf, Ruth M. Carrico, The Clinical Research Coordinating Center Team

The University of Louisville Journal of Respiratory Infections

Insufficient infrastructure is one of the challenges facing investigators in the field of clinical research. At the University of Louisville (UofL) Division of Infectious Diseases, we developed a multidisciplinary coordinating center with the aim to support investigators in all aspects of the clinical research process. The objective of this article is to describe the composition and the role of the different units of the UofL Clinical Research Coordinating Center. The different components of the Center can serve as a template for institutions interested in developing a clinical research support infrastructure.


Race And “Hotspots” Of Preventable Hospitalizations, Caryn N. Bell, Janice V. Bowie, Roland J. Thorpe Jr. Jan 2018

Race And “Hotspots” Of Preventable Hospitalizations, Caryn N. Bell, Janice V. Bowie, Roland J. Thorpe Jr.

Journal of Health Disparities Research and Practice

Abstract

Preventable hospitalizations (PHs) are those for ambulatory care-sensitive conditions that indicate insufficiencies in local primary healthcare. PH rates tend to be higher among African Americans, in urban centers, rural areas and areas with more African American residents. The objective of this study is to determine geographic clusters of high PH rates (“spatial clusters”) by race. Data from Maryland hospitals were utilized to determine the rates of PHs in zip code tabulation areas (ZCTAs) by race in 2010. Geographic clusters of ZCTAs with higher than expected PH rates were identified using Scan Statistic and Anselin’s Local Moran’s I. 10 PH …