CTSI 2018-2020 KL2 Mentored Career Development Award Scholars
The Clinical and Translational Science institute is pleased to announce that four early career faculty have been selected to receive the CTSI KL2 Mentored Career Development Award for 2018-2020. The KL2 Mentored Career Development Program is funded by the NIH NCATS Clinical and Translational Science Award and by institutional funds and is similar to other NIH K series career development awards.
Our new KL2 Scholars, their projects, and their primary mentors are:
Erin Barnes, MD
Instructor, Internal Medicine – Infectious Diseases
Improving Identification of Injection Drug Use Associated Endocarditis in the Health Record
The study of injection drug use endocarditis has been limited by the ability to reliably and efficiently identify these cases in the electronic medical record. This project will explore combining a wide variety of administrative codes and patient characteristics through logistic regression with an approach examining the free text of physician notes. Dr. Barnes will develop, validate, and nationally deploy an efficient case identification and data extraction tool for IDU-IE so that meaningful analysis can result in evidence-based treatment.
Primary Mentor: David Herrington, MD, Professor of Cardiovascular Medicine
Amber Brooks, MD
Associate Professor, Anesthesiology
Development of Behavioral eHealth Treatment for Obese, Older Adults with Chronic Low Back Pain
Treatment of pain with opioid and non-opioid medications in older adults is often limited due to the higher prevalence of side effects in this population. Behavioral treatment programs are a viable nonpharmacological therapy approach for addressing pain conditions in older adults. The purpose of this study is to develop a three-part eHealth Platform that will 1) automatically identify patients likely to benefit from behavioral treatments and deliver tailored communications via the my WakeHealth portal 2) utilize animation to convey health information and 3) guide the patient to existing evidence-based eHealth treatment tools to help manage their low back pain. We will assess the feasibility (usability and acceptability) of the eHealth platform in a single-arm pragmatic pilot study. treatment tools.
Primary Mentor: Robert W. Hurley, MD/PhD, Professor of Anesthesiology
Deepak Palakshappa, MD
Assistant Professor, General Internal Medicine
The Effect of Food Insecurity on Obesity Treatment and Outcomes
Food insecurity, defined as the lack of consistent access to enough food for an active and health life, is a major public health problem that affects over 40 million Americans, disproportionately impacts low-income and minority households, and is associated with numerous negative health outcomes. Although prior studies have evaluated if food insecurity leads to increased weight and obesity, little is known about how food insecurity affects individuals who are obese. The goal of this study is to determine if food insecurity is an independent risk factor for developing medical comorbidities from obesity and advance the understanding of how food insecurity impacts obesity management.
Primary Mentor: Mara Vitolins, Dr. PH., MPH, RDN, Professor, Public Health Sciences – Epidemiology and Prevention
Jaime Speiser, PhD
Assistant Professor, Public Health Sciences, Biostatistics
Random Forest Methodology for Longitudinal Outcomes in Aging
Modern datasets are complex, and innovative approaches for developing prediction models are needed to address understudied issues such as longitudinal outcomes. Using a novel BiMM forest methodology, Dr. Speiser will develop a machine learning method for clustered and longitudinal binary outcome prediction which incorporates variable selection. The proposed methodology will provide insight about the relationship between predictors and outcome, and will offer a procedure for reducing the number of predictors needed to develop models. This work is being developed to improve decision support tools for predicting dynamic changes in mobility disability over time in a geriatric population, but has broad applicability. Accurate predictions of mobility disability will aid in decisions about care (e.g. whether assisted living is needed) and have the potential to improve quality of life in older adults (e.g. implementing preventative interventions), thereby lessening the burden of disability.
Primary Mentor: Edward Ip, PhD, Professor, Public Health Sciences, Biostatistical Sciences.
Please join us in congratulating these early career faculty on receiving this award.