UrogynCREST Program - Research

Deadline for Submissions: August 26, 2020

The NIH/NICHD-funded AUGS/DUKE Urogynecology Clinical Research Educational Scientist Training (UrogynCREST) program offers junior faculty (within approximately 7 years of fellowship) with a passion for research the chance to increase their knowledge of data science and analytics as well as develop a project that can be the basis of future research grants. This program aims to provide in-depth hands-on instruction for promising young physician-researchers in the field of pelvic floor disorders through a combination of online course work in data sciences and one-on-one instruction to design and complete an innovative research project.

The UrogynCREST program has four components:

Coursework: Participants use the online learning platform Sakai to access and complete their coursework. Courses are taught by experts in study design (Module 1, with 6 sessions); economic, psychometric, and decision-analytic studies (Module 2, with 3 sessions), and statistical techniques applicable in health services research with a focus on working with R (Module 3, which covers descriptive statistics, bivariate analysis, multivariable inferential statistics, propensity score matching, and instrumental variables). Course content consists of reading material, didactic videos by the faculty, group discussions, and assignments with feedback from faculty. Each session lasts 2 weeks, with 1 week to prepare assignments. There is a 2-week break between modules. In addition, participants take a self-paced Stanford Statistical Learning course and receive a certificate at successful completion.

Here’s what our inaugural class has said about their coursework:

“I enjoyed this topic [implementation science].I am so happy that it was included as this type of research was new to me and I find it fascinating.”

“This was very helpful for someone who hasn't utilized publicly available health care databases before.”

“I loved the lectures for this session [on systematic reviews], they were clear and very relevant.I thought the Q&A was a great way to test comprehension.”

“Nice assessment format. Not burdensome but really helped solidify some of the concepts.”

“I really appreciated learning how to use plot and line functions to visualize data. This lesson deepened my understanding of how to perform multivariable linear regression as well as linear regression more appropriately/accurately/effectively.”

“I recognize that [difficulties with assignments using R] may come from the varying background students have with exposure to statistical programs/calculations. As someone with very little of this background, the experience has been challenging.”

“This was a rather sophisticated topic. I'm not sure I necessarily mastered the concept but the exercises provided good opportunity to explore instrumental variables.”

Support from Mentors and Biostatisticians: Participants are matched with clinical mentors with expertise in database research, who work one-on-one with them to design and execute a research proposal in pelvic floor disorders. Ongoing interaction with the mentors ensures that projects adhere to the highest standards of scientific validity and remain on track. Participants work directly with a dedicated statistician/statistical programmer in the development of a Statistical Analysis Plan. Statisticians provide expert consultation and analytics support to help participants achieve their research objectives.

Current participants’ projects:

Prevalence and Predictive Features of Urosepsis in Elderly Women Undergoing Evaluation for Urinary Tract Infection
Characteristics of Urinary Tract Infections in Female Medicare Beneficiaries
Complications and Hospital Revisits Following Urogynecologic Surgery
Reoperation and Readmission Following Stress Incontinence Surgery
Is Urinary Incontinence Treatment Impacted by Aging?
Prediction of Postoperative Surgical Site Infection in Urogynecologic Surgery Incidence of Pelvic Organ Prolapse after Cystectomy

Access to Data: Participants access the most common and extensive national healthcare database of standard analytic claims files. The dataset can support a broad range of pelvic floor disorder research questions. It does not contain direct identifiers or prescription information. Data are accessed in Duke’s highly secure data analytics environment (PACE). Access to other publicly available datasets or working with datasets already obtained by participants is also possible in PACE. For more information about allowable datasets, please contact Cindy Amundsen (Program Director) or Rebecca Kameny (Program Coordinator).

Dissemination and Networking: Participants will present their research in front of peers, the biannual Advisory Committee meetings, as well as at scientific conferences such as AUGS. By the end of the program, they are expected to have at least one accepted or submitted manuscript of UrogynCREST-related research. Annual reports will be submitted to the NIH detailing participants’ progress. Networking among participants will also be encouraged throughout the program so that at the conclusion, participants have built the connections that will facilitate multi-center studies and collaboration on grant applications.

Timeline for 2020-2022 Participants

	Jan-Mar 2021	Apr-Jun 2021	Jul-Sep 2021	Oct-Dec 2021	Jan-Mar 2022	Apr-Jun 2022	Jul-Sep 2022	Oct-Dec 2022
Coursework for Skills Development
Concept Proposal for Protocol Design
Data Preparation
Data Analysis
Manuscript/Study Prep and Submission

Interested in applying? See below for more information:

Apply Now!

2019-2021 Participants

The UrogynCREST Advisory Committee has selected six enthusiastic and capable individuals from various institutions for the 2019 inaugural program year. The Committee had a very challenging task reviewing a very strong group of Junior Faculty applicants interested in pursuing additional education and training to conduct Health Services Research (the focus of this program). Thank you to all the applied, and we look forward to the next round of applicants in Fall 2020.