Skip to main content

DataLab for Clinical Care & Population Health

The DataLab for Clinical Care & Population Health utilizes epidemiology, research-design principles, biostatistics, and computational data-science methods to focus on the following areas of research:

  • Clinical outcomes and comparative effectiveness research
  • Health-systems research
  • Health-technology assessment
  • Quality assessment (QA), control (QC), and improvement (QI)
  • Dissemination and implementation science
  • Geospatial analysis
  • Disparities of care
  • Health policy
  • Economic analysis of health care

Clinically, our predominant focus is on pediatric conditions that require complex, multidisciplinary care — for example, cleft lip/palate and craniofacial anomalies. Our main effort in the lab is dedicated to the Allied Cleft & Craniofacial Quality-Improvement and Research Network (ACCQUIREnet), a multi-site, prospective observational study for which we are the coordinating and statistical support center.

The lab has been involved in many fruitful collaborations, including the following: Centers for Disease Control and Prevention (CDC) National Center on Birth Defects and Developmental Disabilities (NCBDDD); the European Registration Network (ERN); the International Consortium on Health Outcomes Measurement (ICHOM); AmericleftNSQIP–Pediatric; and others.

The lab also interacts frequently with other research programs at Duke, including the following: Duke Surgical Center for Outcomes Research (SCORES); Duke Center for Population Health Sciences; Duke Children’s Health and Discovery Initiative (CHDI); Duke-Margolis Center for Health Policy; Duke Global Health Institute (DGHI); Duke AI Health; Duke Center for Computational Thinking; +DataScience; Duke Forge; and the Duke Institute for Health Innovation (DIHI).

Work in the Lab

Opportunities for working with the lab are open to Duke University medical, nursing, and graduate school students and residents. These opportunities include basic collaboration on research projects, as well as longer-term 1- or 2-year associations as part of a formal research sabbatical.

Please note: You must be affiliated with Duke in order to work in the lab. We are unable to accommodate mentees from other institutions, and we are not presently hiring new staff.

Exposure to biostatistics or data science is encouraged, and experience with computer programming in Python or R is very helpful. Priority is given to students already holding an advanced degree in public health, epidemiology, statistics, or policy (or those concurrently enrolled in an advanced degree program).

Collaborate with Us

Are you interested in health-services research, especially as it pertains to surgical and complex, multidisciplinary care? Would you like to propose a collaboration? Please get in touch!

Contact Us

Alexander C. Allori, MD, MPH

Latest Publications

Apon, Inge, Carolyn R. Rogers-Vizena, Maarten J. Koudstaal, Alexander C. Allori, Petra Peterson, Sarah L. Versnel, and Jessily P. Ramirez. “Barriers and Facilitators to the International Implementation of Standardized Outcome Measures in Clinical Cleft Practice.” Cleft Palate Craniofac J 59, no. 1 (January 2022): 5–13.

Full Text

Tillis, Rose T., Reanna Shah, Hannah L. Martin, Alexander C. Allori, Jeffrey R. Marcus, and Dennis O. Frank-Ito. “A systematic analysis of surgical interventions for the airway in the mature unilateral cleft lip nasal deformity: a single case study.” Int J Comput Assist Radiol Surg 17, no. 1 (January 2022): 41–53.

Full Text

Suarez, Alexander D., Brad Taicher, Herbert Fuchs, Jeffery Marcus, Matthew Vestal, Mayumi Homi, Alexander Allori, and Eric M. Thompson. “Predictors of Blood Transfusion for Endoscopic Assisted Craniosynostosis Surgery.” J Craniofac Surg, December 17, 2021.

Full Text

Harrison, Conrad, Inge Apon, Kenny Ardouin, Chris Sidey-Gibbons, Anne Klassen, Stefan Cano, Karen Wong Riff, et al. “An innovative approach to develop, deploy and evaluate personalised, patient-centred, outcome measurement: an international, multicentered study with the CLEFT-Q Computerised Adaptive Test.” In Quality of Life Research, 30:S17–18, 2021.