Joshua R. Vest, PhD, MPH, FACMI

Contact : joshvest@iu.edu

Access to information is a key prerequisite to effective care and service delivery.

Initiatives

Research Scientist, Clem McDonald Center for Biomedical Informatics, Regenstrief Institute
Interim Associate Dean for Research, Indiana University Richard M. Fairbanks School of Public Health
Professor & Vice-Chair of Health Policy & Management, Indiana University Richard M. Fairbanks School of Public Health

Dr. Joshua Vest is a health services researcher with an interest in the adoption and effective application of health information technology to organizational, clinical, and population health outcomes. Much of his work is focused on the adoption, utilization, impact, and policy issues of technologies that facilitate the sharing of patient information between different organizations. His work with health information exchange has ranged from organizational adoption and strategy to impact on outcomes such as readmission rates, repeat imaging, and costs. His 100+ peer-reviewed publications have employed a variety of research techniques from large-scale database analyses, to geographical information system mapping, to survey research, to qualitative focus groups and interviews. As a former local public health practitioner, Dr. Vest has a particular interest in effective public health information systems and the use of social determinants of health data.

Featured Projects

Predictive modeling for social needs in emergency department settings

(AHRQ)

Role: Principal Investigator

This project will develop a predictive model to identify patients in need of social services in the emergency department. Patient and provider focus groups will identify the best means of implementation.

Computable social factor phenotyping using EHR and HIE data

(AHRQ)

Role: Principal Investigator

This project compares three different approaches to patient social factor measurement: computable phenotypes, EHR-based screening questionnaire, and natural language processing. Each approach will be compare to an independently collected reference survey to establish sensitivity, specificity, and predictive value. Each approach will be further tested for predictive validity and assessed for potential bias in a sample of adult primary care patients in two states.

Highlighted Publications

Jan 19, 2022

Assessment of structured data elements for social factors

Publication: American Journal of Managed Care

doi: 10.37765/ajmc.2022.88816

Authors: Vest JR, Adler-Milstein J, Gottlieb LM, Bian J, Campion Jr TR, Cohen GR, Donnelly N, Harper J, Huerta TR, Kansky JP, Kharrazi H, Khurshid A, Kooreman HE, McDonnell C, Overhage JM, Pantell MS, Parisi W, Shenkman E, Tierney WM, Wiehe S, Harle CA

Aug 16, 2021