Editor profiles

Ron Hays, PhD, is a Professor in the UCLA Department of Medicine. He has served as a principal investigator for the Consumer Assessment of Healthcare Providers and Systems (CAHPS®) project at RAND since 1995. In addition, he teaches courses on health outcome measures at the UCLA School of Public Health. Dr. Hays is also the leader of the analysis core for the UCLA/Drew Research Center for Minority Aging Research (RCMAR), a research and mentoring program intended to reduce health disparities for older African Americans and Latinos by training and mentorship of minority faculty.

Dr. Hays specializes in patient-reported measurement development and evaluation, including measures of patient behavior, experiences with health care, and health related quality of life. He has published 582 peer-reviewed papers and 38 book chapters and was acknowledged as one of the most highly cited and influential scientific minds yearly from 2015-2019 by Thomson Reuters/Clarivate Analytics.

Chih-Hung Chang, PhD, is a psychometrician and health services researcher trained in research methodology and quantitative psychology. His research focuses on the integration of methodology and technology to advance clinical outcomes assessment and management across the continuum of care. Dr. Chang has extensive experience and expertise in patient-centered outcomes measurement and management in diverse populations and settings utilizing item response theory (IRT) and computerized adaptive testing (CAT). He has created a discipline called "Clinical Infometrics" that is a synthesis of measurement sciences, predictive analytics, evidence-based medicine and informatics to guide clinical decision making in real time and to improve symptom and disease management over time. Dr. Chang directs the Psychometrics-Informatics Laboratory (The pi Lab) at Washington University School of Medicine in St. Louis, which aims to integrate advanced psychometrics and evolving informatics to advance our understanding of participation and human health. The pi Lab focuses on the knowledge translation of measurement theory and data science methods to clinical applications.