Chintan Pandya

Chintan Pandya, PhD, MPH, MBBS, is an Associate Research Professor in the Department of Health Policy and Management at the Bloomberg School of Public Health, Johns Hopkins University. His work centers on leveraging health information technology and clinical data to improve evidence generation, predictive modeling, continuous care, and population health outcomes.

Dr. Pandya holds a PhD from the University of Rochester (2016), an MPH from Stony Brook University (2009), and an MBBS from Gujarat University (2007), reflecting his interdisciplinary training in medicine, public health, and health services research.

His research spans health informatics, health equity, predictive modeling, and the application of secondary data in health policy. He investigates issues such as frailty in aging populations with HIV, racial disparities in diabetes care, social determinants of health in Medicaid populations, and the integration of behavioral data into claims systems. His methodological expertise includes latent class analysis, risk adjustment modeling, and computable phenotypes.

His recent publications, extending into 2025, demonstrate sustained scholarly productivity in high-impact journals such as Medical Care and Journal of Racial and Ethnic Health Disparities. These works reveal a consistent focus on data quality, health disparities, and the development of frameworks for classifying healthcare needs across the lifespan.

• Approaches to optimally target frailty screening among people with HIV
• Measuring the impact of data quality on racial disparities in diabetes care
• Latent class analysis of social needs in Medicaid
• Population segmentation for morbidity patterns
• Prevalence of lifestyle data in claims

Dr. Pandya teaches the PhD seminar Using Secondary Data to Conduct Health Policy Research, contributing to the training of future health services researchers. He collaborates widely across institutions, particularly within integrated clinical systems such as CNICS, and engages in multidisciplinary research teams focused on aging, HIV, and health equity. His work informs clinical guidelines and health policy by translating data science into actionable insights for improving patient care and population health.