Overview
Dr. Anushka Palipana is a Biostatistician in the Health Statistics and Data Science division at the Duke University School of Nursing. She earned her Ph.D. in Statistics from the University of Cincinnati and her B.Sc. in Statistics from the University of Peradeniya, Sri Lanka. Her research interests encompass longitudinal modeling, survival analysis, and the joint modeling of longitudinal and survival data, with a focus on their applications in health science.
Prior to joining Duke University School of Nursing, Dr. Palipana was a postdoctoral research fellow at Cincinnati Children's Hospital Medical Center (CCHMC). At CCHMC, her research involved designing and analyzing medical monitoring investigations and integrating geo- and bio-markers to enhance the prediction and early detection of disease progression in conditions such as lymphangioleiomyomatosis and cystic fibrosis.
Dr. Palipana has authored numerous peer-reviewed journal articles published in methodological and clinical journals, including CHEST, Biometrics, Pediatric Pulmonology, PLoS One, and the Journal of Cystic Fibrosis, among others.
Recent Publications
Effects of a Digital Intervention to Improve DASH and Blood Pressure Among US Adults.
Journal Article Hypertension · February 2025 BACKGROUND: Dietary Approaches to Stop Hypertension (DASH) is a recommended first-line treatment for adults with hypertension, yet adherence to DASH is low. To evaluate the efficacy of a digital health intervention (DHI), compared with attention control, o ... Full text Link to item CiteReal-world association between ivacaftor initiation and lung function variability: A registry study.
Journal Article Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society · February 2025 BackgroundIncreased variability in forced expiratory volume in 1 s of % predicted (FEV1pp) has been associated with accelerated lung function decline in individuals with cystic fibrosis (CF). Lung function variability is a leading predi ... Full text CiteSecular and modulator-specific drifts in the predictive performance of a rapid lung function decline algorithm: a cystic fibrosis patient registry study
Journal Article Discover Data · September 24, 2024 Full text CiteRecent Grants
A Risk Stratification Model for Health and Academic Outcomes in Children with Concussion Based on Novel Symptom Trajectory Typologies
ResearchStatistician · Awarded by National Institutes of Health · 2023 - 2028A Randomized Controlled Trial of BETTER, A Transitional Care Intervention, for Diverse Patients with Traumatic Brain Injury and Their Families
ResearchStatistician · Awarded by National Institute of Nursing Research · 2023 - 2028EXpanding Technology-Enabled, Nurse-Delivered Chronic Disease Care (EXTEND)
ResearchStatistician · Awarded by National Institute of Nursing Research · 2021 - 2025View All Grants