Ramaa Nathan, PhD
VP, Data Science and Real World Evidence
Expertise:
Ramaa Nathan serves as the VP, Data Science and Real World Evidence at EVERSANA with several years of experience in the financial and healthcare industries.
Ramaa is a data scientist and statistician with extensive programming, statistical and data analysis skills. She holds a PhD in computer and information science from the University of Pennsylvania and an MS in applied statistics from Penn State. She is a data enthusiast and has many years of experience in working with different types of data, including healthcare and non-healthcare data. Ramaa has served in several roles in the financial and health care industries as a researcher, software developer, data analyst, project manager, client engagement specialist and data scientist. She is also very engaged in the local data science community and is the organizer of DataPhilly, a community data science group.
Ramaa initially joined HVH Precision Analytics, which is now part of EVERSANA, and worked on developing various models for building complex patient journeys and identifying new patient cohorts using statistical and machine-learning techniques. At EVERSANA, she continues to lead and work on challenging projects focusing on various pharmacological studies, healthcare resource utilization cost analysis, and building predictive models in the area of rare diseases using a variety of techniques.
Before coming to EVERSANA, Ramaa worked as the Director of Strategic Applications at hMetrix, a health care consulting company, where she spearheaded projects for developing NCQA certification software for HEDIS and for developing care management products using EHR and claims data. She also worked with Buddi.AI in its initial stages as a Product Manager and collaborated in the business process modeling of predictive denial management systems in the Revenue Cycle Management (RCM) domain and automated medical coding (ICD) software as applicable to various medical specialties. In the financial sector, Ramaa worked on developing and building high-performance algorithmic models for proprietary trading of equities.
Expertise: Data Science, Predictive Modeling, Real-World Evidence, Healthcare Resource Utilization, Pricing Analysis, Client Engagement
Articles by Ramaa Nathan, PhD
Association Between Targeted Therapy and Survival in Patients with Myelodysplastic Syndromes
Precision oncology offers a new approach to cancer care by providing targeted treatments for patients with actionable genetic mutations. However, in the U.S., nearly one-third of eligible patients face barriers such as delayed test results, limited awareness and access issues, impacting survival outcomes. Pierantonio Russo, MD, Ramaa Nathan, PhD, Daniel Pfeffer, PhD, and Alex Moore, PhD, conducted a study that highlights the potential of targeted therapies for patients with myelodysplastic syndromes (MDS), a challenging hematologic malignancy. By analyzing genomic and claims data from over 3,600 patients, the research demonstrates a 46.5% reduction in 12-month mortality rates among patients receiving targeted therapies compared to those who did not. Remarkably, therapies like […]
Association Between Targeted Therapy and Survival in Patients With Acute Myeloid Leukemia
Precision oncology innovatively addresses cancer care by targeting treatments to patients with specific biomarker alterations. However, in the U.S., nearly one-third of eligible patients miss out on these life-saving therapies. Operational barriers, physician awareness gaps, slow test result turnaround times (TATs) and reimbursement challenges create significant obstacles, leaving many without treatments that could dramatically improve their chances of living longer. For acute myeloid leukemia (AML)—a blood cancer with a poor prognosis—these disparities are especially dire. High-risk patients face limited options, but even without complete remission, targeted therapies can extend their lives. In a study conducted by Pierantonio Russo, MD, Ramaa Nathan, PhD, Daniel Pfeffer, PhD, and Alex Moore, PhD, they […]
Lead Time Is All You Need: Patient Identification for Cell and Gene Therapies Using Machine Learning and Advanced Data Analytics
Discover how EVERSANA’s cutting-edge approach is revolutionizing patient identification for cell and gene therapies. In our white paper, “Lead Time Is All You Need: Patient Identification for Cell and Gene Therapies Using Machine Learning and Advanced Data Analytics,” we explore the transformative power of machine learning and advanced data analytics in the world of healthcare. Cell and gene therapies offer the promise of one-time cures, especially for rare congenital disorders. However, delayed or missed diagnoses often hinder patient journeys, leading to suboptimal outcomes. EVERSANA’s innovative approach combines clinical expertise and data-driven analytics to construct patient journeys, identifying candidates for these groundbreaking therapies. Our method considers clinical and nonclinical factors, such […]
EVERSANA Featured in NIH Study Detailing the Cost of Treating Rare Disease
“The IDeaS initiative: pilot study to assess the impact of rare diseases on patients and healthcare systems” EVERSANA™ was the only data and analytic organization invited by a consortium of provider organizations and the NIH to participate in a study with the National Institutes of Health’s National Center for Advancing Translational Sciences (NCATS). The study, “The IDeaS initiative: pilot study to assess the impact of rare diseases on patients and healthcare systems,” was published in the Orphanet Journal of Rare Diseases. The study provides new evidence of the potential impact of rare diseases on public health, including the number of individuals with rare diseases and their medical costs being on par […]