Sarmistha Pal, Ph.D. is an Econometrician (Scientist) at Dobson | DaVanzo, who joined the company in October 2014. She is experienced in applied econometrics and quantitative analysis with a focus in Health Care and Labor Economics. Dr. Pal’s research focuses on a broad array of topics in the area of Labor, Health and Applied Microeconomics. After joining Dobson | DaVanzo, she led a workforce study on Orthotics and Prosthetics (OP) Professionals and was the lead analyst for the OP workforce projection model. Dr. Pal developed a workforce supply model for Genetic Counselors that would help the profession to plan for future training needs. She is knowledgeable of hospital finance and conducted analyses of the cost efficiency of New Jersey and Connecticut hospitals. She developed multivariate regression models to estimate the relationship between Medicare inpatient costs and hospital characteristics, as well as econometric models to analyze the impact of standby capacity on hospital outpatient costs. She developed models at both patient and hospital levels to identify the key drivers of outlier payments under the network of a major health system using a logistic regression framework.
Dr. Pal is having conducted research for organizations implementing new payment models. For example, for the National Association of ACOs (NAACOS), she designed a database using Medicare claims data from the Center for Medicare and Medicaid Services (CMS). She estimated a Difference-in-Differences model to examine how Medicare expenditures have changed over time between the ACO assigned beneficiaries and other assignable beneficiaries over the performance years. She also developed profiles of the beneficiaries assigned to different Accountable Care Organizations (ACOs) and created key quantitative metrics associated with their health care expenditures and utilization.
Dr. Pal participated in an evaluation of an innovative demonstration under a Health Care Innovation Award grant. Using different econometric models (e.g., Difference-in-Differences), Mixed Effect Maximum Likelihood models) she evaluated potential cost and utilization savings for Medicare and Medicaid beneficiaries under the new eConsult and eReferral program implemented in academic medical centers. In another project, she also designed Risk Adjusted Readmission Models for IP Psychiatric hospitals using Random Effect Logistic Regression. Using an instrumental variable (IV) approach, she also examined whether patients who are transferred to Long Term Acute Care Hospitals (LTCH) have lower utilization (in terms of payments, costs, readmission, mortality and ED utilization) compared to those who are not transferred to LTCH.
Dr. Pal is also expert in handling Medicaid data. For example, she recently analyzed Medicaid claims data to estimate damages in terms of healthcare expenditures associated with Opioid misuse or high risk of Opioid misuse among a State’s Medicaid enrollees using Propensity Score Regression Method with Inverse Probability Treatment Weighting (IPTW) and Weighted Generalized Linear Model (GLM) with Log-link function and Gamma Distribution models. She estimated different Machine Learning Models to forecast the Opioid overdose rate among Part D Medicare beneficiaries. Currently she is providing technical and analytical support for different model analyses on Medicare part D project for CMS.
She is also experienced in understanding the implications of health issues on individual labor market behavior. She has significant experience in dealing with major micro data in the U.S. such as American Community Survey (ACS) Data, Medicare beneficiary and claims data, Medical Expenditure Panel Survey (MEPS) data, Panel Study of Income Dynamics (PSID) and Child Development Supplements (CDS), American Census micro data, Private School Universe Survey and National Health and Nutrition Examination Survey (NHANES) data.
Dr. Pal earned her Ph.D. in Economics from Clemson University, South Carolina in 2012. Earlier she obtained her Bachelor of Arts and Master of Arts in Economics from Jadavpur University, India with specialization in statistics and econometrics. Her dissertation work empirically examined the implication of public policies such as the Supplemental Security Income on labor market outcomes.
After finishing her Ph.D., Dr. Pal joined University of Alabama in Huntsville as a visiting assistant professor and taught Business Statistics and Principles of Macroeconomics. She was nominated for the Best Teaching Award (UG) in 2013 at University of Alabama in Huntsville. Earlier during her PhD, she was a Graduate Teaching Instructor in the Economics Department at Clemson University and taught microeconomics and macroeconomics to students majoring in Business, Economics, and Finance and in other academic disciplines. In 2011, Dr. Pal received commendation from Clemson University Student Affairs for her positive impact on students.
Dr. Pal presented her research papers in several academic seminars and workshops at Clemson University (2008-12) and at the University of Alabama in Huntsville (2012-13). Her work was also published in Surgical Technology International. Her study on savings estimation of Accountable Care Organization was cited by a MEDPAC report (Assessing the Medicare Shared Savings Program’s effect on Medicare spending, June 2019). She is also a referee of Contemporary Economic Policy, a peer-reviewed academic journal of economics.