The Center for Healthcare Data Analytics is an overarching entity established in 2016 by the faculty and staff of the Department of Health Care Policy after a realization that a large part of our work involved data analytics on either large public or private data sets. The Center's core faculty members are nationally recognized for their work in data analytics, Bayesian methodological approaches, statistical methods for health services, and regulatory policy research. Our areas of research include broad topics on financing and delivery of health care, quality of care, studies on special and disadvantaged populations (including those with mental disorders), and access to care. We manage large-scale efforts related to benefit design and the care of the elderly. In many cases, these applied studies are augmented by fundamental contributions in statistics and biostatistics.
The Center's recent acquisition of many new Medicare files has opened up new opportunities for research in the healthcare domain. Some of our data assets are publicly available, some are available only to HCP investigators as part of funded grants, and others are available through data reuse agreements. Further details about our data resources can be found in our "Data Assets" section. With the richness of these data assets, we are engaged in multiple projects, many of which are highlighted in our “Projects” section.
Sharon-Lise Nomand, PhD, received the American Heart Association’s Council on Quality of Care and Outcomes Research Outstanding Lifetime Achievement Award in April 2017. Normand earned this honor for her leadership in cardiovascular hospital quality assessments at the state level for the Massachusetts Department of Public Health (Mass-DAC public reporting) and at the national level for the Centers for Medicare and Medicaid Services for development of hospital mortality and readmission measures. Dr. Normand has developed analytical approaches for comparing hospitals and physicians using outcomes and process-based measures.
Sherri Rose, PhD, was named the inaugural awardee of a Harvard Data Science Initiative Competitive Research Fund Grant in May 2017. The Harvard University Data Science Initiative aims to facilitate cross-disciplinary collaborations across schools and departments. The program will “harness the vast expertise and innovations that are occurring in disciplines as diverse as medicine, law, policy, and computer science." Sherri Rose's research focuses on designing machine learning tools that incorporate both investigator knowledge and automation to answer critical questions in health economics and health outcomes. Rose's proposal was entitled, “Improving Health Care System Performance: Computational Health Economics with Normative Data for Payment Calibration.”