Conduct analysis and evaluation of internally and externally funded health services research projects including observational studies and randomized control trials.
Work with claims (specifically the IBM MarketScanÂ® Research Databases), survey, administrative and electronic health record data to assess health outcomes and cost reduction of different patient populations.
Prepare statistics and measures for teams and produce reports and presentations as needed for funders and diverse audiences.
Create meaningful data visualizations including charts, infographics, and other visual data elements to effectively highlight findings.
Develop scientific and data-driven methodologies and decision support tools to design patient care processes and systems within the environment of University of Chicago Medical Center and the Biological Science Division, and apply them effectively in the environment.
Typical projects involve healthcare economics, healthcare delivery science, system and process redesign, quality improvement, statistical analysis, simulation, and large-scale, data-driven optimization.
Assist faculty members to develop and write methods sections of project reports, grant applications and papers.
Provide technical support to other investigators and conduct decision and statistical analyses.
Support in publishing the applied and theoretical research.
Communicate findings and share methods and best practices.
Manage various research projects within the Center with the use of survey, billing, administrative and claims data.
Lead and manage individual projects, as well as collaborate with a team of faculty, hospital clinicians, analysts, administrators and students.
Prepare and present key measures designed to assess results and progress of these projects.Â
Assist in the development of proposals as well as post-award reports and metrics.
Oversee research assistants and students in the performance of student projects, data management and data analyses.
Identify and procure relevant data from internal and external sources, including practice sites, university systems and departments, as well as local, regional, national, and global population data which can be used to improve practice, teaching, and discovery.
Examples of data consortiums that are usually used in health services research are Medicare and Medicaid claims, the IBM MarketScanÂ® Research Databases, PCORnet, CAPriCORN, National Death Index (NDI), NIH National COVID Cohort Collaborative (NC3) and Epic Systems, among others.Â
Integrate datasets effectively to improve scope of research and quality of data.
Collaborate with staff and faculty to assess data needs and implement user-driven solutions.
Applies research principles and relevant subject matter knowledge relevant to administer a research project. With a moderate level of direction, manages lab and/or research-related duties and tasks. Helps develop, design and conduct research projects according to plan.
Supports data collection and analytical needs of research projects. Conducts literature reviews and helps write reports and manuscripts. Ensures project compliance with different policies, procedures, directives, and mandates.
Performs other related work as needed.
Advanced degree in statistics, biostatics, computer science, mathematics, economics, sociology, epidemiology, operations research, or related field.
Prior experience with data modeling, data analysis and demonstrated ability to contribute to research papers and grant proposals.Â
Five years of experience with programming and data management.
Supervisory and project management experience.
Experience with Stata, R and SAS and health-related analyses.
Prior experience working with large longitudinal data sets such as healthcare surveys, hospital administrative, billing and electronic health record data, and Medicare or private claims.
Excellent communication skills, both written and verbal.
Ability to work independently and as part of a team and motivation to explore and apply new technologies and methods to problems.
Ability to work simultaneously with multiple investigators, prioritize competing objectives, and identify opportunities to more efficiently accomplish programming tasks.
Cover Letter (required)
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