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Data Analyst - Understanding Barriers and Facilitators to Healthcare Usage Among Patients Seen at Community Health Clinics

The candidate will be expected to conduct data analysis on electronic medical record (EMR) data using R. Job responsibilities include the merger of EMR data with data on the social determinants of health, conduct of descriptive and regression analyses, creation of figures and tables, and written documentation of methods and results in preparation for manuscripts and abstract preparation. The PI will provide specific requests for the analyses to be conducted, with the opportunity for the SGA to collaboratively contribute suggestions for further model specifications and analyses.

  • Location:

    Boston (PI location), remote work (must be in the US).

  • Semester:

    Summer 2025

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  • Project Title

    Understanding Barriers and Facilitators to Healthcare Usage Among Patients Seen at Community Health Clinics

  • Faculty / Project Lead

    Danielle Crookes

  • Project Description

    Cardiovascular disease (CVD) is one of the leading causes of mortality for most racial and ethnic groups in the U.S. When immigrants first arrive in the U.S., they have better CVD risk factor profiles than the U.S.-born, but within 5 to 15 years of living in the U.S., they experience a worsening of their CVD risk factor profiles. Lower preventive care utilization, in part, contributes to their worsening cardiovascular health. Understanding the factors that contribute to lower care utilization is necessary to reduce the burden of CVD mortality in the U.S. This project aims to estimate trends and associations between state- and county-level social determinants of health and CVD preventive care utilization outcomes among immigrants and non-immigrants seen at community health centers across the U.S.

  • Qualifications Necessary

    Candidates must have working experience using R, including conducting data mergers, descriptive analysis, longitudinal analysis, and multi-level regressions. Expertise in conducting quantitative analysis with electronic health records is a plus, but not explicitly required. Ideal candidates are curious researchers interested in applying their quantitative skills to tackle complex epidemiological problems to address social and structural barriers to healthcare access.

  • Hours per Week

    20 Hour Position