Joint Commission is a global driver of quality improvement and patient safety in health care, primarily via its role as a nonprofit accrediting and certification organization for healthcare organizations in the US and worldwide. Recently, the organization established a Research Center to study the impact of accreditation and certification on healthcare outcomes — translating evidence into actionable insights. The Research Center conducts both retrospective and prospective analyses to understand how accreditation and certification influence outcomes such as patient safety, mortality, and organizational change.

The Joint Commission Research Center seeks a highly skilled and motivated summer intern to support a growing portfolio of research initiatives that inform healthcare quality improvement, accreditation strategy, certification programs, and system-level learning. Working directly with the Director of Health Research Services, Research Scientists, and Senior Healthcare Data Analysts, the intern will help prepare and analyze complex healthcare datasets and contribute to the preparation of manuscripts for peer-reviewed journals, technical memos, and other materials for internal and external stakeholders. This is a hands-on role requiring technical rigor, independent execution, and a strong sense of mission.

The purpose of this 8-12 week internship is to support the data analytics work of the Research Center, which primarily consists of three components: (1) data documentation, (2) data processing, and (3) data analysis. Additionally, this internship is meant to provide data analytics experience in the field of healthcare and health services research. Ideally, this internship will expose the intern to different types of patient- and hospital-level healthcare data, as well as each stage of the data analytics lifecycle, allowing them to contribute meaningfully to a project while also learning best practices in data management and governance.

• Support data analytics workflows via collaborating with Sr. Healthcare Data Analysts, Research Scientists and the Director of Health Services Research.
• Prepare, clean, merge, and manage healthcare datasets from a variety of sources, including patient-level electronic health record (EHR) data, accreditation and certification records, and administrative claims (e.g., Medicare, Medicaid) using a variety of programming languages (e.g., R, Python, Stata).
• Extract and manipulate data from relational databases using SQL and/or other tools available.
• Conduct statistical analyses using established and novel methods under the direction of research leadership; contribute to reproducible and well-documented analytic workflows.
• Use statistical programming languages (e.g., R, Python, Stata) to create summary statistics, data visualizations, and model estimates for use in research studies, internal strategy documents, policy briefs, and peer-reviewed publications.
• Implement quasi-experimental research designs and machine learning methods, as well as the associated data pre-processing, hyperparameter tuning, model evaluation, and assumption testing.
• Maintain detailed documentation of data sources, definitions, programming steps, and quality checks to ensure transparency and reproducibility.
• Contribute to the preparation of manuscripts for peer-reviewed journals, technical memos, data briefs, and presentation materials for internal decision-making and external dissemination.

• Bachelor’s degree in a discipline with substantial quantitative components.
• Currently enrolled in a quantitative Master’s degree program (e.g., Biostatistics, Data Science, Economics, Epidemiology, Public Policy, Health Policy, Statistics).
• Experience with R and/or Python programming languages for data processing, analysis, and visualization. Experience with Stata is appealing but not required.
• Experience querying and manipulating data using SQL.

• Experience communicating and collaborating with multidisciplinary stakeholders in a team environment.

Preferred Qualifications:

• Experience analyzing patient- and/or hospital-level healthcare data.
• Experience supporting research using quasi-experimental designs (e.g., difference-in-differences, instrumental variables) and machine learning.
• Experience contributing to or co-authoring peer-reviewed journal publications.
• Experience translating complex analytic findings for non-technical stakeholders.
• Prior work in a mission-driven organization or collaborative research environment

Currently enrolled undergraduate students who demonstrate substantial relevant experience may also be considered.