Curriculum

This opening in-person event will provide an orientation to the certificate program and an overview of the field of health equity data and delivery science. The day’s interactive program includes: what to expect from the next eight months, introductions to program faculty, a chance to get to know program participants and discuss research interests, and perspectives from leaders in the field. 

This virtual introduction will provide an overview of the core areas within the Health Equity Data and Delivery Science certificate program. These sessions will equip participants with foundational understanding of key concepts and provide background knowledge to select one of two concentrations: Healthcare Data Science & Observational Research, or Healthcare Delivery Intervention & Implementation Research. Each session will consist of a large group learning session and interactive small group work.

This optional 12-session, bi-weekly course will provide an overview of key topics, interactive practice sessions, and instruction in the use of R in data analysis. Topics will include study design, sample size, and power calculations; set-up and introduction to the use of R as an analytic program; descriptive statistics, data management and missing data imputation; sensitivity/specificity and ROC; conducting T-tests and chi-square analyses; ANOVA; multiple regression; logistic regression; survival analysis; and interpretation of multivariate analyses. This course will be taught by faculty from the Massachusetts General Hospital Institute for Health Professions. 

For individuals looking for further training in Biostatistics:
Fundamentals in Biostatistics Certificate Program: This can be acquired through the Harvard Catalyst program providing a core curriculum in the fundamentals of Biostatistics over 26 weeks at approximately 4 hours a week. This course consists of 5 units including an introduction and overview; univariate analysis and study design; linear regression, and analysis of dichotomous outcomes and time to event outcomes. Lectures are coupled with hands-on skill development in the use of analytic programs and problem sets.  The Harvard Catalyst Certificate Program in Fundamentals Biostatistics is available here through Harvard Catalyst requiring a separate application, registration and tuition.

Advanced Biostatistics Certificate Program: The advanced course offered through the Harvard Catalyst program includes the topics covered in the Fundamentals course along with additional advanced topics including correlated outcomes and longitudinal data; causal inference modeling; approaches for prediction modeling, and additional advanced models in biostatistics. The material is covered over 48 weeks at 4 hours a week. The Harvard Catalyst Certificate Program in Advanced Biostatistics is available here through Harvard Catalyst requiring a separate application, registration and tuition.

This one-day in-person, two-part workshop will provide an overview of practical and essential research strategies and skills, followed by an interactive session on identifying and crafting a good research question, setting the stage for developing the capstone project.
 
Morning Session: Practical and Essential Research Skills
This session provide an overview of practical knowledge and skills that are essential for success as an independently funded early research career investigator. Topics and panel discussions will include the following:

• Achieving independent funding: agencies, foundations, and mechanisms targeting health care data, delivery, and equity research

• Strategies and tips for successfully working with mentors

• How to work with a biostatistician

• Challenges and strategies in working with IRBs in health care data and delivery research

Lunch Panel and Discussion: Balancing Work and Life
This panel discussion will discuss challenges and successful strategies in balancing work and life as early research career investigators
 
Afternoon Session: Identifying a Good Research Question
This session will begin with a panel discussion from successfully funded experienced investigators on the topic of what constitutes a “good research question” from the perspective of national experts in health equity data and delivery science. Participants will engage in small group learning experiences working with a specific case example of a research problem to craft a high-impact research question with input from experienced researchers. The workshop will conclude with each participant presenting and getting feedback on their own future project research question and preliminary specific aims. This exercise will set the stage for further developing these questions and aims in the subsequent selected concentration.​

This 8-week virtual seminar will provide an overview of major topics, methods, and strategies for conducting research focused on health disparities and engaging diverse research populations. Participants will learn key research strategies and methods pertaining to research on health disparities and advancing health equity. The sessions will be led by national leaders in the field, whose work spans the spectrum of health inequities, including: race and ethnicity; gender and gender identity; sexual orientation; physical and intellectual ability; age; and economic and social determinants of health. Each session will consist of a lecture and interactive small group work.

This one-day in-person, two-part workshop will provide an overview and interactive learning sessions on principles, practice, and tools used in quality improvement and equity-focused learning health system science.
 
Morning Session: Applying Practical Quality Improvement Research Methods and Tools
This session will provide an overview of practical models, methods, and tools in quality improvement research and a brief interactive small group exercise designing a quality improvement project focused improving health equity in a care delivery setting. Topics will include:

• Applying observational research evaluation methods and causal inference to assess access and quality of care

• Applying the PDSA (Plan-Do-Study-Act) model for quality improvement

• Practical tools: Run Charts, Driver Diagrams, Fishbones, Flowcharts

• Small group exercise designing a quality improvement project focused improving health equity in a care delivery setting

Lunch Session: Discussion and example(s) of quality improvement learning collaboratives
 
Afternoon Session: Equity Focused Learning Health System Science
This session will include an overview of components, principles, and methods in equity-focused learning health systems science. Topics will include:

• Principles and Components of Data-informed, Equity-Focused Learning Health Systems

• Using Real-time data analytics, informatics, and registries 

• Leveraging partnerships for co-design and co-production in learning health systems

• Measurement-based care and equity-focused health systems science

• Opportunities and resources for learning health systems research training

This 8-session concentration focuses on experience-based learning in healthcare data science and methods in observational research. Participants will learn fundamental research methods and study designs pertaining to the use of electronic health record data, health care claims, data registries, and large clinical data sets. This concentration will provide an overview of fundamentals of descriptive analyses and causal inference in observational data. This seminar will expose participants to methodological tools and illustrate how they may be applied to key topics in health care data science such as, health equity, health services, and clinical research. In addition to lectures from research leaders in the field, practice sessions will provide participants with the opportunity to develop skills for approaching analyses of observational data and applying analytic tools. Finally, participants will work with the course leaders and mentors to advance their own research project idea and design in a final capstone presentation.

This 8-session concentration focuses on research methods including human-centered design, randomized trials, quality improvement science, implementation science, and learning health systems. It will also provide specific strategies for recruiting and retaining diverse study samples in research as well as considering the methodological approaches that are optimal for community engaged participatory research as well as research conducted in healthcare clinics and hospital settings evaluating different interventions and models of care. Participants will learn about brief tests of change and quality improvement methods, as well as principles and practice of implementation science and learning health systems. In addition to lectures from experts, participants will engage in case-based exercises to learn and apply these principles and practices. Finally, participants will work with the course leaders and mentors to advance their own research project idea and design in a final capstone presentation.

This one-day in-person workshop provides an overview of the fundamentals and use of AI in health care data and delivery science with a focus on health equity. Participants will learn basics in how AI works and applications in research including use of tools, such as ChatGPT/GPT-4, to inform the development of research reviews, designs, and proposals; use of generative AI large language models and natural language processing in accessing and synthesizing data from electronic health records and other electronic large data sources; and the use of machine learning in conducting research in designing and conducting intervention and implementation research. In addition to providing an overview and relevant readings and resources, this workshop will include some hands-on experience in applying some of these approaches that are increasingly being adopted across research and healthcare settings. Finally, this workshop will summarize both the potential benefits and pitfalls of AI including biases in algorithms and analytics with respect to health disparity populations and future potential solutions to overcome these issues in health equity data and delivery science.

The certificate program culminates with a one-day in-person opportunity for each participant to present a poster of their final research question, specific aims, and preliminary research design for final feedback and subsequent refinement. Faculty will provide final observations on key strategies and approaches for successful research projects and careers in the area of health equity delivery data and delivery science and will provide an opportunity for participants to engage in a summary discussion and evaluation of the certificate program. Recommendations for next steps and other resources to continue in learning and mastery of fundamental skills will be provided. This one-day event will close with celebration of accomplishments and awarding of certificates of completion.