MHIDA Office Hours
Have questions about research design from a statistical perspective?
Not sure how to calculate the power analysis for your upcoming grant applications?
Want to extract data from the clinical databases available on campus?
Need help collecting data for research or quality improvement projects?
You can schedule an appointment during the Informatics and Data Analytics Combined Office Hours to discuss your data, information, and statistics needs.
The office hours will be Fridays from 1-3pm with four 30-minute time slots.
The appointment can be scheduled online directly at https://calendly.com/xiaomingzeng/office-hour?month=2020-09 or email the faculty (email@example.com | firstname.lastname@example.org) for other time slots. Please do not hesitate to contact the faculty if you have any questions.
The goal of the service is to support clients — researchers, clinicians, or trainees — who are conducting data-driven research or quality improvement project evaluations, especially when observational data are needed from clinical databases such as EHRs (Electronic Health Records), medical claims, and other secondary datasets. Enormous quantities of observational data are routinely collected for health care operations and service delivery. These data are rich for research and evaluations using real-world data to build new knowledge and insights. One challenge hindering the usage of such data is the need to transform the data from their original raw format and storage location to be ready for analysis. The joint office hours aim to support clients by streamlining the data transformation process from data acquisition to analysis.
Dr. Xiaoming Zeng and Dr. Kai Xia have more than 30-year expertise combined in health informatics, bioinformatics, biostatistics, and data analytics. During the consultation, they will guide clients to operationalize research questions or ideas so that relevant data sources could be identified. They will work closely with NC TraCS and other entities to query and extract data from existing systems. They will also assist in the steps of data cleaning and analysis.