Biostatistics & Bioinformatics Support

Biostatistics, Epidemiology and Research Design (BERD)

The Biostatistics, Epidemiology, and Research Design team offers services through NYU Langone’s Clinical and Translational Science Institute to provide efficient study design and novel methodology through consultation, collaboration, and education.

To schedule a consultation with the Biostatistics, Epidemiology, and Research Design team, please complete our online form. Researchers can also access a series of online biostatistics tools that our team has compiled to help with statistical analysis.

Statistical, Epidemiological, and Study Design Consultations

Faculty from the Biostatistics, Epidemiology, and Research Design team collaborate with researchers to provide statistical, epidemiological, and study design consultations that support translational research at NYU Langone Health and NYC Health + Hospitals.

We provide an initial one-hour consultation at no cost to researchers, including grant application development, data analysis, and assistance with preparing manuscripts.

Bioinformatics Research Analytics – Biomedical/Clinical Research Informatics

Our data scientists and informaticians provide informational technology and informatics services in support of investigators conducting clinical research.

DataCore

DataCore is an institutional resource that provides a variety of research data services, which include querying the electronic health records of patients seen by NYU Langone healthcare providers to identify participants for research studies. Data is available on a variety of patient characteristics, including demographics, behaviors (such as smoking), vital signs, labs, procedures, medications, diagnoses, and problem lists.

Free-text documentation can also be used to identify potential study cohorts. Pattern matching approaches as well as more sophisticated natural language processing methods are available to mine free-text sources. Projects that require processing of free text generally require more substantial resource allocation to complete, including both analyst and developer time, as well as time allocated by someone from the study team to serve as a content expert who validates results generated by the technical work.

DataCore provides researchers attempting to find research participants with three types of data-related services. These include:

• general estimates of patients that meet eligibility criteria
• lists of patients to be used for recruitment purposes
• the ability to send study-related messages to patients at NYU Health via the MyChart online patient portal

No Institutional Review Board (IRB) approval is necessary for researchers to ask DataCore to provide general estimates of patients that meet specific eligibility criteria. These estimates are provided in a de-identified, aggregated format and can be used in grant applications to justify enrollment targets or for general study planning purposes.

Researchers must have IRB approval to request lists of patients with identifiable protected health information, such as contact information or information about upcoming appointments, to be used for research recruitment purposes.

Using DataCore to Message Study Participants via MyChart

Researchers must also have IRB approval to allow DataCore to provide your study team with the ability to send study-related messages to patients within Epic who have an active MyChart account. These messages allow patients the ability to respond if they are interested in potentially participating in a study. Not all studies use this functionality, and there are some policies to keep in mind when recruiting patients and sending messages. For example, study teams are not allowed to recruit a patient more than twice within the same month. Any study-related messages sent to patients via MyChart must undergo IRB review and approval.

Using Slicer Dicer to Identify Participants

In addition to DataCore’s three services, Slicer Dicer is a self-service cohort exploration tool embedded in Epic that is available to researchers. This tool allows researchers to identify patients based on criteria entered into the user interface without needing to write code. The user interface displays counts of patients that meet specified criteria and allows for these aggregate counts to be displayed in several ways. For example, one can see counts of patients broken down using patient characteristics like age groupings, gender, ethnicity, and others. Slicer Dicer includes a derived set of patient characteristics based on the Centers for Disease Control and Prevention’s Social Vulnerability Index.

If IRB approval is obtained, researchers can also use Slicer Dicer to identify a cohort of interest and request the list of patients with contact information to be used for trial recruitment.