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Recruitment Resources

The UMCCTS Informatics and Recruitment Core provides services and tools that investigators can use to evaluate study feasibility, identify appropriate cohorts for clinical trials recruitment, rapidly recruit participants to clinical trials, and access biospecimens:

All services can be accessed by submitting a request through the UMCCTS TRAcs portal:

Cohort Identification for Recruitment:

Extraction of clinical data from Electronic Health Record to assist with patient cohort identification for clinical trial recruitment and study planning.

“Just-in-Time Alert” (JITA) - Real Time Patient Recruitment Application

Recruitment to clinical trials can be challenging especially when clinical trial teams are trying to identify potential participants in “real time” in clinical settings. Leveraging the electronic health record (EHR) system, the informatics team has developed the “Just-in-Time Alert” (JITA) application which receives messages from the EHR, processes those messages, and alerts clinical trial teams of potential participants.  After receiving an alert, the study team can approach and discuss the study with patients while they are still in the clinic or hospital. Only studies which have received IRB approval are included in JITA. A more detailed description of JITA can be found in Lee V, et al. JITA: A Platform for Enabling Real Time Point-of-Care Patient Recruitment. AMIA Jt Summits Transl Sci Proc. 2020 PMID: 32477655.

The National COVID Cohort Collaborative - N3C (

N3C is an NIH NCATS-sponsored analytics platform that contains clinical data from the electronic health records of people who were tested for the novel coronavirus or who have had related symptoms. UMass Chan Medical School was one of the first 12 vanguard sites to deposit COVID data to N3C. CTSA sites across the country are continuing to contribute data to N3C with the goal of creating a harmonized data set from all 60+ CTSA’s. The UMCCTS Recruitment Core has completed all  regulatory and administrative requirements necessary for UMass Chan investigators to access the N3C Data Enclave.

Requirement for IRB approval is dependent on the type of data requested: a) access to de-identified or safe harbor datasets does not require institutional IRB approval;  b) access to datasets with PHI requires institutional IRB approval.

Redcap Survey Distribution

Survey studies utilize Redcap to distribute questionnaire to potential volunteers through email who meet study inclusion and exclusion criteria. When they receive this email, they are able to answer survey questions if they want to participate and answers will be stored and analyzed in Redcap.

Cohort Identification Tools

Data Lake Extraction

Aggregated values that allow researchers to explore and assess the availability of a patient population using the Electronic Health Record data from UMass Chan Data Lake based on specific eligibility criteria.

TriNetX (

TriNetX is a third party software product that provides clinical data network access, for use in rapid identification of potential cohorts for clinical trials across the TriNetX global health research network. TriNetX combines real-time access to longitudinal clinical data allowing investigators to understand study viability and the ways in which inclusion and exclusion criteria impact the size of the anticipated indicated patient population. These insights can be used to help refine inclusion and exclusion criteria, optimizing study design and speeding accrual. Sites that have eligible patients can be identified and invited to participate.

TriNetX software leverages UMass Chan' existing i2b2 database as a data source, therefore, only de-identified data is shared among network users. Additional software is installed onsite at UMass Chan to allow the query results to be sent back to the TriNetX network. When a network user initiates a query, it will inquire of all available data sources and return with aggregate results for the user. The user can further drill down the result in the User Interface (UI) for further analysis. TriNetX offers a robust web-based UI that has intuitive query functions and an out of box reporting tool.


i2b2 is an open-source clinical data warehousing and analytics research platform. In order to use i2b2, you need to request access by completing the Account Request Form. To log in, go here.   

Note: Data lake, TriNetX and i2b2 can be used for assessing study feasibility. TriNetX and i2b2 are both self-service tools where user can select eligible criteria including demographics, diagnosis, labs, medications, and procedures and get aggregated count interactively. Data lake provides more clinical data search domains including encounter information, clinician notes, patient vitals, and others. Data lake extraction involves a clinical data scientist who can tailor the query towards specifics of your request and thus improves the query accuracy.

Although TriNetX and i2b2, both can be used to explore patient cohort based on inclusion and exclusion criteria, we recommend TriNetX over i2b2 because of its better UI design and user friendly interface, among other features.


Accrual to Clinical Trials (ACT) Network is a nationwide federation of leading academic research institutions that share aggregate patient counts (> 125 million patient records) from electronic health record data. Its development is funded by grants from the NIH through the National Center for Advancing Translational Sciences (NCATS) to individual CTSA sites. UMCCTS is a member of the consortium.

Similar to TriNetX and i2b2, ACT also facilitates cohort identification. However, ACT offers the specific ability to  explore the patient cohort not only at UMass site but also at ~60 CTSA sites across the nation.

Other data services

Disease oriented patient registries

Patient registries collect, organize, and display healthcare information from a population defined by a particular disease, condition, or exposure.

Biospecimen related data

Studies that involve human research-related specimens from UMCCTS Biospecimen, Tissue, and Tumor Bank (Biorepository) and related data from the Electronic Health Record System.

Geospatial data

Geospatial data helps investigators to identify spatial disease clusters and can provide information on social determinants of health (access to healthy food/water/air, language barrier, economic barriers). It can thus help to target and tailor interventions and support to specific at-risk patient populations.