Given the large volume of data documented in electronic health records (EHRs), it is complex and labor-intensive for the research staff to manually identify and screen patients for inclusion/exclusion in clinical trials. 

Moreover, every EHR presents a unique interface to get to this data, and in the past there has been no standardized way to store and access this data across EHRs. 

In current environment, clinical trial staff (eg, clinical research coordinators; CRCs) manually screen patients for eligibility before approaching them for enrollment. The process includes reviewing the patients’ electronic health records (EHRs) for demographics and clinical conditions, collating and matching the information to trial requirements, and identifying eligible candidates based on the requirements. 

Compared with the manual screening process, using EHR-based automated screening would improve efficiency of patient identification, streamline patient recruitment workflow, and increase enrollment in clinical trials. However, missing interoperability has hindered automation. Use of FHIR for defining eligibility criteria of clinical trials can facilitate interoperability and allow automatic screening for eligible patients at multiple sites of different healthcare providers with different EHRs.

Big pharma and biotech, contract clinical research organizations (CROs), medical device companies, providers and payers can leverage FHIR to identify participants for clinical trials.