Adverse Event Clinical Research R4 Backport
1.0.1 - STU1

Adverse Event Clinical Research R4 Backport, published by HL7 International / Biomedical Research and Regulation. This guide is not an authorized publication; it is the continuous build for version 1.0.1 built by the FHIR (HL7® FHIR® Standard) CI Build. This version is based on the current content of https://github.com/HL7/fhir-ae-research-backport-ig/ and changes regularly. See the Directory of published versions

## AdverseEvents for Clinical Research Home Page

Official URL: http://hl7.org/fhir/uv/ae-research-backport-ig/ImplementationGuide/hl7.fhir.uv.ae-research-backport-ig | Version: 1.0.1
IG Standards status: Trial-use | Maturity Level: 2 | Computable Name: AdverseEventClinicalResearchR4backport

### Intent

The intent of this guide is to provide a baseline profile on the FHIR AdverseEvent Resource suitable for Clinical Research. The profile serves as foundational specification to meet general needs in communicating adverse events in clinical research. Key elements are highlighted with MS and required cardinality. Also, the implementation guide (IG) provides useful terminology bindings for the clinical research use case. And, there are examples to aid understanding. The IG was developed by subject matter experts and tested through connectathons. This version is an R4 backport of the R5 version, it is for convenience to those systems that cannot operate on FHIR R5.

### Overview

A single Adverse Event (AE) may need to be reported in multiple ways. Choosing the appropriate form of the reporting is dependent upon workflow patterns. In particular, the implementation guides for Clinical Care adverse events and Clinical Research adverse events provide important extensions, value-sets and examples for implementing AdverseEvent.

This guide, the Clinical Research adverse event implementation guide, is for the clinical research setting. In this setting, the event is tracked and evaluated as part of the clinical research process for the research study.

In the research setting an adverse event means any untoward medical occurrence associated with the use of a drug in humans, whether or not considered drug related (this is surfaced in the profile as a constraint of ‘actual’ for the value of ‘actuality’). An example of an adverse event in the clinical research setting would be a patient develops renal failure while on a study drug. These events are characterized by the need to capture cause-and-effect (although they might not be known at the time of the event), seriousness, severity, and outcome.

The context of an adverse event is also important, and captured in the AdverseEvent Clinical Research Profile data elements. A subject may have condition(s) or current treatments (medications, diet, devices) that impact their response to a newly introduced medication, device or procedure. Knowledge of these variables is essential in establishing a cause-and-effect relationship for an adverse event. This information is represented with corresponding resources (e.g. Procedure Resource for procedures, etc.) and referenced.

A potential adverse event may also be called a near miss or an error, which are not reported with the AdverseEvent Clinical Research Profile.

### Scope

This FHIR IG enables the collection of adverse events from sources of real-world data (RWD) such as electronic health records (EHR) and personal health records (PHR) that patients experience while enrolled in clinical trials. In addition, this IG will also collect adverse events from RWD for post-market surveillance.

This IG ensures the appropriate AE representation required to support regulated clinical trials. It is assumed this IG is implemented (by HCPs, sponsors, CROs) as described to ensure that the originating source (e.g., EHRs) capture such details (i.e., it's not an after-the-fact process). As the AEs are collected in RWD sources, the data can be transmitted via FHIR to sponsors, regulatory agencies, and clinical research organizations for further processing and reporting.

In the pre-market clinical research setting, the clinical investigator must report serious and non-serious adverse events to all applicable parties. A serious adverse event must be reported to the sponsor, clinical research organization, and regulatory agencies within a specific time frame. By using this IG, a clinical investigator can document an AE in the EHR system, it can be transmitted to an electronic data capture (EDC) system, a component of the clinical trial management system for triage and then forwarded to the sponsor and regulatory agencies. Similarly, a patient on a clinical trial can record an adverse event in an electronic patient reported outcomes (ePRO) system, which is then shared with the clinical investigator and reported to the sponsor and regulatory agencies as necessary.

In a post-market setting, a patient or their caregiver, healthcare provider, pharmacies or medical products manufacturers can record the adverse event from the EHR system to the medical product manufacturers and regulatory agencies (e.g., FDA). For FDA submission, this IG can support the population of certain requirements in a future MedWatch form FHIR IG.

Within this guide there are several use cases/examples. Every effort has been made to capture the most important details of the use of the AdverseEvent profile. However, some examples may provide only a stub to referenced resources (e.g., instances of Patient Resource will be referenced using logical ids but are not resolvable, implementation of Patient is left for other guidance and is not the subject of this guide). Connectathons are ideal opportunities to create, compare and consider the holistic implementation of all FHIR Resources.

### How to Use this Guide

This implementation guide is focused on the use of the AdverseEvent Resource in Clinical Research. When reviewing profiles begin with the snapshot view to understand the entire set of data elements and rules for implementation. The differential only shows changes from the parent. The snapshot shows all the constraints and rules, including those inherited from the parent. Those new to FHIR should review the Understanding FHIR section below.

### Previous Specifications

FHIR STU4 contained a non-normative version of the AdverseEvent Resource. The specification here is based on changes made in R5.

### Understanding FHIR

This implementation guide is based on the HL7 FHIR standard. It uses terminology, notations and design principles that are specific to FHIR. Before reading this implementation guide, it's important to be familiar with some of the basic principles of FHIR as well as general guidance on how to read FHIR specifications. Readers who are unfamiliar with FHIR are encouraged to review the following prior to reading the rest of this implementation guide.

- FHIR overview
- Developer's introduction
- (or Clinical introduction)
- FHIR data types
- Using codes
- References between resources
- How to read resource & profile definitions
- Base resource
- FHIR Validation

### Extending beyond this Guide

Implementers should use this guide to communicate AdverseEvent Clinical Research events in an interoperable way. It is understood that this guide is not complete, and implementers might identify additional concepts and data elements. It is recommended that additional Implementation Guides should be adapted from this one as a base for tighter specifications such as in oncology clinical trials.

### Acknowledgments

This IG is sponsored by the HL7 Biomedical Research and Regulation Work Group and co-sponsored by the HL7 Patient Care and Devices Work Groups.

The development of the Clinical Research Adverse Event Implementation Guide was made possible by the Vulcan FHIR Accelerator, a member driven community that exists to help Clinical and Translational Research start using FHIR to manage the vast amount of data they have to work with.

The authors of this guide wish to recognize the following Vulcan member organizations that contributed their time and expertise to the continued development of this guide:

- Advarra
- Clinical Data Interchange Standards Consortium (CDISC)
- Epic
- U.S. Food and Drug Administration (FDA)
- Flatiron Health
- Humanized Health Consulting
- ELIMU
- Memorial Sloan Kettering
- MITRE
- PatientLink
- Pfizer
- TransCelerate Biopharma