Ambient In Research
Promoting Responsible Adoption Of Ambient Digital Scribe Technologies in Clinical Research
Change is in the AIR
Ambient Digital Scribes Are Transforming Clinical Documentation
Ambient digital scribes (ADS) are tools used by clinicians to record and transcribe patient-provider encounters, utilizing artificial intelligence (AI) to draft a summary for the clinician's review. When paired with integration and synthesis functionalities, AI can generate comprehensive, integrated clinical summaries.
ADS are being rapidly adopted in healthcare practice and have been shown to reduce documentation burden, improve efficiency, reduce burnout, and allow clinicians to focus more on conversations with patients.
Analysts estimate that by the end of 2025, 50% of healthcare facilities in the US will be using ADS.
What Does this Mean For Clinical Research?
ADS is creating new norms for clinical encounter documentation. Clinical research policies and practices will need to adapt.
By digitizing the patient-clinician conversation in real time, ADS opens the door to intentional applications beyond care, particularly in clinical research and trials.
ADS has the potential to address clinical research's longstanding challenges: recruitment, data documentation, safety oversight, and participant engagement.
Use of ADS in clinical trials requires proactive planning and careful consideration of the regulatory, ethical, technical, and operational requirements that are unique to research.
Introducing Ambient In Research (AIR)
Ambient in Research (AIR) is a newly launched multi-stakeholder coalition dedicated to advancing the responsible adoption of ambient digital scribe (ADS) technologies in clinical trials and real-world research.
AIR convenes technology developers, pharmaceutical and device sponsors, academic research centers, independent sites and networks, IRBs, standards organizations, industry consortia, and others.
AIR participants co-create open-source, practical solutions that address seven key areas for attention:
- Research participant protections
- Research and medical device regulation compliance
- Record accuracy and completeness
- Data structuring and mapping
- AI tuning to the clinical trial context
- Integrations and operational considerations
- Real-world experience and value assessment