Guiding the Safe and Effective Integration of Ambient Digital Scribes into Primary Care

NIH RePORTER · AHRQ · R03 · $96,205 · view on reporter.nih.gov ↗

Abstract

PROJECT SUMMARY Primary care physician (PCP) burnout is a prevalent threat that endangers patients, harms providers who have dedicated their careers to improving the wellbeing of others, and creates significant financial strain on healthcare systems. A major contributing factor to PCP burnout is the burden of documentation and other electronic health record (EHR) tasks. Major healthcare industry partners (e.g., Amazon, Nuance, Oracle) are already leveraging advances in artificial intelligence (AI) to address this issue, as several AI documentation technologies are currently on the market. These technologies, referred to as Ambient Digital Scribes (ADSs), utilize AI technology to passively capture real-time patient-provider conversational interactions and assemble them into a structured note. In a testament to the severity of this documentation problem and the potential of these technologies, ADSs are currently being implemented and pilot tested at hospital systems nationally. As many as 1 in 3 PCPs have already tried AI scribe tools, and in January of 2024, Nuance announced their ADS is set to be deployed at more than 150 health systems nationwide. The rapid implementation of ADSs in healthcare systems is incongruous with growing concerns about their safety. While ADSs have a great potential for addressing documentation burden, they, like any AI technology, may have dangerous unintended consequences. While large, financially robust healthcare systems may have the resources to address these consequences, small rural hospitals are likely to be late adopters with fewer resources to combat barriers to the safe and effective use of this new technology. This work, “Guiding the Safe and Effective Integration of Ambient Digital Scribes into Primary Care,” proposes to develop a prototype guide for the safe and effective integration of ADSs into primary care. As little is known about the safety, efficacy, and usability of these new technologies and the impact they will have on primary care, this work first seeks to identify the barriers and facilitators to successful ADS implementation through the lens of systems engineering. A mixed method approach consisting of retrospective data analyses and interviews with PCPs and patients will provide foundational knowledge on how ADSs integrate into the primary care workflow. Using key insights developed from this foundational data, our team will co-develop a prototype guide with a panel of internationally recognized experts in primary care, healthcare technologies, patient safety, and AI. Our innovative approach is strategically designed to be effective for any current or future ADS and reflects the speed at which AI-driven technologies are being developed and implemented. This guide will serve as a tool to support ADS implementation and use at healthcare provider organizations of all sizes ranging from large multi-facility healthcare systems to individual clinics and federally qualified health centers, and thus wi...

Key facts

NIH application ID
11038097
Project number
1R03HS030307-01
Recipient
MEDSTAR HEALTH RESEARCH INSTITUTE
Principal Investigator
Joshua Biro
Activity code
R03
Funding institute
AHRQ
Fiscal year
2024
Award amount
$96,205
Award type
1
Project period
2024-09-30 → 2025-09-29