The opioid crisis has had a profound impact on U.S. veterans, prompting the Veterans Health Administration (VHA) to implement stringent guidelines for opioid prescriptions. A recent study explored how dual-system healthcare usage—where veterans receive care from both VHA and non-VHA providers—affects the risk of Opioid Use Disorder (OUD). Using advanced deep neural networks (DNN) and explainable artificial intelligence, researchers analyzed 856,299 patient records from VA Medical Centers in Washington DC and Baltimore (2012-2019). The findings revealed that dual-system use significantly increases OUD risk, especially when interacting with demographic and clinical factors. Interestingly, older patients who are dual-system users face heightened OUD risks, while a history of other drug use mitigates this risk. This research underscores the need for targeted interventions to protect vulnerable veteran populations.

Understanding the Elevated Risk Among Dual-System Users

Dual-system healthcare utilization among veterans presents unique challenges in managing opioid prescriptions. The study found that nearly 17% of the analyzed cohort had OUD, identified through natural language processing of clinical notes and ICD diagnoses. Dual-system users were more likely to have OUD, driven by fragmented care and lack of coordinated information sharing between healthcare systems. The DNN model confirmed that dual-system use is a significant risk factor, alongside prior opioid or substance use. Importantly, the interaction between dual-system use and certain demographic and clinical factors further complicates the risk profile.

Older age was generally associated with a lower OUD risk but interacted positively with dual-system use, indicating that older patients enrolled in dual systems may be particularly vulnerable. Conversely, a history of other drug use interacted negatively with dual-system use, suggesting a protective effect against OUD. These nuanced interactions highlight the importance of personalized care strategies for different patient profiles. For instance, younger veterans with multiple comorbidities and those receiving care from multiple systems require special attention. The study also revealed that baseline conditions like PTSD, depression, chronic pain, and TBI played a role in increasing OUD risk among dual-system users.

Implications for Policy and Future Research

The implications of this study extend beyond understanding risk factors; they provide valuable insights for policymakers and healthcare providers. The research underscores the necessity of improving care coordination between VA and non-VA systems to mitigate the elevated OUD risk among dual-system users. Advanced AI models can play a crucial role in identifying high-risk subgroups, enabling targeted interventions. For example, older veterans without a history of substance use might benefit from enhanced monitoring and support when enrolled in dual systems.

Moreover, the study highlights the underdiagnosis of OUD in electronic health records (EHRs), as NLP methods identified over eight times more cases compared to ICD-based diagnoses. This discrepancy suggests that traditional diagnostic methods may overlook many cases, necessitating the integration of NLP tools into routine clinical practice. Future research should explore the underlying causes of these interactions and incorporate social and community factors to develop comprehensive prevention strategies. Additionally, investigating the impact of treatment dose and duration on OUD outcomes could provide further insights into effective management practices.

Abridge, a pioneering company in the field of generative artificial intelligence for healthcare, has introduced an innovative solution specifically tailored for emergency medicine. Over the past six years, Abridge has been dedicated to enhancing medical documentation through cutting-edge technology. The new product, Abridge Inside for Emergency Medicine, is currently being utilized by several prominent health systems, including Deaconess Health System, Emory Healthcare, Johns Hopkins Medicine, and UChicago Medicine. This tool integrates seamlessly with Epic’s workflows, offering clinicians the ability to create accurate and efficient clinical notes without manual adjustments.

The development of this advanced technology was made possible through Abridge’s participation in the Epic Workshop program, where third-party vendors collaborate closely with Epic to co-develop technologies. Clinicians can now select patients from the department’s Track Board and immediately begin ambient recordings using Haiku. Abridge’s speech recognition models automatically detect specialty, language, and multiple speakers, ensuring precise transcription and documentation. According to Dr. Tricia Smith, an attending emergency physician at Emory University Hospital Midtown, Abridge Inside has significantly reduced burnout and increased job satisfaction among emergency department staff. She emphasized that no one who uses Abridge would want to revert to traditional methods.

Addressing the high rates of burnout in emergency medicine, which stands at 63% according to a 2024 Medscape survey, Abridge aims to alleviate the documentation burden faced by clinicians. Dr. Shiv Rao, CEO and cardiologist who founded Abridge in 2018, highlighted the importance of helping clinicians focus on patient care while reducing administrative tasks. The chaotic nature of emergency medicine requires tools that can handle discontinuous workflows, allowing clinicians to stitch together conversations and interactions into coherent notes. Collaboration with emergency department clinicians ensured that the final product met their specific needs, including stylistic preferences and medical-legal compliance.

Abridge’s rapid growth and widespread adoption across the healthcare industry underscore its commitment to delivering enterprise-grade solutions. The company’s AI-powered platform has been deployed in numerous health systems, including Kaiser Permanente, Christus Health, Sutter Health, Yale New Haven Health System, and many others. Feedback from thousands of users has enabled Abridge to iterate quickly and meet the scale of the opportunity. As healthcare providers increasingly adopt generative AI technology, Abridge continues to innovate, leveraging both internal and external advancements to enhance its capabilities.

Abridge’s success in transforming medical documentation has led to the company’s name becoming synonymous with ambient note-taking. Clinicians now use “Abridge” as a verb, reflecting the integration of this technology into daily practice. On the patient-facing side, Abridge is collaborating with OpenNotes to evaluate AI-generated visit summaries from a patient-centric perspective. This approach not only streamlines clinical documentation but also enhances communication between healthcare providers and patients, fostering better understanding and trust. Abridge’s mission to bridge the gap between clinicians and their workload, while improving patient care, exemplifies the positive impact of technology in healthcare.