Seminars in Neurology最新文献

Carotid artery stenosis is a major cause of acute ischemic stroke, accounting for approximately 15% of cases. Although optimal medical therapy remains the cornerstone of management, current guidelines recommend consideration of surgical intervention for symptomatic patients with ≥50% stenosis and asymptomatic patients with ≥70% stenosis. Extensive evidence supports carotid endarterectomy (CEA) as the gold standard procedure, whereas transfemoral carotid angioplasty and stenting (TF-CAS) and transcarotid artery revascularization (TCAR) offer safe alternatives for patients with high surgical risk. Emerging data suggest that TCAR provides safety and efficacy profiles comparable to CEA and superior to TF-CAS in select patients. Considering these findings, selecting an appropriate revascularization strategy should rely on a multidisciplinary, individualized risk-benefit assessment. This article aims to provide a comparative review of the latest evidence on clinical indications, surgical techniques, and outcomes for current carotid revascularization strategies.

Stroke is a major global health burden, requiring time-sensitive diagnosis and treatment to improve patient outcomes. This urgency has created a compelling role for artificial intelligence in the stroke imaging workflow to accelerate diagnosis and treatment. Artificial intelligence has demonstrated a significant impact across multiple aspects of stroke care, including automated detection of acute findings, expedited triage and notification of findings, quantitative assessment of infarcts, predictive prognostication of outcomes, as well as acceleration of image acquisition. However, these advances are accompanied by important limitations including introduction of biases and challenges in the real-world clinical integration of such tools. In this review, we examine the current applications of artificial intelligence in stroke imaging and evaluate the limitations and real-world implementation challenges.

Documentation, coding, and billing (claims submission) are foundational to neurologic practice in the United States, enabling accurate reimbursement, effective communication, and data-driven advancements in patient care, research, and education. Neurologists navigate complex regulatory frameworks and evolving payer guidelines, requiring meticulous attention to diagnostic coding, evaluation and management (E/M) services, and procedure-specific requirements. This chapter examines critical aspects of neurologic billing and coding, including ICD-10-CM (International Classification of Diseases, Tenth Revision, Clinical Modification) for diagnostic accuracy, updated E/M guidelines emphasizing medical decision-making and time, and new telemedicine codes. It highlights the best practices for procedure coding and the use of digital health technologies. The challenges posed by prior authorization are explored, alongside potential solutions like artificial intelligence-driven tools and policy reform. By prioritizing precision, compliance, and technological adaptation, neurologists can enhance patient outcomes, support practice sustainability, and contribute to the broader goals of equitable, efficient, and innovative neurologic care.

The practice of neurology is undergoing significant transformation due to evolving economic pressures, workforce shortages, and increasing demand for neurologic care. Lower reimbursements, increasing operating expenses, and complexity of care challenge the sustainability of existing practice models. This study outlines critical considerations for practice and staffing models in neurology, focusing on strategies to optimize access to care, contain costs for patients and the practice, and enhance operational efficiency. Key topics discussed include integrating advanced practice providers, expanding teleneurology and intravisit care, exploring value-based care models, and enhancing workflows via technology to improve patient experience and clinic efficiency. As the field continues to evolve, neurology practices must adopt agile strategies that balance clinical excellence with economic sustainability in order to meet the demands of a challenging healthcare landscape.

Neurologic disorders are prevalent in the United States, with an estimated 60% of Americans experiencing at least one neurologic condition. This volume of neurologic disease requires commensurate care. In this article, we review access to neurologic care and examine challenges and opportunities across several dimensions of access. Long wait times for neurologists and evidence that neurologists see only a fraction of certain neurologic conditions suggest issues with the availability of care; better triage of neurologists' expertise and employment of neurology advanced practice providers may improve the supply of neurologic care. Accessibility of neurologic care is hindered by regional inequities and urban/rural disparities, which may be attenuated through the use of telemedicine. High out-of-pocket costs and excessive pharmaceutical prices inhibit the affordability of neurologic care; these obstacles may be addressed with more appropriate test utilization and more effective drug price negotiation. Lastly, innovative care models facilitated by recent technological advances have the potential to profoundly expand access to neurologic care.

Although the quality movement in healthcare in the United States has been maturing for the last several decades, neurology remains a frontier of work related to learning healthcare systems (LHS) and the science of improvement. This review describes the use of LHS models in neurology and the use of Improvement Science to advance position system changes and improve care. LHSs are broadly understandable, widely supported, and have a developing yet proven track record. However, there are distinct challenges at multiple levels in successful implementation, as well as nuances related to variability in practice patterns and institutions. This review outlines these hurdles and approaches to addressing them. There are examples of effective work currently being conducted in this emerging field, with an emphasis on two subspecialties that have been the primary early adopters of these models and methodology within neurology: stroke and epilepsy. As LHS models take shape in neurology subspecialties, there will be an ongoing need for collaboration and iterative change to support continuous improvement in systems of care and improve outcomes for patients with neurologic disease.

Effective negotiation with health insurance payers is crucial for neurology practices to maintain financial sustainability and optimal patient care. This paper outlines strategic approaches to payer negotiations, emphasizing the importance of clearly defining practice strengths, understanding market conditions, and leveraging detailed contextual data to counter incomplete or misleading payer analytics. Specific considerations discussed include customer service efficiency, claims management, provider-payer relationships, clinical management policies, contract terms, and fee schedule clarity. We present actionable negotiation strategies illustrated by a case study, highlighting tactics such as targeted utilization reports, social media advocacy, and data-driven reimbursement proposals. Additionally, practical advice is provided on managing payer interactions, addressing common administrative inefficiencies, and strategically limiting patient volumes when negotiations stall. This structured negotiation approach empowers neurologists to effectively align clinical value with payer objectives, ensuring fair reimbursement and enhanced practice viability.

Advocacy is an important part of the practice of neurology integral to optimal patient care and research. Opportunities exist for neurologists to further their engagement in advocacy outside of the office, and neurologists are well-positioned to share their knowledge and expertise as advocates. Many barriers to care, such as the cost of and access to prescription drugs, have an outsized impact on patients with neurological conditions, which underscores the importance of neurological advocacy. Advocacy opportunities span many different forms and range from local to global in scale. The benefits to a neurology career can be vast, from improved knowledge of health care systems to leadership opportunities, to networking among colleagues and community leaders, and enhanced academic profiles. Numerous resources are available for neurologists seeking further engagement in advocacy for their patients and profession.

This manuscript examines the expanding role of population health strategies in neurology, emphasizing systemic approaches that address neurological health at a community-wide level. Key themes include interdisciplinary training in public health, policy reform, biomedical informatics, and the transformative potential of artificial intelligence (AI) and large language models (LLMs). In doing so, neurologists increasingly adopt a holistic perspective that targets the social determinants of health, integrates advanced data analytics, and fosters cross-sector collaborations-ensuring that prevention and early intervention are central to their efforts. Innovative applications, such as predictive analytics for identifying high-risk populations, digital twin technologies for simulating patient outcomes, and AI-enhanced diagnostic tools, illustrate the transition in neurology from reactive care to proactive, data-driven interventions. Examples of transformative practices include leveraging wearable health technologies, telemedicine, and mobile clinics to improve early detection and management of neurological conditions, particularly in underserved populations. These emerging methodologies expand access to care while offering nuanced insights into disease progression and community-specific risk factors. The manuscript emphasizes health disparities and ethical considerations in designing inclusive, data-driven interventions. By harnessing emerging technologies within frameworks that prioritize equity, neurologists can reduce the burden of neurological diseases, improve health outcomes, and establish a sustainable, patient-centered model of care benefiting both individuals and entire communities. This integration of technology, interdisciplinary expertise, and community engagement fosters a future where brain health is preventive, accessible, and equitable.