Abstract
Ambulatory surgery centers (ASCs) have become a cornerstone of surgical delivery in the United States, offering high-quality care with lower costs and reduced nosocomial infection rates compared with hospitals. Over the past two decades, clinical and anesthetic innovations have enabled migration of increasingly complex procedures from hospital operating rooms to ASCs, generating billions in savings for Medicare and patients. Projections estimate an additional $73.4 billion in Medicare savings from 2019 to 2028. The first wave of ASC growth was defined by advances in surgical techniques and anesthesia; a second wave is emerging, driven by artificial intelligence (AI), machine learning (ML), and advanced data analytics. These technologies promise to expand access, optimize efficiency, and redefine surgical care. This article reviews the historical context, current challenges, and frontier opportunities of ASCs as they enter this new era.
Introduction
Ambulatory surgery centers represent one of the most significant structural innovations in American healthcare delivery. By design, they provide same-day surgical care in streamlined facilities with targeted resources, reducing costs and enhancing patient satisfaction. The growth trajectory of ASCs has been remarkable: from simple procedures such as cataracts and endoscopies, to complex orthopedic, spine, and cardiovascular interventions now routinely performed outside hospital walls.
For clinicians and health system leaders, the question is no longer whether ASCs are viable but how to sustain their momentum in the face of reimbursement compression, rising labor and supply costs, and regulatory complexity. A deeper look reveals that the key may lie in the integration of frontier technology, particularly artificial intelligence.
The First Wave: Clinical Innovation
When I was a medical student in the early 1990s, total hip patients often remained hospitalized until their staples were removed. Within a decade, clinical innovation rendered that approach laughably obsolete. By the early 2000s, ambulatory surgery centers (ASCs) were rapidly expanding across the United States, driven largely by advances in minimally invasive techniques, refined instrumentation, and modern anesthesia protocols. Procedures like total hips, that once required a week-long hospital admission could now be performed safely on an outpatient basis, transforming both patient experience and healthcare delivery.
Regional anesthesia is a prime example of the transformative developments of the time. Horner and Dellon’s anatomical studies of knee innervation (1994) led to modern lower extremity blocks, providing durable analgesia without muscle impairment. Our work laid the foundation for outpatient anterior cruciate ligament (ACL) reconstruction and total knee arthroplasty (TKA), among others. Refinements, such as the adductor canal block and interspace between the popliteal artery and posterior capsule of the knee (iPACK) block, have further optimized pain control while enabling early ambulation (Thobhani et al., 2017).
Many clinical advances such as these allowed high-complexity surgical cases to shift from hospital main operating rooms into ASCs, catalyzing the first wave of growth. The economic impact was profound: UC–Berkeley researchers estimated $7.5 billion in Medicare savings between 2008 and 2011, and future projections anticipate an additional $73.4 billion by 2028 (Xu et al., 2020).
The Second Wave: Artificial Intelligence and Machine Learning
While the first wave was clinical, the second wave is digital. Artificial intelligence and machine learning are now poised to transform ASC operations, clinical care, and financial sustainability.
At its core, AI enables pattern recognition at a scale and speed beyond human capability. In healthcare, this means automating repetitive tasks, supporting clinical decision-making, and optimizing resource allocation. For ASCs, where efficiency and throughput are paramount, these capabilities have immediate relevance.
Key Applications
Revenue Cycle Management: AI-driven platforms can now automate much of coding, charge capture, and denial management, reducing errors and accelerating reimbursement. Eligibility verification can occur in real time, preventing costly delays.
Patient Flow Optimization: Conversational AI can autonomously (independently, without constant human direction) manage scheduling, confirmations, and pre-op checklists. For example, the system might call a patient the day before surgery, confirm their arrival time, and remind them not to eat after midnight. This reduces cancellations and delays, while freeing staff to focus on patient care and safety.
Compliance and Accreditation: Regulatory compliance remains a major burden. AI-based software now provides automated tracking of staff certifications, infection control logs, and licensure requirements. Generative AI further assists administrators in interpreting regulatory updates and drafting responses to licensing and accrediting bodies.
Intraoperative Imaging: AI models are increasingly capable of generating near-CT quality 3D reconstructions from fluoroscopic or X-ray images. In orthopedic surgery, this means immediate verification of implant placement or tumor resection margins—functionality previously unavailable even in most hospital settings.
Surgical Robotics and Augmented Reality: Robotics already extend precision and visualization in the OR. With AI integration, robots will begin performing with complex microsurgical maneuvers and facilitating remote surgery. Augmented reality overlays, supported by AI, can help surgeons visualize cancer margins, ligament function and much more with unprecedented clarity. For example, during a total knee arthroplasty, the surgeon could assess joint stability using virtual ligaments projected into the operative field, allowing them to simulate how the reconstructed knee will behave under real-world movement before finalizing implant placement.
Management and Measurement: Perhaps the most transformative application lies in management science. You cannot manage what you cannot measure. AI now enables real-time activity-based costing and productivity analytics. Cutting-edge centers generate weekly reports identifying unprofitable cases, complete with detailed supply usage and fractional staff allocation, without requiring consultants or burdensome paperwork.
Data as a Strategic Asset
The operating room is a data-rich environment. Video feeds, physiologic monitoring, and instrument usage records all represent untapped assets. Historically, this data has been siloed for documentation; increasingly, it is recognized as a strategic resource.
Surgical video, for instance, can be anonymized and repurposed to train robotic algorithms, accelerating the sophistication of next-generation platforms. De-identified patient data can feed predictive models that anticipate complications or optimize care pathways. Synthetic data, generated to mimic real-world patterns without exposing individual privacy, allows researchers to innovate safely.
Operational datasets—turnover times, supply utilization, outcomes—can also be aggregated to benchmark performance across centers.
Monetization of such data does not simply create new revenue streams; it positions ASCs as active participants in shaping the future of surgical science.
Challenges and Barriers
Despite opportunity, ASCs face familiar headwinds. Payer reimbursement remains a challenge for most centers even as inflation drives up labor and supply costs. Staffing shortages, particularly in nursing and anesthesia providers, place pressure on throughput, safety and profitability. Regulatory requirements have multiplied, often consuming resources disproportionate to the size of ASC organizations.
Integration of AI introduces new challenges: data security, algorithmic bias, interpretability, and medicolegal liability. Physicians and nurses must remain vigilant that adoption of these technologies enhances, rather than distracts from, patient care. Ethical stewardship of operating room data is particularly critical if ASCs are to maintain public trust.
Catalyzing Collaboration
Recognizing both the promise and the peril of this transition, my venture capital fund, Untethered Ventures, has launched a program for ASC leaders to collaborate and guide the second wave of innovation: ASCIQ. This initiative aims to convene leading clinicians, administrators, and technologists, to share best practices, evaluate emerging tools, and develop frameworks for responsible implementation. The goal is to ensure that ASCs remain not only cost-effective alternatives but also incubators of surgical innovation.
Conclusion
Ambulatory surgery centers have proven their value through two decades of lower costs, reduced infections, and billions in Medicare savings. The first wave of ASC growth was enabled by clinical and anesthetic advances; the second wave is being shaped by artificial intelligence, machine learning, and the strategic use of data. These technologies offer the potential to double economic savings, expand access to underserved populations, and enhance both efficiency and outcomes.
For physicians, nurses, and ASC leaders, the opportunity is clear: engage actively in shaping this digital transformation. By doing so, ASCs can continue to lead in the delivery of affordable, high quality surgical care.