The Journal of surgical research · 2025
Leveraging Artificial Intelligence in the United States Health System: Point-of-Care Automation in Reducing Care Cost Burden.
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Manasyan Artur, Harshbarger Raymond, Padwa Bonnie L, Hammoudeh Jeffrey A
Аннотация
INTRODUCTION: The United States healthcare system is at an inflection point, with the majority of hospitals now operating at suboptimal margins, ranging from -3.8% to 2.3%. Concurrently, perioperative inefficiencies and the escalating burden of administrative work have driven rising operating costs.
METHODS: A scoping review was conducted to evaluate how artificial intelligence can improve surgical margins and reduce inefficiencies across medicine and surgery. The extracted data was then synthesized both qualitatively and quantitatively.
RESULTS: Surgical care, which accounts for 70% of hospital revenue and profit, lags behind other fields in terms of efficiency and artificial intelligence integration. Administrative hiring has outpaced physicians nearly 20-fold over the past 40 years. Perioperative workflows remain fragmented, hampered by outdated static preference cards, scheduling delays, and inefficient case preparation. Particularly burdensome is the manual tasks required to trace implantables, biologics, and consumables intraoperatively, a process that is error-prone and diverts clinical staff from patient care.
CONCLUSIONS: This gap creates significant opportunities for artificial intelligence to streamline perioperative processes in real-time at point-of-use, provide 360° traceability, reduce waste, improve surgical efficiency, and recapture margins while maintaining quality and safety.
METHODS: A scoping review was conducted to evaluate how artificial intelligence can improve surgical margins and reduce inefficiencies across medicine and surgery. The extracted data was then synthesized both qualitatively and quantitatively.
RESULTS: Surgical care, which accounts for 70% of hospital revenue and profit, lags behind other fields in terms of efficiency and artificial intelligence integration. Administrative hiring has outpaced physicians nearly 20-fold over the past 40 years. Perioperative workflows remain fragmented, hampered by outdated static preference cards, scheduling delays, and inefficient case preparation. Particularly burdensome is the manual tasks required to trace implantables, biologics, and consumables intraoperatively, a process that is error-prone and diverts clinical staff from patient care.
CONCLUSIONS: This gap creates significant opportunities for artificial intelligence to streamline perioperative processes in real-time at point-of-use, provide 360° traceability, reduce waste, improve surgical efficiency, and recapture margins while maintaining quality and safety.