Vein - Insights

Will PIV “Hard Sticks” Meet Their Match In AI-Driven Ultrasound?

January 10, 2018

As one of the most commonly performed invasive medical procedures in America1, the placement of peripheral intravenous (PIV) catheters is a critical yet often challenging procedure for nurses. With patient comfort top-of-mind for nurses, any difficulty in starting a PIV not only sets a patient’s experience down the wrong path, but can also lead to delay in execution of other basic medical procedures if vascular access is not secured.

Industry studies reveal that due to chronic illness, chemotherapy, obesity and drug abuse, 35% of emergency department PIV placements are “hard sticks” 2 requiring multiple attempts, referral to more invasive and expensive central lines with a possibility of increased bloodstream infection rates. This is a staggering number of patients who are subject to at best an uncomfortable introduction to treatment and at worst a painful and extended insertion procedure time. Both make up an entirely preventable problem faced by the health care industry today. Even cursory surveys of patients who have had a recent healthcare experiences routinely yield frustrating stories about IV stick problems, which are at the very least consistent anecdotal evidence.

There have been attempts to utilize more modern imaging or infrared technologies to replace the “blind stick” and address this issue. However, till date no solution has cracked the code of “price versus performance” which is critical for large-scale adoption by healthcare systems and driving use at the bedside to improve first stick rates.

Ultrasound technologies designed for other purposes have been modified to meet this need, yet have not proven to be adaptable enough for this micro-ultrasound application. These technologies struggle to display a single shallow vein in the center of the imaging screen, while coming packaged in a large, bulky device that crowds an already busy hospital room. Infrared-based “illuminators” have shown promise in locating an accessible vein, but are unable to provide additional necessary information about depth, diameter and integrity to truly address the hard stick issue.

Where current solutions come up against adoption barriers, there is an emerging solution that offers promise of combining the best of current options with some unique next-gen features, aimed at improving patient comfort, reducing nurses time and saving healthcare costs. As seen in other industries such as telecom, auto and manufacturing, ultrasound continues to not only be miniaturized for ease-of- use and portability while retaining high image quality, but more importantly infused with artificial intelligence (AI) or “machine learning”.

Nursing today needs a Peripheral IV insertion tool that is compatible with the profession’s ‘see one, do one, teach one’ method of learning. A tool that that offers quick and clear access to veins at shallow and deep points within the access point and provides immediate recognition of vein versus artery. AI can and will help here.

Not a scene from the next sci-fi movie, but soon nurses will be able to pick up an AI-driven ultrasound tool to locate and label a patient’s venous system. Artificial Intelligence in tools, when applied correctly, has the potential to address system inefficiencies and resolve problems with many clinical applications that complicate the lives of patients and healthcare providers.

Providing nurses with a rapid and clear vein assessment several centimeters deep, these imminent technologies aim to dramatically increase first time accuracy, patient safety and patient satisfaction – which is a true win for patient, provider and healthcare systems alike.

Kevin Goodwin is the CEO of Signostics, a pioneer is applying the emerging field of artificial intelligence with the extreme miniaturization of ultrasound to solve common every day problems in healthcare.

REFERENCES 1 Bernatchez SF, Care of Peripheral Venous Catheter Sites: Advantages of Transparent Film Dressings Over Tape and Gauze. The Journal of the Association for Vascular Access, December, 2014. Volume 19, Issue 4, 256 - 261.

2 Stolz LA, Stolz U et al, Ultrasound-guided peripheral venous access: a meta-analysis and systematic review. J Vasc Access, 2015; 16 (4):321-326.