How AI is Improving Efficiency When the World Needs it Most

Agnes Berzsenyi, President & CEO, Women’s Health & X-ray, GE Healthcare

No one could have predicted what this year was going to bring and more so, the impact it would have on the healthcare industry.

As the number of COVID cases are back on rise in many parts of the world and beds in the ICU once again fill with critically ill patients, our heroic healthcare providers are continuing to work around the clock to care for patients with limited staff and resources.

With the prospect of a vaccine on the horizon, a sense of hope for the role innovation can play to aid in combatting COVID-19 is also on the rise.

At GE Healthcare, we’ve seen the role innovation can play in today’s environment firsthand with mobile X-Ray, a technology that is the first image for most COVID-19 patients worldwide and used daily to monitor patients’ progress.

Early in the pandemic, our mobile X-ray team managed to increase manufacturing three-fold to meet the unprecedented demand for X-Ray at the beside. Throughout the summer months, the team worked closely with customers on redefining workflows, sharing X-Ray best practices worldwide, and launching a suite of AI algorithms in many parts of the world to help automatically detect consolidation and Pneumonia indicative of COVID-19. 

Today as COVID-19 is closer to home than ever in the United States, we’re launching the newest version of on-device artificial intelligence (AI) algorithms designed to help healthcare providers in the fight against it.

The industry-first AI algorithm to assess Endotracheal Tube (ETT) placements within our Critical Care Suite 2.0[1] helps clinicians efficiently care for COVID-19 patients. The technology uses AI to automatically detect ETTs in chest x-ray images and provides an accurate and automated measurement of ETT positioning to clinicians within seconds of image acquisition.

With 45% of ICU patients receiving time critical, high-risk ETT intubation for ventilatory support and the serve complications that can derive from ETT misplacement[2],[3],[4], this algorithm is designed to help ICU staff identify and correct misplacements quickly. Currently one in four patients intubated outside of the operating room have misplaced ETTs on chest x-rays.[5],[6],[7],[8],[9] The new AI algorithm is expected to help provide increased confidence and precision for providers performing intubations.

The AI solution is one of five included in Critical Care Suite 2.0, an industry-first collection of AI algorithms embedded on a mobile x-ray device for automated measurements, case prioritization and quality control.

Already, we’ve seen the value AI can bring, helping providers prioritize and adjust care for critically ill patients with the Critical Care Suite[10] pneumothorax AI algorithm introduced last year. In one case, the AI discovered a pneumothorax, a type of collapsed lung, within an hour in an intubated COVID-19 patient in Cleveland – potentially helping ICU staff save a life[11].

For everyone, the pandemic is personal. It’s affecting our families, friends, neighbors and community. For our team, it’s been an honor to provide these cutting-edge technologies to the healthcare heroes on the frontlines.

 Every time we can help make a bustling ICU more manageable for staff and improve their efficiency with AI, is another moment we can help improve patient care when the world needs it most.

To hear about the impact AI on mobile X-Ray can have during the COVID-19 pandemic, join our upcoming webinar and live Q&A with Dr. Amit Gupta, cardiothoracic radiologist at University Hospitals in Cleveland, on December 1st at 12:30 PM in GE Healthcare's innovation theater.

[1] Only available in the United States. Not cleared or approved by the FDA. Distributed in accordance with FDA imaging guidance regarding COVID-19 public health emergency.

[2] Hannah Wunsch, Jason Wagner, Maximilian Herlim, David Chong, Andrew Kramer, and Scott D. Halpern. ICU Occupancy and mechanical ventilator use in the United States. Crit Care Med. 2013 Dec; 41(12): 10.1097/CCM.0b013e318298a139.

[3] Dawei Wang, Bo Hu, Chang Hu, et al. Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus–Infected Pneumonia in Wuhan, China. JAMA. 2020;323(11):1061-1069. doi:10.1001/jama.2020.1585

[4] Lingzhong Meng, M.D.; Haibo Qiu, M.D.; Li Wan, M.D.; Yuhang Ai, M.D.; Zhanggang Xue, M.D.; et al. Intubation and Ventilation amid the COVID-19 Outbreak: Wuhan’s Experience. Anesthesiology 6 2020, Vol.132, 1317-1332.

[5] Jemmett ME, Kendal KM, Fourre MW, Burton JH. Unrecognized misplacement of endotracheal tubes in a mixed urban to rural emergency medical services setting. Acad Emerg Med 2003;10:961–5.

[6] Katz SH, Falk JL. Misplaced endotracheal tubes by paramedics in an urban emergency medical services system. Ann Emerg Med 2001;37:32–7.

[7] Lotano R, Gerber D, Aseron C, Santarelli R, Pratter M. Utility of postintubation chest radiographs in the intensive care unit. Crit Care 2000;4:50–3.

[8] McGillicuddy DC, Babineau MR, Fisher J, Ban K, Sanchez LD.

[9] Is a postintubation chest radiograph necessary in the emergency department? Int J Emerg Med 2009;2:247–9.

[10] Not available in all geographies.

[11] GE Healthcare data on file.