After a long struggle with the COVID-19 epidemic, healthcare providers are now facing a crisis that will reach critical heights in the future. Surveys show that at the beginning of 2022, almost one in two health professionals (47%) said they felt exhausted, compared to 42% a year earlier. [1].
Use of AI to reduce the consumption of medical staffPhoto by Philips
At the international level, more and more health professionals are thinking about leaving the field, a trend that is causing concern among the authorities և health systems, which are facing staff shortages. [2]. In this context, one can consider the immediate benefits of technology – how we can use artificial intelligence to improve the experience of professionals by improving the quality of medical care.
The epidemic has in many ways exacerbated what has affected healthcare professionals over time: the tedious repetition of routine tasks, the growing number of data needed to extract relevant information, and the widespread frustration with inefficient work that hinders patient care. This was summed up by the doctor in a study by Medscape Physician Burnout and Depression. [3] From 2022, when asked “Where are the relationships with patients that have made this work satisfying?”.
Simplify workflows through automation based on artificial intelligence
What we are seeing is the urgency of relieving health professionals of the stress of elementary, repetitive tasks so that they can focus on what they are primarily focused on in medicine, patient care. And this is exactly the facilitation that artificial intelligence can make possible by transferring the burden of tedious manual labor from technology to humans. AI allows healthcare providers to use their time and energy to care for the patient rather than to perform cumbersome procedures.
Take, for example, the section on medical imaging and radiology technology. It was ranked second by hospital managers as the profession with the largest shortage of qualified staff [4]Radiologists face the challenge of performing the best quality scans with an accurate diagnosis every day, while high workloads are a major contributor to work-related stress. [5]. In addition, patients are often anxious, which increases the pressure to perform an effective examination.
By automating many of the time-consuming tasks, healthcare professionals can focus on communicating with the patient while improving patient experience և consistency with results. Research shows that medical imaging staff welcome such technological support. they think that almost a quarter of their work (23%) is inefficient և can be automated. [6].
An example of this is putting the patient in the correct position for the examination. In imaging, such as computed tomography, misalignment of the patient is a common problem with undesirable effects, such as an increase in the patient’s radiation dose or imaging. [7]. This is where the new AI camera technology can change everything.
The camera on the ceiling above the patient’s table uses algorithms that can automatically detect the patient’s anatomical guidelines, supporting the patient’s fast, accurate, and postural posture.
Smart touchless detection technology leads to technologists saving on manual labor during MRI scans by automatically monitoring the patient’s breathing. It is also possible to schedule routine MRI scans in less than a minute [8], even for less experienced operators, which allows them to pay more attention to patients. In addition, intelligent systems with the help of AI can offer the most convenient protocol for each MRI examination, which will lead to the automation of planning, scanning and control processing.
With such AI-based automation, technologies are less likely to worry about equipment configurations և can improve patient experience by making their work less stressful և rewarding.
Providing relevant information on a scale
In the event of an information overload, artificial intelligence can also facilitate the work of health professionals by providing them with relevant information directly at the point of care.
For example, one of the biggest challenges facing critical care teams in intensive care units (ICUs) is the large amount of data collected for each patient. Each patient in the intensive care unit can generate up to thousands of data units per day, leading to overcrowding of medical staff seeking to separate relevant information from irrelevant information. [9].
The need for human-centered artificial intelligence
Of course, technology can only be part of an effective way of managing staff and reducing fatigue. But as these examples show, others’s artificial intelligence can make a significant contribution to improving human experience in the healthcare sector by ‘improving workflow efficiency’ and enhancing clinical experience.
To reduce fatigue, but also to restore the joy of health professionals, we must first ask ourselves how we can develop digital tools to support the patient-physician relationship. Research has consistently shown that the lack of workflow integration is one of the main barriers to the wider adoption of artificial intelligence in the healthcare sector, indicating the need for a system-oriented, people-centered design.
By prioritizing human needs, AI-based solutions can be developed that act as a discreet helper to support healthcare professionals when they are under a lot of pressure. Because if there is one truth that underscores the growing personnel crisis, the lack of health, it is that there is no health care without the involvement of professionals who lead a healthy lifestyle.
reference
[1] https://www.medscape.com/viewarticle/966996:
[2] https://www.sciencedirect.com/science/article/pii/S2542454821001260
[3] https://www.medscape.com/viewarticle/966996:
[4] https://healthexec.com/topics/healthcare-administration/hospital-ceos-workforce-shortages-challenging
[5] https://www.usa.philips.com/healthcare/medical-specialties/radiology/improving-radiology-staff-and-patient-experience/staff-research
[6] https://www.usa.philips.com/healthcare/medical-specialties/radiology/improving-radiology-staff-and-patient-experience/staff-research
[7] Habibzadeh MA, Ay MR, Asl AR, Ghadiri H, Zaidi H. The effect of incorrect concentration on patient և և image noise on X-ray CT image. Phantom և clinical studies. Phys Med. 2012; 28 (3): 191-199:
http: // doi: 10.1016 / j.ejmp.2011.06.002:
[8] Based on internal tests. Results may vary.
[9] https://hbr.org/2018/03/how-mayo-clinic-is-combating-information-overload-in-critical-care-units
This article supports Philips Romania