For emergency nurse Maranda Bradshaw, AI helps reduce the stress it calls “cognitive fatigue of stack”.
“Think about it this way: for any given procedure that I perform, there could be 20, 30, 40 steps that I am, and each step is represented by a stackable plate. The “plates stack” of a procedure symbolizes your memory charge. The higher the memory load or the memory battery.
I have to get the start -up IV kit, the needle, chlorhexidine (an antiseptic that helps prevent infections), an IV extension and right fluids. Let’s say in the middle of the procedure that the charge nurse sees that I have to draw a lactate to help resuscitation. So, I take the plate on which I just worked out of the battery, put it on the side and add the lactate “plate” to the top of my battery. Now the memory pile is no longer organized.
The AI helps me not to drop the plates or lost or lost. The technology captures the steps of the process that we, as a infirmières, already do manually, invites me to the computer and helps me to keep the control points. »»
– Maranda Bradshaw, RN MSN, nurse manager for emergency services at UC San Diego Health.
The example of Bradshaw is only one of the many ways in which artificial intelligence can help improve nursing jobs: it increases the skills and responsibilities of practice of clinical nurses, incorporates different databases and technological systems and, ultimately, helps make their work more efficient.
Kay Burke, MBA, BSN, RN, NE-BC, Vice-President and Head of Nurse IT at UCSF Health, share: “Sometimes we call this” back to bedside “-allowing nurses to remove computers, get out of documentation software and take care of patients”.
Burke also notes how AI can help reduce the cognitive burden of nurses. “The nurses spend so much brain power over what to do next. AI can help prioritize these tasks so that nurses know what is the next procedure. It provides a fast and efficient control list. ”
UC Health recognizes the essential role that nurses play in the health care system
According to the American association of nursing collegesNurses represent the largest segment of health care workforce in the United States, with 4.7 million nurses authorized in the field. In California, there are roughly 542,000 authorized active nurses.
At UC Health, nurses are an integral part of programs and initiatives that examine how AI can be integrated into the health care landscape to improve both their professional roles and the experiences of their patients. Nurses in the UC system are seated on examination and advice committees that assess and select new technologies, and many use cases for applications are submitted by UC nurses working every day with patients.
The immediate advantage of the AI: decrease the time of documentation and execution of administrative tasks
Overall, clinicians claim that the decrease in the time they spend documenting graphics in electronic health files is one of the main advantages of IA integration into their workflow.
According to Donna Wellbaum, MSN, RN, NEA-BC, NI-BC, leader in nursing at UCLA Health, “in a quarter of 12 hours, a nurse spends an average of 132 minutes to document patient information in the DSE (Electronic Health Recording) system”.
This represents around 18% of the time of a nurse for a quarter of 12 hours. This time does not also take into account other research than a nurse may need to conduct outside the DSE to consult other databases and systems on policies, patient education, health standards or other procedures.
Credit: UC Health
Burke, from UCSF Health, offers an example familiar to anyone who composes emails or text documents. “The use of AI in DSE is similar to the predictive function that has been used in many email and text processing applications.
Wellbaum agrees. “The nurses spend a lot of time in the graphics. AI helps them put this time with patients. ”
Integration of protocols, policies and procedures
First -line nurses and nurses in management roles both cite another key advantage that AI provides the profession: being able to collect information from several sources and systems on a single screen to help them get what they need to help their patients.
Wellbaum says that “AI can help investigate separate databases so that when a nurse must complete the documentation, this nurse can ask the system to help consolidate the required documentation.”
With an AI superposition, nurses no longer need to “hunt and peck” different systems to find patient education, information on drugs, pathological processes, policies and procedures, health standards or even refreshment on the stages of a routine clinical task that they may have not done for some time. But even with these time savings, nurses are always those that assess suggestions.
Burke says: “The nurses will always have to apply a clinical judgment and a critical thinking in the way they take care of their patients…. Each AI tool requires a clinician to review and validate what has been suggested. ”
Whether in a hospital, outpatient, clinical or urgent community, every minute that a nurse can spend directly with a patient and not in a technical system can lead to a better result for the patient.
AI in nursing and health care: this is not new
Sewn nurses emphasize that AI models were in health care long before the current buzz around the new technology, its offers and its possibilities. To support and recommend nursing interventions, Burke points to various AI applications that have already helped nurses provide care, including decision support systems, risk prediction scores and early deterioration models.
Burke adds: “As we know, AI is – in terms of computer programs that process reasoning, designed to act rationally using smart software to support clinical decision -making. It’s not new. “
Bradshaw, an emergency nurse, agrees.
During her 25 -year -old career career, Bradshaw remembers when the nurses created paper processes and decision -making trees to document best practices alerts, and in particular around the stages to be taken to fight sepsis. (Septicemia is a condition where the body does not respond to an infection and infection propagates to other organs and vital systems.) This type of logical work was the precursor of current computer algorithms.
For a certain time, sepsis was a clinical priority where each patient in an emergency room would be subject to the protocol with high intensity of workforce and several stages to treat it, including repeated verifications to give liquids and monitor vital signs at regular intervals. But each patient did not need this protocol.
“Now, an AI model goes beyond what we could work with paper graphics and decision trees to examine all data on the patient and helps us to eliminate those who are not seriously at risk of sepsis. This model supported by technology allows us to focus on taking care of those who need care most. ”
Nurses stimulate AI innovation in health care
In the UC health system, nurses are at the center of conversations around AI, its possibilities, its applications and its limits in current clinical circles.
At UCSF Health, Burke notes “We do not make descending decisions with regard to nursing practices. We make sure that we have front line nurses who participate and stimulate decision -making. Nurses lead changes in practice and innovation. ”
At UC San Diego Health, there is both an Ai Thinkshop program and an AI committee which assesses all ideas on their feasibility and their safety, many of which come from first line nurses. All ideas go through an in -depth examination process to ensure that any implementation meets the standards of the health system and is obviously implemented with the comments of a diversified group of stakeholders. In addition, Bradshaw, a member of the committee and former candidate for potential project ideas, said that the committee assesses each submission to determine whether the use of AI is appropriate, transparent, precise, reliable, safe and fair. Thanks to coordination with legal teams, compliance and information security, the Committee is also able to ensure that patients’ privacy is protected in the use of AI.
Ellen Pollack, MSN, RN-BC, Director of Information at the UCLA Health Sciences, said that “we will never implement AI technology involving care of patients without nurses.”
Another example of how managers and nurses lead AI innovation is the “Casteal Care” project of UCSF Health. A pilot program currently in discovery, the project examines how an improvement activated by the voice could deposit information at the appropriate place in the DSE. If he meets health standards, nurses would also direct his implementation and measure his success.
Look forward to
The nurses who have shared their thoughts have all agreed that AI is currently opening opportunities to the profession and will continue to do so in the future.
Burke estimates that “in five to seven years, nurses will not remember life without AI as part of their daily workflows. Something as simple as having this intelligence at hand to help them write messages and notes can increase the time they can spend with patients. ”
Bradshaw agrees. “It is wild how much a simple machine that helps remind you of what we know is a clinical standard in clinical decision -making helps you correct all of these things.” Nurses continue to play a central role in decision -making processes concerning AI in health care.
Bradshaw concludes: “The nurses write the new history of health care.”