Issue link: https://nnumagazine.uberflip.com/i/1521950
shift. Sometimes they are emergency admissions from outside hospi- tals or even a code stroke that happens in house." But since her hospital transitioned to Clairvia about six months ago, the nurses noticed that resource nurse hours are being whittled away because the system is saying the nursing demand hours don't justify the staff. When they argued with the hospital, management said, "No, we are only going to staff for what we have at the moment in real time." Lastly, and arguably most importantly, nurses say that these EHR systems do not account for the time it takes nurses to provide the educa- tion and compassionate, psychosocial care to patients and their families that is absolutely critical to their well-being and successful healing. "It's about you putting your hands on a patient and just loving them and showing how much you care, how much you value them," said Aretha Morgan, an emergency pediatric RN at NewYork-Presbyterian hospital in Manhattan and a New York State Nurses Association board member. "You cry when they're sad. You're happy when they're getting healed. You're the one that when they're about to fall, you're catching them. We should not ever ascribe to any type of artificial intelligence that moves us away from taking care of our patients. Our patients are number one." As Deb Quinto Capistrano, a Kaiser Permanente San Francisco RN who works in a medical-surgical-telemetry-stroke unit, notes, she is con- tinually providing patient education during the patient's stay, but the Epic acuity system gives her no credit for this work that should translate into more time and better staffing. "We do patient education from the start of admission through their time in the hospital, but we only get education points when they have an active discharge," said Capistrano. Conversely, aspects of the EHR systems that are supposed to proac- tively help nurses often do the opposite: make nurses spend valuable time responding to false "advanced alert monitoring" or "early warning system" alarms for conditions such as sepsis. For Melissa Beebe, an oncology RN at UC Davis Medical Center in Sacramento, Calif. and a member of CNA/NNOC's joint nursing practice commission, the sep- sis alerts generated by their Epic EHR are often incorrect. The system will flag patients as likely sepsis cases when Beebe knows in her profes- sional judgment that this is extremely unlikely, and miss the ones whom she knows truly are in danger and she is already acting upon. "Everybody on my unit knows the sepsis warning system is not help- ful," said Beebe. "I've sent people to ICU and that thing never went off." Beebe's experience matches the published research: One A.I. Early Warning System (EWS) analyzed patient data with the goal of identifying patients with a substantial risk of developing sepsis. The EWS was widely implemented at hundreds of hospitals throughout the country. However, when this sepsis EWS underwent external validation, researchers found that the program missed over 67 per- cent of sepsis cases. The authors of this study, published in August 2023 of JAMA Network Open, concluded of the EWS that "it appears to predict sepsis long after the clinician has recognized pos- sible sepsis and acted on that suspicion." These faulty alerts are not just merely an annoyance, though. They take real time away from needed patient care. E.C. Mitchell, an ICU nurse at Kaiser Permanente in Modesto, Calif. who also serves on his hospital's rapid response team, noted that he could spend close to an hour following up on false alerts. "This is a waste of time when I could be checking in on the really sick patients, or doing actual procedures," said Mitchell. "I have to call the attending physician to respond to it, and then we both write a report on it. All these things are taking up time. The bigger deal is that it doesn't really catch the problem patients, so it is a false sense of security. I find the really sick ones by checking in on the nurses, by asking them, 'Any concerns about your patients?'" Nurses and Patients' Bill of Rights: Guiding Principles for A.I. Justice in Nursing and Health Care The right to high-quality person-to-person care. Patients have the right to in-person health care based on their needs and wishes provided by skilled and licensed health care professionals, in the appropriate set- tings. The right to health care in-person by a licensed health care professional underlies all other medical care and should not be compro- mised by uses of A.I. or other technologies that contribute to worker displacement or deskilling. The right to safety. Patients and workers have a right to safety at work or while receiving care. This includes mandatory, pre-market testing and approval of any new technology and ongoing monitoring by a regu- latory agency to ensure that it is safe, effective, therapeutic, and equitable—the precautionary principle in action. The burden of demon- strating safety should rest with developers and deployers, not patients and their caregivers. Technology is no substitute for appropriate staffing levels for all health care workers that are necessary to ensure the highest standards of safety and care for both workers and patients. The right to privacy. Patients and workers have the right to privacy about their health care and the right to private and secure data. Collect- ing information on nurses and patients should require informed consent and an opt-in process. Health care employers should be limited in the data they collect on workers and patients and should not be allowed to profit from that data. The right to transparency. Workers and patients have the right to know what information is being collected about them, what purpose it serves, where it is stored, and whether it is being sold or shared. Patients, patient advocates, and health care professionals have the right to see the data and clinical research that underlies A.I.-based recommendations, and in the case of large language models and other generative A.I. systems, clinicians and patients should have access to the rationale behind artificial intelligence that should be explainable and interpretable by clinicians and patients. Patients and health care providers have the right to clearly understand the information about their care that is presented to them. The right to exercise professional judgment. Nurses and other clinicians have the right to exercise their professional judgment, within their scope of practice, and to override decisions made by A.I., automated worker surveillance and management (AWSM), and other health informa- tion technologies when doing so is clinically appropriate, without the threat of discipline or discharge. Patients have the right to a second opinion The right to autonomy. Workers and patients have the right to refuse to participate in data collection and worker surveillance. Patients deserve the right for their health care information to be technology neu- tral. Using A.I. to diagnose and treat patients should require informed consent and an opt-in process. The right to collective advocacy for workers and their patients. Health care workers have the right to be consulted and engaged on all policies, procedures, and best practices surrounding the implemen- tation of A.I. Union workers must have the opportunity to bargain over whether and how technology should be implemented in the workplace before it is selected or deployed in a health care setting, and all workers have the right to workplace democracy. Workers have the right to under- stand how the decisions governing their working lives are made—including hiring—and patients have the right to understand how the decisions con- cerning their care are made, including insurance coverage determinations. 22 N A T I O N A L N U R S E W W W . N A T I O N A L N U R S E S U N I T E D . O R G A P R I L | M AY | J U N E 2 0 2 4