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AI is now one of the biggest disruptors in healthcare as it works its way into all corners of the industry.
Many nurses have ethical concerns about generative AI, along with worries about job displacement and the potential loss of human touch and connection with patients. For CNOs and other nurse leaders, implementation is another big concern.
It's critical that CNOs incorporate AI into workflows in a way that will help nurses and patients, and not become a hinderance. According to Robbie Freeman, vice president of digital experience and the chief nursing informatics officer at Mount Sinai Health System, nurses need to have a seat at the table during decision making to make implementation go smoothly.
"One of the things that I think will be important as we start to see AI make its way into patient care is that our care team members, our nurses, have a seat at the table," Freeman said, "and that their voice is included in how we design these AI products, understand how they work, and then implement and ensure that it's a seamless experience."
At Mount Sinai, Freeman said they take a co-design approach to decision-making surrounding AI products, meaning that everyone sits down together at the table, including data scientists, engineers, and frontline team members, to design the best product that will work for everyone.
"Some of our best ideas come from our frontline team and our nurses," Freeman said. "Anyone in our organization can submit a request for an AI concept or idea, and we have many examples where the frontline team has sent us an idea, we would scope it out together, and where it makes sense, we would partner, develop, and bring it to life."
The goal is to help reduce the burden of documentation and improve the ability to keep patients safe while delivering high quality care, Freeman explained.
"I think when done in the right way, we can do a lot," Freeman said, "but we want to make sure that the key is having the nursing voice at the table along the way."
"It was inspired by the five rights for medications," Freeman said, "so we took that, and we wanted to look at it through the lens of AI."
Freeman said the authors came up with five things that are important to consider while implementing AI. Leaders should first identify the right objective, meaning the problem they want to solve with AI.
"[Make] sure that [it's] really clear why you're using the tool and the problem that you're solving," Freeman said.
Second, CNOs need to consider the right approach, while making sure that the AI will be integrated into the workflow and that the approach makes sense. Third, CNOs must have the right competency on the team that will be using the AI, and make sure that the team members understand the "why."
"We don't want to just blindly follow the output of an AI model," Freeman said, "because we really look at this as an augmented intelligence tool and it's not going to ever replace our clinical decision-making."
Fourth, the right data is critical. CNOs need to understand how the data is sourced and interpreted by asking questions about how the AI was trained. Fifth, any implemented AI tool must have the proper safeguards.
"We [need to] make sure that we've tested it prospectively, we understand how it works, we've checked for bias, and that we've ensured that those steps were taken before it gets used for clinical care," Freeman said.
For nurse leaders
The goal of this framework is to empower nurse leaders with a set of high-level questions to ask before they implement an AI product, according to Freeman.
"If this was written for an audience of data science experts, we may get into some more technical discussions on hyperparameter tuning, or the way things are working under the hood," Freeman said, "but we tried to keep it at the business leader [and] clinical leader perspective to make sure we're at least addressing those big boulders."
However, health systems still should utilize those teams to work on the details, Freeman recommended.
"[As organizations] think about their AI governance structure, they need to have teams that can do that deeper dive into the very technical evaluations around the model," Freeman said, "like performance and how you're going to measure that over time, and watch for performance drift, and other considerations."
"This was really through the lens of a nurse manager or nurse leader," Freeman said, "and it's not meant to replace organization-wide, overarching, robust governance processes that are also critical."
Taking action
To move forward with AI implementation, Freeman recommended that CNOs ask about AI governance and make sure that nurses have a voice at that table. Nurse leaders should have a voice in any tools that are used at the point of care by the frontline nursing team.
"I think the CNO plays a really important role there advocating for the nursing team, advocating for the safe and ethical use from the patient perspective as a patient advocate, and ensuring that they have a voice within the governance process," Freeman said. "I think that organizations who do that well are going to be really well positioned to realize a lot of value from their use of AI."
CNIOs can also be a great partner for CNOs, Freeman explained, since they can help with communication between the technology teams and the clinical teams.
"I would encourage our CNOS and chief nurse executives to lean on their CNIOs and their nursing informatics team members who can play a really important role here," Freeman said.
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The use of telemedicine following the COVID-19 pandemic kick started the virtual nursing movement. And while some systems are just getting started, many have been utilizing virtual nursing for years and continue to expand.
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Nurse leaders should follow these steps to determine what staffing model works best for both patients and nurses, says this CNO.
When implementing new staffing models, there are several factors to consider. CNOs must prioritize what works best for patients while also meeting the needs of their nurses.
According to Vicky Tilton, vice president of patient care services and chief nursing officer at Valley Children's Healthcare, there are four steps that CNOs should take to determine what staffing model works best for their health system.
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Nurse leaders must determine what staffing model works best for both patients and nurses, says this CNO.
The nursing shortage continues to be one of the biggest concerns for CNOs across the country, and many are brainstorming creative staffing models to recruit and retain more nurses.
When implementing new staffing models, there are several factors to consider. CNOs must prioritize what works best for patients while also meeting the needs of their nurses.
According to Vicky Tilton, vice president of patient care services and chief nursing officer at Valley Children's Healthcare, there are several innovative staffing models that CNOs could implement at their health systems.
Innovative staffing models
Staffing models have recently been expanding to include more specialized roles and nurses of different designations, Tilton explained. Leveraging advanced practice nurses can help enhance care delivery while filling gaps in the workforce.
"Contingency labor and role specialization to ensure operational efficiency and adaptability in meeting patient care demands are being leveraged as well," Tilton said.
There are four examples of new staffing models that Tilton emphasized, the first being team-based care, which promotes collaboration between nurses, nurse practitioners, physicians, physician assistants, pharmacists, social workers, and other healthcare professionals. This model empowers nurses to be more autonomous, Tilton explained, and to participate in decision-making by contributing their expertise.
"Team-based care enhances coordination, communication, and efficiency in healthcare delivery," Tilton said, "leading to improved patient outcomes and satisfaction."
The second model is flexible staffing, which, can help health systems adapt to fluctuations in patient volume and acuity as well as staffing shortages, according to Tilton.
"These strategies may include the use of float pools, cross-training programs, per diem staffing, and contingency staff," Tilton said. "Implementation of innovative scheduling practices such as self-scheduling, shift bidding, and predictive analytics-based staffing algorithms are being considered to optimize staffing levels and match resources with patient needs."
Care continuity models are also necessary to promote patient safety, reduce medical errors, and enhance the patient experience, Tilton emphasized.
"Care continuity models aim to maintain consistent nurse-patient relationships across care transitions and settings," Tilton said. "These models may involve assigning care coordinators or a primary nurse to patients throughout their healthcare journey."
The last innovative staffing model is telehealth nursing. Virtual care has revolutionized nursing and other aspects of healthcare in general, by providing new opportunities for nurses to work remotely and flexibly, while still providing patients with quality care. According to Tilton, nurses in telehealth roles can provide direct patient care, health education, counseling, and support through virtual consultations, remote patient monitoring, and tele-triage.
"Telehealth nursing enables greater access to care, especially for underserved populations," Tilton said. "It improves care coordination and enhances patient convenience and satisfaction."
Choosing for patients
The second piece of the puzzle is choosing which staffing model works best for patients. According to Tilton, there are several factors regarding patient needs, nursing practice, organizational resources, and external details that CNOs must consider when making the right decision.
First, CNOs need to assess the demographics, acuity levels, and care needs of their patient population, Tilton recommended, while working with their teams to make sure their workforce is experienced and competent to address those needs.
"This assessment helps CNOs determine the appropriate nurse-to-patient ratios, skill mix, and expertise needed to deliver safe and effective care," Tilton said.
Next, CNOs must remain in compliance with regulatory requirements, accreditation standards, professional staffing, and patient care guidelines, according to Tilton.
"They need to stay informed about state regulations, nurse licensure laws, staffing ratios mandated by regulatory agencies," Tilton said, "and recommendations from professional organizations such as the American Nurses Association and the National Council of State Boards of Nursing."
Then, CNOs should assess their health system's financial resources, budget constraints, and reimbursement mechanisms to decide a staffing model's feasibility.
"Analyze staffing costs, productive metrics, revenue generation opportunities, and return on investment associated with each model," Tilton said.
Finally, Tilton recommended that CNOs engage with key stakeholders during the decision-making process, including the nursing staff, interdisciplinary team members, healthcare executives, patients, families, and community partners.
"Through soliciting feedback, gathering input, and fostering collaboration, [CNOs] can ensure buy-in and support for the chosen staffing model," Tilton said.
Throughout this entire process, communication is key. Tilton emphasized the need for CNOs to promote transparency, communication, and shared decision-making to make successful changes to the organization.
"By considering these factors holistically and collaboratively," Tilton said, "CNOs can determine the staffing model that best meets the needs of their patients, optimizes nursing practice, and supports organizational goals and priorities."