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NURSING SCIENCE
Cooperation Not Competition:
Why Nurse-Technology Partnerships Are Necessary for the Future of Patient Care

By Michelle C. Hehman, Ph.D., RN, NPD-BC

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We are at a critical inflection point for the profession of nursing. Future workforce projections indicate a worsening registered nurse (RN) staffing crisis as increasing demand for nursing services continues to outpace supply, creating an ever-widening labor gap (Vozzella & Hehman, 2023).
A strong correlation exists between nurse staffing, patient outcomes, and cost, with higher RN staffing levels associated with lower in-hospital mortality risk, fewer incidents of missed nursing care, and shorter lengths of stay (Brennan et al., 2013; Griffiths et al., 2018; ). Given the reality of a worsening RN shortage and the demonstrated impact of nurse staffing and workload on patient safety, hospital systems are searching for innovative technologies that can act as nurse extenders to maintain the quality of care. Here at Houston Methodist, the expansion of digital technologies like telenursing and remote virtual monitoring services into the inpatient environment allowed us to reimagine traditional models of nursing care during and after the COVID-19 pandemic (Hehman et al., 2023).

Continued advancements in artificial intelligence (AI) and robotics capabilities hold additional potential for the future of nursing work. Healthcare systems around the world have begun to integrate these technologies into existing workflows, using service robots to perform a range of tasks, like fetching and delivering supplies, lifting patients for transfers, monitoring vital signs, drawing blood, and inserting IVs (Kyrarini et al., 2021). Future patient care will include helper robots with embodied AI systems designed to reduce nursing workload, increase efficiency, and improve patient safety. But are nurses ready to embrace these new technologies? And how can we ensure that integrating AI and robotic systems positively impacts the nursing work environment?
Nurses and technology have a long, complex, and sometimes contradictory history. While new discoveries and innovative devices have improved patient outcomes, increased practice standards, and added to our professional expertise, managing these technologies creates additional workloads for nurses tasked with troubleshooting any inefficiencies or finding workarounds for process gaps. Navigating the technology-heavy space of the inpatient environment also means that nurses spend a significant percentage of their time on non-clinical tasks and that the devices are becoming a physical barrier to nurse-patient interaction.
Naturally, many nurses express skepticism about the possibility of integrating even more complex technology systems like robotic nursing assistants into their workspace, and some worry that advanced AI and robotic technology will compete for nursing jobs or replace nurses altogether (von Gerich et al., 2022). While understandable, nurses' continued cynicism and distrust of these technologies will neither prevent their introduction to the healthcare environment nor guarantee that they are integrated in a way that maintains care quality, safety, and efficiency. Many thought leaders assume robots will be integrated into nursing practice in some capacity in the next five to 10 years, so nurses must be involved in every stage.
The time has come for nurses to shift their perspective from one of competition to one of cooperation. Cultivating partnerships with multidisciplinary experts in AI, robotics, and other digital technologies will allow nurses to participate in the early development phases of new healthcare applications. Centering the experience of nurse clinicians in the planning process will help ensure intelligent design and reduce the need for aftermarket workarounds. And finally, participating in nurse-led research studies about the impact of robots in healthcare will identify potential barriers to successful implementation and determine whether the new technology reduces nurse workload burden.
References:
  1. Vozzella, G. M., & Hehman, M. C. (2023). Cardiovascular Nursing Workforce Challenges: Transforming the Model of Care for the Future. Methodist DeBakey cardiovascular journal, 19(2), 90–99. https://doi.org/10.14797/mdcvj.1188
  2. Brennan, C. W., Daly, B. J., & Jones, K. R. (2013). State of the science: the relationship between nurse staffing and patient outcomes. Western journal of nursing research, 35(6), 760–794. https://doi.org/10.1177/0193945913476577
  3. Griffiths, P., Recio-Saucedo, A., Dall'Ora, C., Briggs, J., Maruotti, A., Meredith, P., Smith, G. B., Ball, J., & Missed Care Study Group (2018). The association between nurse staffing and omissions in nursing care: A systematic review. Journal of advanced nursing, 74(7), 1474–1487. https://doi.org/10.1111/jan.13564
  4. Hehman, M.C., Fontenot, N.M., Drake, G.K., & Musgrove, R.S. (2023). Leveraging digital technology in nursing. Health Emergency and Disaster Nursing, 10(1), 41-45. https://doi.org/10.24298/hedn.2022-0014
  5. Kyrarini, M., Lygerakis, F., Rajavenkatanarayanan, A., Sevastopoulos, C., Nambiappan, H. R., Chaitanya, K. K., Babu, A. R., et al. (2021). A survey of robots in healthcare. Technologies, 9(1), 8. http://dx.doi.org/10.3390/technologies9010008
  6. von Gerich, H., Moen, H., Block, L.J., Chu, C.H., DeForest, H., Hobensack, M., Michalowski, M., Mitchell, J., Nibber, R., Olalia, M.A., Pruinelli, L., Ronquillo, C.E., Topaz, M., Peltonen, L.M. (2022). Artificial intelligence-based technologies in nursing: A scoping literature review of the evidence. International Journal of Nursing Studies, 127: 104153. https://doi.org/10.1016/j.ijnurstu.2021.104153.