Unit II Overview Research Memo-Implementation of Artificial Intelligence in Healthcare Delivery-Nursing Paper Examples

Memorandum (Artificial Intelligence-Nursing Paper Examples)

To: The policymakers (Quality and compliance department of the hospital) (Implementation of Artificial Intelligence)

From:

Date:

Subject: Implementation of Artificial Intelligence in Healthcare Delivery

Purpose

I am writing this memo to highlight the need to implement artificial intelligence (AI) in healthcare delivery across hospitals. AI is a rapidly evolving concept associated with promising benefits in healthcare delivery (Reddy et al., 2019). For instance, it is an integral component of modern healthcare since it has significantly revolutionized patient diagnosis. In addition, treatment, and monitoring procedures, resulting in improved patient outcomes (Artificial Intelligence-Nursing Paper Examples).

It facilitates precision and accuracy in healthcare research and administration, enabling nurses to offer patient-centered care. It also reduces the operating costs of hospitals since most activities in the nursing workflow are automated. Hence, resulting in an overall reduction in the cost of care (Chew & Achananuparp, 2022) (Artificial Intelligence-Nursing Paper Examples).

Additionally, Panesar (2021) illustrates that machine learning algorithms have significantly enhanced the accessibility and processing of large volumes of patient’s clinical information. Hence, making it easy to make accurate and precise diagnoses quickly. For example, medical imaging has improved the quality of treatment, such as enhancing visualization during surgery. In this case, surgical imaging technology provides vital information to surgeons, reducing surgery-related complications (Artificial Intelligence-Nursing Paper Examples).

Furthermore, the machine learning and concept-based information retrieval system will significantly improve patient data search accuracy and retrieval speed. AI can help establish a collaborative and effective healthcare environment that improves decision-making and the provision of primary care (Chatterjee et al., 2021). Also, AI can streamline healthcare delivery systems activities. More so, through accurate and swift identification and resolution of problems within the system (Panesar, 2021). Therefore, Implementing AI into healthcare delivery would improve patient treatment outcomes and reduce hospital readmissions (Artificial Intelligence-Nursing Paper Examples).

Background

Healthcare organizations are increasingly adopting AI to enhance improved patient care delivery. The technology will transform organizations by replacing human activities with machine-based models of care (Panesar, 2021). The demand for AI has increased exponentially over the decades. More so, due to the increased susceptibility of individuals to disease and increased resistance of diseases to available medications.

Furthermore, the expanding need for healthcare resources across hospitals (Rangareddy & Nagaraj, 2022). Besides, healthcare worker shortages are also increasing consistently with the increase in population. Hence, the need to implement precise and accurate treatment interventions to bridge the gaps. Automating healthcare activities through AI is necessary for addressing emerging challenges (Artificial Intelligence-Nursing Paper Examples).

Findings

Researchers have extensively examined, analyzed, and tested the effectiveness of AI in healthcare delivery. For instance, Chew and Achananuparp (2022) reviewed 26 previous studies on AI in healthcare published before 2021 based on the 5-stage framework by Arksey and O’Malley. The study explored AI perceptions and their necessity in improving healthcare delivery (Artificial Intelligence-Nursing Paper Examples).

The study results indicate that AI was positively viewed as the solution to efficient healthcare delivery. Moreover, it is readily available, easy to use, and can significantly reduce the cost of healthcare. However, the studies indicated data privacy concerns, patient safety, technology maturity, and whether it can be fully automated across hospital operations (Artificial Intelligence-Nursing Paper Examples).

Besides, Yoo et al. (2023) also explored the role of AI in improved healthcare delivery through semi-structured interviews among 15 nurses and physicians practicing at the emergency and intensive care units of a hospital in Seoul. The qualitative study focused on understanding physicians’ and nurses’ needs and concerns about using AI in healthcare delivery. It also aimed to determine recommendations and measures that should be considered in implementing AI into healthcare (Artificial Intelligence-Nursing Paper Examples).

The participant responses showed positive expectations of the role of AI in increasing work efficiency, reducing patient care costs, and improving patient outcomes. They were also concerned about workflow disruption, lack of adequate skills to operate the technology, and alert fatigue. (Yoo et al., 2023) Their recommendations emphasize the importance of integrating alert fatigue management into the hospital system, indicating their willingness to utilize the technology in their practice settings (Artificial Intelligence-Nursing Paper Examples).

Moreover, Istasy et al. (2022) also examined the effectiveness of AI in promoting equitable oncological care. The researchers conducted a scoping review of 133 articles published between 2000-2021 on the Application of AI in oncology across the MEDLINE and Embase electronic databases. Three themes were evident from the review; the application of AI in reducing health disparities, AI technology and bias concerns, application of AI in examining the biological and social health determinants. The identified themes confirm the increased need for AI for equitable healthcare delivery and its associated concerns.

Rangareddy and Nagaraj (2022) also confirm the above findings through their analysis of the AI application in healthcare delivery in India. The authors observe that AI has revolutionized healthcare by enhancing precision screening, diagnosis, and provision of patient-centered care. They believe that continued adoption of AI across healthcare organizations will reduce mortality rates and hospital readmissions due to improved patient outcomes. Based on the identified benefits of AI in healthcare delivery, the policymakers at the hospital should draw strategies and guidelines to guide its implementation (Artificial Intelligence-Nursing Paper Examples). 

Conclusion

The research results indicate significant benefits of implementing AI in healthcare delivery. For instance, the researchers found that AI improves efficiency in the delivery of healthcare, reduces healthcare costs, is a readily available system, and improves patient outcomes. They also found that AI reduces disparities in healthcare provision, can predict biological and social health determinants, enhance precision in disease screening and diagnosis, and facilitate patient-centered care.

However, the findings also highlight concerns associated with the technology, such as data privacy issues, inadequate skills for operating it, workflow disruption, increased bias, and the potential of automating the technology across hospital operations. Henceforth, AI implementation in healthcare delivery is still in its infancy with uncertain long-term consequences; hence, it should be implemented cautiously to reduce its potential negative impacts (Artificial Intelligence-Nursing Paper Examples).

Recommendations

The algorithms and datasets for AI implementation should be easily auditable and supported by valid and evidence-based practice to enhance the assessment of its efficacy in screening, diagnosis, and treatment processes (Connected Health, 2019) (Artificial Intelligence-Nursing Paper Examples).

The AI framework should consist of easy-to-understand representations to enhance their effective use (Yoo et al., 2023). The representations should accurately define the AI system’s intended use and potential risks to enable health professionals to uphold ethical practices.

The hospital’s policy developers should ensure that the implemented AI system is easily accessible and affordable to satisfy its necessity in reducing the cost of healthcare (Artificial Intelligence-Nursing Paper Examples).

The policy frameworks for AI implementation should promote ethical applications of the technology to ensure that it satisfies its intended goal of facilitating safe, efficient, and equitable patient care (Connected Health, 2019). It should be consistent with international and align with the ethical obligations of healthcare professionals in ensuring quality and improved patient care (Artificial Intelligence-Nursing Paper Examples).

Policymakers should also develop frameworks for balancing the increased needs of patient care, informed decision-making, and the augmented capabilities of the AI system to promote patient safety and efficient care.

Healthcare practitioners, patients, and other stakeholders should be educated on the application of AI to enhance its integration into the organization’s workflow systems. Ongoing education will promote a critical understanding of the context of AI, resulting in its safe and effective use in patient care (Connected Health, 2019) (Artificial Intelligence-Nursing Paper Examples).

References

Chew, S. H. J., & Achananuparp, P. (2022). Perceptions and needs of artificial intelligence in health care to increase adoption: A scoping review. Journal of Medical Internet Research, 24(1), e32939–e32939. https://doi.org/10.2196/32939

Connected Health. (2019). Policy principles for artificial intelligence in health. https://actonline.org/wp-content/uploads/Policy-Principles-for-AI.pdf

Istasy, P., Lee, W. S., Iansavichene, A., Upshur, R., Gyawali, B., Burkell, J., Sadikovic, B., Lazo-Langner, A., & Chin-Yee, B. (2022). The Impact of Artificial Intelligence on Health Equity in Oncology: Scoping Review. Journal of Medical Internet Research, 24(11), e39748–e39748. https://doi.org/10.2196/39748

 Panesar, A. (2021). Machine learning and AI for healthcare: Big data for improved health outcomes (2nd ed.). APress. https://doi.org/10.1007/978-1-4842-6537-6

Rangareddy, H., & Nagaraj, S. K. (2022). Artificial intelligence and healthcare. Journal of Clinical and Diagnostic Research, 16(11), YI01–YI03. https://doi.org/10.7860/JCDR/2022/56148.17020

Reddy, S., Fox, J., & Purohit, M. P. (2019). Artificial intelligence-enabled healthcare delivery. Journal of the Royal Society of Medicine, 112(1), 22-28. https://doi.org/10.1177/0141076818815510

Yoo, J., Hur, S., Hwang, W., & Cha, W. C. (2023). Healthcare professionals’ expectations of medical artificial intelligence and strategies for its clinical implementation: A Qualitative study. Healthcare Informatics Research, 29(1), 64–74. https://doi.org/10.4258/hir.2023.29.1.64