The Benefits and Risks of Predictive AI in Clinical Care
Artificial intelligence (AI) is increasingly transforming healthcare, particularly through predictive applications in clinical settings. AI-based technologies make it possible to predict patients’ health conditions from a big dataset to diagnose diseases and optimize individual and public healthcare costs and resources (Alowais et al., 2023). Real-time analytical capability implies that an immense volume of patient data is processed by AI, which in turn possibly improves clinical decision-making, decreases mistakes, and enhances safety. The use of AI technology also has many advantages, but introducing AI in clinical practice has several ethical and practical implications: The Benefits and Risks of Predictive AI in Clinical Care.
Potential Benefits and Risks
Predictive AI in healthcare offers significant advantages. It improves diagnostic imaging, aids in early diagnosis, and increases the implementation of personalized medicine through the development of disease treatment plans in relation to the profile of the patient (Ueda et al., 2023). AI can also disseminate clinician burdens and explicate administrative tasks.
In the same way, AI, through the use of powerful tools, can assist population care by analyzing patterns and eventual outbreaks of diseases. However, some of the risks include problems in developing algorithms, personal data protection, and a shift from using professional judgment on the part of doctors (Ueda et al., 2023).
Considerations for Healthcare Systems
Before adopting AI, healthcare systems must evaluate several key factors. First, they have to guarantee that machine learning algorithms are trained to reduce the risk of bias and increase effectiveness for different patients. Second, patient data should be protected from access by unauthorized personnel by observing HIPAA rules and using other forms of protection (Dixon et al., 2024). Third, AI must remain a supportive tool for clinical assessment and not a complete replacement for professional human experience, so the provider must continue their training to apply AI successfully when providing care.
Further, there can be guidelines designed for clients themselves, enabling them to decide whether to allow AI to perform certain functions or not, and there should be an explanation of how the decision-making process with the use of artificial intelligence is administered. Finally, there is a need for codes of conduct in the use of AI to regulate and ensure there are checks and balances in the development of AI systems (Dixon et al., 2024).
In summary, predictive AI has become a powerful tool that can improve the effectiveness of precision medicine as well as logistic processes in healthcare. Still, its application must be handled with caution in order to avoid adverse consequences on healthcare delivery and be fair, moral, and efficient. It is, therefore, possible for AI to enhance clinical knowledge and positively impact the health outcomes of patients as well as the efficiency of health systems.
References
Alowais, S. A., Alghamdi, S. S., Alsuhebany, N., Alqahtani, T., Alshaya, A., Almohareb, S. N., Aldairem, A., Alrashed, M., Saleh, K. B., Badreldin, H. A., Yami, A., Harbi, S. A., & Albekairy, A. M. (2023). Revolutionizing healthcare: The role of artificial intelligence in clinical practice. BMC Medical Education, 23(1). https://doi.org/10.1186/s12909-023-04698-z
Dixon, D., Sattar, H., Moros, N., Kesireddy, S. R., Ahsan, H., Lakkimsetti, M., Fatima, M., Doshi, D., Sadhu, K., & Hassan, M. J. (2024). Unveiling the influence of AI predictive analytics on patient outcomes: A comprehensive narrative review. Cureus, 16(5). https://doi.org/10.7759/cureus.59954
Ueda, D., Kakinuma, T., Fujita, S., Kamagata, K., Fushimi, Y., Ito, R., Matsui, Y., Nozaki, T., Nakaura, T., Fujima, N., Tatsugami, F., Yanagawa, M., Hirata, K., Yamada, A., Tsuboyama, T., Kawamura, M., Fujioka, T., & Naganawa, S. (2023). Fairness of artificial intelligence in healthcare: Review and recommendations. Japanese Journal of Radiology, 42(1). https://doi.org/10.1007/s11604-023-01474-3
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Review Chapters 13 and 14 in Knickman and Elbel (13th edition)
Some advancements happen in response to an event; for example, the COVID-19 pandemic resulted in several improvements to vaccine development, telehealth opportunities, and other digital and medical technologies. The COVID-19 pandemic also made it clear that it is important to plan for the future. Scientists could create vaccines relatively quickly because of previous knowledge gained through research on coronavirus vaccines.
The Benefits and Risks of Predictive AI in Clinical Care
While we can’t predict the next pandemic, it is important to use the current modeling tools and technology to quickly respond to health emergencies. For individuals interested in the health profession, looking into future predictions and healthcare trends could provide insights into what careers to pursue and what health issues may arise.
Artificial Intelligence
- Artificial intelligence (AI) applications for precision medicine are entering the healthcare system. These applications are often used to predict health outcomes based on the specific profiles of patients.
Questions to Address:
- What are the potential benefits and risks to individual and societal well-being of deploying predictive AI applications in clinical care?
- Which factors would a healthcare system need to consider before adopting AI?
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