From MD to Dr. AI:
A HCP's Learning Journey

Over the last 50 years, it has been like a cycle: with each new decade, new technologies would disrupt markets and reshape almost every industry. If the ’90s were the decade of cell phones and personal computers, the 2000s were about bringing the internet into daily life, and the 2010s were all about smartphones, especially mobile apps. Similarly, we are now in the decade of artificial intelligence (AI) and the Internet of Things (IoT). After the arrival of generative AI, we are seeing the same loop repeat: industries pivoting. The healthcare industry is no different in this wave of AI transformation.

Healthcare professionals (HCPs) are adopting AI fast in their everyday practices. AI is certainly offering them a powerful new toolkit to add to their arsenal. But HCPs are also wary of the changes they need to adapt to on this transformative journey. Here, we’ll explore this journey of HCPs, answering questions like how artificial intelligence will affect healthcare, why it is important, and what they should know to integrate AI into their practices.

Key Takeaways

• AI has the potential to completely transform healthcare for the better.
• Ethical AI use simply means guaranteeing trust, safety, and fairness.
• Investors are finding new opportunities in AI-driven healthcare tools.
• Continuous learning and ongoing education are a must for HCPs to make the most of AI.

1. How Will Artificial Intelligence Affect Healthcare?

AI is likely to reduce healthcare job opportunities, but this will happen gradually, not overnight. As AI takes the automation of routine office work to the next level, many of the currently people-intensive administrative roles will be substituted. On the flip side, AI could save approximately $200-360 billion annually for providers, with 35% in administrative savings ⁽¹⁾.

At present, AI does not have that level of intelligence that it could replace real clinicians. It still has a long road ahead of itself. Clinical care involves many subtle aspects that AI is unable to mimic. For example, on a given day, only a human physician can physically verify whether a patient looks more confused than usual. That said, AI will probably complement clinicians rather than substitute them ⁽²⁾,⁽³⁾.

AI also has the potential to make monitoring and diagnosis of patients less expensive. Hospital stays often incur a heavy financial toll on patients, particularly due to the need for continuous monitoring. AI could reduce those hefty hospital bills by making remote patient monitoring easier. It can also allow less expensive clinicians to perform procedures traditionally done by specialists, as seen in anesthesia ⁽³⁾.

2. Why is Artificial Intelligence Important in Healthcare?

The use of AI enables big data analytics in healthcare. AI has the power to process and analyze large amounts of complex health data. What might have taken days or weeks for statisticians can be completed by AI in seconds to several hours ⁽³⁾.

AI is especially helpful in uncovering hidden trends and patterns in data. AI-powered diagnostic tools can detect patterns in medical imaging that even highly trained radiologists might overlook, enabling earlier detection and intervention. A study published in Nature Medicine suggested that AI’s potential in diagnostic imaging could improve early detection, particularly in complex cases ⁽⁴⁾.

AI’s predictive models, too, play a critical role by analyzing patient histories to predict health risks and disease progression. This type of artificial intelligence for healthcare allows HCPs to act proactively, improving patient care outcomes and reinforcing AI’s importance in modern healthcare ⁽⁵⁾.

Artificial Intelligence: Healthcare Applications

The scope of AI in healthcare is broad. It covers several key areas beyond diagnostic imaging and administrative tasks. By analyzing genetic and patient-specific data, AI can quickly suggest tailored treatment plans based on each patient’s unique needs. Pharmacovigilance AI solutions help detect adverse drug reactions and identify potential safety concerns.

Recently, AI-enabled wearable cameras have shown potential in reducing medication errors. Moreover, AI reduces the time and cost involved in drug discovery and development by suggesting candidate drug molecules ⁽²⁾,⁽³⁾,⁽⁴⁾,⁽⁵⁾,⁽⁶⁾.

Opportunities in Artificial Intelligence: Healthcare Stocks

We are likely to witness robust growth in AI-driven healthcare tools and systems. Estimates suggest that the AI market for healthcare will be worth $150 billion by 2029 ⁽⁷⁾. So, now is the time to invest in quality AI healthcare stocks. For example, despite negative returns in 2023, Medtronic’s low forward P/E of 14.5 and a dividend yield of 3.11% make its stock attractively valued for investors ⁽⁸⁾.

3. Artificial Intelligence: Healthcare Ethics

AI algorithms are more likely to generate biased responses if the models are not trained on diverse datasets. We also need to consider the likelihood of humans making poor or biased decisions. Hence, ensuring data diversity alone is not enough to guarantee fair and unbiased AI output. AI models should also be trained to exceed human capabilities, not just replicate them ⁽³⁾.

4. Step into the Future of Healthcare with IT Medical’s AI Solutions

Discover the future of healthcare with IT Medical. As AI continues to transform diagnostics, treatment, and patient care, staying informed and equipped is essential. IT Medical provides innovative AI-powered solutions that help professionals navigate and leverage AI’s full potential for better patient outcomes.

Explore how our healthcare solutions can support ethical AI integration, enhance administrative efficiency, and bring personalized care to the forefront. We’re here to guide you in adopting AI ethically and effectively.

Ready to take the next step in healthcare innovation? Connect with IT Medical today and see our artificial intelligence healthcare examples.

References

1. Sahni, N., Stein, G., Zemmel, R., & Cutler, D. M. (2023). The potential impact of artificial intelligence on healthcare spending (No. w30857). Cambridge, MA, USA:: National Bureau of Economic Research.

2. Mello, M. M., & Guha, N. (2023, May). ChatGPT and physicians’ malpractice risk. JAMA Health Forum (Vol. 4, No. 5, pp. e231938-e231938). American Medical Association.

3. Cutler, D. M. (2023, July). What artificial intelligence means for health care. In JAMA Health Forum (Vol. 4, No. 7, pp. e232652-e232652). American Medical Association.

4. Yang, Y., Zhang, H., Gichoya, J. W., Katabi, D., & Ghassemi, M. (2024). The limits of fair medical imaging AI in real-world generalization. Nature Medicine, 1-11.

5. Khalifa, M., & Albadawy, M. (2024). Artificial Intelligence for Clinical Prediction: Exploring Key Domains and Essential Functions. Computer Methods and Programs in Biomedicine Update, 100148.

6. Chan, J., Nsumba, S., Wortsman, M., Dave, A., Schmidt, L., Gollakota, S., & Michaelsen, K. (2024). Detecting clinical medication errors with AI enabled wearable cameras. npj Digital Medicine, 7(1), 287.

7. MarketsandMarkets. (2024, March 19). Artificial intelligence in healthcare market by offering, technology, application, end user & region – Global forecast to 2029.

8. Stock Analysis. (2024). Medtronic plc (MDT) dividend history, dates & yield. Stock Analysis.