As technology develops, medical professionals gain more ways of practicing their profession. From simple diagnoses to complicated treatments, AI has improved the healthcare industry. But this is not without any disadvantages.

In this article, we aim to identify specific ways technology can be utilized to improve the quality of healthcare facilities.

Revolutionizing Healthcare Through Artificial Intelligence

Like other industries, the healthcare sector has benefitted from cutting-edge technologies in recent years, with AI being one of the biggest game-changers. As we learn to integrate and implement AI, its medical applications also rapidly expand.

According to Statista, the value of AI in the healthcare market is projected to reach $188 billion by 2030, with an increase in compound annual growth rate of 37 percent since 2022.¹ This growth reflects the increasing reliance on AI’s potential to revolutionize healthcare delivery and improve patient care. With AI technologies becoming more sophisticated and accessible, healthcare organizations can leverage them to address emerging challenges and capitalize on opportunities across the industry.

AI Improving Medical Decisions and Diagnosis

The application of AI in healthcare significantly enhances medical decisions and diagnostic processes. AI algorithms have demonstrated remarkable capabilities in aiding healthcare professionals in making data-driven choices that lead to positive patient experiences.

The following are specific ways companies and organizations utilize AI for medical decision-making:

1. Aiding clinical decisions.

AI can aid in clinical decisions by providing valuable insights and recommendations. With machine learning, AI helps professionals identify potential risks and provide action plans based on vast amounts of patient data, such as:

• Patient medical records
• Lab results
• Medical imaging

By leveraging predictive analytics, AI can assist healthcare professionals in making more informed and data-driven decisions, creating accurate diagnoses, and tailoring treatment strategies for each patient.

2. Supporting human judgement.

A survey by Health Management Academy reveals that many C-suite executives are choosing to invest in AI to support their clinical and non-clinical staff.² While AI proved its worth in various medical applications, it’s important to recognize they’re designed to complement and support humans—not replace them.

Using natural language processing, AI can produce summarized information that can support medical experts. Its algorithms become incredibly useful in augmenting expert knowledge and decision-making capabilities.

It’s also valuable to note that AI doesn’t solely help make decisions. Automation can also finish repetitive tasks so clinicians can have more time and energy to focus on complex cognitive functions like interpreting medical scenarios and making important judgments in critical situations.

3. Diagnosing and treating illnesses.

One of the most significant impacts of AI in healthcare is diagnosing and treating illnesses with greater accuracy and efficiency. AI-powered diagnostic systems can precisely analyze medical images, such as:

• X-rays
• CT scans
• MRI scans

Moreover, AI can even outperform human capabilities in detecting and identifying abnormalities. Through machine learning and deep learning techniques, AI algorithms can detect subtle discrepancies and patterns that a human eye may overlook.

AI Enhancing Treatment and Patient Outcomes

According to the Pew Research Center, 38 percent of American respondents think AI will positively improve patient outcomes.³ Similarly, healthcare workers have echoed similar thoughts considering the rate of AI usage in the medical field.

Since we’ve established that AI integration can revolutionize medical diagnosis and decision-making, it’s also important to recognize its potential to enhance the treatment process and improve outcomes. Specifically, artificial intelligence can contribute to quality patient care through the following ways:

1. Personalized Treatment Plans

AI algorithms can analyze vast amounts of patient data to develop personalized treatments for everyone’s unique medical needs. Considering factors like disease severity, genes, and response to treatment, AI-driven systems have the potential to optimize treatment strategies that can maximize efficacy and minimize side effects.

2. Precision Medicine

AI technologies enable the identification of biomarkers and genetic signatures associated with specific diseases or treatment responses. This helps experts become more precise in approaching patient care and treatment.

Moreover, with its machine learning capabilities, AI is used to conduct clinical trials for different medical situations. It can aid professionals in optimizing trial designs and figuring out the best treatment to deliver the best patient care.

3. Patient Engagement and Adherence

Aside from improving health care through creating personalized plans, AI ensures patients are engaged throughout their treatment journey.

Virtual assistants and chatbots can provide patients with vital medical information, answer queries, and remind them about appointments or medication schedules. This ensures patients can easily track their well-being and be on time for treatment.

Additionally, remote patient monitoring systems can track patient vital signs using wearable devices. This aids healthcare providers in identifying potential health issues early on, providing timely interventions, and improving patient care.

Challenges of AI Usage in Healthcare

Although artificial intelligence can immensely improve healthcare systems, professionals should still expect challenges in its implementation and integration. For example, medical professionals should consider the following issues with AI usage in healthcare:

1. Data Availability and Quality

AI algorithms rely on large volumes of high-quality data. However, healthcare data often suffer from incompleteness, inaccuracies, and biases. This can significantly affect the performance and reliability of AI to make data-driven decisions.

2. Algorithmic Bias

Since AI’s machine learning can only rely on which data is fed into it, it’s possible to perpetuate biases. This can lead to unfair outcomes, particularly for underrepresented or marginalized individuals.

3. Regulatory and Legal Compliance

AI applications in healthcare are subject to various regulatory frameworks and legal requirements, including:

• Data privacy laws
• Medical device regulations
• Ethical guidelines

Navigating the complex regulatory landscape and ensuring strict compliance can be too complicated for some healthcare institutions, especially smaller facilities.

4. Transparency and Accountability

This is not just in healthcare; anyone using AI will have difficulty understanding how this technology makes decisions. Since AI lacks transparency, holding anyone accountable for the results is challenging, making AI vulnerable to errors and wrong judgments.

Potential Ways to Manage Challenges

To effectively manage challenges associated with AI, healthcare professionals need to implement comprehensive strategies. This includes establishing robust data governance frameworks to ensure the quality and integrity of data. Further, the data used needs to be driven by diversity and inclusion to provide equitable solutions to patients. You can implement this by creating dedicated teams focused on regulatory compliance.

Moreover, healthcare organizations should prioritize developing transparent and comprehensible AI models to build trust among stakeholders in the decision-making process. Prioritizing collaboration across the board will help identify and mitigate algorithmic biases and ensure alignment with legal requirements and ethical standards.

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References

1. “Artificial Intelligence (AI) in Healthcare Market Size Worldwide from 2021 to 2030.” Statista, 28 Sep. 2022, www.statista.com/statistics/1334826/ai-in-healthcare-market-size-worldwide/.
2. “Survey by The Health Management Academy Reveals Accelerating Use of AI to Overcome Workforce Challenges.” BusinessWire, 15 Mar. 2023, www.businesswire.com/news/home/20230314005243/en/Survey-by-The-Health-Management-Academy-Reveals-Accelerating-Use-of-AI-to-Overcome-Workforce-Challenges.
3. Tyson, Alec, et al. “60% of Americans Would Be Uncomfortable With Provider Relying on AI in Their Own Health Care.” Pew Research Center, 22 Feb. 2023, www.pewresearch.org/science/2023/02/22/60-of-americans-would-be-uncomfortable-with-provider-relying-on-ai-in-their-own-health-care/.