The story of improving patient outcomes in healthcare is often tied up with technological development and evolution. Artificial intelligence (AI) is the latest tech area receiving constant attention, with leaders across the medical field tapping into its potential.
AI is a term that covers more than one specific type of development. Technologies, including generative AI (GenAI), deep learning, natural language processing, and machine learning (ML) all fall under the general umbrella of AI. Each of these areas has its own potential healthcare provider applications.
To keep their hospitals, pharmaceutical companies, and other medical organizations on the cutting edge, executives and medical professionals are deepening their knowledge of AI's promise, as well as the early use cases that have already emerged. Courses dedicated to this subject, like MIT Sloan Executive Education's Transforming Healthcare with AI, provide an ideal setting to gain this familiarity.
How are healthcare providers using AI today?
Considering how different the multiple forms of AI are in their functionality, it makes sense that organizations have already found numerous ways to use the technology. While the most impactful future applications of AI tool use in healthcare may still be years off, the technology has already found its place.
There are immediate AI system use cases in:
- Medical diagnosis: At their core, many AI applications are advanced forms of big data analytics, capable of assessing massive amounts of information to provide insights that can strengthen healthcare delivery. This has obvious applications in enhancing diagnostics, providing a digital set of eyes that can find traces of disease that are too subtle to be noticed otherwise and ideally leading to better patient outcomes.
- Monitoring and patient care: In addition to analyzing samples and medical imaging to detect early warning signs of illness, AI algorithms can handle other patient care tasks that require careful study of data, such as real-time condition monitoring.
- Drug discovery: Working on complex formulations for new potential treatments is another task that can benefit from powerful AI algorithms. Pharmaceutical manufacturers can speed up and deepen their development workflows when medical professionals are trained in AI deployment and use.
- Organizational management: Despite the unique nature and high stakes of the healthcare industry, it is essentially like any other industry. This means there are use cases for GenAI tools that speed up the back-office management of large organizations. Hospital staff can benefit from efficiency-building AI assistants assisting with administrative tasks.
AI applications' ability to crunch large data sets and provide fast insights is a highly versatile capability, one that can be applied to almost any kind of information. As industry leaders find ways to meld this power with the safety and regulatory complexities of the medical field, new use cases will emerge.
Potential advantages of AI in healthcare
Some of the most promising advantages of using AI in healthcare revolve around the fact that the industry has evolved beyond the capabilities of legacy technology. Advanced sensors have enabled the collection of large patient data sets. Organizations that can unlock insights from these massive, varied information stores can make progress in developing breakthrough treatments.
The extra power provided by an AI algorithm can lead to advantages such as:
- The ability to work with complex data: Some resources would be impossible to parse effectively using older algorithms. This may be due to the sheer size of the information, its unstructured nature, or its velocity.
- Automation of administrative tasks that take up time in employees' days: Clinical and administrative staff that turn some of their rote, repeated tasks over to AI algorithms can spend more time on value-adding work.
- Deeper insights into patterns within data sets: Some signs may be too subtle for conventional solutions to discover. Machine learning algorithms that train themselves to effectively recognize patterns can prove pivotal in care settings.
Healthcare organizations that are feeling the limitations of legacy technology can look to the new generation of AI to keep pushing the limits on their digitization projects, in both clinical and administrative settings.
AI healthcare challenges to overcome
While AI is a promising technology area for medical organizations, using it correctly is far from automatic. Leaders will have to put in extensive work in the years ahead to understand the best ways to use these algorithms. Along with their power, AI tool adoption comes with new issues and challenges that set them apart from the legacy technologies currently in place.
Potential pitfalls of medical AI solution use for healthcare provider organizations to overcome include:
- Regulatory concerns around data access: Due to its sensitive and private nature, medical data is protected by a variety of laws, perhaps most prominently the Health Insurance Portability and Accountability Act (HIPAA). Researchers using AI to work with patient data will have to make sure they're not exposing that information or putting it at risk.
- Ethical issues regarding potential algorithm bias: GenAI algorithms come to conclusions based on the data they're fed. If there is an inherent bias against certain patient traits encoded within a data set, this could lead to unfair output — users must guard against such an outcome.
- Operational issues managing algorithms: In addition to concerns about their fairness, GenAI algorithms also come with challenges regarding unpredictable or inaccurate output. "Hallucinations," outcomes when an AI algorithm contradicts reality, are a major risk when dealing with sensitive matters like patient health.
There is a balance inherent to AI — extreme potential matched with complex challenges. The rising generation of experts working with these systems in the healthcare industry and beyond will have to sharpen their own knowledge to make the most of the technology.
Learning about healthcare AI through executive education
The combination of rapid development and high demand for experts who understand AI has created a complex hiring situation for any healthcare organization. These institutions need to build teams of AI model experts, and to be considered for these positions, healthcare professionals must have up-to-date knowledge of the most promising AI solutions.
Executive education can fill this gap in the market, providing a way for participants to quickly engage with the latest insights from the AI development space. This is the purpose of the MIT Sloan Executive Education course Transforming Healthcare with AI. Taught over two days in person, the course presents insights from multiple experts who have engaged directly with the latest AI developments.
Transforming Healthcare with AI is led by Distinguished Professor for Health and AI Regina Barzilay, Professor Dimitris Bertsimas, and Visiting Senior Lecturer Paul McDonagh-Smith. The featured guest speaker is Dr. Lecia Selquist, MD, MPH, who serves as the Program Director of the Cancer Early Detection and Diagnostics Clinic at Mass General Cancer Center. Perspectives such as hers are essential for understanding the way technology is being used, in practice, by healthcare professionals on the cutting edge of medicine.
Additional MIT Sloan Executive Education offerings include the Artificial Intelligence in Health Care self-paced online course or the Executive Certificate in Digital Business, one of our certificate programs.
Prepare for the tech-driven future of healthcare
Whether you're hoping to excel in your current role or make yourself a more intriguing prospect in the healthcare technology job market, studying advanced applications of AI is a way to add depth to your knowledge. Adding still-developing AI technology to the sensitive healthcare sector is a demanding task, one that will require well-prepared executives.
By learning both the theory behind medical AI model usage and the practical applications that have already emerged for related tech tools, you can immerse yourself in the present and future of healthcare organization technology use.
Enroll in Transforming Healthcare with AI to stay engaged with this fast-moving field.