AI in Healthcare: Shedding Light on Some Misperceptions

By Steve Allen, Director, Clinical Systems Segment, Health and Life Sciences at Intel

As we continue to battle the COVID-19 pandemic, applying innovative technologies such as artificial intelligence (AI) to healthcare is more critical than ever. Many don’t know how AI functions in healthcare, and its use is sometimes met with fear. Some envision a world where robots replace physicians, taking over the human element that powers the patient experience and doing away with the expertise of practitioners. This could not be farther from the truth, in healthcare or other industries.

AI is already employed by several key industries, including the financial sector, which has long integrated its capabilities to enhance consumer offerings and improve the overall financial system. While many thought AI would replace human workers there, the opposite has occurred. Higher paying financial jobs have been created because of the technology. AI in healthcare can have an even greater impact.

To best understand what AI in healthcare means, it’s helpful to gain an understanding of what it does not mean. Using AI in healthcare does not mean that computers are diagnosing diseases and health conditions rather than physicians.

Rather, AI is helping humans make better, more effective diagnoses, equipping doctors and other medical practitioners with quicker insights and targeted data so that they can make more informed, more precise diagnoses and present patients with tailored treatment options. Computers don’t diagnose, treat, or cure diseases; doctors do. AI simply produces the information that allows doctors to get to the “why” of conditions faster than ever before. It is still the doctor who translates the AI-generated data, producing a more accurate diagnosis and treatment plan.

By leveraging the power of AI, medical practitioners can relieve overburdened workloads and better prioritize the most critical cases. One important use case involves alarm fatigue, which has been exacerbated with so many patients entering hospitals with COVID-19. Alarm fatigue occurs when an excessive number of alerts meant to draw the attention of care staff to a patient become overwhelming, desensitizing staff and raising the risk that they will overlook a truly critical notification. AI can help sort through the cacophony of alarms, identifying the issues and resolving false alarms, even creating predictive analytics to show the nursing staff developing issues so that the most serious are managed first.

Harnessing AI for healthcare also does not mean that patients will lose the personalized experience and insight of a doctor’s care. In fact, AI can lead to more personalized care. AI can combine the needs of an individual patient with the largest body of knowledge of related cases. Tuned by the specific genetic makeup of the patient, AI can equip practitioners to provide the best type of personalized care. At a more basic level, when patients use mobile devices to read and communicate their blood pressure, heart functions and glucose levels, AI is a natural for analyzing those complex data.

AI can also allow doctors to spend more time getting to know individual patients by reducing non-patient activities. At its most basic level, AI can help better schedule doctors, nurses and other healthcare workers to accurately meet demand, leading to more one-on-one time with patients. AI and machine learning also help health management professionals handle resource flow and process in a way that simply can’t be accomplished without their capabilities. Again, during the COVID-19 pandemic, the logistical support provided by AI is not only important for its own sake; it also leaves more time for doctors to spend with patients.

Overall, AI provides doctors with additional tools to make them better equipped for what they do best – caring for their patients.

With a rapidly aging population, we must make the decisions and investments that allow us to democratize healthcare for all. AI is critical to doing that, and currently it is being harnessed to help understand and manage a major outbreak of disease. In addition to helping countries with advanced healthcare systems, AI could play an important role in addressing global healthcare inequities at the individual patient, health system and population levels.

We often hear about world-class doctors and care teams at preeminent hospitals around the world, but the reality is that most people don’t have access to the best of the best. We must create a healthcare ecosystem where everyone has access to world-class care. AI can help make that a reality for all citizens of the world by leveraging a deep pool of data and providing evidence-based clinical decision support for doctors, therefore improving the level of care across the board.

To reach its full potential, AI needs the power of public-private partnerships and innovation. Most of all, AI needs data, and lots of it. Congress should consider requiring electronic health record vendors and healthcare providers to share data with health researchers using federated homomorphic encryption solutions. These encryption solutions can help while still preserving the privacy and cybersecurity of the underlying personal health information. Additionally, the Department of Health and Human Services should encourage health researchers to use the increased data provided by telehealth services to train AI software that can further improve both the telehealth services, but also other clinical care, healthcare operations, and research. New policies that support AI’s need for data will allow the healthcare industry to swiftly adopt a tremendous technology that is helping professionals offer better care – not replacing them in doing so.

1 thought on “AI in Healthcare: Shedding Light on Some Misperceptions

  1. Nicely written article. How are other countries dealing with the access to data issue? Any lessons learned that are applicable to the US healthcare system and your call to action from US federal government?

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