Artificial Intelligence, not Artificial Care: Healthcare & AI

Healthcare as we know it is broken. It’s expensive, slow-moving, and can even seem unattainable to some. I want to acknowledge that we have made strides in improving population health, but there’s still much work to be done to make healthcare more efficient while maintaining the quality of patient experience. While many leaders throughout the industry have different ideas as to how we can improve health outcomes and efficiency, there’s one solution that I’m most passionate about, and it's the role artificial intelligence (AI) plays in accelerating care.

With large amounts of data stored by healthcare organizations in medical records, such as images or patient histories, clinical research trials, and medical claims, we can analyze the data by using AI to find patterns and insights not typically identified by humans. The AI algorithms are taught to identify and label data patterns, while natural language processing (NLP) allows these algorithms to isolate relevant data. With deep learning (DL), the data is then analyzed and interpreted with the help of extended knowledge by computers. 

I recently spoke at Ai4, a leading conference discussing all things AI. My discussion centered on our disjointed healthcare system: where do we go from here? As the healthcare system looks to adopt the latest technologies, is AI the answer to mending this broken system? I discussed this at Ai4 last week with my presentation, “Artificial Intelligence, not Artificial Care.”

AI has the potential to address four key areas in healthcare: enhancing the patient experience, improving population health, reducing costs, and improving daily clinician operations. It’s estimated that AI applications can cut annual healthcare costs in the United States by $150 billion in 2026.

Here are some of my key takeaways:

• The patient experience: I firmly believe telehealth will continue to be a game-changer for those seeking healthcare across the country…even the world. Utilizing AI will be able to free up providers from some of the more “routine” tasks so they can focus on providing better care.
• Improving population health: AI has the potential to provide equal access to treatment, especially knowing that the COVID-19 pandemic has exacerbated gaps in care. Sixty-eight percent of consumers have at least one social determinant of health (SDoH) issue, and those with high SDoH stress are nearly 50% more likely to suffer from chronic conditions….and 2.3 times more likely to rate their health as “fair” or “poor.”
• It’s important to note that AI is already being used throughout the industry. For example, the Pregnancy+ offering from Philips and Avent features an app to allow the mother to track and share her pregnancy journey with family and professionals. It’s a simple tool to incorporate AI into women’s healthcare and address maternal health gaps in care. 
• Reducing costs: AI can help forecast disease. Let’s look at acute kidney injury (AKI): it can be difficult to detect by clinicians but can cause patients to deteriorate very fast and be life-threatening. With an estimated 11% of deaths in hospitals following a failure to identify and treat patients, the early prediction and treatment of these cases can have a huge impact to reduce life-long treatment and the cost of kidney dialysis. 
• Improving daily clinician operations: Early AI experiments have successfully replaced or supplemented the physician’s judgment (and implicit biases) when diagnosing a patient’s pain or medical needs. 

…but, there are still challenges to address to further AI in the industry, including racial bias and differences in infrastructure among payers and providers across the country that make implementing the technology at scale challenging.

How do you see AI being used in healthcare? Are there other challenges you foresee? Are your organizations utilizing tech in a new way? Drop your comments below; I’d love to hear from you!

Be well, 

Liz