Featured Product
This Week in Quality Digest Live
Customer Care Features
Etienne Nichols
How to give yourself a little more space when things happen
Jennifer Chu
Findings point to faster way to find bacteria in food, water, and clinical samples
Smaller, less expensive, and portable MRI systems promise to expand healthcare delivery
William A. Levinson
Automation could allow baristas to be paid more and still net higher profits for company
Peter Fader
In an excerpt from The Customer-Base Audit, the authors ask critical questions

More Features

Customer Care News
Precision cutting tools maker gains visibility and process management across product life cycles
A Heart for Science initiative brings STEM to young people
Three new single-column models with capacities of 0.5 kN, 1 kN, and 2.5 kN
Recognition for configuration life cycle management
Delivers real-time, actionable 3D data across manufacturing and business operations
On the importance of data governance in the development of complex products
Base your cloud strategy on reliable information
Forecasts S&A subsector to grow 9.2% in 2023
Facilitates quick sanitary compliance and production changeover

More News

Michael Glickman

Customer Care

How AI Drives Innovation in Healthcare

In the medical realm, AI’s most powerful use is to enhance human capabilities—not replace them

Published: Thursday, May 11, 2023 - 12:03

Artificial intelligence (AI) is revolutionizing the healthcare industry by enhancing decision-making capabilities, improving quality of care, and reducing costs. In the age of supercomputers and technological advancement, the health sector generates vast amounts of data, which AI can process and analyze to extract meaningful information.

But are we making good use of those data? As I see it, we need better, but not necessarily more, data. We have a lot of data, but much are of little use because they aren’t being turned into meaningful information. If, for example, we want to use AI to help make accurate forecasts and recommendations, we need high-quality data that can provide us with information. 

Personalized healthcare

As an IT and healthcare professional, I’ve seen health informatics evolve during the past 35 years. Health informatics focuses on information technology to positively affect the patient-physician relationship through effective collection, storage, normalization, and analysis of health data.

How does it work? Electronic health records (EHR), for one, capture all relevant data about a patient so that when an individual arrives at a doctor’s office or hospital, all their medical information is readily available in digital form. Records are up to date and secure, and healthcare is easier to coordinate between facilities and providers.

This type of record collection means that data can be extrapolated from whole populations, e.g., to identify commonalities between groups, such as those suffering from, or at risk of, a condition like diabetes. All this points to a shift toward personalized healthcare (also known as precision medicine). 

Eliminating bias in AI

I don’t think that it will be too long into the future when we’ll be able to tailor treatment and prevention plans to an individual based on factors like genetics, age, lifestyle, and environment. Much like other technologies and improvements, the more tailored the medical plan, the better and more cost-effective the patient outcome.

Although the future is promising, there are still significant challenges to overcome when implementing AI in healthcare. Part of the problem we need to sort out is bias. Bias appears in multiple forms, including omission and commission. Models containing bias will likely exacerbate social inequalities and may even cause deaths. But I’d also point out that there are times in healthcare when it’s beneficial to have an algorithm that contains a bias. To give a real-world example of this, being older than 65 during the Covid-19 pandemic was an important bias that needed to be reflected in monitoring and treatment.

Toward a definition of AI

AI is creating a lot of interest in healthcare because of its potential for cost savings and improved quality. Investment in AI in the medical sphere is growing, but the industry is slow to change. There are a lot of issues that need resolving before AI can, and likely should, really take off. In my opinion, one of the big stumbling blocks is that there’s no single accepted definition of AI. 

For the physician, AI is a host of computational methods that produce systems that perform tasks that would normally require human intelligence. These methods include image recognition and natural language processing. A phrase I’ve heard repeatedly is “augmented intelligence,” reflecting the need to enhance human decision-making capabilities when coupled with computational methods. This moves us away from the term “artificial,” but from the physician’s viewpoint AI is about it being able to assist doctors in their decision making.

AI for precision medicine

According to a World Health Organization report, AI holds great promise for improving the delivery of healthcare and medicine worldwide—but only if ethics and human rights are put at the heart of its design, deployment, and use. Will there come a time when AI will replace humans in the healthcare industry? I think this is unlikely. Instead—and we’re already seeing this to some degree—there will be a shift toward a working relationship between the two. 

As AI technology is steadily applied to all corners of medicine, regulators will need to consider multiple approaches for ensuring the safety of AI in healthcare. This includes International Standards. Finding that common vocabulary, taxonomy, and definition is vital, because it means that the practitioner and the regulator can speak the same language as the technical expert. These standards will guide future AI use to ensure that AI systems are fully interoperable and transparent, and to prevent bias and inequality. The nondeterminism of machine learning and the “hallucinations” of today’s large language models are also significant challenges that must be addressed to ensure safe and effective AI in health. 

We’re still on a long and complex journey in healthcare. While I don’t think you’ll be seeing a robot instead of a doctor anytime soon, I believe we must keep in mind that AI’s most powerful use is to enhance human capabilities—not replace them. Amid the uncertainty and change, we must look for new ways to transform the journey of care. As technology continues to get smarter, faster, and more reliable, the possibilities are endless to ensure patients receive the best possible care. These efforts will ensure that the full potential of AI for healthcare and public health will be used for the benefit of all.

First published April 6, 2023, by ISO.


About The Author

Michael Glickman’s picture

Michael Glickman

Michael Glickman, founder and CEO of Computer Network Architects, has many years of experience in the computer industry and 35 years in healthcare information technology. He is an internationally recognized subject matter expert on systems integration and secure interoperability, and a pioneer in healthcare informatics as a founding member of the HL7 working group in 1987. Michael is the chair of ISO/TC 215, health informatics.


Decisionmaking without accountability

AI in healthcare will just be an excuse for humans to make decisions that hurt other humans while deflecting moral culpability for the harm they cause. That said, this will honestly be no different than the current system, whereby top-down decisionmaking from administrators and bureaucrats strips physicians of their autonomy and associated moral responsibility for patient outcomes. 

In Spring of 2020, hospitals in the United States prevented patients from having their advocates with them while they were in hospital. We all know what happened next.

Not to worry, though... everyone involved was just following orders.