The Human Element in AI in Healthcare: Data, Insights, and Action

In recent years, the notion of collecting a million data points per day during any process was unimaginable for most organizations. However, with the advent of powerful acquisition methods and affordable storage options, we are now inundated with data. The challenge lies in extracting insights from this deluge and converting them into actions that transform processes and organizations.

AI can significantly aid in this endeavor. Regardless of the industry, AI's ability to analyze and identify patterns in data promises to revolutionize how organizations operate. For instance, AI can enhance the productivity of sales calls, reduce waste in factories, and save lives in high-risk industries. To achieve true AI-driven transformation, it is essential to understand human behavior more than the technology itself.

Cognitive scientists have identified three stages in the AI transformation process: collecting data, finding insights, and taking action. The latter two stages require a deep understanding of what drives human behavior, including fears, motivations, biases, cognitive capacity limitations, and other brain processes that influence actions. AI can identify patterns in data, but deriving insights and designing effective organizational change initiatives necessitate a profound understanding of human dynamics.

Using AI to Save Lives

Let's examine the three-step AI transformation process with a real-world example. Dr. Teodor Grantcharov, a professor of surgery at Stanford University, aimed to use AI to analyze and reduce surgical errors in the operating room. Studies suggest that between 44,000 and 250,000 patients die annually in the U.S. due to medical errors, with about one-fourth of those deaths attributed to preventable mistakes in the OR.

For 20 years, Grantcharov has been developing an "operating room black box" that analyzes everything that occurs during a surgical procedure. Inspired by flight data recorders, which have been mandated on all passenger aircraft since 1957, Grantcharov's black box aims to identify and mitigate preventable errors. Recent advancements in AI have enabled his team to overcome their former bottleneck in data analysis. The insights gained significantly enhanced individual and team performance, increased compliance with standard operating procedures, and reduced morbidity, mortality, and costs in operating rooms using the black box.

Step 1: Collecting Data

The first step in AI transformation is collecting data, which has become the easiest part of the process. Grantcharov has placed the OR black box in around 20 operating rooms across the U.S. The platform captures up to 1 million data points per day per site, including audio-visual data of surgical procedures, electronic health records, input from surgical devices, biometric readings from the surgical team, and brain activity measured by wireless EEGs.

Step 2: Finding Insights

Identifying patterns in data is where AI excels. Modern AI methodologies can empower us to turn data into actionable insights. However, understanding human behavior is crucial. For instance, Grantcharov's team hypothesized that stress could impact a surgeon's performance by affecting cognitive processing and decision making. They collected physiological data from surgeons and found that stressed-out surgeons had a 66% higher chance of making an error. Additionally, they observed that distractions, such as a door opening or someone talking about last night's football game, were the root cause of catastrophic errors. These findings required an understanding of the brain's finite cognitive capacity.

Deriving other insights necessitated an understanding of team dynamics. The researchers observed that teams with poor communication and lacking psychological safety had worse outcomes regardless of the surgeon's technical skill. Grantcharov noted, "One of the most dangerous operating rooms is a silent one, where nobody is speaking up or communicating." While one might assume that the surgeon's skill is the most important determinant of success, non-technical attributes such as collaboration and psychological safety most strongly affected patient outcomes. Grantcharov emphasized, "It all comes down to culture."

Step 3: Taking Action

Once AI revealed the biggest sources of OR errors, hospitals and surgical centers could introduce new procedures to prevent mistakes. However, understanding how behavior change happens is essential. Successfully changing an entire organization's culture requires establishing priorities, habits, and systems.

Priorities are tasks or activities deemed most important to an organization. Communicating these priorities ensures everyone knows where to focus their time and attention. In this case, the priority is clear: improving patient outcomes by avoiding preventable OR mistakes.

Habits are behaviors performed automatically with little conscious thought. For example, speaking up with concerns instead of remaining silent can become a habit with training and practice.

Systems are procedures or principles put into place that make the desired behavior the easiest to do. To reduce distractions and preserve cognitive capacity, hospitals could institute a new rule restricting non-relevant discussions during critical steps of a surgical procedure.

Along with priorities, habits, and systems, AI transformation requires everyone in the organization to embrace a growth mindset—the belief that failures are opportunities to get better, rather than threats to one’s standing or status. Grantcharov recalls that initially, many surgical teams were wary of the OR black box, fearing it would make them look bad or leave them vulnerable to litigation. However, their attitudes gradually changed.

"Once we realize that we can’t improve without objective measures of our performance, it really opens the world of growth mindset and continuous improvement," Grantcharov says. Hospitals that welcomed this transition have realized tremendous gains in quality, safety, efficiency, and productivity.

Beyond the OR

Not every industry has as much at stake in terms of human life as the healthcare industry. Yet, no matter the sector, AI can analyze data and lead to valuable insights that drive action, from improving a specific process to changing an entire culture. However, simply pointing AI at a data set will reveal little without a hypothesis worth testing.

For example, in a meeting setting, AI-powered devices could collect audio and visual data (in an anonymized and ethical fashion), and, with the help of human insights, detect patterns that might not be obvious: Are there quiet people in the room who have great ideas, but others constantly talk over them? Is anyone showing signs of excessive anxiety or stress? Are people looking down often in a video call, possibly distracted by devices?

In this way, AI could help leaders first recognize obstacles that get in the way of productive meetings, then find ways to address them, such as working to increase psychological safety or decrease distractions.

Whether in the operating room or the boardroom, AI can help unlock potential in your organization. Ironically, the more technology plays a central role in our lives, the more we need to understand how humans interact with and process the world.