AI and data-driven decision making — Is the C-suite ready?

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Gartner defines augmented intelligence as a human-centered partnership model where people and artificial intelligence work together to enhance learning, decision-making and cognitive performance.

Augmented analytics play a central role in this vision. By assisting with data preparation, insight generation and insight explanation, augmented analytics help humans explore, analyze and act upon the information residing in analytics and business intelligence platforms.

Becker's Hospital Review recently spoke with Jason Jones, PhD, chief analytics and data science officer at Health Catalyst, about the growing importance of augmented analytics in healthcare. While these tools have become more widely available, some organizations haven't considered their value in clinical settings or in the C-suite.

Augmented intelligence supports strategic efforts to reduce healthcare costs and improve care

Historically, many healthcare organizations have used augmented intelligence to aid with transactional decisions, like selecting the right antibiotic for patients. The danger with this approach, however, is that organizations may miss the bigger picture of where to focus their efforts, allocate resources and set accountability targets that will promote higher quality care.

An example of this problem is clostridium difficile in healthcare settings. "Hospitals have focused on the issue of C. diff for a long time in the inpatient setting, but less so in the emergency department. If hospital leaders don't recognize, however, that the root of the problem may lie in the emergency department, then the organization may fail to implement preventive measures like terminal room cleaning in the ER," Dr. Jones said. "Hundreds or thousands of patients could be harmed because leaders didn't recognize the real problem."

Augmented intelligence can help leaders better understand clinical quality, identify performance variance and root causes of underperformance and zero in on areas that fall short of clinical improvement benchmarks.

AI-driven decision-making tools can assist with organizational change management

Once a healthcare organization makes macro-level decisions about where to focus attention and resources, the executive team usually appoints one person to lead the change. Augmented intelligence and analytics can help these change leaders, as well. If a hospital is trying to improve pneumonia care, for instance, the person implementing the pneumonia risk-prediction model must identify where to set the threshold for action. That means calibrating the analytic tools so they meet the needs of the organization's patient population and operations.

Unfortunately, many organizations are so eager to deploy artificial intelligence they forget about context and then the initiative goes poorly. It's crucial to view predictive modeling and AI as tools used in the change management process. This lens enables organizations to deliver much greater benefit through augmented analytics.

"Health Catalyst spends a lot of time working with change agents in healthcare organizations," Dr. Jones said. "We help them understand whether a predictive tool will help more than it will harm. We then analyze how to integrate the tool into existing workflows. Augmented analytics are most effective when the best possible people act upon them at the best possible time."

In 2022, more C-suites will recognize the value augmented intelligence can bring to decision-making

With augmented intelligence and analytics, humans focus on the aspects of decision-making where they excel and get assistance in the areas where they need help, such as interpreting quantitative data. Augmented intelligence offers computer-generated insights into data interpretation, but then lets humans focus on questions related to the organization's values and priorities.

"Computers can predict, for example, a patient's short-term risk of mortality from pneumonia and can tell us how much of an improvement in pneumonia outcomes would be significant for the organization," Dr. Jones said. "What they can't tell us is how a multi-specialty, multi-facility healthcare organization wants to think about 'systemness.'"

In this scenario, augmented intelligence allows the organization's leadership team to decide what systemness means to them. For instance, will all hospitals need to focus on pneumonia or will each hospital identify the area where it sees the best opportunity to improve?

Augmented intelligence and analytics are a good match for the healthcare environment. "There are some cases in healthcare where you can replace people with technology, like stocking supplies in the pharmacy. However, most healthcare decisions involve some sort of value judgment," Dr. Jones said. "Augmented intelligence respects the value of human knowledge and keeps people in the decision-making loop."

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