Checklists work well for complicated health care problems. But they don’t work to solve complex ones, like pandemics

Federal public health officials did many good things in response to Covid-19, like investing in Operation Warp Speed, but they misdiagnosed the nature of the pandemic: They deemed it a complicated problem rather than a complex problem. This error reduced the effectiveness of the country’s pandemic response, and a course correction is necessary to improve the response to future pandemics.

In 2001, I developed a checklist for health care workers to reduce infections from catheters, tubes that are widely used to deliver fluids and critical medicines to people who have been hospitalized. At the time, catheter infections resulted in approximately 31,000 deaths a year in the U.S, putting it in the top 15 leading causes of death.

The checklist included measures such as washing hands and wearing masks. When tested at Johns Hopkins, where I worked at the time, and then adopted in Michigan, and overseen by a diligent nursing staff, use of the checklist eliminated almost all catheter-related infections. The intervention was then adopted state by state across the U.S., helping reduce these infections by 80% across the U.S and several other countries, though catheter-related infections have increased with Covid-19.

That checklist, and others like it, are being used in hospitals worldwide to improve patient outcomes.

Checklists work because they address complicated problems that can be effectively managed with experts adhering “to a comprehensive and robust set of axioms and rules,” writes Rick Nason in his book, “It’s Not Complicated: The Art and Science of Complexity in Business.”

Not all medical challenges, however, are “complicated.” Some, like the Covid-19 pandemic, are “complex” and require a different mindset and problem-solving approach.

Complex problems are punctuated by numerous unknowns and interrelated factors. Complicated problems, such as reducing catheter-related infections, respond to the application of strict rules and processes. Complex problems, by comparison, can be likened to raising a child: The results are often unpredictable and small inputs can have large, unanticipated changes.

“Complex systems are nuanced and require a nuanced approach,” writes Nason, not “a rigid, rules-based, complicated approach.”

A complex environment requires managers to learn from mistakes and adjust their plans as they move forward. A grand plan or strategy just won’t work. “Complexity thinkers have the humility and flexibility not to get trapped into this low-probability strategy,” he says. “Complicated thinkers tend to get too intellectually invested in an idea and refuse to let go, despite sometimes overwhelming evidence that the plan is not working.”

Sound familiar? Federal policymakers approached Covid as a complicated problem, taking a simplistic, linear view that vaccines alone would solve the problem while they underfocused on testing, tracking, and treating. They engaged in too little experimentation and learning. To respond to future pandemics more effectively, policymakers should consider the following:

Testing. Robust testing is needed to determine who is infected, contagious, sick, and most vulnerable, and how vaccines and therapies affect those variables. Leaders in the White House and at the Department of Health and Human Services should structure these and other questions and encourage the market to run these tests.

Vaccines and treatments. While vaccines are an essential part of the U.S. Covid-19 response and have provided tremendous benefits, the narrow focus on them was limiting. The White House and HHS should have recognized the uncertainties surrounding vaccines and their outcomes and the emerging nature of the pandemic by broadening investments to speed the development not only of vaccines but also of drug therapies, treatments, and supportive care. In the future, Warp Speed-type efforts should be mounted to develop capabilities to prevent viral spread, cure those who are infected, and care for those who cannot be cured.

Learning. A tremendous amount of knowledge about Covid-19 has accumulated since the outbreak of the pandemic, yet there is much more to learn. Future pandemics require robust learning and communications systems in which HHS coordinates questions and recommends — but does not control — the research questions asked, the experiments implemented, and the results and learnings that emerge. For example, HHS can coordinate a transparent learning website to facilitate the asking of questions and sharing of results.

Policymakers must communicate the learnings and recommended paths forward. These communications need to be simple, clear, and practical.

If policymakers had viewed Covid as a complex problem, it is likely that fewer people would have suffered and died, or had their livelihoods disrupted. We would have recognized that the virus would evolve and have been better prepared for that eventuality. Ample testing, vaccines, and treatments would have been deployed rapidly when and where they were most effective. And we would have learned much sooner who is infected, what works and for whom, and what does not work. We have seen the impact when a complex problem is addressed with complexity science: A broad effort to eliminate defects in value reduced the annual cost for a Medicare patient by 21% over two years while increasing the quality score of their care from 73% to 100%.

Covid-19 will not be the last public health crisis. When the next one hits, policymakers will better serve the public by identifying whether the problem at hand is complex rather than complicated and using the appropriate approach for that diagnosis.

Peter Pronovost is a critical care physician, health care executive, and chief quality and clinical transformation officer for Cleveland-based University Hospitals.