By Pamela J. Gallagher

The modern healthcare industry is dependent on data. The steady improvement of how data is collected and analyzed has allowed us to make great strides in providing quality care and improving the health of our patients. At the same time, the pandemic has highlighted how this dependence on data can lead to “analysis paralysis” that can harm communities' health and well-being.

Reality is often far more complex than the data can demonstrate. As the adage goes, “correlation does not imply causation.” Furthermore, the data collection process can impact the story the numbers are telling. Consider, for example, the complicated web of diagnosis codes. While they may certainly indicate the types and quantities of maladies treated or services provided, they also signify which codes insurance companies are more likely to cover, allowing the provider to get paid.

With healthcare professionals drawing different conclusions and making opposing decisions using the same set of data, weighing the potential implications and consequences of our data-based choices can be frustrating and baffling. It seems increasingly difficult to say what is “reliable.”

Clearly, we’re working within a broken system, but for the time being, it’s the one we have to work with. How, then, do we move forward with decisiveness and avoid “analysis paralysis?”

Research both sides.

Don’t look for data in order to make a point, support the opinion you already hold or, perhaps even worse, back up the decision you’ve already made and moved ahead with. As I’ve written about before, engage with the very best versions of varying arguments. Get the opinions of others within your organization who may have a different lens through which to view the issue. Decisiveness is no virtue if you haven’t taken the time to understand a matter from many angles.

Make the best decision with the most reliable information you can find. Conflicting information is all around. Anyone who has googled something seemingly simple as the best way to treat a runny nose knows this. We need to use data to help us make good decisions, but if you’re looking for it to lead you to an action that won’t have any dissenters, I’m afraid you will be disappointed.

As leaders, we may lean only slightly one way or another, feeling 60-40 for or against a particular course of action. But in the end, the decision has to be 100-0. We either do it, or we do not. We go this way or that. In the end, all you can do is make the best decision you can with the best information available to you at the time.

Be willing to live with the consequences of your decision. Even carefully researched decisions will have consequences we don’t anticipate or intend, for good and ill. We must be willing to live with and be accountable for those consequences. Rather than using data as a weapon to double down and justify your actions, openly admit what did and didn’t work as a result of the decision, and analyze those factors to take a wiser course of action next time.

Respect that data might lead someone else in a different direction. Are there bad actors who deliberately misuse data to suit their own purposes? Yes. But generally, people are doing their best to analyze the data with integrity and make good decisions, even in the face of uncertainty. Often, people who arrive at different decisions using the same numbers are operating in good faith and may be simply emphasizing different elements of the data or operating within a different context than yours. We must learn to respect people and organizations whose decisions diverge from our own.

References

Cognitive overload: When processing information becomes a problem, Mayo Clinic Health System

Is there such a thing as ‘too much data?’, Precise Data Consulting

Why, Yes, There Is Such A Thing As Too Much Data (And Why You Should Care), Forbes

How to Make Sure You’re Not Using Data Just to Justify Decisions You’ve Already Made, Harvard Business Review

How much data is too much data?, ResearchGate

HLTH22: Google, Epic ink deal to migrate hospital EHRs to the cloud to ramp up use of AI, analytics, Fierce Healthcare