When we hear big numbers in the news, they often grab our attention. For example, on Tuesday, 11th November, 1,200 flights were cancelled across 40 major U.S. airports due to staffing shortages caused by a government shutdown. That sounds alarming, right? But here’s the catch: those cancellations represented only 6% of total flights. In other words, 94% of flights operated as expected. Suddenly, the situation doesn’t seem quite as catastrophic. This simple example shows how data can be manipulating, even when the facts remain the same. Manipulating data in healthcare works similarly. In clinical trials, results can be described in multiple ways: -“80% survival rate” -“20% mortality rate” -“800 out of 1,000 patients survived” All statements are accurate, but each evokes a different emotional response. This is why manipulating data in healthcare through framing can significantly impact decision-making. Common Cognitive Biases in Data Interpretation Denominator Neglect Focusing on absolute numbers instead of proportions can distort perception. For example, 1,200 cancelled flights sounds huge—until you know there were 24,000 flights scheduled that day. In healthcare, this bias can lead patients or professionals to misinterpret risk. Base Rate Neglect Ignoring general statistical context can exaggerate risk. If you hear 6% of flights were cancelled yesterday, you might panic. But if you know that 2% are cancelled on any typical day, the extra risk seems less severe. In healthcare, failing to consider base rates can distort treatment success or disease prevalence. Gain vs. Loss Framing The same data can sound positive or negative depending on wording: -“6% of flights were cancelled” (loss frame) -“94% of flights ran on time” (gain frame) In healthcare, framing survival rates versus mortality rates can influence patient choices—even when the numbers are identical. Why This Matters for Healthcare Professionals Understanding these psychological effects is crucial. Whether you’re reading research or presenting data, framing can nudge decisions without changing the facts. Awareness helps prevent misinterpretation and promotes informed choices. Next time you encounter healthcare statistics, ask: -What’s the denominator? -What’s the base rate? -Is this framed as a gain or a loss? By doing so, you’ll spot when data is being manipulated in healthcare, intentionally or not. Want to learn more about manipulating data in healthcare? Contact ourBehavioural Science team at shift@hrwhealthcare.com. Apply Now!