Mohamad-Ali Salloum is a Pharmacist and science writer. He loves simplifying science to the general public and healthcare students through words and illustrations. When he's not working, you can usually find him in the gym, reading a book, or learning a new skill.
Correlation vs Causation: How Pharmacists Should Think
Mohamad-Ali Salloum, PharmD • April 29, 2026
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Correlation vs Causation: How Pharmacists Should Think
As pharmacists, we live at the intersection of biology, numbers, and everyday patient decisions. Every day, we interpret studies, assess drug effects, and educate patients. And whether we explicitly mention it or not, we are constantly navigating one of the trickiest concepts in science:
Correlation does not
equal causation.
But what does that really mean for pharmacists—clinically, scientifically, and practically? Let’s unpack it in a friendly, conversational way, while staying rooted in clear evidence-based thinking.
1. What Exactly Is Correlation?
Correlation simply means two things change together. It doesn’t tell us why or how. It just tells us there’s a relationship.
In biomedical research, correlation is a statistical association. For example:
- Higher BMI often accompanies higher systolic blood pressure. That’s a positive correlation.
- Higher physical activity often accompanies lower fasting glucose. That’s a negative correlation.
These patterns help researchers spot trends, but they don’t prove one causes the other. Correlation is the spark—not the fire.
💡 Quick example pharmacists see often:
Older adults taking more medications also tend to have more side effects—but age itself can be the reason, not the medications.
2. So What Is Causation?
Causation means A truly makes B happen.
To determine causation, researchers look for three key ideas:
- The cause happens before the effect.
- The cause is directly related to the effect.
- There’s no better explanation for what happened.
A classic example from healthcare: long-term cigarette smoking increases the risk of lung cancer. This relationship has strong causal evidence.
As pharmacists, causation matters because it tells us which actions actually change patient outcomes.
3. Why Pharmacists Must Be Extra Careful With Correlation
Most medication safety signals come from observational studies, which are prone to confusion between correlation and causation.
Example:
A study finds that patients on PPIs have lower B12 levels. But…
• PPI users are typically older
• Older adults already have higher risk of deficiency
• They often have multiple comorbidities
So the correlation may be real, but the cause may not be the drug alone.
• PPI users are typically older
• Older adults already have higher risk of deficiency
• They often have multiple comorbidities
So the correlation may be real, but the cause may not be the drug alone.
This is why pharmacists must dissect data carefully when evaluating drug risks and benefits.
4. The Danger of Misinterpreting Correlation in Pharmacy Practice
Misinterpreting correlation as causation can lead to:
- Inappropriate medication changes
- Misleading patient counseling
- Poor public health decisions
✅ A temporal relationship alone (e.g., “I took Drug X, then symptom Y happened”) is not enough to establish causation.
5. How Pharmacists Should Think: A Practical Framework
Here’s a simple mental checklist:
- Is the mechanism plausible?
- Did the cause happen before the effect?
- Are there confounders?(age, comorbidities, lifestyle, polypharmacy)
- What study design is being used?
- What deeper mechanisms might be at play?(critical realism mindset)
6. Bringing It All Together: A Practical Example
Imagine a study reports that patients taking Drug A have higher rates of insomnia. Before concluding Drug A causes insomnia, ask:
- Is there correlation? Yes.
- Is the timing right? Did insomnia begin after starting Drug A?
- Confounders? Steroids? Anxiety? Other meds?
- Plausible mechanism? CNS stimulation?
- Study design? Observational or randomized?
This thinking protects patients and leads to more accurate clinical decisions.
✅ Quick Interactive Quiz
Test your understanding!
References:
- Zaniletti I, Larson DR, Lewallen DG, Berry DJ, Maradit Kremers H. How to Distinguish Correlation from Causation in Orthopaedic Research. J Arthroplasty. 2022;38(4):634‑637. [pmc.ncbi.nlm.nih.gov]
- Association of Health Care Journalists. Correlation vs. Causation. [healthjournalism.org]
- Rush J, Ajami M, Look K, Margolis A. Statistics Review Part 10: Causality and Confounding. J Pharm Soc Wis. [jpswi.org]
- Biostat Prime. Correlation vs Causation: Meaning, Differences & Examples. [biostatprime.com]
- Koopmans E, Schiller C. Understanding Causation in Healthcare: An Introduction to Critical Realism. Qual Health Res. 2022;32(8–9):1207–1214. [pmc.ncbi.nlm.nih.gov]
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Mohamad-Ali Salloum, PharmD
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