1. Definition

Evidence-Based Medicine (EBM) is the conscientious, explicit, and judicious use of current best evidence in making decisions about the care of individual patients. It integrates:

  • Best available research evidence
  • Clinical expertise
  • Patient values and preferences

2. Key Components

A. Best Research Evidence

  • Derived from clinically relevant research, often from peer-reviewed journals.
  • Includes randomized controlled trials (RCTs), cohort studies, case-control studies, and systematic reviews.

B. Clinical Expertise

  • Skills and past experience of the clinician.
  • Involves diagnosing, evaluating, and managing patient health.

C. Patient Values & Preferences

  • Individual concerns, expectations, and values.
  • Shared decision-making is essential.

3. The EBM Process

  1. Ask – Formulate a clear, answerable clinical question (PICO: Patient, Intervention, Comparison, Outcome).
  2. Acquire – Search for the best available evidence.
  3. Appraise – Critically assess the evidence for validity, impact, and applicability.
  4. Apply – Integrate the evidence with clinical expertise and patient preferences.
  5. Assess – Evaluate the outcome and seek ways to improve.

EBM Process Diagram

4. Hierarchy of Evidence

Evidence is ranked by reliability:

  1. Systematic Reviews & Meta-Analyses
  2. Randomized Controlled Trials (RCTs)
  3. Cohort Studies
  4. Case-Control Studies
  5. Case Series/Reports
  6. Expert Opinion

Hierarchy of Evidence Pyramid

5. Surprising Facts

  1. EBM is not new: The concept dates back to the 19th century, but only gained widespread adoption in the 1990s.
  2. Medical reversals: Up to 40% of common medical practices have been overturned by new evidence in the last two decades.
  3. Bias in research: Over 50% of published research findings may be false or exaggerated due to publication bias and poor study design (Ioannidis, 2005).

6. Emerging Technologies in EBM

Artificial Intelligence (AI) & Machine Learning

  • AI can analyze vast datasets rapidly, identifying patterns and predicting outcomes.
  • Machine learning models assist in diagnosis and personalized treatment.

Big Data Analytics

  • Integration of Electronic Health Records (EHRs) enables large-scale, real-world evidence generation.
  • Facilitates population-level studies and rapid evidence synthesis.

Digital Health & Wearables

  • Devices track patient metrics (heart rate, activity, sleep) in real time.
  • Data from wearables contribute to evidence for preventive and chronic care.

Blockchain

  • Secures patient data, ensuring integrity and traceability in clinical trials.

Recent Study:
A 2022 article in Nature Medicine (Esteva et al., 2022) demonstrated that deep learning algorithms can match or outperform dermatologists in diagnosing skin cancer, highlighting AI’s role in EBM.

7. EBM and Technology

  • Integrated Unit Testing: Like software, medical interventions are “tested” in RCTs before clinical use.
  • Output Pane: Clinical trial registries and systematic reviews function as “output panes,” showing results of evidence synthesis.
  • Terminal: EBM relies on real-time data inputs (patient records, lab results) similar to terminal commands.
  • Active Document: The clinician’s current patient is the “active document,” with EBM guiding decisions.

8. Advantages of EBM

  • Improves patient outcomes and safety.
  • Reduces unnecessary interventions.
  • Promotes cost-effective care.
  • Encourages lifelong learning and adaptation.

9. Challenges

  • Time constraints for clinicians to appraise evidence.
  • Limited access to high-quality research in some settings.
  • Patient diversity and unique contexts may not fit available evidence.
  • Publication bias and conflicts of interest.

10. Memory Trick

“ACE the EBM”:

  • Ask – Formulate the question.
  • Collect – Gather the evidence.
  • Evaluate – Critically appraise and apply.

11. Water & EBM – Fun Connection

The water you drink today may have been drunk by dinosaurs millions of years ago.
Just as water cycles through time and space, evidence in medicine is continually recycled, updated, and refined. Old practices may be replaced as new “evidence” flows in.

12. Citation

Esteva, A., et al. (2022). “A Deep Learning Approach to Dermatology.” Nature Medicine, 28, 52–58. Link

13. Revision Checklist

  • [ ] Define EBM and its components.
  • [ ] Understand the EBM process (Ask, Acquire, Appraise, Apply, Assess).
  • [ ] Recognize the hierarchy of evidence.
  • [ ] Identify emerging technologies in EBM.
  • [ ] Connect EBM to technology and clinical practice.
  • [ ] Recall surprising facts and the memory trick.

14. Summary Table

Component Description Example
Best Evidence Research studies, trials RCTs, meta-analyses
Clinical Expertise Physician’s experience Diagnosis, management
Patient Values Individual preferences Shared decision-making
Emerging Technologies AI, Big Data, Wearables, Blockchain Automated diagnosis

End of Revision Sheet