University of Pittsburgh logo

Evidence, Discovery, & Reasoning 1, 2, & 3

EDR1 Course Director
Aaron Brown, MD
Department of Emergency Medicine
brownam3@upmc.edu

EDR2&3 Course Directors
John Maier, PhD, MD
Department of Family Medicine
jsmaier@pitt.edu

Peter Drain, PhD
Department of Cell Biology
drain@pitt.edu

Course Description

The skills of reading biomedical literature, interpreting data, and evaluating clinical studies are the focus of this course, integrating themes of clinical expertise and scientific reasoning.  Students learn basic statistical methods and  how clinical trials, medical databases, and translational medicine are foundations of evidence-based medicine and patient-centered care. Together, the EDR1-3 course suite ensures a progressive build in student knowledge, and reinforces past skills learned as students progress through the course sequence.

USMLE Step 1 Content Area: Biostatistics, Study design & interpretation, Interpretation and use of evidence-based data and recommendations in clinical decision-making

Course Objectives

EDR1​

  1. Describe and identify potential study designs and research questions across observational, clinical, and translational research contexts, and their associated benefits, limitations, and ethical implications
  2. Summarize statistical testing foundational concepts such as statistical significance, descriptive and inferential statistics, and hypothesis testing and criteria for choosing a specific statistical test as applied to clinical and translational research
  3. Identify bias and confounding as applied to the evaluation of clinical and translation research including sources and types of bias and ways to limit and assess the validity of conclusions for populations and patients
  4. Calculate, report, and interpret study outcomes including odds ratios, relative risk, absolute risk reduction and NNT/H as they apply to statistical and clinical significance and patient centered decision making
  5. Correctly interpret survival data including curves and hazard ratios and apply findings to clinical prognostic reasoning and patient-centered decision-making
  6. Define components of randomized controlled trial implementation and ethical considerations with specific attention to ethics, informed consent, equipoise, sampling, allocation, blinding, outcome selection as well as recognize issues that can arise during analysis and methods of analysis in clinical research
  7. Calculate diagnostic test characteristics and apply to clinical decisions in proposed cases to support understanding of evidence-based clinical decision making
  8. Interpret systematic reviews and interpret and calculate cost analysis data including common components such as cost-effectiveness ratio, incremental cost-effectiveness, and utility factors, and connect findings to translational research priorities, patient care, and health policy decision-making

EDR2

  1. Design and describe a mentored research project
  2. Write a research proposal for a focused research project
  3. Demonstrate understanding of ethical principles, federal regulations and best practices for protecting human subjects in research and identify the ethical safeguards governing each stage of trial conduct, including informed consent, equipoise, and IRB oversight
  4. Engage in self-directed learning and meta-cognition in research and medicine

EDR3

  1. Critique the medical literature and relate it to a patient. Analyze and evaluate biomedical research article – background, hypothesis, study design, results, statistics, key information, validity of conclusions in the setting of the patient
  2. Identify and correct inaccuracies of Large Language Model (LLM) assessments of the research article appraised. Provide evidence and reasoning from primary literature for the corrections
  3. Describe the conceptual landscape of artificial intelligence in clinical care
  4. Analyze the cognitive risks of over-reliance on AI during medical training and articulate strategies for building and protecting those skills in an AI-rich environment
  5. Explain the phenomenon of automation bias and describe the mechanisms by which embedded AI tools can subtly alter reasoning and decision-making

Educational Methods​

  • Small group workshops
  • Self-study
  • EDR1: Weekly quizzes
  • EDR2&3: Listening and providing feedback to peers; Presentations

Assessment

EDR1: Assessment for this course is based on a cumulative score of weekly quizzes.

EDR2&3: Assessment includes active participation, presentations, research proposal (EDR2), and critical appraisals of medical literature (EDR3).

Requests for excused absences should be submitted via Elentra. Unexcused absences may result in grading penalties as outlined in the Policy on Absence and Attendance.