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Shawn Chen and Mary Ferrill

Week 1 - Learn the most common statistical tests used in medical literature. Week 2 - Be able to define, calculate, interpret, and describe the appropriate use of number needed to treat (NNT) and number needed to harm (NNH) in clinical trials. Week 3 - List the potential outcomes for a noninferiority compared to a superiority study. Week 4 - Describe the purpose of clinical practice guidelines with regards to how it should be used in clinical practice. Week 5 - Explore the process of PICO structure in a clinical trial. Week 6 - Learn the principles of Evidence-Based Medicine(EBM) in clinical settings. Most FutureLearn courses run multiple times. Every run of a course has a set start date but you can join it and work through it after it starts. Find out more This course is for professionals or students looking to build their clinical pharmacokinetic knowledge. You might be an undergraduate pharmacy student, a postgraduate pharmacy student or a pharmacist in clinical practice.

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Week 1 - Learn the most common statistical tests used in medical literature. Week 2 - Be able to define, calculate, interpret, and describe the appropriate use of number needed to treat (NNT) and number needed to harm (NNH) in clinical trials. Week 3 - List the potential outcomes for a noninferiority compared to a superiority study. Week 4 - Describe the purpose of clinical practice guidelines with regards to how it should be used in clinical practice. Week 5 - Explore the process of PICO structure in a clinical trial. Week 6 - Learn the principles of Evidence-Based Medicine(EBM) in clinical settings. Most FutureLearn courses run multiple times. Every run of a course has a set start date but you can join it and work through it after it starts. Find out more This course is for professionals or students looking to build their clinical pharmacokinetic knowledge. You might be an undergraduate pharmacy student, a postgraduate pharmacy student or a pharmacist in clinical practice.

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    Reviews summary

    Clinical pharmacy ebm: practical & clear

    According to students, this course is a largely positive resource for pharmacists and pharmacy students seeking to apply Evidence-Based Medicine in clinical settings. Learners consistently highlight the practical relevance and its ability to enhance understanding of medical literature. The lectures are praised for their clarity in explaining complex statistical concepts like NNT/NNH and PICO structure. While many find the course well-structured and paced for professionals, some undergraduate students found the statistical sections rushed and felt it assumed too much prior knowledge, suggesting it's better for those with some EBM foundation. Additionally, a few reviews noted that some case studies or cited literature seemed slightly dated, although the core principles remain sound.
    Good introduction, but some content may need updating.
    "It's a good introduction, but don't expect deep dives."
    "My only feedback is that some of the case studies felt slightly dated, but the principles remain sound."
    "Decent course, but it could use an update. Some of the examples and literature cited seemed a bit old."
    "I was hoping for more advanced content, as some parts felt superficial."
    Better suited for those with some EBM exposure or professionals.
    "I think it's better suited for undergraduates or those completely new to EBM. As a pharmacist with some prior EBM exposure, I was hoping for more advanced content."
    "I struggled to keep up with the pace, especially with the more advanced statistical tests. It felt more geared towards seasoned professionals."
    "My only minor critique is sometimes the pacing felt a bit fast in the stats section if you're not already familiar."
    "I found this invaluable. Highly recommend it for anyone in clinical pharmacy, whether student or professional."
    Generally well-structured with a good learning pace.
    "The course is well-structured and moves at a good pace."
    "I found it highly relevant for my upcoming clinical rotations. The quizzes were also good for reinforcing learning."
    "The course material is generally high quality."
    Complex EBM statistical concepts are clearly explained.
    "The modules on NNT/NNH and PICO were particularly insightful, offering clear explanations..."
    "The content on statistical tests was broken down perfectly, making complex concepts much easier to grasp."
    "The way they explained NNT/NNH was incredibly clear, and I can now confidently interpret these values in research."
    "I found the content on noninferiority studies particularly well-explained."
    Highly applicable for practicing pharmacists and students.
    "This course was largely practical and highly relevant for a practicing pharmacist."
    "It definitely enhanced my understanding of how to critically appraise medical literature."
    "Absolutely essential for any clinical pharmacist! ... It definitely helps you navigate the vast medical literature more effectively."
    "I learned how to apply these concepts in daily clinical practice."

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    Learners who complete Evidence-Based Medicine in Clinical Pharmacy Practice will develop knowledge and skills that may be useful to these careers:

    Reading list

    We haven't picked any books for this reading list yet.
    A classic introductory text that provides a practical, step-by-step approach to practicing and teaching evidence-based medicine. It is concise and emphasizes direct clinical application, making it ideal for busy clinicians and students. is commonly used as a core textbook in EBM courses and is excellent for gaining a broad understanding.
    Provides a foundation in clinical epidemiology, which is the science of studying the distribution and determinants of health-related states or events (including disease), and the application of this science to the prevention and treatment of disease.
    Provides a comprehensive overview of statistical methods used in medical research.
    This comprehensive and authoritative guide to understanding and applying evidence-based medicine. It provides detailed methods for critically appraising medical literature across various study designs. Widely considered a foundational text and valuable reference tool for students and professionals seeking to deepen their understanding of EBM principles and practice.
    Is an excellent starting point for anyone new to evidence-based medicine. It clearly explains how to critically appraise published research papers and understand different study designs. It is highly accessible and widely recommended for high school students, undergraduates, and those needing foundational critical appraisal skills.
    Aimed at helping readers understand and critically evaluate clinical research papers, this book covers various study designs and statistical concepts in a relatively accessible manner. It is useful for students and professionals who want to improve their skills in reading and interpreting medical literature.
    Provides a broad introduction to health informatics, a field increasingly intertwined with evidence-based medicine. It covers topics such as electronic health records, data science, and clinical decision support systems. It is relevant for understanding the technological infrastructure and data handling aspects of contemporary healthcare and EBM.
    Focusing on epidemiological principles within a public health context, this book helps build foundational knowledge necessary for understanding population-level health data and research. It is relevant for those interested in applying EBM principles to public health issues and interpreting studies in this area.
    An essential guide for anyone involved in planning or conducting clinical research. While focused on generating evidence rather than solely using it, understanding research design is crucial for critical appraisal in EBM. provides detailed information on various study designs and methodologies.
    Provides in-depth coverage of the design, conduct, and analysis of randomized controlled trials (RCTs), a cornerstone of evidence in many areas of medicine. It is valuable for researchers and those who need a deep understanding of how high-quality evidence is generated from clinical trials.
    Introduces statistical concepts and methods relevant to understanding and applying evidence in practice and evaluating outcomes. It helps build the necessary statistical literacy to critically appraise the quantitative data presented in research studies. Useful for students and practitioners needing to strengthen their statistical foundation for EBM.
    A practical guide for conducting meta-analyses using the statistical software R. It covers essential steps and more advanced topics, making it highly relevant for researchers and graduate students actively involved in performing systematic reviews and meta-analyses. Requires some familiarity with R programming.
    Provides a comprehensive introduction to the concepts and statistical methods of meta-analysis. It explains the principles behind combining results from multiple studies to synthesize evidence. Useful for those wanting a thorough understanding of the methodology of meta-analysis, a key tool in EBM.
    Offers a critical examination of the pharmaceutical industry and its impact on medical research and the evidence base. It highlights issues of transparency, bias, and the challenges in obtaining reliable evidence. It's relevant for understanding contemporary issues in EBM and fostering a critical perspective on evidence generation.
    Provides a concise introduction to the basic principles of evidence-based medicine, including critical appraisal, biostatistics, and epidemiology. It is geared towards new learners and those seeking a fundamental understanding of EBM without extensive prior knowledge. A good resource for gaining a broad understanding at an introductory level.
    A comprehensive and advanced textbook on Bayesian statistical methods. While not exclusively focused on EBM, Bayesian approaches are increasingly used in medical research and analysis that contribute to the evidence base. is suitable for those with a strong statistical background looking to understand advanced methods relevant to contemporary evidence generation.
    Covers the fundamentals of biostatistics, including descriptive statistics, probability, inferential statistics, and regression analysis. It is written in a clear and concise style, making it an excellent choice for students and researchers who are new to the field.

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