Advanced Medical Clinical Research Certificate
Our Advanced Medical Clinical Research Certificate program offers a comprehensive and advanced curriculum designed for continuing education, professionals, and graduate students in the healthcare field. Throughout the program, participants will gain the following benefits and experience a significant increase in their knowledge. Advanced Research Skills: Participants will acquire advanced concepts and skills related to research study designs and evidence-based healthcare. They will learn to design appropriate studies, manage bias, and assess the quality of published research. Additionally, students will develop expertise in data collection, analysis, and the application of statistical tests. Proficiency in Biostatistics: The program provides a thorough introduction to probability and statistics, with a focus on clinical and translational research. Students will learn to summarize and analyze data, understand probability concepts, and apply hypothesis testing. This proficiency in biostatistics will enable participants to conduct robust medical research. Evidence-Based Medicine (EBM) Knowledge: Participants will receive rigorous training in the principles of evidence based medicine. They will learn to frame answerable clinical questions and find the best evidence to guide clinical decisions. The program covers various categories of clinical questions and the appropriate use of evidence to inform patient care. Health Care Data Analytics: The program also includes foundational training in health care data analytics.Participants will learn to create, structure, and analyze clinical datasets, patient-generated health data, and digital medical records. This skillset will enable students to contribute effectively to healthcare organizations and improve healthcare delivery.
Upon completion of the Advanced Medical Clinical Research Certificate program, participants will be well-equipped to conduct high-quality medical research, make evidence-based decisions in clinical practice, and contribute significantly to the advancement of healthcare and patient outcomes.
MODULE 1: STUDY DESIGN
This module will introduce advanced concepts and skills of research study designs, emphasizing how they relate to evidence-based health care. Students will design the most appropriate study to address a clinical question and generate the best evidence. They will acquire skills including managing bias and assessing quality of published research, designing research protocol, data collection and analysis, in order to include appropriate statistical tests.Topics covered during the curriculum include epidemiology, biostatistics, statistical programming and study design, as well as research ethics, scientific communication and clinical trials.
MODULE 2: BIOSTATISTICS
This module is an introduction to the basic concepts and methods of probability and statistics designed specifically for clinical and translational research scientists. The module will cover the fundamentals of statistical inference:summarizing and visualizing data, probability, normal and binomial distribution, sampling, central limit theorem, confidence intervals, and hypothesis testing. Topics include numerical and graphical summaries of data, basic probability concepts, sampling distributions, basic concepts for estimation, estimation for population means and proportions, basic concepts for hypothesis testing, hypothesis tests for population means and proportions, analysis of variance, power and sample size calculations, simple linear regression, multivariable linear regression, additional regression techniques, chi-square distribution and analysis of frequencies, statistical evaluation of diagnostic tests, survival analysis, and nonparametric and distribution-free statistics.
MODULE 3: EVIDENCE BASED MEDICINE
This module provides a rigorous introduction to the principles of evidence-based medicine (EBM), which is the practice of medicine and patient care that is based on the best available research evidence to guide clinical decisions and is applicable to the individual patient. The module will begin with an overview of how to frame an answerable clinical question and then it will shift towards how to find the best evidence to answer it. The major categories of questions that arise in clinical practice, including treatment, diagnosis, harm (etiology), and prognosis will be covered, with instruction on what the best type of evidence is to answer these questions and how to apply it to a given patient. Topics include Epidemiology, Biostatistics, Research Methods, Preventive Medicine, and Public Health in relation to Evidence-based Medicine and clinical decision making. As well as summarizing evidence (e.g.,through systematic reviews and meta-analysis), putting evidence into practice (e.g., implementing clinical practice guidelines), and the limitations of the EBM approach.
MODULE 4: DATA ANALYTICS
This module will provide foundational skills and knowledge in health care data analytics that will equip students to contribute more effectively to local data analytics and performance improvement efforts. It will explore the role of analysts and analytics in healthcare organizations, building on the creation, structure and maintenance of clinical datasets, patient generated health data, and elements of the digital medical record, while embracing team-based approaches to solving complex issues in the healthcare delivery system. Topics will include Quality Improvement, Health Care Data as an Organizational Asset, Data Analytics Tools and Techniques, and Using Data to Solve Problems. Overall, the module will generate, aggregate, and analyze data relevant to the optimal delivery of healthcare and maintenance of health.