Clinical Epidemiology made really, really simple.
ClinEpi Review is an introductory level course on clinical epidemiology that explains the most commonly encountered terms and concepts in health research and evidence-based medicine. This course was designed for all healthcare professionals seeking to better understand health research and practice evidence-based medicine. ClinEpi Review consists of 16 videos on a variety of topics each ranging from 3 to 13 minutes in duration for a total duration of just under 2 hours and 20 minutes and includes a downloadable workbook and answer key based on the content of the videos.
Access to course materials is granted for a period of 6 months from the time of purchase and requires you to be logged into the beem.ca website.
|00||Introduction (FREE)||2:41||Welcome and Introduction to the series.|
|01||Definitions||6:30||An explanation of cohorts, prevalence & incidence and how to calculate the latter two.|
|02||Variables||5:15||An explanation of independent, dependent & confounding variables and how they relate to one another.|
|03||Observational Studies||8:59||An explanation of the features, strengths and limitations of the following observational study designs: case & case series studies, cross-sectional study, ecologic study, cohort study, & case-control study.|
|04||Randomized Controlled Trials||11:07||An explanation of the features, strengths & variations (parallel, cross-over, cluster, factorial) of RCTs as well as some of the commonly associated biases. Also, an explanation of methods of data analysis, missing data and the CONSORT Statement.|
|05||Two by Two Tables||2:59||An explanation of the two by two table, the foundation on which many calculations in clinical epidemiology are performed including but not limited to relative risk, absolute risk reduction (& increase), relative risk reduction, number needed to treat (& harm), predictive value, sensitivity & specificity.|
|06||All About Risk||7:17||An explanation of risk, event rate, absolute risk reduction (& increase), number needed to treat (& harm) & relative risk reduction as well as how to calculate each.|
|07||Risk & Odds||10:30||An explanation of risk & odds, specifically relative risk (risk ratio) and odds ratio, how to calculate each, and their differences.|
|08||Predictive Values, Sensitivity and Specificity||8:43||An explanation of positive predictive value, negative predictive value, sensitivity & specificity, their strengths, weaknesses, similarities, differences, clinical applications & how they are each calculated.|
|09||ROC Curves||6:09||An explanation of the Receiver Operating Characteristic (ROC) Curve and how it relates to sensitivity & specificity.|
|10||Likelihood Ratios||11:35||An explanation of likelihood ratios as diagnostic performance measures, their relationship to sensitivity & specificity and how each is calculated.|
|11||Data & Distribution||9:50||An explanation of categorical & quantitative data, data distribution, central tendency (mean, median, mode) range and variability (standard deviation & interquartile range).|
|12||Hypothesis Testing and Errors||9:13||An explanation of null and alternate hypotheses, P-value, alpha, beta, type I & II errors & power and how each is related to the others.|
|13||Point Estimates & Confidence Intervals||6:15||An explanation of point estimates, interval estimates, confidence interval, confidence level, precision and how they relate to each other.|
|14||Which Test to Use||10:34||An explanation of parametric and nonparametric statistics, some of the more commonly used biostatistical tests (Chi-square test, McNemar’s test, Student’s T-test, Mann-Whitney U-test, analysis of variance [ANOVA], Kruskall-Wallis, linear regression, Spearman rank correlation), the parameters of each & examples of when each is typically applied.|
|15||Systematic Reviews||12:54||An explanation of systematic & non-systematic reviews, their differences as well as biases associated with the former.|
|16||Meta-analyses||9:46||An explanation of meta-analyses, how they relate to systematic reviews & heterogeneity in the pooling of results of meta-analyses.|