Can lead to unneeded testing and medications.Statistical Tests and Data Representation A rejection of a true null hypothesis Null hypothesis The null hypothesis (H0) states that there is no difference between the populations being studied (or put another way, there is no relationship between the variables being tested).Disclosure of Information in which a test result incorrectly indicates the presence of a condition when the condition is not truly present An error Error Refers to any act of commission (doing something wrong) or omission (failing to do something right) that exposes patients to potentially hazardous situations.Known as a type I error Error Refers to any act of commission (doing something wrong) or omission (failing to do something right) that exposes patients to potentially hazardous situations.An FP test result indicates that a person has the disease when they do not.The standard table is presented below (with screening Screening Preoperative Care test results on the left, true disease state on top, and “yes” answers before “no” answers).įalse Positives and False Negatives False positive It is important that the table is set up in a standard fashion in order for standard formulas to be applicable. To evaluate the epidemiologic value of a screening Screening Preoperative Care test, a table similar to that presented below can be used to determine the relative frequencies of individuals with different combinations of screening Screening Preoperative Care test results (positive or negative) and true disease state (truly have or do not have the disease). Screening Screening Preoperative Care for diseases for which early intervention has shown no benefitĬontingency tables used in evaluating screening Screening Preoperative Care testsĬontingency tables are commonly used in the statistical analysis of multiple variables.Adverse effects of the test: Is the test painful or otherwise damaging?.Frequency of overdiagnosis: How often does a test suggest a patient has a disease when in fact they do not?.The usefulness of screening Screening Preoperative Care tests requires assessment of: A positive screening Screening Preoperative Care test is followed up by another diagnostic test, which (ideally) can definitively verify the suspicion (e.g., a biopsy Biopsy Removal and pathologic examination of specimens from the living body.Screening Screening Preoperative Care tests don’t “prove” that a person has a disease, but only provide suspicion. Screening Screening Preoperative Care tests do not provide a definitive diagnosis: Measures of Health Status and mortality Mortality All deaths reported in a given population. Screening Screening Preoperative Care tests are used to identify people in the early stages of a disease and enable early intervention with the goal of reducing morbidity Morbidity The proportion of patients with a particular disease during a given year per given unit of population. Overview of Screening Tests Screening Screening Preoperative Care tests Basics of Probability of disease in the case of certain test results. There are several basic rules of probability that can be used to help determine the probability of multiple events happening together, separately, or sequentially. Alternatively, positive and negative predictive values help determine the probability Probability Probability is a mathematical tool used to study randomness and provide predictions about the likelihood of something happening. For example, a test with high sensitivity is useful as a screening Screening Preoperative Care test, whereas high specificity is required for an accurate diagnosis. Some of the most important epidemiological values of diagnostic tests include sensitivity and specificity, false positives and false negatives, positive and negative predictive values, likelihood ratios, and pre-test and post-test probabilities. Causality, Validity, and Reliability of the tests themselves can help turn the data into usable, applicable information. Certain statistical information about the accuracy and validity Validity Validity refers to how accurate a test or research finding is.
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