Pharmacoepidemiology: Types of Errors and Bias

Running Head: PHARMACOEPIDEMIOLOGY
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Pharmacoepidemiology
Student Details

PHARMACOEPIDEMIOLOGY 1
Table of Contents
Introduction................................................................................................................................1
Random errors........................................................................................................................1
Systematic errors....................................................................................................................2
Confounding...........................................................................................................................5
Conclusion..................................................................................................................................5
References..................................................................................................................................6

PHARMACOEPIDEMIOLOGY 2
Introduction
Pharmaco-epidemiology is the combined study of pharmacology and epidemiology.
Pharmacology is the study of effects of a drug in a population and epidemiology is basically
the study of factors that associated with the disease (Montastruc et al. 2015). There are
various errors encountered in pharmaco-epidemiological studies. These errors will be
discussed in this report.
Pharmaco-epidemiology
Pahrmaco-epidemiology is defined as the study of utilization and side effects of a drug in a
large population. It helps to estimate the probability of favorable effects of the drugs. It
concentrates on the outcome of clinical patient form therapeutics. Pharmacovigilance is the
part of pharmaco-epidemiology which involves monitoring of unwanted effects and the
safety concerns arise due to the use of a particular drug in a population (Pharma IQ, 2018).
Common errors
There are two types of errors can be occurred in pharmacoepidemiology
1. Random errors
2. Differential errors
Random errors
These types of errors occur when invalid outcome measures are used that misclassifies the
cases and control. Random errors are basically a divergence because of chance alone, of the
sample observation from a real value of a population. This results in lack of precision in the
measurement of association. Random errors can be a result of sampling errors, biological
variation, and measurement errors. The effects of random errors can produce such estimations