Why Biostatistics is important in Healthcare and Pharmaceutical Industry?
Do you ever come across the term “Biostatistics” before? I guess maximum will tell yes and minimum will tell no. Or maybe maximum will tell no and minimum will tell yes. Relax, I will leave it to you.
Biostatistics is a branch of statistics which deals with the data related to medical science, public health, medical research, epidemiology and so on. In simpler words, when we apply statistics in biological science – it is called biostatistics.
Let’s discuss a few scenarios like
- A local PHC wants to know the proportion of people affected by an outbreak of certain disease and to find out the causes behind it and to prevent further circumstances.
- During a clinical trial, there are many phases for drug or device development and now the question is “How will they know whether the trial is going good or bad?”
- In a pharmaceutical company, they want to know the dissolution rate of a particular tablet and to know whether it satisfies the desired rate or not. Similarly, they want to know the mean weight of a tablet and to compare with other batches. Now, our question is “How will they do the analysis?”
In the above-mentioned scenarios, we apply biostatistics concepts and do the analysis. Based on the analysis results, we draw inference about the given problem. So basically, biostatistics is a method that comprises of a collection of data, summarizing, analyzing and drawing inferences.
By now, you might get the overall outlook of biostatistics application in the healthcare sector.
We will discuss a few basic concepts of Biostatistics.
- Data is the first thing which pops out on the head when we talk about any kind of analysis. Since we are dealing with data for analysis, we should know the basic concepts of it. Data are the actual pieces of information that we collect through our process or experiment. It can be categorized into categorical and numerical data. Categorical data are defined in categories or groups. For e.g. male or female, yes or no, etc. Numerical data are further classified into discrete and continuous data. Discrete data are the data which take certain values. For e.g. no of patients, devices, etc. Continuous data are the data which can take any values either fractional or decimal. For e.g. blood pressure level, height and weight of the patient, etc.
- Sampling is a method used in statistical analysis of a data where a specific number of samples are taken from a population for a study. For e.g. health ministry wants to know the opinion or suggestions of recently implemented health programme in Karnataka. Here the population – Karnataka and sample – Bangalore, Mysore, Mangalore, Hubli, etc.
- Hypothesis testing is a method to determine whether the results are statistically significant or not. In simpler words, the process of drawing inferences (making decisions) about the sample with regards to the population as a whole is known as hypothesis testing.
- Measurement system analysis helps us to detect the amount of variation exists within a measurement system. Suppose during the initial clinical trial phase of a particular medicine, “If the data are not taken properly?” And move forward for further analysis. Then “What would be consequences of it?” Obviously, it may fail later on final phases.
Now, I would like to mention the final overview of biostatistics applications in healthcare. It helps to a great extent during the clinical trials by designing the trial, sampling techniques, measurement system analysis and analyzing for appropriate results. We can improve our health policies, new drug policy, assessment of environmental protection guidelines, quality improvement in hospitals and pharmaceuticals, and so forth.