Odds and risk ratios are commonly used in medical practice to conduct different analyses of the patient’s health and identify new diseases. Both methods of analysis support each other, and in case of insignificant gaps in RR, OR can conduct additional testing to find solutions to the existing problems. Therefore, this paper will demonstrate the concepts’ definitions and the advantages or disadvantages they bring to the medical process.
It might be challenging to understand the real use of odds and risk ratios, and it is important to teach healthcare students to use these concepts correctly and understand them right. An odd ratio is mainly used to find the relationship between two events (Norton et el., 2018). The calculation is clearly seen in the connection between people allergic to specific products and the general amount of control over people who could potentially have the exposure.
The odds ratio can help to calculate the most realistic outcome of the patients’ treatment using specific formulas. Additionally, this type of estimation helps to find a correlation between risk factors and the possible conclusions in the clinical practice (Norton et el., 2018). Randomly chosen data allows for making the most realistic calculations to better understand the issues that occurred during the patient treatment or analyses of the blood tests.
The risk ratio has approximately the same purpose as the odds ratio, but the calculation method differs. According to Bakbergenuly et al. (2019), in this type of ratio, medical workers compare the results taken from a group of sick people and those who have never been diagnosed with a specific disease. For example, while treating people with cancer, experts analyze the level of exposure and can identify what factors influence the development of the problem and why some immune systems cannot cope with the external factors, but others can.
Risk ratio is important in the medical industry as in every sphere of life, risk prediction can help to mitigate problems and be prepared for different events. RR may allow to discover of the causes of many health problems by evaluating different conditions in patients. The changes in blood results or other testing operations of sick people compared to those who have never suffered from serious problems are the main indicators of RR processing. The concept is also used for the future progression of medicine.
The main comparison between odds and risk ratios is that both of the concepts are used in medical analyses, and the results retrieved from both processes can be used to treat specific health issues. Moreover, OR and RR significantly influence the future of medicine as the results of the analyses help identify more related symptoms to specific illnesses (Chowdhury et al., 2019). However, the risk ratio pays more attention to one group of patients which could be potentially exposed to specific health issues, while the odds ratio analyses two different groups without paying attention to exposure.
The advantages of the odds ratio are massive as it is easy to calculate using exinitic formulas and ensures that the number is accurate. Nevertheless, the method does not allow for estimating risks and finding the most common solution in the future (Chowdhury et al., 2019). Chowdhury et al. (2019) also stated that the advantage of risk ratio is related to the ability to define the appearance of a specific health event at the early stage of its development. However, to conduct these analyses, many people should participate in research to make the most realistic results for further improvements.
In conclusion, odds and risk ratios play a significant role in the medical sphere as they allow to make breakthroughs for the future improvement of the patient’s treatment. OR and RR support the operation of each other to achieve better results in the analyses of different events by filling the appealing gaps. Even though there are some disadvantages in the procedures of both concepts, the general idea brings more positive sides to the healthcare sector.
References
Bakbergenuly, I., Hoaglin, D. C., & Kulinskaya, E. (2019). Pitfalls of using the risk ratio in meta-analysis. Research Synthesis Methods, 10(3), 398-419. Web.
Chowdhury, S., Tiwari, R. C., & Ghosh, S. (2019). Non-inferiority testing for risk ratio, odds ratio and number needed to treat in three-arm trial. Computational Statistics & Data Analysis, 132, 70-83. Web.
Norton, E. C., Dowd, B. E., & Maciejewski, M. L. (2018). Odds ratios – current best practice and use. JAMA Network, 320(1), 84-85. Web.