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Clinical epidemiology is a critical field of study in contemporary health care. It is a discipline of predicting the health outcomes of patients with a particular condition by considering the outcomes in groups of similar persons (Fletcher & Fletcher, 2021). Therefore, epidemiological studies directly impact the diagnosis, prognosis, and clinical treatment by presenting medical practitioners with relevant data on the course, presentation, and treatment of an illness.
Epidemiological studies can inform the prognosis or the predictions of how a disease will develop in an individual under different conditions. According to Fletcher and Fletcher (2021), prognosis accounts for the natural history of the disease, with no recorded medical intervention and its clinical course, with medical care being provided. Thus, studies on disease progress allow practitioners to make more informed clinical choices. For example, a Dutch study on the risk of pregnancy complications in women with Type I diabetes revealed that good blood sugar control is not sufficient in preventing the development of various issues (Fletcher & Fletcher, 2021). Therefore, additional treatment is needed to prevent associated developmental diseases and infant death. Similarly, data on how COVID-19 progresses in individuals can inform clinicians on how to address a novel disease in vulnerable populations (Liu et al., 2021). Thus, prognostic epidemiological studies identify prognostic and risk factors that allow measuring the clinical outcomes for individual patients.
Diagnosis is the method of identifying the disease by examining various clinical symptoms. It is a challenging process as many clinical presentations exhibited by patients and test results may indicate different illnesses. Epidemiological studies are crucial as they provide more in-depth data that help medical practitioners make the diagnosis. Thus, a study on vertebral disc abnormalities showed that they are common and may not cause discomfort in patients complaining of lower back pain (Fletcher & Fletcher, 2021). Meanwhile, a study conducted in India proposes a machine learning method that accurately diagnoses dementia in older adults (Bhagyashree et al., 2018). Furthermore, epidemiological studies offer data on treating the diagnosed conditions with the known clinical course. For example, research on cardiovascular disease in individuals diagnosed with insulin-dependent diabetes indicates that blood sugar control is ineffective in preventing various heart conditions from development (Fletcher & Fletcher, 2021). Therefore, other factors need to be addressed in groups of similar patients. In summary, epidemiological research is essential as it informs medical professionals and provides them with more data on the prognosis, diagnosis, and treatment procedures.
References
Bhagyashree, S. I. R., Nagaraj, K., Prince, M., Fall, C. H., & Krishna, M. (2018). Diagnosis of Dementia by Machine learning methods in Epidemiological studies: a pilot exploratory study from south India. Social psychiatry and psychiatric epidemiology, 53(1), 77–86.
Fletcher, G., & Fletcher, R. (2021). Clinical epidemiology: The essentials (6th ed.). Lippincott Williams & Wilkins.
Liu, X., Zhu, L., Lu, T., Liu, X., Jiao, D., Tang, X., Chen, J., Chen, Y., Yu, W., & Chen, Q. (2021). Epidemiologic characteristics of and prognostic factors for COVID-19 among hospitalized patients: Updated implications from Hubei province, China.Frontiers in Public Health, 9, 1–10. Web.
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