Healthcare Epidemiology Designs and Bias Effects

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Table of Contents

Introduction
Background Content
Conclusion
Reference List

Introduction

Healthcare is the prevention and cure of diseases through specialized doctors in the sector of medical insurance. It is an important activity to our bodies due to changes and consistent environs surrounding us. Heredity factors, environmental factors, and physical behaviors change the normal function of our body resulting in the incorrect function of the immune system. Epidemiology status was examined every time, to protect several people from infections (Hebel & McCarter, 2006).

Background Content

Epidemiology

This is the study of how regularly diseases occur in diverse groups of people and how some peoples get definite diseases. Clinical healthcare concentrated on our adaptations since many diseases were not haphazardly distributed all through the population (Gordis, 2000).

An epidemiologist examines individual patients and collects their data to compute the level of their disease through physical examination hence providing assumption statements for the distinct diagnosis. Every person was vulnerable to diseases due to the environment around them, physical behaviors, and heredity factors (Dodson & Hammar, 2005).

Epidemiologists help many especially when there was an outbreak of the disease in a certain group of people and termed to cause more problems when they were not treated. They provided the best solution on how faster the outbreak could be prevented and controlled (Rothman, 2002).

Food-borne illness and cancer were problems facing several people in those communities, threatening their life. They were known as complicated diseases to ordinary people expecting a specialist to examine and give them correct measures. The two diseases were examples of epidemiology diseases, general on the population of that time. Epidemiology played a bigger role in the community through intervention, development, and evaluation of the health problems surrounding various communities facing many peoples (Stuck & Belkin, 2001).

Characteristics of Epidemiology designs

The use of cohort or case studies helps the epidemiologist to take data and evaluate the normal working of a human body. The cohort was advantageous since it was good for rare exposures. It establishes numerous outcomes of a person and demonstrates temporal relationships within a group of people in a certain community. Meanwhile, a case study was used widely in this evaluation to determine the cause of these diseases. Drugs were a major problem for pregnant women and they had caused birth defects in infant babies (Lash & Rothman, 2008).

Most pregnant women were studied using a study design case. This study follows certain behaviors of women who were pregnant and associated with drugs giving out data analysis results. It compares their daily behaviors directed to their offspring, giving out some heredity factors used in their results presentation. On other hand, Risk ratio analysis was used for the comparison of moral values. The case-control design was taken randomly to women with infant children to determine their cardiovascular behaviors. The analysis showed confidence in cardiovascular behavior and folic antagonist exposure of 95% (Penq & Dominicia, 2008).

Biases

This is an epidemiological mistake that results in wrong estimations on exposure and risk of diseases. It appeared naturally to human beings but it was easy to prevent it through positive emotions. An epidemiological research person should have prevented and controlled his bias attitude using an accurate replication method. General, Selection, and Observation bias were major results of Bias (Morris, 2004).

In selection bias, it was completely expelled out when a case study was used. When both cases and control subjects were used, a bigger difference was determined. Moreover, observation bias was commonly used as bias systems case study. In addition, Confounding was characterized as a third major group of biases that categorizes compound interrelationships in various exposures and diseases (Aschengrau & Seage, 2007).

Bias was caused by logical variation as compared to random variation. Most of this bias was minimized and eliminated with a special type of design for a better resume of human health. Underestimation size and mask variation of spurious defects were results of bias on an epidemiology patient who was in a position of losing his internal validity (Woodward, 2004).

Conclusion

All in all, epidemiology played a bigger role in many different groups of people, realizing their health status through medical check-up. Epidemiologists use various techniques and ways to examine their patients affected and through their observations, they provide precise reports and preventive measures. It was highly advisable as a member of the epidemiologist family, to do away with biased emotions to have a precise report and correct measures, during case study research.

Reference List

Aschengrau, A. and Seage, G. (2007). Essentials of Epidemiology in public health, second edition. New York: Jones & Bartlett Publishers.

Dodson, R. and Hammar, S. (2005). Asbestos: Risk assessment, Epidemiology and Health effects. London: CRC Press.

Gordis, L. (2000). Epidemiology: with student consult online access. New York: Saunders publishers.

Hebel, R. and McCarter, J. (2006). Study guide to Epidemiology and Biostatistics. New York: Jones & Bartlett Publishers.

Lash, T. and Rothman, K. (2008). Modern Epidemiology. United Kingdom: Lippincott Williams & Wilkins publisher.

Morris, M. (2004). Network Epidemiology: a handbook for survey, design and data collection. London: Oxford University Press.

Penq, R. and Dominicia, F. (2008). Statistics methods for environmental Epidemiology with R: a case study in Air pollution and Health. New York: Springer publisher.

Rothman, K. (2002). Epidemiology: an introduction. London: Oxford University Press.

Stuck, B. and Belkin, M. (2001). Laser and noncoherent light ocular effects: Epidemiology, Prevention and Treatment. New York: SPIE-International Society for Optical Engine Publisher.

Woodward, M. (2004). Epidemiology: Study design and Data analysis, second edition. London: Chapman and Hall/CRC publisher.

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