Epidemiology Paper – Analysis and Application

Epidemiology Paper – Analysis and Application

  1. Identify an existing at-risk population. Using aggregated statistics, include identified criteria and data that substantiates why this population is at risk.
  2. Using analyzed population data, identify a health risk within this population that nursing science can impact. Describe the specific variables. Provide SPSS data that correlates population to the identified health risk.
  3. Identify potential obstacles that may hinder the implementation of the prevention and health promotion activities.
  4. Identify stakeholders, individuals, and agencies with whom you may need to collaborate.

Descriptive Epidemiology

According to Naito (2014), “descriptive epidemiology is the epidemiological studies with much of the activities being in the descriptive component rather than the analytical component”. From the analytical epidemiology prospective, descriptive epidemiology deals with the reporting and identification of patterns and frequency of disease process in a population. In descriptive epidemiology, “the focus is on the occurrence of the diseases which is described through temporal trends and geographical comparisons” (Cassone & Mody, 2015). Descriptive epidemiology is therefore at the realm of evidence-based pyramid, they dictate an influence that is strong in the approach of epidemiology. Prevalence and incidence data of disease are relevant in today’s healthcare setting and research. Epidemiology Paper – Analysis and Application

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Relationship of Descriptive Epidemiology in Nursing Science

Unarguably, descriptive epidemiology centers on distribution and frequency of the health-related exposure or health outcome. “The analysis of who is affected by health outcome and how common it is showing prevalence as well as incidence” (Kim & Hooper, 2014). Person, place, and time can describe the aspect of people affected. An example in the explanation of the description of the distribution of health outcome with elements such as geography, population and time. “These aspects are crucial in nursing science as they provide a guideline which will be employed in the provision of quality care to outcome” (Montoya, Cassone & Mody, 2016). Subsequently, better understanding of disease severity is increased which enhance the development of prevention and management strategies. Whenever there is an improvement in healthcare outcome, the process that allows understanding of the changes that resulted in attaining the improvement is made possible through descriptive epidemiology.

Role of Descriptive Epidemiology in Nursing Science

Health data source and disease surveillance system are used to gather information when monitoring disease and health trends, and they are organized in such a way that enables the data to be systematically analyzed by descriptive epidemiology. Thus, the discrepancies in the frequency of the disease can be better understood over a given time (Fazel, Geddes & Kushel, 2014). Moreover, better understanding of disease variation of individuals in the basis of personal traits such as place and time is made possible thereby making the process of planning resources to address healthcare issues of the population easier. “The hypothesis that are used in making of the determinants about health and diseases are generated from the descriptive epidemiology” (Karimi et al., 2014). Most importantly, generating hypothesis is an initial step in starting analytic epidemiology which depends on the testing of the association between disease and health. Descriptive epidemiology has other specific functions such as priority establishment of possible health in a given population and its role is fundamental in identifying any emerging health problem and setting an alarm for possible outbreak. “The reporting and monitoring of health status and other traits in a population is possible by descriptive technology” (Naito, 2014). To determine the effectiveness of any intervention, descriptive epidemiology must be utilized. Suffice to say that descriptive epidemiology provides detail description of individuals affected by disease with all factors surrounding the individual. Through the analysis of descriptive data, causative factors of a disease could be derived. Therefore, both systems can be useful to explain the progression of risk factors and reduction of disease incidence. “More importantly, these factors are important in understanding the circumstances and factors that might require public health improvement” (Montoya, Cassone & Mody, 2016). Epidemiology Paper – Analysis and Application

Application of Descriptive Epidemiology in Public Health Nursing

As a science of public health, epidemiology has procedures which promotes accuracy and validity in drawing of a conclusion. “The results from epidemiology can prompt effective measures such as the declaration of formal emergency, legislative action, urgent legal action and large-scale quarantine” (Kim & Hooper, 2014). Notable organizations such as CDC and WHO are well positioned in their roles and methods due to the far- reaching impact from epidemiology results. Epidemiology methodologies proficiency and efficiency are often needed for DNP students to enhance their ability to work in healthcare settings in case there is disease outbreaks.

Public health nursing therefore focuses on individuals affected by factors such as genetic, lifestyle, and environment in a community and the goal of public health nursing is to prevent disease and improve health care outcomes. Besides this, they provide more direct care such as screening services, preventive care and health education (Fazel, Geddes & Kushel, 2014). While working in such an environment, they are expected to recognize and respond to healthcare crisis, hence the need for epidemiology knowledge.

Example of Descriptive Epidemiology in Public Health Nursing

Breastfeeding practices is widely known to improve baby’s health and bonding with their mothers. A study can therefore be conducted on the significance of breastfeeding in children with emphasis on socioeconomic status, educational level, ethnicity, mother’s age, marital status, and geographical locations. The relevant information gathered from this study can be used to identify what is needed in that population to enhance the concept. For example, length of breastfeeding and frequency with different race and socioeconomic status to develop a comprehensive analysis and strategies that can be used to booster breastfeeding practices.

Components of Epidemiology Used to Analyze At-Risk Populations

Health issues or disease is a measure of the frequency of disease when compared to population at risk at a time. “Numerators and denominators are two important components highlighted in the analysis of population at risk” (Karimi et al., 2014). The formal represents in a mathematical term the upper section of the fraction otherwise called the epidemiology and it is an indication of what has been counted for example, the amount of people affected by a specific disease while the latter represents lower portion of the fraction and populations derived which is the composition of the entire population that if affected by the disease were to be included in the numerator. “This is what is referred to as the population at risk as it is all those people who are free of the disease during the collection of data” (Montoya, Cassone & Mody, 2016). The calculated risk occurs when there is the inclusion of people who were not in the position of developing the disease of interest is underestimated.

Incidence and prevalence give rise to the frequency of the diseases affecting the population of interest. “Incidence is expressed in the person-time unit and measures the new cases of disease while prevalence is expressed as a population and measures the existing cases of the disease” (Fazel, Geddes & Kushel, 2014). According to Kim & Hooper 2014, the prevalence is measure by noting the proportion of people affected by a disease or health-related event in a specified population at a given time. While the existing cases are measured using prevalence of the emerging cases of the disease in a given population at a specified time are measured as incidence.

There is ample evidence of the association between socioeconomic status (SES) and multiple disease outcomes (National Center for Health Statistics [NCHS], 2010). Lower socioeconomic status as reflected in poverty, minority status, and low education levels is consistently related to higher occurrence of a range of major diseases including cancer, heart disease, stroke, and diabetes, and to fair or poor health status (NCHS, 2010). “Low SES (individual poverty, income inequality, and area level poverty) was related over a 25-year period to mortality even when the causes of death changed over time” (Galea et al., 2011). Epidemiology Paper – Analysis and Application

Conclusion

In conclusion, disease risk factors are described with descriptive epidemiology using such factors as place, people, and time. Epidemiology studies is critical to the determination, influence, distribution, and frequency of disease in a given population. In a null shell, descriptive epidemiology describes not only time, place, and people but also how these factors are related to health issues or disease. When these factors are evaluated, a pattern that correspond the risks factor for a specific disease can be noted. Epidemiology data collected is used to furnish specific information necessary to influence public policy. It is therefore pertinent for the DNP to study epidemiology as they will be required at some point to undertake such roles in healthcare setting.

Socioeconomic status as a fundamental cause of health inequalities. It influences multiple disease outcomes, meaning that SES is not limited to only one or a few diseases or health problems but to many, SES affects these disease outcomes through multiple risk factors (currently things such as smoking, diet, exercise), it involves access (or lack of access) to resources that can be used to avoid risks or to minimize the consequences of disease once it occurs, and the association between a fundamental cause and health status is reproduced over time via the replacement of intervening predisposing factors (e.g., overcrowding and poor sanitation replaced by lifestyle choices and behaviors); that is, SES continues to influence health inequalities even when the susceptibilities to major morbidity and mortality change over time (Link & Phelan, 1995)

References

Cassone, M., & Mody, L. (2015). Colonization with multidrug-resistant organisms in nursing homes: scope, importance, and management. Current geriatrics reports4(1), 87-95.

Fazel, S., Geddes, J. R., & Kushel, M. (2014). The health of homeless people in high-income countries: descriptive epidemiology, health consequences, and clinical and policy recommendations. The Lancet384(9953), 1529-1540.

Galea, S., Tracy, M., Hoggatt, K. J., DiMaggio, C & Karpati, A (2011). Estimated deaths attributable to social factors in the United States. American Journal of Public Health, 101(8):1456–1465.

Karimi, P., Islami, F., Anandasabapathy, S., Freedman, N. D., & Kamangar, F. (2014). Gastric cancer: descriptive epidemiology, risk factors, screening, and prevention. Cancer Epidemiology and Prevention Biomarkers23(5), 700-713.

Kim, E. S., & Hooper, D. C. (2014). Clinical importance and epidemiology of quinolone resistance. Infection & chemotherapy46(4), 226-238.

Link, B. G & Phelan, J. C (1995). Social conditions as fundamental causes of disease. Journal of Health and Social Behavior, 35:80–94

Montoya, A., Cassone, M., & Mody, L. (2016). Infections in nursing homes: epidemiology and prevention programs. Clinics in geriatric medicine32(3), 585-607. Epidemiology Paper – Analysis and Application

National Center for Health Statistics. Health United States 2010: With chartbook on trends in the health of Americans. Hyattsville, MD: 2010. Retrieved from http://www.cdc.gov/nchs/data/hus/hus10.pdf#056.

Naito, M. (2014). Utilization and application of public health data in descriptive epidemiology. Journal of epidemiology24(6), 435-436.

Practice Hours Completion Statement DNP-825

I, Steve Akinbehinje, verify that I have completed 10 clock hours in association with the goals and objectives for this assignment. I have also tracked said practice hours in the Typhon Student Tracking System for verification purposes and will be sure that all approvals are in place from my faculty and practice mentor.

Epidemiology Paper – Analysis and Application