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High-Risk Populations
A high-risk population is a term used commonly healthcare to describe certain people or groups of people in relation to their demand for health or characteristics that predispose them to an increased risk for certain disease. For instance, Edberg (2015) finds that pregnant women are high-risk groups because of their increased energy needs as well as the need for medical care. The classifying characteristic, in this case, is the physiological state of the person. Other dimensions create a combination of factors that increase the risk in a given population. For instance, the racial disparities in the access to care make minority groups high-risk populations. This is more the case when the minority groups have chronic conditions that require sustained medical care. In addition to the increased need for medical care, the inhibiting factors such as the disproportionate access to care make them high-risk populations.
The identification of the high-risk populations is an important aspect in the delivery of care. Firstly, the understanding of the factors which make them high risks groups is necessary for the determination of the best approaches through which these groups can receive health care services. Wei et al., (2013) also find that the identification of the high-risk populations aids in the diagnosis and treatment. More specifically, their identification results in increased knowledge of their disease patterns, health seeking behavior, clinical indicators, and other behavioral characteristics that increase their risk for certain diseases. In underscoring the importance of the identification of these groups, Kirsh, Lawrence & Aron, (2008) argue that the design of interventions that address the specific needs of high-risk populations is dependent on among other things, their identification.
Identification of High-Risk Populations
As an advanced practice nurse working in a primary care clinic, the care provided is mostly at the microsystem level. By definition, Sloboda & Petras (2014) understand the microsystem to entail all the risks, causative factors, and the protective factors that are within the proximity of the individual and the factors on which the individual has a direct influence and participation. In addition to the diagnosis and treatment of cases, primary preventive services also characterize the delivery of health services at the clinic. High-risk populations who are common recipients of health services are the elderly people who also have diabetes as a chronic condition.
The classification of this group of high-risk populations is due to the prevalence of several factors either individually or as a combination. One of these factors is the competing needs. At this age, most of the members of this population are not economically active and rely on the family members financially. Some of the members of this population may not have family members on whom they can depend for the financial wellbeing. As such, their socioeconomic status requires them to make priorities. More often than not, seeking health care is relegated in the favor of other priorities such as housing and food.
Another attribute characteristic of this group that classifies them as a high-risk population is the presence of one or more chronic diseases. American Journal of Managed Care (2006) argues that this is one of the definitive attributes of vulnerable groups. The presence of other inhibiting factors such as a prevalent lack of medical insurance, low education levels, low-income levels, poor health seeking behaviors, and the presence of chronic conditions increases their risk for poor health outcomes. The intersection of social and economic factors such as the need for housing, low income levels, low education levels, racial disparities in the access to care, lack of insurance coverage with physiological factors such as their diminished immunity due to the advancement in age and health problems in the form of chronic conditions makes this population a high risk population (American Journal of Managed Care, 2006).
The epidemiological triangle aids in the understanding of how the host, the agent, and the environment interplay to cause illness. The immediate environment where these people live is an important indicator. The environment in this instance is operationally defined also to include the social and economic environments. The influence of the social and economic environment in the access to care either heightens or reduces the risk of the exacerbation of the chronic conditions. For instance, factors in the social environment such as the cultural dietary practices, education and employment status and the health care systems affect the ability of the elderly to access care and also manage their chronic conditions (Herman, 2007). As factors in the epidemiological triangle, the host and agents coexist and disturbances in the balance between the two play an influencing role in the health outcomes.
The Epidemiology of the Elderly Population with Diabetes
Epidemiological data on diabetes helps illustrate the seriousness of the condition. The prevalence rates of diabetes among the elderly population in the United States shows a worrying trend. The prevalence rate of diabetes among the senior population in the United States is estimated at 27% (Institute of Alternative Futures, 2011). The operational definition for seniors in this instance is people who are above the age of 65 years. For the same population, the prevalence rate of pre-diabetes is 50% (Institute of Alternative Futures, 2011). This is an indication that without the adequate management of this population, the prevalence rate will increase even further in the coming years.
Publications by the Center for Disease Control and Prevention in their National Diabetes Fact Sheet for 2011 showed that the projected increase in the prevalence of diabetes would be significant from 2010 to 2050 (Institute of Alternative Futures, 2011). Various institutions have used the projections by the Center for Disease Control and Prevention to develop estimation models. One such model by the Alternative Futures shows that the elderly population living with diabetes, whether diagnosed or otherwise will increase to 17,191,000 by 2025 from 10,821,600. This represents an increase in the prevalence rate by 59% (Institute of Alternative Futures, 2011).
Further projections have also been done to show the morbidity rates, mortality rates, and the rates of complications associated with diabetes for this population. The table below summarizes some of these statistics.
Source: (Institute of Alternative Futures, 2011).
The statistics above show the projections for the prevalence of pre-diabetes, diabetes and its variants and the occurrence of complications among the elderly population. The trends show that the projected increase between 2010 and 2025 is exponential. The medical costs associated with management of the condition and the treatment of the complications that arise as a result also increase exponentially and are projected to increase further. The increase in the non-medical costs is also significant. The non-medical costs relate to the reduction in labor force through attrition as a result of deaths related to diabetes and its complications (Jain & Paranjape, 2013). As shown in the table, the deaths among the senior population that were attributable to diabetes in 2010 were 109,520 and are projected to increase 135,900 by 2025.
Adverse Health Outcomes
The identification of this high-risk group is even direr considering the adverse health outcomes and the effect on the quality of their lives. Zeyfang and Walston (2009) find that there are adverse health outcomes in the elderly people who also have diabetes as a chronic condition. Zeyfang and Walston (2009) also find that these adverse health outcomes result in poor quality of life. Of note is that the adverse health outcomes are at times the result of an interplay of a multiplicity of factors and multimorbidities. One of the adverse health outcomes is increased frailty as a result of glucose intolerance which further leads to emaciation and the loss of muscle strength (Munshi & Lipsitz, 2007).
It is also noteworthy that the multimorbidities that characterize the adverse health outcomes for this population group as also the result of the biological processes in the body that stem from the occurrence of certain adverse health outcomes. For instance, Zeyfang and Walston (2009) find that the occurrence of frailty as a result of diabetes causes neuroendocrine dysregulation and the inflammatory pathways in the bodies of the elderly ton be activated. The result of these biological processes is an increased risk for the occurrence of other chronic disease states.
The adverse health outcomes in this population are also characterized by the interdependence and the reciprocal influence of various geriatric syndromes and diabetes. Zeyfang and Walston (2009) highlighted the prevalent medical complications that are associated with diabetes including stroke cardiovascular diseases and renal failure. In addition to these complications, Zeyfang and Walston (2009) also find that the elderly population is also predisposed to the geriatric syndromes that set in later in life. Some of these syndromes include incontinence, frailty, mobility disability, and depression. The interplay of these syndromes and diabetes in this population leads to the exacerbation of the existing morbidities and the occurrence of new ones resulting in adverse health outcomes.
Summary
The elderly people with diabetes as a chronic condition are a high-risk group. The presence of the chronic condition predicts their high-risk status. The high-risk status is also predicted by the competing needs, disproportionate access to care, low education and low-income levels. The identification of this population is important for the development of interventions that are specifically designed to meet their unique needs. The epidemiology of diabetes in this population indicates the need for concerted efforts to prevent the occurrence of adverse health outcomes through the management of the manifestations and the complications. However, preventive measures in other age cohorts are needed to curtail the unabated increase in the prevalence of the condition.
References
American Journal of Managed Care. (2006). Vulnerable Populations: Who Are They?. Retrieved from http://www.ajmc.com/journals/supplement/2006/2006-11-vol12-n13suppl/nov06- 2390ps348-s352.
Edberg, M. C. (2015). Essentials of health behavior: Social and behavioral theory in public health. Burlington. Jones & Bartlett Learning.
Herman, W. (2007). Diabetes Epidemiology: Guiding Clinical and Public Health Practice: The Kelly West Award Lecture, 2006, Diabetes Care, 30(7): 1912-1919.
Jain, A. and Paranjape, S. (2013). Prevalence of type 2 diabetes mellitus in elderly in a primary care facility: An ideal facility. Indian Journal of Endocrinology and Metabolism. 17(S1): S318-S322.
Kirsh, S., Lawrence, R. and Aron, d. (2008). Tailoring an intervention to the context and system redesign related to the intervention: A case study of implementing shared medical appointments for diabetes. Implementation Science. 3: 34
Munshi, M. and Lipsitz, L. (2007), Geriatric diabetes. Boca Raton. CRC Press.
Sloboda, Z., & Petras, H. (2014). Defining prevention science. New York. Springer.
Wei, X., Zou, G., Yin, J., Walley, J., Zhou, B., Yu, Y., Tian, L., and Chen, K. (2013). Characteristics of high risk people with cardiovascular disease in Chinese rural areas: clinical indictors, disease patterns and drug treatment. PLoS One, 8(1): e54169.
Zeyfang, A. and Walston, J. (2009). Perspectives on diabetes care in old age: A focus on frailty. In Sinclair, A. Diabetes in old age. Chichester, UK: Wiley-Blackwell.
