WEEK 10 APPLYING EPIDEMIOLOGY TO PROGRAM DESIGN FOR CHRONIC DISEASE ASSIGNMENT PAPER

WEEK 10 APPLYING EPIDEMIOLOGY TO PROGRAM DESIGN FOR CHRONIC DISEASE ASSIGNMENT PAPER

WEEK 10 APPLYING EPIDEMIOLOGY TO PROGRAM DESIGN FOR CHRONIC DISEASE ASSIGNMENT PAPER

Applying Epidemiology to Program Design for Chronic Disease

Applying Epidemiology to Program Design for Chronic Disease

Chronic diseases are the primary cause of global mortality, increased care costs, disability-adjusted life years, and poor quality of life. According to Dona et al. (2021), chronic conditions result in approximately 41 million deaths (71% of all deaths) annually. People grappling with chronic diseases require appropriate pharmacological and non-pharmacologic interventions for alleviating complications, preventing exacerbation of symptoms, and improving care outcomes. Diabetes is among the burdensome chronic diseases that result from the interplay between genetic, environmental, behavioral, and Psychopathology factors. Smith et al. (2021) contend that diabetic patients are susceptible to various adverse complications, including nephropathy, neuropathy, and vision loss. These complications contribute to premature deaths, prolonged hospitalization, high readmission rates, and low quality of life. Therefore, this paper focuses on the plausibility of applying epidemiology to design diabetes management programs in the United States.

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Identification of the Selected Chronic Health Issue and Population

Type 2 diabetes mellitus (T2DM) poses a significant public health problem globally. According to the US Department of Health and Human Services [DHHS] (2023), diabetes is a long-lasting health condition that affects how the body produces and utilizes insulin. Hampered utilization of blood glucose in patients with type 2 diabetes results in hyperglycemia (elevated glucose levels in the bloodstream), leading to massive damage to various body systems. The World Health Organization [WHO] (2023) argues that the clinical manifestation of diabetes includes multiple symptoms like unexplained weight loss, tiredness, blurred vision, and excessive thirst. Diabetes can have adverse ramifications if timely and evidence-based management strategies are lacking. According to the World Health Organization [WHO] (2023), diabetes and associated kidney complications accounted for approximately 2 million deaths in 2019. Although non-modifiable factors like gender, ethnicity, genetics, and age can increase the risk of type 2 diabetes mellitus, modifiable unhealthy lifestyle choices like sedentary lifestyles, limited physical activity, unhealthy diets, alcoholism, and smoking significantly predispose people to diabetes (Yang et al., 2022). In the United States, African Americans are at risk for type 2 diabetes mellitus and associated complications, including retinopathy and nephropathy.

Description of the Geographical Region and Important Characteristics of this Population

Type 2 diabetes mellitus remains a burdensome chronic disease in the United States due to its associated adverse ramifications. Smith et al. (2021) contend that approximately 34 million Americans had diabetes in 2018. In the same year, about 88 million American adults were prediabetic, meaning they had elevated glucose levels that did not satisfy thresholds for diabetes diagnosis (Smith et al., 2021). Despite the alarming statistics regarding diabetes and pre-diabetes prevalence in the United States, predictive statistics indicate that the disease’s prevalence rate will increase to over 60 million American adults by 2060 (Smith et al., 2021). Risk factors contributing to an upsurge in diagnosed cases of type 2 diabetes include overweight and obesity, tobacco use, alcoholism, physical inactivity, and limited awareness of self-management strategies.

Although the United States is a highly-diverse country comprising Non-Hispanic Whites, Black Americans, Asian Americans, and Latinos, African (Black) Americans are at a higher risk of type 2 diabetes than other ethnic groups. The US Department of Health and Human Services [DHHS] (2023) states that African Americans were twice as likely to succumb to diabetic complications in 2019 as non-Hispanic white. In the previous year (2018), non-Hispanic Blacks were about 60% more likely than white adults to be diagnosed with diabetes. Such statistics predict the presence of various population characteristics predisposing them to a high risk of diabetes and its complications. These characteristics include adulthood obesity, unhealthy behaviors like smoking, physical inactivity, socioeconomic barriers to quality care access, food insecurity, and stress. Also, Cheng et al. (2019) identify various physiological predispositions that increase diabetes prevalence among Black Americans. In this case, studies reveal that non-Hispanic Black people have higher levels of HbA1c than non-Hispanic white people due to the potential prevalence of hemoglobinopathies and other genetic factors. Consequently, it is vital to consider these characteristics when developing and implementing population-centered diabetes management programs.

Patterns of the Disease in the Selected Population Using the Epidemiologic Characteristics of Person, Place, and Time

Notably, there are information gaps in establishing the prevalence patterns of type 2 diabetes mellitus (T2DM) in African Americans across different states in America. Although it would be complex to obtain datasets that effectively emphasize diabetes patterns consistent with the epidemiological characteristics of person, place, and time, the Centers for Disease Control and Prevention [CDC] (2022) provides crude datasets on the overtime prevalence of diagnosed diabetes, undiagnosed, and total diabetes among American adults. In a 2017-2020 dataset, the Centers for Disease Control and Prevention [CDC] (2022b) states that non-Hispanic Black adults had a higher percentage of diagnosed diabetes (12.7%), followed by Asians (11.3%), Hispanic (Latino) (11.1%), and White (11.0%). Regarding the total diabetes percentage, Black Americans had the highest share (17.4%), followed by Asians (16.7%), Hispanic (15.5%), and White (13.6%). These intergroup differences in the prevalence rate of diabetes emanate from variations in genetic predispositions and various social determinants of health, including access to physical activity opportunities, food security, socio-economic status, and access to healthy diets.

Health Outcome for the Population

One significant health outcome indicator for people with diabetes is the glycated hemoglobin (HbA1c) level. In this case, people with type 2 diabetes have above-average blood sugar levels. The recommended blood sugar level is below 5.7%. Therefore, higher HbA1c levels can enable effective diagnosis of prediabetes (5.7% to 6.4%) and diabetes (≥6.5%). The Centers for Disease Control and Prevention (2022a) states that a high blood sugar level predisposes diabetic patients to other associated complications, including nephropathy and retinopathy. Consequently, an effective diabetes management program should empower diabetic patients to regulate their blood sugar levels as the primary health quality indicator. It is possible to assess participants’ blood glucose levels after every three months to ascertain the efficacy and effectiveness of the diabetes management program.

Current Evidence that Supports the Importance of Improving This Health Outcome

The current scientific evidence supports improved blood sugar levels as the most reliable indicator of quality diabetes management programs. According to Lamidi et al. (2020), control of HbA1c and low-density lipoproteins (LDLs) are ideal outcome indicators of diabetes projects. The Finnish Current Care Guidelines for diabetes recommend that the normal glycated hemoglobin (HbA1c) level be around 53 mmol/mol (lower than 7.0%). Although the treatment goals for diabetes management programs should be sensitive to people’s risk-factor levels, the duration of diabetes, age, and the severity of the associated co-morbidities, HbA1c regulation presents a strong incentive for diabetes management. Adu et al. (2019) contend that blood glucose level regulation signifies efficient and impactful diabetes self-management approaches. In this case, diabetic and pre-diabetic people can regulate their blood sugar levels and prevent further adverse complications by implementing evidence-based self-management approaches, including healthy eating habits, adherence to treatment interventions, participating in moderate to vigorous physical activities, and reducing risks by avoiding risky behaviors (Adu et al., 2019). Consequently, improving HbA1c levels can represent an ideal outcome and impact measure.

Description of the Evidence-Based Program

The proposed evidence-based program for improving health outcomes of the population grappling with prediabetes and diabetes should capitalize on the tenets of self-efficacy and self-management. A self-management education (SME) program is essential in preventing, treating, and managing diabetes. According to Kumah et al. (2021), a comprehensive self-management education program entails “the process of teaching people with chronic disease to manage their illness and treatment by providing them with the knowledge and skills that are needed to perform self-care behaviors, manage crises, and make lifestyle changes” (p. 2). Improving people’s self-efficacy and self-management through educational programs aligns with the World Health Organization’s recommendation for addressing chronic diseases. Kumah et al. (2021) state that the World Health Organization [WHO] proposes the need to “educate and support patients to manage their conditions as much as possible” (p. 2). Consequently, a self-management education program for prediabetes and diabetes can support effective disease control, management, and treatment.

A self-management education program for diabetes management, control, and treatment should encompass various elements consistent with the desired outcomes. According to Kumah et al. (2021), the recommended content for diabetes educational programs includes strategies for managing stress, the rationale for healthy eating habits and physical activity, relaxation and fatigue management strategies, problem-solving skills, communication skills, and the requirements for working in partnerships with healthcare professionals. Also, people struggling with diabetes should learn to self-monitor diabetes symptoms, medication management, and conditions for making informed treatment decisions (Kumah et al., 2021). Successful implementation of a self-management education program can improve self-efficacy, interprofessional collaboration between healthcare professionals and patients, stress management practices, and timely communication during emergencies. Also, an educational program can promote adherence to pharmacological and non-pharmacologic interventions for diabetes management and treatment.

Besides the recommended content for the self-management education program, it is essential to apply teaching methods that promote collaboration and interactions between healthcare professionals and the target population. Hong et al. (2022) recommend a teach-back teaching strategy for improving knowledge acquisition, retention, and interprofessional interactions. According to Hong et al. (2022), this teaching approach promotes shared decision-making, confidence in self-care, patient-provider interactions, and health outcomes. The teach-back strategy can integrate various content delivery modalities, including physical education sessions and virtual learning opportunities. Therefore, it is profound in promoting individual and group-based learning activities.

Data Collection

Data collection and analysis are profound project phases that allow effective testing and evaluation of short-and long-term objectives. During the implementation of the diabetes self-management education program, it is essential to collect primary data using quantitative and qualitative data collection methods, including surveys and questionnaires, interview transcripts, participants’ testimonials, and observations. In this case, data regarding participants’ experiences, learning outcomes, attitudes toward the education program, and increased knowledge and skills can inform the program’s outcome and impact measures (Heydari et al., 2019). After collecting qualitative and quantitative data, it is possible to analyze datasets using pretest and posttests strategies to assess measures given to participants before and after the intervention. For example, pretests and post-test data analysis tools can evaluate participants’ behavior changes before and after participating in diabetes self-management education sessions.

Short-and Long-Term Objectives (SMART Method)

Diabetes self-management education aims at promoting healthy behaviors and self-care in at-risk populations. Therefore, the short-term goals of educating prediabetic and diabetic people include the following:

• Motivating participants to participate in 30 minutes of moderate to vigorous physical exercises from Monday to Friday (5 days per week)
• Improving medication adherence
• Promoting stress management practices, including motivating participants to try a 10-minute relaxation exercise daily.
• Enabling participants to record their HbA1c, blood pressure, and cholesterol levels.
• Enlightening participants about the need for alcohol and smoking cessation.

The long-term objectives of a self-management education program include the following goals.

• Promote consistent regulation of participants’ HbA1c levels to achieve the recommended levels (below 6.7%).
• Prevent diabetes complications and reduce diabetes progression in prediabetic people by 60%.

Identification of Stakeholders for the Program

Successful planning and implementation of diabetes self-management education programs rely massively upon multidisciplinary and interpersonal collaboration between healthcare professionals, the target group, families, and communities. Ryan et al. (2021) argue that a comprehensive diabetes management plan should entail inputs from various stakeholders, including policymakers, payers, healthcare professionals like nurses, physicians, dietitians, healthcare institutions, patients, family members, peer support groups, and principal investigators, including data analysts. Healthcare professionals play a front role in educating participants, establishing inclusion criteria, developing metrics for assessing outcomes and impacts, and providing learning materials.

Program Planning Model

When planning and implementing a diabetes self-management education program, it is vital to align processes and practices with the PRECEDE-PROCEED model. According to Curley (2020), the propositions of this program planning model include the belief that health and health risks emanate from multiple factors and the need to adopt multidimensional change interventions to address health risks. The PRECEDE (Predisposing, Reinforcing, and Enabling Constructs in Educational Diagnosis and Evaluation) process entails identifying population needs and their determinants, analyzing behaviors and environmental determinants relevant to health needs, outlining factors that predispose, reinforce, or enabling specific behaviors, and determining the best interventions for changing behaviors (Curley, 2020, p. 176). These steps can inform diabetes education programs by promoting a comprehensive analysis of health needs and priorities for diabetes patients, determination of social and environmental determinants, and selecting ideal teaching methods consistent with people’s needs and preferences.

The PROCEED (Policy, Regulatory, and Organizational Constructs in Educational and Environmental Development) framework encompasses steps for implementing and evaluating quality improvement initiatives. According to Curley (2020), it entails engaging stakeholders, describing the project, designing evaluation plans, gathering credible evidence, and justifying conclusions. In a diabetes self-management education program, the PROCEED process can guide interventions for establishing evaluation metrics, quantitative and qualitative data collection, information dissemination, feedback, follow-up activities, and evaluation of the program’s outcomes and impacts.

Cultural or Ethical Considerations Related to Program Design

The cultural and ethical considerations when designing diabetes self-management education programs revolve around the four bioethical principles: beneficence, non-maleficence, justice, and autonomy. According to Sugiharto & Huang (2020), it is essential to ensure that diabetes management interventions benefit the target population (beneficence). Also, it is ethically profound to avoid coercive measures of enticing potential participants to participate in educational sessions to prevent possible harm and exploitation. Thirdly, healthcare professionals should respect individual rights to self-determination and autonomy to decide in favor or against participating in education sessions. They should acknowledge cultural values that guide dietary choices and obtain informed consent from potential participants. Finally, healthcare professionals should uphold respect, integrity, fairness, and dignity when implementing the program.

Conclusion

Diabetes poses significant health challenges by exposing at-risk people to multiple adverse complications. A population-centered self-management education program proves reliable in promoting healthy behaviors, improving people’s self-efficacy, and enhancing positive outcomes. When implementing diabetes education programs, a multidisciplinary approach is central to realizing desired results. Equally, adopting a proven program planning model, including the PRECEDE-PROCEED model, is crucial to inform program planning and implementation. Finally, healthcare professionals should understand ethical and cultural considerations and dilemmas that guide individual choices and decisions.

References

Adu, M. D., Malabu, U. H., Malau-Aduli, A. E. O., & Malau-Aduli, B. S. (2019). Enablers and barriers to effective diabetes self-management: A multi-national investigation. PLOS ONE, 14(6), e0217771. https://doi.org/10.1371/journal.pone.0217771

Centers for Disease Control and Prevention. (2022a). All about your A1C. https://www.cdc.gov/diabetes/managing/managing-blood-sugar/a1c.html

Centers for Disease Control and Prevention. (2022b, September 30). Prevalence of both diagnosed and undiagnosed diabetes. https://www.cdc.gov/diabetes/data/statistics-report/diagnosed-undiagnosed-diabetes.html

Cheng, Y. J., Kanaya, A. M., Araneta, M. R. G., Saydah, S. H., Kahn, H. S., Gregg, E. W., Fujimoto, W. Y., & Imperatore, G. (2019). Prevalence of diabetes by race and ethnicity in the United States, 2011-2016. JAMA, 322(24), 2389. https://doi.org/10.1001/jama.2019.19365

Curley, A. L. C. (Ed.). (2020). Population-based nursing: Concepts and competencies for advanced practice (3rd ed.). Springer

Dona, S. W. A., Angeles, M. R., Hall, N., Watts, J. J., Peeters, A., & Hensher, M. (2021). Impacts of chronic disease prevention programs implemented by private health insurers: A systematic review. BMC Health Services Research, 21(1). https://doi.org/10.1186/s12913-021-07212-7

Heydari, M. R., Taghva, F., Amini, M., & Delavari, S. (2019). Using Kirkpatrick’s model to measure the effect of a new teaching and learning methods workshop for health care staff. BMC Research Notes, 12(1). https://doi.org/10.1186/s13104-019-4421-y

Hong, Y.-R., Jo, A., Huo, J., Cardel, M. I., & Mainous, A. G. (2022). Pathways of teach-back communication to health outcomes among individuals with diabetes: A pathway modeling. Journal of Primary Care & Community Health, 13, 215013192110666. https://doi.org/10.1177/21501319211066658

Kumah, E., Otchere, G., Ankomah, S. E., Fusheini, A., Kokuro, C., Aduo-Adjei, K., & A. Amankwah, J. (2021). Diabetes self-management education interventions in the WHO African Region: A scoping review. PLOS ONE, 16(8), e0256123. https://doi.org/10.1371/journal.pone.0256123

Lamidi, M.-L., Wikström, K., Inglin, L., Rautiainen, P., Tirkkonen, H., & Laatikainen, T. (2020). Trends in the process and outcome indicators of type 2 diabetes care: A cohort study from Eastern Finland, 2012–2017. BMC Family Practice, 21(1). https://doi.org/10.1186/s12875-020-01324-5

Ryan, J. C., Wiggins, B., Edney, S., Brinkworth, G. D., Luscombe-March, N. D., Carson-Chahhoud, K. V., Taylor, P. J., Haveman-Nies, A. A., & Cox, D. N. (2021). Identifying critical features of type two diabetes prevention interventions: A Delphi study with key stakeholders. PLOS ONE, 16(8), e0255625. https://doi.org/10.1371/journal.pone.0255625

Smith, M. L., Zhong, L., Lee, S., Towne Jr, S. D., Ory, M. G., & Towne, S. D. J. (2021). Effectiveness and economic impact of a diabetes education program among adults with type 2 diabetes in South Texas. BMC Public Health, 21(1), 1–12. https://doi.org/10.1186/s12889-021-11632-9

Sugiharto, & Huang, M.-C. (2020). Diabetes self-management engagement: A case study analysis of respect for patient’s autonomy. Saudi Journal of Nursing and Health Care, 3(8), 237–240. https://doi.org/10.36348/sjnhc.2020.v03i08.003

United States Department of Health and Human Services. (2023). Diabetes and African Americans. https://minorityhealth.hhs.gov/omh/browse.aspx?lvl=4&lvlid=18

World Health Organization. (2023, April 5). Diabetes. https://www.who.int/news-room/fact-sheets/detail/diabetes

Yang, J., Qian, F., Chavarro, J. E., Ley, S. H., Tobias, D. K., Yeung, E., Hinkle, S. N., Bao, W., Li, M., Liu, A., Mills, J. L., Sun, Q., Willett, W. C., Hu, F. B., & Zhang, C. (2022). Modifiable risk factors and long-term risk of type 2 diabetes among individuals with a history of gestational diabetes mellitus: Prospective cohort study. BMJ, 378, e070312. https://doi.org/10.1136/bmj-2022-070312

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WEEK 10 ASSIGNMENT INSTRUCTIONS

APPLYING EPIDEMIOLOGY TO PROGRAM DESIGN FOR CHRONIC DISEASE

Roughly 28.5 million Americans were still uninsured as of 2017, and 133 million Americans […] suffer from at least one chronic condition.
—Nash et al. (2021, p. 5)

As you know, promoting positive social change is a part of the Walden mission. To be an effective agent for social change, nurses must be able to logically and critically analyze population health issues using epidemiologic concepts, and then translate this knowledge into evidence-based practice to improve healthcare outcomes. This exercise will afford you such an experience at the population level. This is an exciting time to be working in the field of population health with all the new, dynamic, and innovative technologies and strategies to help patients and populations become more knowledgeable about their health.

This week’s Learning Resources present numerous health problems that result in a need for ongoing care. Your Assignment is to select a chronic disease of professional importance to you, and then design an intervention program to improve the health of populations affected by it.

_Reference:

LEARNING RESOURCES:

• Curley, A. L. C. (Ed.). (2020). Population-based nursing: Concepts and competencies for advanced practice(3rd ed.). Springer.
  • Chapter 7, “Concepts in Program Design and Development”
• Center for Community Health and Development. (n.d.). Toolkits. In Community tool box.Links to an external site.University of Kansas. https://ctb.ku.edu/en/toolkits
  Note: The toolkits page provides guidance on designing and developing programs to improve population outcomes.
• Centers for Disease Control and Prevention. (2021). National Center for Chronic Disease Prevention and Health Promotion (NCCDPHP): Links to an external site.https://www.cdc.gov/chronicdisease/index.htm
• Centers for Disease Control and Prevention. (2015). Public health professionals gateway: Develop SMART objectivesLinks to an external site..https://www.cdc.gov/phcommunities/resourcekit/evaluate/smart_objectives.html
• The Community Guide. (n.d.). Program planning resourceLinks to an external site.. https://www.thecommunityguide.org/content/program-planning-resource
• Minnesota Department of Health. (n.d.). Smart objectivesLinks to an external site.. https://www.health.state.mn.us/communities/practice/resources/phqitoolbox/objectives.html

THE ASSIGNMENT

In a 7- to 10-page proposal (not including title page and references), address the following:

• Briefly identify your selected chronic health issue and population.
• Describe the geographic region and important characteristics of this population.
• Describe the patterns of the disease in your selected population using the epidemiologic characteristics of person, place, and time.
• Identify one health outcome you would like to improve for the population.
• Briefly summarize current evidence that supports the importance of improving this health outcome.
• Briefly describe the evidence-based program you are developing, and why this approach will best fit the needs of your population.
• Explain what data you would need to collect, and how you would obtain and analyze it. You may choose to collect primary data or use secondary data. Justify your choice.
• Using the “SMART” method, write short- and long-term objectives for the program.
• Identify the stakeholders who should be involved in program planning.
• Identify which program planning model (see Curley, Chapter 7) you selected for your program. Justify your selection of model. Based on the model, explain how you would plan, implement, and evaluate the program.
• Explain any relevant cultural or ethical considerations related to your program design.
• Explain how you would fund the program.
• Describe strategies that would be appropriate for marketing the program.
• NURS_8310_Week10_Assignment_Rubric

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