Translation Science and Evidence Synthesis

Evidence Synthesis

Evidence synthesis is a way of putting relevant information on a particular research question or problem together with the aim of identifying knowledge gaps, selecting evidence-based information to inform, or making essential decisions in the field. It helps identify the connection between two or more sources, thus deriving a conclusion of the required evidence.

Translation Science and Evidence Synthesis

Additionally, evidence synthesis is usually unbiased to assist decision-making or address a particular practice problem. The purpose of this paper is to present an evidence synthesis of the diabetes practice problem based on three quantitative articles and non-research evidence sources.

Introduction to the Practice Problem

The selected national practice problem is diabetes. Diabetes is a health condition that affects glucose regulation in the body. Diabetes is characterized by inadequate insulin production or problems with insulin use, thus increasing blood glucose levels. The three diabetes types include type 1, 2, and gestational diabetes. Type 1 diabetes is characterized by inadequate/lack of insulin production.

In type 2 diabetes, the body resists insulin or does not produce adequate insulin. Gestational diabetes is common in pregnancy but mainly disappears after giving birth. However, gestational diabetes increases the risk of type 2 diabetes diagnosis in the woman’s life (CDC, n.d.).

Diabetes is a significant health concern and practice problem since it adversely affects the patient’s life quality, increases the risk of other health conditions such as cardiovascular diseases, and contributes to lifestyle changes. Additionally, diabetes increases healthcare costs and exerts pressure on the entire healthcare system.

Introduction of the Evidence-Based Intervention

The evidence-based intervention selected for this project is Diabetes Self-Management Education (DSME). DSME is a tool used to teach diabetic patients and empower them to make self-management decisions and effectively carry out self-management activities. It improves health behaviors and outcomes for people living with diabetes.

According to Hermanns et al. (2020), DSME is mainly delivered in 6-week programs whereby the patients are taught the different diabetes self-management activities and best practices. DSME has been found to improve diabetes patients’ health outcomes by positively impacting their self-care behavior and empowering them by increasing their knowledge and self-efficacy regarding diabetes (Hailu et al., 2019).

Analysis of the Practice Problem

Diabetes as a practice problem is one of the significant health concerns globally. Despite experts maintaining that diabetes is preventable and controllable (Streit & Spritzer, 2022), it potentially overwhelms healthcare systems as it influences patient comorbidities, time spent in the hospital, and readmissions (Ellahham, 2020) and negatively affect economies and individual lives (‘O’connell & Manson, 2019).

Approximately 422 million people have diabetes globally, with a higher burden in low and middle-income nations (WHO, n.d.). More so, there is an alarming rise in newly diagnosed diabetes cases, and many remain undiagnosed. In their Aetna diabetes white paper publication, George et al. (2019) contend that the weight of the burden of the practice problem is mainly increased by ineffective prevention strategies, late-stage diagnosis, low screening rates, underequipped care facilities, and diabetes specialists’ scarcity. In my opinion, and based on this evidence, diabetes increases an individual/family’s economic burden, following increased healthcare costs, decreased productivity, and high insurance costs.

Significance, Prevalence, Mortality, and Economic Ramifications of the Practice Problem

Diabetes’ significance is profound and felt globally. The disease increases the risk of early death, and diabetes complications negatively impact the patient’s life quality. Diabetes is also related to various health issues, including amputations, heart disease, loss of sight, kidney failure, and stroke. Additionally, current research shows that diabetes has been found to positively affect hearing loss, dementia, and different forms of cancer, especially in older populations (CDC, n.d.). At the local level, diabetes has contributed to increased numbers of the blind and physically impaired following diabetic foot amputations and poor outcomes and quality of life for diabetic patients with other comorbidities.

The global diabetes prevalence stands at 8.8% of the total population, with approximately 77% living in developing countries. The prevalence is anticipated to increase to 9.9% by 2045 (Standl et al., 2019). On the age distribution, people aged 40-59 are the ones who are most affected by the condition. In the US, diabetes prevalence lies at 11.3% (approximately 37.3 million) of the total population, with about 8.5 million undiagnosed cases (CDC, 2022).

Furthermore, 1 in 9 deaths globally is associated with diabetes and diabetes complications. Diabetes is ranked as the seventh leading cause of mortality in the US and is attributed to 102,188 deaths (CDC, n.d.). In Florida, 13.1% of the adult population, or approximately 2,350,321, are diabetic. According to Khan et al. (2021), the country-level age-adjusted diabetes prevalence is 4.7%-17.8%.

According to Standl et al. (2019), diabetes significantly impacts the economy and the economic productivity of affected individuals. More so, it has an enormous impact on the healthcare systems due to increased care costs incurred in treating and managing the condition and its associated complications. Every 1 in 4 dollars in the US healthcare system is spent on diabetes and diabetes complications treatment and management, and $237 billion are spent on diabetes treatment direct costs (CDC, n.d.).

Additionally, Standl et al. (2019) state that individuals with diabetes spend close to four times more than individuals without diabetes due to medication costs, lifestyle adjustments, follow-ups, and hospitalizations. Diabetes also impacts the productivity of an individual by reducing their efficiency at work, increasing absenteeism, and, therefore, low outputs. It also impacts local and national economies by the reduction of the gross domestic product (Standl et al., 2019). Additionally, diabetes costs approximately $25 billion in Florida annually (Khan et al., 2021).

Evidence Synthesis

I searched reputable data sources to locate three quantitative articles that can be used to address the diabetes practice problem. The Google search engine, google scholar database, PubMed and CINAHL were used. The articles are peer-reviewed, published in recognized journals, and published within the last five years, thus appropriate for addressing the practice problem.

The three articles, Zheng et al. (2019), focuses on Diabetes Self-management Education; Seboka et al. (2021) focuses on the use of information technology in diabetes management; and Fang et al. (2021) focuses on diabetes and the risk of hospitalization for infection.

The sources contribute to addressing the diabetes national practice problem. The main aim that is salient in the three sources is to make recommendations that can be used in improving life quality for diabetes patients considering they all cover the essential aspects of diabetes. The main themes emerging from the synthesis of the three research evidence sources include diabetes self-management education, healthcare technology, and hospitalization risk for diabetes patients (Fang et al., 2021; Seboka et al., 2021; Zheng et al., 2021).

The salient points in the evidence synthesis include that diabetes complications are the primary cause of hospitalization for diabetes patients (Fang et al., 2021). However, diabetes complications can be prevented and reduced by empowerment through diabetes self-management education (Zheng et al., 2021), which can be implemented through healthcare technology (Seboka et al., 2021).

The other point is that healthcare technology-assisted DSME is effective in improving diabetes self-management behavior, which in turn reduces the risk of complications and related hospitalization, thus improving the overall life quality for the patients (Jain et al., 2020).

Comparison and Overarching Objective of the Main Points from the Research Evidence Synthesis

The three research evidence sources aim at addressing the practice problem by improving patient outcomes. As mentioned earlier, diabetes self-management education, healthcare technology, and complication-related hospitalizations significantly influence patient outcomes in diabetes patients (Fang et al., 2021; Seboka et al., 2021; Zheng et al., 2021).

Additionally, healthcare technology has facilitated DSME use and self-management behavior (Seboka et al., 2021; Zheng et al., 2021), thus helping prevent complications that increase the risk of hospitalization (Fang et al., 2021) and other related comorbidities, and mortality.

However, pertinent differences exist in the main points from the research evidence obtained. Foremost, Seboka et al. (2021) note that the perception of the care providers majorly influences the use of healthcare technology in facilitating diabetes management and diabetes self-management. On the other hand, Fang et al. (2021) only focuses on diabetes as a risk for hospitalization but fail to include parameters of exclusion of diabetes and non-diabetes-related infections that can lead to hospitalization.

In addition, Zheng et al. (2021) emphasized the effectiveness of DSME in promoting diabetes self-management behaviors and practices in T2DM patients only. The disparities notwithstanding, the overarching objective in the three research evidence sources, as evident in the synthesis, is that DSME, utilizing healthcare technology (Seboka et al., 2021), can help promote self-management behavior, thus reducing complications leading to hospitalizations (Fang et al., 2021), hence improving patient outcomes and quality of life (Fang et al., 2021; Seboka et al., 2021; Zheng et al., 2021).

Practice Problem

Among Type 2 Diabetes patients, does DSME utilizing healthcare technologies compared to routine patient education reduce diabetes-related complications within six months?

Translation Science Theory, Application, and Stakeholder Integration

The translation science theory selected for the implementation of the practice change project is the normalization process theory. The theory addresses the elements needed for the successful implementation and integration of a particular intervention into routine processes.

It serves as a framework for designing a practice change project to direct the planning and implementation to enhance the integration of the intervention into routine work. Reflexive monitoring is one of the theory’s elements, which entails analyzing the intervention’s benefits before its implementation, thus identifying its feasibility. Reflexive monitoring will be applied in analyzing the cost and benefits of the intervention before its implementation to determine its feasibility.

Stakeholders of the intervention would be integrated into the model phases during planning, implementation, and evaluation. A stakeholder such as the American Diabetes Association would be enquired for guidelines to develop the DSME intervention according to the recommended standards, thus integrated into the planning. Healthcare providers and diabetic patients would be integrated into the implementation and evaluation phases of the project.

Conclusion

Diabetes is a national practice problem whose significance is felt at local, national, and global levels. Research evidence can be used to inform diabetes self-management, thus addressing the practice problem. Essentially, it is possible to summarize the evidence synthesis presented above in one statement; diabetes self-management education enhanced by healthcare technology can be used to improve diabetes self-management, prevent diabetes complications and related hospitalizations, promote desirable health outcomes, and ensure a better quality of life for diabetes patients. The normalization process theory can be used as a framework to integrate stakeholders into the practice change project.

Translation Science and Evidence Synthesis References

Centers for Disease Control and Prevention (2022). National Diabetes Statistics Report website. https://www.cdc.gov/diabetes/data/statistics-report/index.html

Centers for Disease Control and Prevention. (n.d.) What is Diabetes? https://www.cdc.gov/diabetes/basics/diabetes.html

Ellahham, S. (2020). Artificial intelligence: The future for diabetes care. The American Journal of Medicine133(8), 895-900. https://doi.org/10.1016/j.amjmed.2020.03.033

Fang, M., Ishigami, J., Echouffo-Tcheugui, J. B., Lutsey, P. L., Pankow, J. S., & Selvin, E. (2021). Diabetes and the risk of hospitalization for infection: The Atherosclerosis Risk in Communities (ARIC) study. Diabetologia64(11), 2458-2465. https://doi.org/10.1007/s00125-021-05522-3

George, S., Stetz, L. & Patel, M. (2019). Diabetes: The Worlds Weightiest Problem. [White Paper] Aetna. https://www.aetnainternational.com/en/about-us/explore/future-health/diabetes-world-weightiest-problem.html

Hailu, F. B., Moen, A., & Hjortdahl, P. (2019). Diabetes self-management education (DSME)–Effect on knowledge, self-care behavior, and self-efficacy among type 2 diabetes patients in Ethiopia: A controlled clinical trial. Diabetes, Metabolic Syndrome, and Obesity: Targets And Therapy, 2489-2499. https://doi.org/10.2147/DMSO.S223123

Hermanns, N., Ehrmann, D., Finke‐Groene, K., & Kulzer, B. (2020). Trends in diabetes self‐management education: Where are we coming from and where are we going? A narrative review. Diabetic Medicine37(3), 436-447. https://doi.org/10.1111/dme.14256

Jain, S. R., Sui, Y., Ng, C. H., Chen, Z. X., Goh, L. H., & Shorey, S. (2020). Patients’ and healthcare professionals’ perspectives towards technology-assisted diabetes self-management education. A qualitative systematic review. PloS One15(8), e0237647. https://doi.org/10.1371/journal.pone.0237647

Khan, M. M., Roberson, S., Reid, K., Jordan, M., & Odoi, A. (2021). Geographic disparities and temporal changes of diabetes prevalence and diabetes self-management education program participation in Florida. Plos one16(7), e0254579. https://doi.org/10.1371%2Fjournal.pone.0254579

O’Connell, J. M., & Manson, S. M. (2019). Understanding the economic costs of diabetes and prediabetes and what we may learn about reducing the health and economic burden of these conditions. Diabetes Care42(9), 1609-1611. https://doi.org/10.2337/dci19-0017

Seboka, B. T., Yilma, T. M., & Birhanu, A. Y. (2021). Factors influencing healthcare providers’ attitude and willingness to use information technology in diabetes management. BMC Medical Informatics and Decision Making21(1), 1-10. https://doi.org/10.1186/s12911-021-01398-w

Standl, E., Khunti, K., Hansen, T. B., & Schnell, O. (2019). The global epidemics of diabetes in the 21st century: Current situation and perspectives. European Journal of Preventive Cardiology26(2_suppl), 7-14. https://doi.org/10.1177/2047487319881021

Streit, L. & Spritzler, F. (2020). [Experts Opinion] 11 Ways to Prevent Diabetes.  https://www.healthline.com/nutrition/prevent-diabetes

World Health Organization. (n.d.). Diabetes. https://www.who.int/health-topics/diabetes#tab=tab_1

Zheng, F., Liu, S., Liu, Y., & Deng, L. (2019). Effects of an outpatient diabetes self-management education on patients with type 2 diabetes in China: A randomized controlled trial. Journal of Diabetes Research2019. https://doi.org/10.1155/2019/1073131

Appendix A: Johns Hopkins Nursing Evidence-Based Practice Individual Evidence Summary Tool

Practice Question: Among Type 2 Diabetes patients, does DSME utilizing healthcare technologies compared to routine patient education reduce diabetes-related complications within six months?  

Date: 11th February 2023

 Article Number   

Author and Date

  

Evidence Type

 Sample, Sample Size, Setting Findings That Help Answer the EBP Question  Observable Measures   

Limitations

 Evidence Level, Quality
64 (11) Fang, M., Ishigami, J., Echouffo-Tcheugui, J. B., Lutsey, P. L., Pankow, J. S., & Selvin, E. 2021 Experimental research   12379 participants of the Atherosclerosis Risk in Communities (ARIC) study were used in the study The findings of this study are that diabetes is associated with a higher risk for infection and hospitalization. These infections may result from diabetes complications or other related comorbidities. The ‘article’s main aim was to determine the association between diabetes and the risk of infections leading to hospitalization. It was observed that people with diabetes are more likely to be hospitalized due to infections than people without diabetes. The definition of hospitalization for infection was not validatedThe association between glycemic control and infections complication was not measured

There was a physician’s bias toward referring diabetes patients to the hospital due to infections

Fang et al. (2021) was appraised at Level 3 evidence with grade A quality. The study has generalizable results and the sample size is sufficient for the study design.
21(1) Seboka, B. T., Yilma, T. M., & Birhanu, A. Y. 2021 Cross-sectional study  The sample contains 406 participants, with 283 nurses and 123 physicians in two teaching and referral hospitals where remote monitoring of patients had not been implemented. 

 

The findings that can address the practice problem are: care providers are willing and ready to use healthcare information technology to facilitate diabetes management. Among the observable measures in this study is the use of structured questionnaires to collect data and descriptive statistics in analysis. Tables and figures are also used to display the results for the attitude and willingness of care providers to use information technology in diabetes management. The study had two major limitations; one, only a quantitative approach was used. Thus, the findings may lack enough strength. Second, the study was conducted; thus, the generalizability of findings may be difficult. Seboka et al. (2021) was appraised at level 3 evidence and Grade A quality. The results are reasonable and consistent. The study is based on a comprehensive literature review.
11(1) Whittemore, R., Vilar-Compte, M., De La Cerda, S., Marron, D., Conover, R., Delvy, R., Lozano, A. M. & Pérez-Escamilla, R. 2019 Qualitative Descriptive study The sample included 20 adults with type 2 diabetes and 19 care providers from Mexico and different clinics around.   

 

The findings contributing to addressing the evidence-based practice question include that personal challenges mentioned by the patients include inadequate social support, difficulties in lifestyle modification, and mental health issues. The system challenges identified by care providers include patient engagement barriers, perceived care quality and inadequate resources. The study’s aim was to identify the challenges in diabetes self-management as perceived by type 2 diabetes patients and care providers.Tables and figures are used to display the different challenges in diabetes self-management as perceived by patients and care providers. One of the major limitations of this study is that the study setting was confined to one geographical setting. Although Mexico is a mirror for other low-income settings, the findings may not represent all vulnerable populations. Whittemore et al. (2019) was appraised at level 3 evidence. It presents a qualitative study with grade-A quality evidence. It has generalizable results and a consistent conclusion. however, the sample size and characteristics are not representative of vulnerable populations.
1073131 Zheng, F., Liu, S., Liu, Y., & Deng, L. 2019 Randomized Controlled Trial (RCT) Sixty patients with type 2 diabetes. 30 were allocated to a control group, and 30 to an intervention group The findings of this study are that diabetes self-management education effectively improves the level of self-reported self-management, psychological distress, and glycemic control in patients with type 2 diabetes. To determine the effects of an outpatient diabetes self-management education program, two regular and health education programs were provided. The observable measures were the diabetes self-care activities measured and recorded before and after the intervention. Despite mentioning the effects of diabetes self-management interventions, the article does not include the effectiveness of these effects in improving patient outcomes.The use of only two education sessions may have provided limited evidence. Zheng et al. (2019) appraised at Level 1 evidence with grade A quality. The study was unbiased, and the risk of systematic errors was minimal. The sample size is sufficient for the study design.

Attach a reference list with full citations of articles reviewed for this Practice question.

Reference List

Fang, M., Ishigami, J., Echouffo-Tcheugui, J. B., Lutsey, P. L., Pankow, J. S., & Selvin, E. (2021). Diabetes and the risk of hospitalization for infection: the Atherosclerosis Risk in Communities (ARIC) study. Diabetologia64(11), 2458-2465. https://doi.org/10.1037/hea0000710

Seboka, B. T., Yilma, T. M., & Birhanu, A. Y. (2021). Factors influencing healthcare providers’ attitude and willingness to use information technology in diabetes management. BMC Medical Informatics And Decision Making21(1), 1-10. https://doi.org/10.1186/s12911-021-01398-w

Whittemore, R., Vilar-Compte, M., De La Cerda, S., Marron, D., Conover, R., Delvy, R., Lozano, A. M. & Pérez-Escamilla, R. (2019). Challenges to diabetes self-management for adults with type 2 diabetes in low-resource settings in Mexico City: a qualitative descriptive study. International Journal For Equity In Health18(1), 1-10. https://doi.org/10.1186/s12939-019-1035-x

Zheng, F., Liu, S., Liu, Y., & Deng, L. (2019). Effects of an outpatient diabetes self-management education on patients with type 2 diabetes in China: a randomized controlled trial. Journal of Diabetes Research2019. https://doi.org/10.1155/2019/1073131