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Evidence-Based Research: Type 2 Diabetes


Type 2 diabetes is a metabolic disorder characterized by high blood glucose levels and other risk factors such as hypertension, cholesterol, and coagulation. This condition is common and becomes more prevalent as the world’s population ages and obesity rates rise. 2 Indeed, the global prevalence of diabetes is expected to increase by 66% over the next two decades. Governments and health insurers are concerned about rising prevalence rates because type 2 diabetes patients have more comorbid conditions than those who do not. Lowering blood pressure or cholesterol, on the other hand, can significantly reduce the risk of macrovascular and microvascular complications. As a result, patients who are elderly or have multiple risk factors should take both medications simultaneously.

Unfortunately, the need for multiple chronic medications is inextricably linked to issues with medication adherence. Non-adherence is common in type 2 diabetics, and it appears to be associated with increased morbidity and mortality. Diabetes was also the second most common reason for non-adherence-related hospitalizations in fourU.S. hospitals, trailing only mental health issues. Non-adherence in diabetes appears to be a very expensive issue, with non-adherence costing the United States $100 billion per year. A 20% improvement in medication adherence could save each diabetic $1074 in total healthcare costs. The question is whether adherence interventions can consistently improve such high adherence rates. Nobody knows how much adherence-improvement interventions cost.

Clinicians have reported favorable treatment results, which has motivated them to investigate other similar anecdotal experiences in the area that they may have heard about. There is significant potential for getting new ideas from both inside and outside of the profession and from the broader health care industry. Practitioners must be involved in research to engage with experienced researchers and transfer their ideas via realistic research topics that need their participation. The connection between doctors and researchers may suffer due to a lack of knowledge of how to respond to these questions. The practitioners’ comprehension of research and their level of research literacy and aptitude may prevent them from participating in studies.

On the other hand, practitioners are under growing pressure to base their recommendations on the most current scientific research as the healthcare industry increasingly expects evidence-based treatments. Clinical researchers were excluded from research projects, which may have influenced the growth and new achievements in medicine. The fact that doctors were not involved in research development has also contributed to the difficulty of transferring results into clinical practice. Participation in the research endeavor to integrate translation of information is open to both researchers and knowledge consumers. Also necessary is for a clinician to have an important role in the conceptualization of the research topic and the interpretation of results and application of those findings.

The two individuals involved must collaborate to have a better probability of success. One way to illustrate this is via the use of a randomized controlled trial (RCT), which may demonstrate how physicians can utilize existing literature and the PICOT framework to construct research questions concerning the treatment’s efficacy (Committee on Quality of Health Care in America & Institute of Medicine, 2001). Because of this, developing a well-structured research plan is essential to conducting a comprehensive inquiry into how therapy selection impacts patients’ health.

Research Question

When it comes to Type 2 diabetics, do not taking prescribed medication increase the chance of having raised cholesterol?

Type 2 diabetics who are overweight or obese. Diabetes patients with type 2 diabetes will be included in the study, while everyone else will be excluded.

Triglycerides are seen in high concentrations in the blood of Types I and II patients. Over six months, the participants will be randomly chosen and exposed to manipulation every week, several times a week.

C– Is high cholesterol a contributing factor to diabetes? This information will determine if increased cholesterol levels are associated with diabetes on a comparative basis.


Increased likelihood of acquiring high cholesterol levels.

It will take around six months. Approximately six months after that, the outcome would be known. The research subject for this case study will assist in the selection of the most suitable study design. However, a prospective or retrospective cohort design is significantly more straightforward to conduct than an RCT. The comparison with the non-randomized groups, on the other hand, is likely to have an undesired effect on the results and make them more unclear. This method is especially effective when looking for connections between a person’s traits and the outcomes of interest obtained. Compared to RCT, this strategy is more reasonable and less costly to implement since it considers the individual employing it over a wide range of spectrums. However, despite the design’s benefits, the most significant disadvantage is the difficulty in remembering information from respondents who self-report their responses.

Case study

Case-control studies are particularly useful for establishing relationships between diabetes-related characteristics and outcomes that take a long time to manifest themselves or are very rare. Pharmacotherapy is often used in the treatment of chronic illnesses such as diabetes. The fact that these therapies are effective does not change the reality that around half of the patients do not follow their prescription as directed. Many factors play a role in such events, including those relating to patients, such as a lack of health literacy and engagement in the decision-making process about their care and treatment.

The prescription of complex treatment regimens, poor communication, and insufficient distribution of information regarding the negative effects of drugs are among the issues that worry physicians. Other factors affecting healthcare systems, such as time limits on office visits, access restrictions, and a lack of health information technology, are significant contributors (Klein and Sorra, 1996). It is necessary to look for approaches to improve adherence to improve outcomes to overcome these hurdles. The EBP strives to blend clinical competence, external scientific knowledge, and the perspectives of the individual’s caregivers and family members into delivering high-quality services that are representative of the individual’s preferences as much as possible.

In addition to posing a major hazard to human health, the rising incidence of type 2 diabetes poses a serious challenge to the long-term survival of many healthcare systems. Inability to adhere to prescription regimens increases the likelihood of a variety of health problems, including increased morbidity and death and increased healthcare expenses. Despite various helpful adherence predictors, the ability to explain or forecast noncompliance with established risk factors is insufficient.

Study approach

In a community cohort of individuals with diabetes, assess medication adherence, identify risk factors for poor adherence, and test the hypothesis that as the number of medications given rises, so does medication adherence.

Design and research methods- A pharmacist-administered questionnaire was completed by 128 individuals with type 2 diabetes from a single community health center. The results of the survey were cross-referenced with medical records stored electronically. We looked at self-reported medication adherence rates, obstacles, and attitudes toward medication usage, HbA1c, total cholesterol, blood pressure levels, and the effects of several diabetes-related medications. It was agreed that persons who had Read codes entirely and indicated the existence of type 2 diabetes should participate in this investigation. Nowhere whether or not a particular kind of diabetes was discovered where there are a few examples where the history of the patient was full of contradicting types Patients were labeled as having type 2 diabetes if they had one or more of the following: a record with a Read code indicative of type 2 diabetes and at least one record with a Read code an antidiabetic drug prescription they were given different types of oral antidiabetic medication, or if they were prescribed both.

A patient’s age was a factor in their exclusion. At 35 years of age, he began his presentation. Without the requirement for a prescription, insulin antidiabetic drugs, Patients with diabetes mellitus as a secondary disease were also not eligible. Patients must have a minimum of care and follow-up for 36 months before at least six months of observation before the commencement of the mortality observation period, a wash-in phase of insulin therapy. They must be on insulin for at least a year and a half. It is feasible to measure a subject’s degree of compliance. Mortality was analyzed after the 36-month evaluation period ended. The assessment period was designated as the day following the index number, with an index date. Patients were between January 1 and November 30, 2000. Extraction of data from 2009 revealed the following results: in a sample size of 15,984 individuals. Patients of all ages were monitored until death or data suppression.


Because they used the visit nonattendance Read code, people in this group missed a lot of appointments. This ranged from 0 to 39 missed appointments. During the assessment period, 6,227 patients failed to appear for one or more of their appointments. 4,346 people missed one to two and 1,881 people missed more than two. Seven hundred and five patients were discovered to be not adhering to their medication regimens (4.4 percent ). There were 423 people who did not take their medicine according to their doctor’s instructions (2.6 percent of all patients and 6.8 percent of those who missed more than one appointment). Those who did not take their medication were more likely than those who did to miss their appointments (odds ratio 2.45 [95 percent CI 2.099–2.857]). A single study looked at index-date patient characteristics as well as both types of treatment noncompliance.

People who did not visit the clinic had higher A1c levels. They also had more previous doctor visits and higher Charlson morbidity scores than those who did not. They were also more likely to be smokers and younger than clinic visitors (all P, 0.001). Women (P = 0.001) and smokers (P = 0.014) were more likely to break the rules than people who took medication (as were HbA1c and the number of prior primary care contacts; the Charlson morbidity score was also higher in medication noncompliers than in medication comply).


Patients who did not take their medications or attend clinics had higher crude, unadjusted mortality rates than those who did. When confounding variables were evaluated, it was shown that a diagnosis of medication noncompliance substantially increased the risk of mortality (HR 1.58 [95 percent confidence interval: 1.17–2.14]). There was an elevated mortality hazard of 1.16 (1.04–1.30) for those who missed one to two visits and 1.61 (1.36–1.90) for those who missed three or more appointments. Nonattendance and disobedience with medication instructions demonstrated statistically significant interaction. The interaction implies that the group with both risk factors has a considerably lower risk than the group with the same risk if the effects were additive.

As a consequence, the group with both risk factors had no statistically significant greater risk than the group with just one risk factor. In contrast, the risk would be much larger if the major impacts were cumulative. An additional investigation was done to determine the nature of this interaction further. As nonattendance rose, there was a statistically significant (P = 0.001) monotonic rise in death among medication complying; however, there was no statistically significant change in mortality among medication non-compliant (P = 0.489) as nonattendance grew in the other group. A sensitivity analysis was done on patients who survived at least one month, and both markers of treatment noncompliance were shown to be strongly linked with death in this sample.

Application to practice

Patient education has increased drug adherence across a broad spectrum of illnesses and disease extents. Even if a patient is fully informed, this does not ensure that they will follow recommendations. Patients who are well-prepared and well-informed may better cope with their disease, doctor’s instructions, and any side effects. Individuals who thoroughly grasp their ailment are less prone to get complacent with their care and treatment regimens. A history of noncompliance, a stressful lifestyle and surroundings, a poor socioeconomic position, a lack of social support, a shortage of financial resources, and a weak emotional state are all risk factors for noncompliance. These and other variables may also lead to noncompliance. Noncompliance has been associated to poor clinical results, greater hospitalizations, worse quality of life, and higher healthcare expenses. Between 30 and 50 percent of persons with chronic diseases do not take their prescriptions precisely as recommended. Medication non-adherence is projected to cause 125,000 fatalities, 10 percent of hospitalizations, and $100 billion in yearly healthcare expenses in the United States.

Medication non-adherence can be caused by several factors created by the Massachusetts Medical Society, as depicted in the diagram below. Many of these issues can be addressed by providing targeted education and resources to patients by their nurses. For example, “limited language proficiency” is one factor to consider. A nurse’s job is to ensure that patients receive medication information (such as dosing schedules and instructions, as well as side effects and refill schedules) in the language they understand. Furthermore, nurses can work to ensure that patients can communicate with healthcare providers in the language of their choice. As a result, patients will be able to learn about their illnesses and medications more understandably and openly discuss concerns and questions.


Several studies have found that discharged older adults do not take their medications as directed. Medication regimens for older adults changed during hospitalization and the first week after discharge [8]. Medication adherence has been linked to changes in medication regimens and complex treatment plans. Older adults may have failed to start new medications started during hospitalization or have taken incorrect dosages. Furthermore, patients are not adequately informed about medication changes at discharge. In the days and weeks after release from the hospital, older persons are more likely to fail to comply to their treatment plans. To keep older persons on track with their treatment, healthcare providers, especially community nurses, must routinely check in. Most healthcare facilities employ nurses who are physically near to patients and serve as liaisons between patients and doctors.

Medication adherence and continuity of treatment may be improved by patient education, medication management systems, and electronic monitoring reminders. The impact of post-hospital drug adherence programs have not been studied extensively. An previous Cochrane study looked at a larger variety of strategies to promote medication adherence in diverse patient categories more extensively. Nursing interventions had minimal influence on medication adherence in older persons who have been discharged, regardless of whether they are carried out alone or in partnership with other healthcare providers. This systematic study compares the efficacy of nursing treatments to improve medication adherence among recently released inpatients aged 65 and older, either alone or in combination with other health providers.


An adherent’s behavior is defined by the World Health Organization as “the extent to which a person’s behaviour is consistent with that of a health care practitioner.” The term adherence is used interchangeably with the term compliance; nevertheless, adherence is distinct from compliance. Compliance is defined as the degree to which a patient’s actions match those of the prescriber. An individual’s willingness to comply with an order from their doctor is known as compliance. When it comes to health, the patient and physician work together, integrating the doctor’s medical opinion with the patient’s lifestyle, beliefs, and treatment choices to achieve optimal health outcomes.


Therefore, employing the PICOT format helps portray the factorial RCT approach that is primarily guided by the existing literature. A good RCT is vital in resolving numerous concerns connected to the effectiveness of diabetes therapy. This is highly costly, time-consuming, and also a tough activity. Thus not all issues that may be asking for answers are viable in such a research approach but employing the PICOT structure may still be employed in other study designs. Therefore, it is upon physicians with a research interest to explore employing literature search and PICOT format in interaction with clinical researchers.


Committee on Quality of Health Care in America & Institute of Medicine (2001). Crossing the quality chasm: A new health system for the 21st century. Washington, D.C.D.C.: National Academies Press

Blackburn, D. (., Swidrovich, & Lemstra. (2013). Nonadherence in type 2 diabetes: Practical considerations for interpreting the literature. Patient Preference and Adherence, 183.

Cramer, J. A., Benedict, Á., Muszbek, N., Keskinaslan, A., & Khan, Z. M. (2007). The significance of compliance and persistence in the treatment of diabetes, hypertension, and dyslipidemia: A review. International Journal of Clinical Practice62(1), 76-87.

Currie, C. J., Peyrot, M., Morgan, C. L., Poole, C. D., Jenkins-Jones, S., Rubin, R. R., Burton, C. M., & Evans, M. (2012). The impact of treatment noncompliance on mortality in people with type 2 diabetes. Diabetes Care35(6), 1279-1284.

Grant, R. W., Devita, N. G., Singer, D. E., & Meigs, J. B. (2003). Polypharmacy and medication adherence in patients with type 2 diabetes. Diabetes Care26(5), 1408-1412.

Jimmy, B., & Jose, J. (2011). Patient medication adherence: Measures in daily practice. Oman Medical Journal26(3), 155-159.

Klein K.J., & Sorra, J.S. (1996) The challenge of innovation implementation. The Academy of Management Review 21(4)1055-1080.

Melnyk, B. M., Gallagher-Ford, L., Fineout-Overholt, E., & Sigma Theta Tau International. (2016). Implementing the evidence-based practice (EBP) competencies in healthcare: A practical guide to improving quality, safety, and outcomes.

Ross, S. M. (2019, April 24). How nursing interventions fill a vital need for medication adherence. Blog | Cureatr.

Wayne G. (2019, October 21). Noncompliance nursing diagnosis guide. Nurseslabs.


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