The Role of Telenursing in the Management of Diabetes Type 1

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Table of Contents

Introduction
The Intervention
Population Selection Criteria
Chosen Population
Research Findings: Control Group
Research Findings: Intervention Group
Issues with Results
Conclusions
References

Introduction

Diabetes Mellitus is a chronic metabolic disorder that affects the patient’s hormonal and cardiovascular systems, resulting in increased morbidity and mortality rates (Dagogo-Jack, 2017). Although the disease is not as wide-spread as Type 2 diabetes mellitus (t2DM), its frequency of appearance in vulnerable populations increases by roughly 3% a year (Rowley et al., 2017). As it stands, t1DM constitutes about 5% of the entire world DM population, amounting to roughly 20 million reported cases worldwide (Rowley et al., 2017). The number of underreported t1DM cases is currently unknown. Management and maintenance of diabetic patients requires regular hospital visits. Many patients are either unwilling or incapable of reaching hospitals at such a basis. Telemedicine is the solution that could potentially increase the coverage and improve the situation for many t1DM patients in the world.

The Intervention

The solution proposed in the article written by Kotsani et al. (2018) is telenursing. Telenursing is comprised of a set of practices aimed at maintaining appropriate home care without the need to a hospital. These practices include consultation, review of blood analyses taken domestically, provision of training and advice required by patients to manage their symptoms, motivation and reinforcement, and information support on the subject of t1DM (Kotsani et al., 2018). The practice is rooted in Orem’s theory of self-management, and seeks to alleviate the pressure off of hospitals while empowering the patient to exhibit greater autonomy and encourage decision-making when managing one’s own health (Kotsani et al., 2018). In the scope of the reviewed study, the test group received weekly phone calls, received assistance in measuring glucose levels, and was instructed on how to lead a healthier lifestyle.

Population Selection Criteria

Population selection criteria was formulated in regards to the absence of knowledge on the subject as well as the prevalence of the disease among different age groups of people (Kotsani et al., 2018). Since diabetes studies are overwhelmingly focused on the elderly patients, and the average age of an individual with Type 1 DM is between 19 and 39 years old, that diapason was chosen to represent the majority of individuals receiving outpatient care (Kotsani et al., 2018). t1DM affects insulin intake, soliciting different ways of its management. Multiple daily injections (MDI) was the chosen method of self-care, as insulin pumps and continuous glucose intake procedures required less instructions or allowed for limited patient autonomy in the first place (Kotsani et al., 2018).

Chosen Population

The chosen sample included 94 participants, which were split into the intervention and control groups. The reasons why the control group was slightly smaller was because some participants were deemed ineligible or refused to participate (Kotsani et al., 2018). In the intervention group, the average participant age 26.35 years, and 27.63 years for the control group. The average length of enduring diabetes was about 15 years for both. Male and female representation was roughly equal, with 25-23 and 22-24 balance between the two cohorts (Kotsani et al., 2018). The majority of patients were unmarried and living with parents or housemates. Two thirds of the population were students or otherwise unemployed, with only one third having either a part-time or a full-time job. The average morning blood, pre-prandial, and post-prandial blood glucose levels were slightly increased in the intervention group, by roughly 20-30 mg/dl (Kotsani et al., 2018).

Research Findings: Control Group

Control group had patients whose overall glucose levels were lower by 20-30 mg/dl on average (Kotsani et al., 2018). They did not receive the telemedicine intervention reserved for the control group, and operated using the standard routine, which included infrequent visits to the hospital, and self-management of symptoms using the information received during those visits. While their glucose levels were lower than they were in untreated cases, they did not show any significant improvement in reducing glucose levels in one’s blood, throughout the intervention (Kotsani et al., 2018). Such results indicate a skill ceiling for patients trying to manage their symptoms unassisted, which cannot be overcome without additional support (Kotsani et al., 2018).

Research Findings: Intervention Group

Research findings for the intervention group showed remarkable results. Average glucose levels for morning blood sugar dropped from 120 mg/dl to around 93 mg/dl (Kotsani et al., 2018). Pre-prandial glucose levels have dropped from 148 mg/dl to 114 mg/dl, and post-prandial blood glucose levels dropped from 248 mg/dl to 193 mg/dl (Kotsani et al., 2018). These significant blood sugar level decreases were achieved in only 2 months, without invasive procedures or strong medical drugs. As it was discovered, the primary reasons for such results were the increased compliance of patients to the prescribed treatments, increased skill in administering glucose, and the adoption of a healthier way of life (Kotsani et al., 2018). These factors contributed to improvements in the quality of life for the majority of the patients.

Issues with Results

The results presented in the study by Kotsani et al. (2018) provide some evidence of effectiveness of telemedicine for t1DM patients. However, there are some limitations to the interpretation of the results. The primary issue is with the initial glucose levels in patients. It was shown that the test group had, on average, 20-30 mg/dl more glucose than the control group (Kotsani et al., 2018). While the achieved 30-40 mg/dl drop is impressive, it is only 10 mg/dl below the ‘baseline’ established by the control group (Kotsani et al., 2018). It is unclear whether the improvements would be the same had the baseline for the test group been lower. The main reason for the effectiveness of the intervention was associated with the disciplining effect on students and young people, who were found to have notoriously poor in time management and drug intake. It is unclear whether the results would be the same for adult, working, family members (Kotsani et al., 2018).

Conclusions

Based on the results of the study, it could be concluded that telemedicine results in a net improvement for t1DM patients aged 19-39. As it was shown, lifestyle choices and stressors associated with study and part-time work were the primary reasons why most patients did not comply very well with the prescribed treatments. Gender differences had very little effect on the outcomes. Telemedicine provided expertise, information, and a disciplining effect on the target population, resulting in a 30-40 mg/dl drop in blood glucose in all three measured parameters. While the exact scope of influence on the t1DM population is unclear, it could be concluded that telemedicine provides a relatively cheap and widely available option for hospitals to help manage and control outpatient treatment of t1DM patients in the surrounding communities.

References

Dagogo-Jack, S. (2017). Diabetes mellitus in developing countries and underserved communities. New York, NY: Springer International Publishing.

Kotsani, K., Antonopoulou, V., Kountouri, A., Grammatiki, M., Rapti, E., Karras, S.,… & Kotsa, K. (2018). The role of telenursing in the management of Diabetes Type 1: A randomized controlled trial. International Journal of Nursing Studies, 80, 29-35.

Rowley, W. R., Bezold, C., Arikan, Y., Byrne, E., & Krohe, S. (2017). Diabetes 2030: insights from yesterday, today, and future trends. Population Health Management, 20(1), 6-12.

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