Diabetes Mellitus is a common chronic disease that requires lifelong medical care and control as well as constant patient self-management, education, and support to prevent severe complications and to reduce the incidence of long-term complication
70
. Type II diabetes mellitus is increasingly common, mainly because of increase in the prevalence of a sedentary lifestyle and obesity
1
.
This study evaluates and compares whether an intervention using SMS and telephone call would improve plasma blood glucose levels (HbA
1
c, FBS, PPBS) for three months in patients with type II diabetes mellitus. Similar study was conducted by
Piette
et al
. (2001)
in which patients in a telephone disease management group had a reduction of HbA
1
c during the one year study period
79
.
Hanauer
et al
. (2009)
used email and SMS reminders to support diabetes management and noted a decrease in SMS use after two to three months
74
.
Mahwi
et al
. (2013)
reported that in their study pharmaceutical care provided by pharmacist to type II diabetes mellitus patients yielded a statistically significant reduction in the glycemic level
83
.
Soriano Marcolino
et al
. (2013)
concluded in their findings that in clinical practice, positive motivation and contact through telemedicine should be intensified over time to increase the impact on glycemia
75
.
This study was conducted at the hospital. A total of 135 type II diabetic patients who visited the outpatient diabetic department of the hospital were included in the study. Out of which 40 patients were assigned into the SMS group, 45 patients into the telephone group and 50 patients into the control group. After duration of 3 months, 27 patients from SMS group, 30 patients from telephone group and 24 patients from control group came for review.
The demographic details among the subjects reveals that 29 (34.6%) were males and 52 (65.4%) were females. The percentage of males in SMS, telephone and control group was 37.1, 36.7 and 33.3 respectively and the percentage of females in each of the groups was 62.9, 63.3 and 66.7{Table 1; Figure 1}. The mean age of male among the study population was 50.28±9.05 and that of female was 49.98±10.67 {Table 2; Figure 2}. In SMS group the mean age was found to be 48.85±13.95, the mean age in telephone group was found to be 50.16±8.21 and in control group it was 51.29±11.46 {Table 3; Figure 3}. From a study conducted in Pune, India, it was found that the prevalence of type II diabetes was 4.6% with equal prevalence in both the sex. Greater prevalence in male was found in the age group of > 60 years while in females it was 51-60 years (
Patil
et al
., 2013
)
30
.
Valliyot
et al
. (2013)
reported that those above 50 years of age have five times more chance to get diabetes when compared with those in the 20-30 age groups. Gender did not show any statistical significant relationship with diabetes
31
. A study done by
Deepthi
et al
. (2013)
showed an increase in the prevalence of diabetes with increase in age irrespective of the gender
73
.
From the literacy distribution 53.0% of the patients are in the primary level, 23.5% of the patients are in the secondary level, 21.0% have degree and 2.5% are post graduate {Table 4; Figure 4}. Some studies reported that there is a relationship between literacy and health outcomes. For example
DeWalt
et al
. (2004)
confirmed that low literacy is linked with a series of adverse health outcomes
61
.
Agardh
et al
. (2011)
reported that educational level was most consistently associated with increased possibility of type II diabetes
62
. From all the three groups 50.6% of the patients were housewives, 16.0% of the patients were doing business, 13.6% were professionals, 10.0% were labour, 4.9% were retired and 4.9% were jobless {Table 5; Figure 5}. In women, high job stress and low work social support had a higher risk of type II diabetes compared to those not exposed to work stress, according to
(Heraclides
et al
., 2009)
44
. It was also found that work stress and shift work contributed to the development of type II diabetes in women. In men, the risk was decreased by high work demands, high strain, and an active job
(Eriksson
et al
., 2013)
45
.
Patient’s data were collected for their smoking habits and 13.6% were found to be smokers. Alcohol history of the study population was collected, out of this 1.2% were found to be alcoholics and 6.2% were found to have both the habits {Table 6; Figure 6}.
Majgi
et al
. (2012)
in their study reported that there is no relationship between smoking and alcohol consumption with diabetes
38
.
Kokiwar
et al
. (2007)
concluded that abnormal glucose tolerance was more prevalent among males, physically inactive persons and alcohol consumers
39
. Distribution of patients with activity and those without activity were 30.9% and 69.1% respectively {Table 7; Figure 7}.
Jeon
et al
. (2007)
in their findings stated that those who are regularly engaged in physical activity of moderate intensity had 30% lower risk of type II diabetes as compared with inactive individuals. They also stated that physical activities such as brisk walking can considerably reduce the risk of type 2 diabetes
55
.
Bacchi
et al
. (2013
) did a systemic review and concluded that regular work out improves insulin sensitivity and blood sugar control in individuals with type 2 diabetes and is considered a chief factor in the management of this situation
54
.
Concerned with the duration of diabetes, 7 (8.6%) had an experience of >1 year, 50 (61.7%) had 1-5 years, 20 (24.7%) had 6-10 years, 2 (2.5%) had 11-16 years and 2 (2.5%) had more than 16 years of experience {Table 8; Figure 8}. On considering the complications 17.2% had heart related problems, 20.9% had thyroid disorders, 18.5% had other problems and 44.0% had no complications {Table 9; Figure 9}. Duration of diabetes is often known to be associated with complications of diabetes.
Song (2008)
reported that type II diabetes may be an aggressive disease phenotype to develop cardiovascular complications
37
. Several studies had found that in cardiovascular disease, adherence to medications is low. Over 50% of patients do not take medications as prescribed. Similar study was reported by
Granger
et al
. (2011
)
34
. There was no significant difference in age, gender, duration of diabetes, activity, literacy, occupation and social habits between the three groups. The mean difference between the baseline and review values of HbA
1
c, FBS and PPBS in each group of the study population i.e. SMS, telephone and control were measured and the significant difference produced were compared by paired student t test.
HbA
1
c reflects the average blood glucose levels of the previous six weeks. Glycosylated haemoglobin has developed into a standard measurement of glycaemia and a standard component of diabetes supervision
20
. The baseline value of HbA
1
c in these three study group were found to be respectively 8.25±1.84, 7.84±1.68 and 7.87±1.85. The review values of HbA
1
c in these three groups were found to be 7.70±1.50, 7.16±1.01 and 7.35±1.48 {Table 10; Figure 10}. There was a significant percentage change in HbA
1
c for the SMS (p = 0.023) and telephone group (p = 0.001). But no significant percentage change in HbA
1
c for the control group (p = 0.130) was found {Table 15}.
In this study, HbA1C levels decreased 6.7% in SMS group, 8.7 % in telephone group and 6.6% in the control group after twelve weeks compared with baseline {Table 15}. HbA1C did differ significantly with telephone and control group (p = 0.037) {Table 19}. Previous studies showed the following results:
Zolfaghari
et al
. (2012)
reported that after the three month follow up examination, HbA
1
c level in diabetic patients in SMS and nurse led telephone groups decrease to 1.01% points and 0.93% points respectively
20
.
Seung Kim
et al
. (2006)
in their study revealed that SMS and telephone intervention by a nurse improved HbA
1
c in type II diabetes patients after twelve weeks, with a decrease of 1.1% and 1.2% respectively
6
.
Goodzari
et al
. (2012)
concluded that HbA
1
c levels decreased in experimental group greater than control group after three months compared with two baseline (p = 0/24)
19
.
Seung Kim
et al
. (2007)
revealed that internet based intervention by a nurse in patients with type 2 diabetes resulted in a decline of 1.15% points of HbA
1
c at three months and 1.05% points at six months
33
.
The baseline value of fasting blood sugar in three groups of patients was found to be 154.29±59.00, 129.73±52.20 and 131.80±49.02. The review values in each group of patients were found to be131.59±44.26, 111.60±25.69 and 121.20±39.24 {Table 11; Figure 11}. Fasting blood sugar did differ significantly with telephone and control group (p = 0.011) as well as SMS and telephone group (p = 0.040) {Table 19}. There was a significant percentage change in FBS for the SMS (p = 0.016) and telephone group (p = 0.017). However, there was no significant percentage change found in the control group (p = 0.078). In the telephone, SMS and control group a decrease of 14.7%, 14.0% and 8.0% points were noted respectively, at three months compared with baseline {Table 16}.
Ferror Roca
et al
. (2004)
in their experiment recommended that SMS may provide a easy, quick and efficient accessory to manage diabetes
76
. The present study adds that an educational interventional program using telephone call and SMS improves levels of glycosylated hemoglobin and fasting blood sugar for three months in patients with type II diabetes.
The baseline values of PPBS in the three groups of patients were found to be 222.03±93.20, 226.56±99.90 and 219.09±85.84. The review values in each study group were found to be 206.10±77.00, 187.86±34.30 and 199.18±63.50 {Table 12; Figure 12}. Patients in the telephone group had a decrease of post prandial blood sugar of 17.5% mg/dl at three months compared with baseline in this study. In the SMS group it decreased 6.9% mg/dl and 9.0% mg/dl in the control group {Table 17}. Although PPBS level of the telephone group decreased after intervention, it was still above the target PPBS level.
Ilknur Cinar
et al
. (2010)
revealed that a nurse led telephone intervention may improve glycaemic parameters including HbA
1
c, FBS, PPBS, diet, exercise, medication adherence in patients with type II diabetes mellitus after twelve weeks
64
. In this study, PPBS did differ significantly with telephone and control group (p = 0.047) but did not differ significantly with SMS and telephone group (p = 0.245) as well as SMS and control group (p = 0.480) {Table 19}. There was no significant mean change in PPBS for the SMS group (p = 0.337) and control group (p = 0.704) but a significant percentage change in telephone group was found (p = 0.030) {Table 17}.
This study evaluated patients medication adherence behaviour and satisfaction with and demand for SMS and telephone call service after the intervention. The effect of intervention on medication adherence in the three groups found that there was significant difference between the baseline and review values of the SMS (p = 0.005) and telephone groups (p = 0.002). However, the control group was not found to be significant (p = 0.119). It was observed that there was a mean percentage change of medication adherence in SMS, telephone and control groups and found 5.8, 11.2, 2.5% increase after three months from baseline {Table 18}. It was suggested that beside telephone follow-up, increased disease awareness, positive lifestyle modifications (diet, exercise and drug) could be the reason for improvements in glycaemic parameters
35
.
In several studies like
Ling Huang
et al
. (2013)
88.1% of diabetic patients according to the pre-test reported as frequent missing of medication in the control group, compared with 88.5% of patients in the intervention group. The percentage of patients who earlier missed a dose was 43.7% in the control group and 46.1% in the intervention group, respectively
29
.
Samir Patel
et al
. (2013)
reported that a mobile phone based automated medication reminder system shows promise in improving medication adherence and blood pressure in high cardiovascular risk individuals
46
.
Fenerty
et al
. (2012)
in their study reported that reminder based interventions improved adherence to daily medications. Meta analysis showed a statistically significant rise in adherence in the intervention groups receiving a reminder compared to controls
78
.
In a study about 85% of patients reported that they were pleased with the ATDM intervention and 76% of patient’s reported that they would prefer to receive such calls in the future
(Piette
et al
., 2000)
84
. According to the questionnaire determining the patient satisfaction in this study, it was found that all patients in the SMS group were satisfied with short service message and 93.3% of the patients in the telephone group were satisfied with telephone call {Table 14}.
Ramachandran
et al
. (2013)
stated that their study showed mobile phone messaging is acceptable to the recipients, potentially scalable, could be delivered at low cost and is a part of an alternative strategy
7
.
Samith Shetty
et al
. (2011)
concluded that frequent communication for one year through SMS was satisfactory to patients with diabetes and it helped to improve the health outcome
43
.
At the end of the study, a statistically significant reduction was observed in the HbA
1
c and FBS levels of patients in the telephone and SMS group while a small reduction, which is statistically not significant, was detected in the control group. This result confirms that the use of telemedicine approaches has a positive impact on patient’s glycemic control.
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