Diabetes - rural - teleconsultation
Introduction
The prevention and control of diabetes is a multifaceted and complex task for the
least developed countries such as Nepal. Despite an excellent hierarchy of health
units at different levels, the service seekers have difficulties accessing even the
basic health services primarily due to difficult topography, economic constraints
and skewed distribution of major health facilities in the urban areas. Moreover, consultation
services on diabetes is an expensive feat for an average Nepalese. According to a
study conducted in selected outpatient clinics of Kathmandu on average, the consultation
fee was approximately US$ 4 per diabetic patient while per visit cost amounted to
US$ 11.[1]
The technological advancements in the field of science and technology have resulted
in alteration of orthodox concept of imparting health care. Today patients and medical
doctors do not have to meet in person for consultation, the use of telemedicine which
may be via telephone or internet has helped connect professional health workers to
the needy population.
In a study designed to evaluate the impact of a tele-assistance system on the metabolic
control of type 2 diabetes patients it was found that the tele-assistance system using
real-time transmission of blood glucose results with an option to make telephone consultations
was feasible in the primary care setting as a support tool for family physicians in
their follow-up of type 2 diabetes patients.[2] The basic functions of the telemedicine system can include tele-monitoring of patient′s
blood glucose data, self-management actions, and remote care from doctors to diabetes
patients.[3] The use of telecommunications backed up by a paraprofessional outreach workers and
an expert medical team of registered nurses and endocrinologists was really useful
in enhancing quality of diabetes care which was manifested in the significant decrease
in glycated hemoglobin to 7.2% from 9.6% (P = 0.001) in a hispanic population of in
United States of America.[4]
Till now there is no study in Nepal that has explored the possibility of using telemedicine
to improve diabetes care. This pilot study was conducted to test the feasibility of
telemedicine in improving the quality of diabetes care in rural Nepal.
Materials and Methods
This study is a comparative-cross sectional study between two groups of diabetes patients.
An interventional group (at Manari Village Development Committee, a rural community
in Makwanpur) was provided with tele-consultation for diabetes care mediated via local
doctor was compared with a non-interventional group/control group (chosen from 23
km away urban area, Hetauda). In total 40 patients were selected for the study, 20
each from the intervention and the non-intervention group were selected purposively
for the study.
Patients coming to Hetauda District Hospital were followed as usual by their local
physician. All participants got regular monitoring of glucose and were given diabetes
self-management education (DSME) both locally by local health care workers and by
team from Kathmandu intermittently.
At the beginning of the study, a diabetes camp was organized in both Manari Primary
Health Care Centre and Hetauda District Hospital. Fasting and postprandial blood glucose
was done on the patients coming to the clinic. A colorimeter was used to do a blood
sugar. People with known diabetes (already on one or more medications) and patients
who fit the diagnosis of diabetes (based on World Health Organization definition of
diabetes[5]) during screening were identified. Patients with diabetes were given option to enroll
in the study and willing patients who consented were enrolled in the study. Patient
below age 30 years and above 70 years and anyone with a history of kidney or liver
disease were excluded. First 20 patients who gave consent to participate in the study
were chosen.
Initially baseline data was collected to obtain information on smoking and alcohol
intake habit, laboratory investigation data, as well as physical activity of the respondents.
Patients were followed up for a year and at the end of the study data baseline date
were recollected. End line data was compared to baseline data. Likewise, data comparison
was done between experimental group and control group.
The project was approved by national health research council. An informed consent
was obtained from each participant. All the forms, formats and questionnaire used
in the study were pre-tested, and necessary modification was done.
Moreover, an initial 1 day workshop was organized for 20 health care workers and seven
doctors on diabetes care from both the groups. Ongoing mentorship and supervision
was provided to local doctor/local health care worker in the intervention group via
tele-technology on medical, nutritional management of diabetes. Local doctor and health
worker team intermittently provided -DSME.
Descriptive statistics was used. Frequency distribution, percentage analysis, means
and standard deviation was used in descriptive statistics. The analysis was carried
out by Statistical Package for Social Science 16.0 (ERAA Biochemistry Analyzer).
Results
The average age of the respondent in the interventional group was 45.3 years with
standard deviation 8.4 years and in the control group was 50.4 years with a standard
deviation 6.4 years [Table 1]. Almost, all the participants from both groups were married. Majority of the respondent
from the interventional group and the control group were Aryan, and rest was Mongols
[Table 2].
Table 1
Age and sex distribution of the respondents in percentage
|
Demographic characteristics
|
Experimental group (n = 20)
|
Control group (n = 20)
|
|
SD: Standard deviation
|
|
Sex
|
|
|
|
Women
|
30.0
|
15.0
|
|
Men
|
70.0
|
85.0
|
|
Age group
|
|
|
|
30-40
|
20.0
|
5.0
|
|
40-50
|
55.0
|
40.0
|
|
50-60
|
15.0
|
40.0
|
|
60 and above
|
10.0
|
15.0
|
|
Mean age±SD
|
45.3±8.4
|
50.4±6.4
|
Table 2
Caste/ethnicity and educational status of the respondents in percentage
|
Socioeconomic characteristics
|
Experimental group (n = 20)
|
Control group (n = 20)
|
|
Caste/ethnicity
|
|
|
|
Aryan
|
80.0
|
85.0
|
|
Mongol
|
20.0
|
15.0
|
|
Educational status
|
|
|
|
Illiterate
|
25
|
20
|
|
Literate
|
75.0
|
80.0
|
Most of the subjects felt, a telemedicine service is less expensive (90%) than the
service they had taken before it, and they felt it was a useful service. Most of them
also reported that telemedicine was significantly cost saving in terms of travel.
All of them reported it is a useful service and felt there is a necessity of such
service in their community, and they highly recommended such service to other similar
communities.
In the interventional group, 30% of respondents had a smoking habit which did not
change even at the end of the study. Alcohol consuming habit was similar in both groups
and remained constant in the intervention group in the end, but interestingly it decreased
in the control group [Table 3].
Table 3
Smoking and alcohol consumption habits of respondents
|
Activity
|
Experimental group (n = 20)
|
Control group (n = 17)
|
|
Baseline
|
End line
|
Baseline
|
End line
|
|
Smoking habit
|
30.0
|
30.0
|
35.3
|
35.3
|
|
Soft drinking habit
|
20.0
|
40.0
|
41.2
|
29.4
|
|
Hard drinking habit
|
15.0
|
15.0
|
41.2
|
23.5
|
In the interventional group, more than half of the respondents were doing regular
exercises which increased by the end of the study. The study results also showed that
percentage of respondents performing strenuous activities like brisk walking, working
in the garden, physical exercise, etc. increased in the intervention group in comparison
to the control group (55% vs. 29%) [Table 4].
Table 4
Utilization of leisure work by the respondents
|
Physical activity of the respondents
|
Experimental group (n = 20)
|
Control group (n = 17)
|
|
Regular exercise
|
55.0
|
70.0
|
47.1
|
70.6
|
|
Utilization of leisure work by the respondent
|
Experimental group (n=20)
|
Experimental group (n=17)
|
|
Activity
|
Baseline
|
End line
|
Baseline
|
End line
|
|
Mild intensity activities
|
10.0
|
0.0
|
0
|
0
|
|
Moderate intensity activities
|
65.0
|
20.0
|
47.1
|
17.6
|
|
Strenuous activities
|
25.0
|
80.0
|
52.9
|
82.4
|
No significant difference was observed between groups in regards to the results of
the laboratory investigation except significant improvements were observed in blood
sugar in the control group and improvement of micro albumin in the intervention group
[Table 5].
Table 5
Laboratory investigation
|
Mean ± SD of the following
|
Experimental group
|
Control group
|
|
Baseline
|
End line
|
Baseline
|
End line
|
|
*Significant at 1%; **Significant at 5%; ***Significant at 10%. aSignificant increase/decrease from baseline to end line in the experimental group;
bSignificant increase/decrease from baseline to end line in the control group; cSignificant increase/decrease from the experimental group to control the group in
the baseline; dSignificant increase/decrease from the experimental group to control the group in
end line. SD: Standard deviation; HDL: High-density lipoprotein; LDL: Low-density
lipoprotein; HBA1C: Glycated haemoglobin; TC: Total cholesterol; TG: Triglyceride,
SGPT: Serum glutamic pyruvic transaminase; PP: Post-prandial
|
|
Blood sugar fastingb**
|
189±94.2
|
171.0±77.0
|
241.7±117.4
|
170.7±62.0
|
|
PPa*,b*
|
295.6±103.0
|
166.3±87.1
|
341±140.2
|
202.5±77.9
|
|
Creatninea*,b*
|
98.0±15.1
|
83.2±15.2
|
96.8±15.6
|
88.8±17.9
|
|
SGPTb**
|
38.3±16.5
|
37.6±24.9
|
42.7±21.3
|
31.6±10.3
|
|
TCa*,b*
|
5.4±1.0
|
4.9±1.0
|
5.6±1.4
|
4.7±1.1
|
|
TGc**,d***
|
2.3±1.0
|
1.9±1.0
|
3.4±2.0
|
3.1±2.4
|
|
HDLa***,c***,d***
|
1.2±0.3
|
1.1±0.2
|
1.1±0.2
|
1.0±0.2
|
|
LDLd**
|
2.8±0.6
|
2.8±1.0
|
2.4±0.9
|
2.0±1.2
|
|
HBA1Cb***
|
8.0±2.0
|
8.9±2.5
|
7.8±2.5
|
8.7±1.9
|
|
Micro albumina***
|
85.9±109.4
|
40.3±60.7
|
54.5±59.0
|
53.4±67.8
|
|
Systolic blood pressured**
|
121.5±23.2
|
122.9±18.2
|
132.9±21.1
|
138.3±22.4
|
|
Diastolic blood pressurec***,d**
|
76.5±11.8
|
74.1±9.9
|
83.8±11.7
|
82.1±12.1
|
|
Weight
|
63.4±11.2
|
62.5±10.6
|
66.6±11.2
|
66.5±11.2
|
Similarly, the knowledge of the respondents on various aspects of the disease was
also found to be better in the interventional group than in the control group [Tables 6]
[7]
[8].
Table 6
Knowledge on diabetes in percentage
|
Meaning of diabetes
|
Experimental group
|
Control group
|
|
Increased sugar in the blood
|
85.0
|
47.1
|
|
Increased sugar in the urine
|
10.0
|
0.0
|
|
Liver failure
|
5.0
|
0.0
|
|
Others
|
5.0
|
52.9
|
|
Part of the body affected
|
|
|
|
Eye
|
100.0
|
88.2
|
|
Heart
|
100.0
|
64.7
|
|
Stroke
|
20.0
|
5.9
|
|
Kidney
|
100.0
|
70.6
|
|
Leg
|
100.0
|
17.6
|
|
Teeth
|
10.0
|
0.0
|
|
Should have to check eye
|
95.0
|
94.1
|
Table 7
Methods of management before telemedicine in the experimental group
|
Methods of management
|
Frequency
|
Percentage
|
|
Taking medicine
|
8
|
40
|
|
Regular exercise
|
4
|
20
|
|
Controlling food habit
|
7
|
35
|
|
Nothing were done
|
2
|
10
|
|
Total
|
20
|
100
|
Table 8
Cost benefit of telemedicine in percentage
|
Cost benefits understanding patients
|
Frequency
|
Percentage
|
|
As same as others
|
2
|
10
|
|
Less expensive than other
|
18
|
90
|
|
Total
|
20
|
100
|
|
Travelling expenses
|
|
|
|
As same as others
|
1
|
5
|
|
Less expensive than other
|
19
|
95
|
|
Total
|
20
|
100
|
It the first telemedicine service experience for the interventional group. In the
interventional group, before implementation of this service, they were attempting
to manage their disease by following means 40% were taking medications, followed by
diet control-35%, regular exercise-20%) and 10% of them did none of it.
Discussion
This study demonstrates that the use of telemedicine in management of diabetes in
rural Nepal is feasible and comparable to treatment as usual in the urban area. The
results do not show much difference between the biochemical parameters between the
interventional and the control group except for the significant improvements observed
in blood sugar in the control group and improvement of micro albumin in the intervention
group. This could be due to small size or short period of the study. This study shows
that the use of telemedicine in the diabetic population will lead to increase physical
activity as well as increased understanding of disease and complications, which could
ultimately translate to better outcome for these patients. Most of the subjects in
this study felt that telemedicine service is less expensive and that it was a useful
service. Most of them also reported that telemedicine was significantly cost saving
in terms of travel. Most of the subjects felt that it is a useful and needed service
which they would readily recommend to other similar communities. This clearly exhibits
that the use of telemedicine is acceptable and useful tool for delivery of diabetic
care in this population.
The finding of this study should be taken with caution as this study is very small
(only 40 subjects).
Conclusion
This pilot study demonstrates that the use of telemedicine in rural Nepal is feasible
and can be useful tool to access specialized services in a rural community, especially
where such services are not available. In future, larger, controlled studies are needed
to exploit the full usefulness of telemedicine, which could been an important tool
in delivery of specialized health care in country like ours where there are lot of
rural communities with limited health care access.
How to cite this article: Bhattarai J, Shakya S, Shrestha N. Pilot study on the effectiveness of telemedicine
in improving the quality of diabetes care of the rural Nepal. J Soc Health Diabetes
2015;3:52-5.
Source of Support: Nil.
