Effectiveness of Telemedicine in Type 2 Diabetes Mellitus, Bueng Kan Hospital, Bueng Kan Province,
2.3. Telemedicine
Telemedicine was performed on MohPrompt platform between Bueng Kan Hospital and 14 subdistrict health promotion hospitals in a one-stop service. The hospital information system of the subdistrict health promotion hospitals was on cloud service then the doctor could view and edit electronic medical records including medication prescriptions (Fig. 1). The telemedicine services provide to patients were treatment, follow-up, and teleconsultation.
2.4. Cost of illness
The cost of illness in this study was categorized into direct and indirect costs. The direct cost was divided into medical costs and non-medical costs. The medical cost was determined from both drug and laboratory test costs. The non-medical cost was examined by the meal and travel expenses. The indirect cost was collected from the work absence cost [9].
2.5. Statistical Analysis
The generalized characteristics were described using descriptive statistics, including apercentage for categorical variables. Continuous variables were reported as mean and standard deviation of normally distributed variables and median, interquartile range of non-normally distributed variables. Compared to different HbA1C use the segmented regression analysis [10]. Compared to the divided type of cost of illness using the Wilcoxon Signed-Rank test analysis due to the non-normal distribution of data.
Fig. 1. NCD telemedicine service diagram on cloud.
Table 1. Clinical characteristics of type 2 diabetes patients.
Characteristics Patients(217 cases) Percentage
Sex
Male 15 6.9
Female 202 93.1
Age (years)
35-39 1 0.5
40-44 6 2.8
45-49 10 4.6
50-54 25 11.5
55-59 51 23.5
60-64 48 22.1
65-69 44 20.3
>70 32 14.7
Mean (S.D.) 61.1 (8.1)
Median (IQR) 61 (11.5)
Marital Status
Married 187 86.1
Divorce 16 7.4
Single 14 6.5
Education
No education 18 8.3
Elementary school 100 46.1
Primary school 57 26.3
Junior high school 31 14.3
High school 11 5.0
Table 1. Clinical characteristics of type 2 diabetes patients (cont.)
Characteristics Patients (217 cases) Percentage
Occupation
Farmer 135 62.2
Freelance 45 20.7
No occupation 28 12.9
Merchant 7 3.2
Officialdom 1 0.5
Other 1 0.5
Health Insurance
Universal Coverage (UC) 216 99.5
Civil Servant Medical Benefit Scheme (CSMBS) 1 0.5
Income (Baht)
Mean (S.D.) 6,016.59 (4,191.98(
Median (IQR) 5,000 (3,500)
Comorbidity
Hypertension 17 8.4
Dyslipidemia 52 25.7
Hypertension with Dyslipidemia 133 65.9
Body Mass Index (BMI) (kg/m2) Mean (S.D.) 25.7 (4.9) IQR= Interquartile Range, SD=Standard Deviation
2.6. Ethical issue
This study was conducted after the internal review board and hospital ethics committee approved at Bueng Kan Hospital (BKHEC2022-10).
3. Results
The demographic data of the patients are presented in Table 1. A total of 217 type 2 diabetes patients were treated by telemedicine at Bueng Kan Hospital. Most of the patients were females (93.1%) with the most common age in the range of 55-59 years (23.5%).The majority were married (86.1%) and the most educational level was Elementary school (46.1%). The major occupation was in agriculture (62.2%). Most health insurance is universal coverage (99.5%).
The average income is 5,000 Baht (IQR=3,500).
The co-morbidities were 65.9 percent of hypertension and hyperlipidemia. The mean BMI was 25.7 (±4.9) kg/m2.
Changes in the averaged blood glucose (HbA1C) were analyzed, divided into the period before telemedicine use for the period March 2021-September 2021 (7 months) and the period when telemedicine was used. In the period from
October 2021 to June 2022 (9 months), the data characteristics are shown in Fig. 2. Segmented regression analysis was used.
HbA1C prior to telemedicine was 12.89%
(95% CI: 10.327 to 15.459), with no significant difference in the trends in HbA1C levels (P-value=0.533). After the telemedicine was applied use, it was found that the HbA1C decreased by -2.63% (95% CI -5.210 to -0.047) statistical significantly (P-value < 0.05). The data analysis was shown in Table 2.
In the diabetic complications assessment by assessing hyperglycemic and hypoglycemic coma among 217 patients with type 2 diabetes, there were 3 cases of hyperglycemic coma before telemedicine.After treatment through telemedicine, 2 cases of hyperglycemic coma were found. Exact McNemar significance probability test statistics were used in the analysis, which was not statistically different. (McNemar's Chi-Square
=0.33, p-value 1.000) (Table 3). There are no patients who had hypoglycemic coma before and after telemedicine. In assessing the cost of illness, the study found that the cost of medical care during the time of telemedicine service increased significantly in all categories, including the cost
Fig. 2. Comparison of monthly HbA1C before and after telemedicine.
Table 2. Segmented regression analysis of the difference in HbA1C before and after telemedicine periods.
Parameter Estimation Coefficient Standard
Error
95% CI t P-value
Constant (Intercept) (β0) 12.89 1.31 10.33 to 15.46 9.87 <0.001
Baseline HbA1C trend (β1) 0.18 0.29 -0.39 to -0.75 0.63 0.533
HbA1C change after telemedicine (β2) -2.63 1.31 -5.21 to -0.05 -2.00 0.046*
HbA1C trend change after telemedicine (β3)
-0.13 0.03 -0.18 to -0.07 -4.48 <0.001
CI = Confidence Interval
*p < 0.05 is statistically significant.
Table 3. Comparison of the acute complications before and after telemedicine.
Pre-telemedicine
Telemedicine
total p-value Complication Case )percentage)
hyperglycemia normal
hyperglycemia 1 (50.0( 2 (0.93( 3 (1.38( 1.000
normal 1 (50.0( 213 (99.07( 214 (98.62(
total 2 (100.0( 215 (100.0( 217 (100.0(
of medicines and laboratory tests. The cost of medicine increased by 229.96 baht during the 6-month period, the laboratory cost increased by 173.69 baht during the 6-month period, and the total medical cost increased by 403.66 baht
during the 6-month period (Table 4).
It was also observed that non-medical costs during telemedicine services decreased significantly in all categories, such as meal and transportation costs. The average cost of food for
Table 4. Comparison of cost of illness before and after telemedicine.
Cost of illness Pre-telemedicine Telemedicine
Z p-Value Mean (SD) Median (IQR) Mean (SD) Median (IQR)
Medical cost
Drugs cost 377.60
(327.75)
297 (256.57)
607.56 (407.55)
514.8 (328.05)
-12.24 <0.001 Laboratory testing cost 17.55
(32.81)
11.01 (3.67)
191.24 (43.17)
201.75 (53.90)
-12.74 <0.001 Total medical cost 395.14
(336.04)
313.41 (247.11)
798.80 (414.07)
706.79 (335.86)
-12.70 <0.001 Non-medical cost
Meal cost of patient 115.92 (72.1)
100 (80)
48.59 (92.83)
50 (100)
-9.73 <0.001 Meal cost of relative 133.69
(81.55)
100 (100)
41.06 (74.12)
0 (65)
-10.68 <0.001 Travel expense of patient 207.33
(126.72)
200 (200)
47.56 (74.76)
0 (100)
-11.11 <0.001 Travel expense of relative 212.21
(135.44)
200 (200)
28.25 (45.23)
0 (50)
-11.80 <0.001 Total non-medical cost 669.15
(296.75)
620 (300)
165.46 (169.82)
150 (195)
-12.32 <0.001 Indirect cost
Work absence cost of patient
250 (177.23)
300 (350)
64.98 (119.49)
0 (25)
-10.28 <0.001 Work absence cost of relative 275.51
(205.83)
300 (275)
67.28 (129.87)
0 (0)
-10.58 <0.001 Total indirect cost 522.51
(285.09)
600 (400)
132.26 (200.58)
0 (300)
-11.73 <0.001 The total cost of illness 1586.80
(564.14)
1532.74 (646.62)
1096.52 (510.51)
1009.74 (574.38)
-11.10 <0.001
*p < 0.05 is statistically significant.
patients and relatives was reduced by 67.33 baht, and 92.63 baht, respectively. The average travel expensed for patients was reduced to 159.77 baht, while the average relative travel expensed was reduced by 183.96 baht. Total non-medical costs could be reduced to 503.69 baht (Table 4).
Results of the study on indirect costs revealed that the work absence cost in telemedicine could be reduced in both patients and their relatives statistical significantly. The average loss of patient income was 185.02 baht, the average relative income loss was 208.23 baht, and the total indirect costs were 390.25 baht (Table 4).
The average cost of illness before and after using telemedicine was 1,586.80 baht, and 1,096.52 baht, respectively. The average decrease in the illness cost was 490.28 baht.
4. Discussion
The effectiveness of telemedicine was measured by HbA1C. Telemedicine has a lower HbA1C level than the previous service. This is consistent with the study in Japan during the COVID-19 outbreak. The study showed that telemedicine had a statistically significant reduction in mean HbA1C levels in the presence of base HbA1C above 7% [11]. The study conducted the telemedicine system on people with type 2 diabetes during the COVID-19 pandemic and followed for four months.
Glycemic control was measured using HbA1C before and after telemedicine. It was found that HbA1C before was 9.98±1.3 and after using telemedicine was 8.32±1.3, which was able to reduce statistically significant 1.66±1.29.
(CI=1.43–1.88; P-value<0.001) [6]. Although the HbA1C level of the telemedicine group is lower than the pre-telemedicine, the HbA1C level does not achieve the standard target (HbA1C< 7.0%).
Nevertheless, the trend of HbA1C is continuously declining. If the service is continuously used the HbA1C level may achieve the goal.
There is no difference in the safety of acute diabetic complications. There are few patients that occur with hypoglycemic coma in each group, and these are not statistically significant.
No hyperglycemic coma in both groups is observed. These results are corresponding with the systematic review, the effect of telemedicine was not different in the occurrence of hypoglycemia that had a relative risk=0.59 (95%CI = 0.17-2.05) [12].
In the cost of illness aspect of telemedicine, the total illness cost is lower in the telemedicine group compared to the previous service group.
This result is due to the non-medical direct cost and the indirect cost. The medication and laboratory tests were increased after telemedicine implementation due to high-frequency follow-up and adjusting medication when the A1C was not targeted. This present study confirms the study in Saudi Arabia. This is a retrospective study of patients with type 2 diabetes whose blood sugar levels were uncontrolled. In the study, the HbA1C value greater than 9 was defined as a comparative study, compared to a control group of 100 patients. The average cost was $1,285.27, compared to $1,106.85. Compared to treatment outcomes, HbA1C reduction was 1.82% in telemedicine, and 1.52% in prior service. The Incremental cost-effectiveness ratio (ICER) was
$632.67 per 1% HbA1C reduction [13].
5. Conclusion
The effectiveness of telemedicine in type 2 diabetic patients was greater than the previous service. The safety is not different in the two groups. The total illness cost was lesser in telemedicine because of the non-medical cost and indirect cost. Due to the unreached HbA1C goal, the results of telemedicine treatment should be studied for a longer period until the HbA1C level can reach the controllable threshold.
Telemedicine is suitable for the new normal medical service in type 2 diabetes patients. Due to a large number of people with type 2 diabetes, therefore, the responsibility of caring for patients should be divided into each primary care unit (PCU) or a network primary care unit (NPCU). It should improve the coverage and efficiency of telemedicine services. The extended coverage of this service can improve diabetic control and finally will reduce diabetic complications.
Finally, telemedicine will improve the ultimate goal of Thailand and SDGs.
Conflict of interest
There is no conflict of interest.
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