Web-Based Telemedicine System Is Useful for Monitoring Glucose Control in Pregnant Women with Diabetes

Abstract

Objective:

The aim of this study was to examine the impact of a Web-based telemedicine system for monitoring glucose control in pregnant women with diabetes on healthcare visits, metabolic control, and pregnancy outcomes.

Subjects and Methods:

A prospective, single-center, interventional study with two parallel groups was performed in Puerto Real University Hospital (Cadiz, Spain). Women were assigned to two different glucose monitoring groups: the control group (CG), which was managed only by follow-ups with the Gestational Diabetes Unit (GDU), and the telemedicine group (TMG), which was monitored by both more spaced GDU visits and a Web-based telemedicine system. The number of healthcare visits, degree of metabolic control, and maternal and neonatal outcomes were evaluated.

Results:

One hundred four pregnant women with diabetes (77 with gestational diabetes, 16 with type 1 diabetes, and 11 with type 2 diabetes) were included in the TMG (n=40) or in the CG (n=64). There were no significant differences in mean glycated hemoglobin level during pregnancy or after delivery, despite a significantly lower number of visits to the GDU (3.2±2.3 vs. 5.9±2.3 visits; P<0.001), nurse educator (1.7±1.3 vs. 3.0±1.7 visits; P<0.001), and general practitioner (3.7±2.0 vs. 4.9±2.8 visits; P<0.034) in the TMG. There were no significant differences between groups in maternal or neonatal outcomes.

Conclusions:

A Web-based telemedicine system can be a useful tool facilitating the management of pregnant diabetes patients, as a complement to conventional outpatient clinic visits.

Introduction

Diabetes is one of the most common complications of pregnancy and affects approximately 1% of all pregnant women.^1,2 As the ongoing epidemic of obesity and diabetes has led to an increase in type 2 diabetes mellitus prevalence in women of childbearing age, the number of pregnancies complicated with diabetes is increasing.³ Pregnant women with diabetes (gestational or pregestational) are at significant risk of perinatal morbidity and mortality; therefore, nowadays it is proposed that these patients maintain blood glucose levels as close to normal as possible through changes in lifestyle and insulin when required.^1,2 In this sense, data from two large randomized trials have shown that treating gestational diabetes (GDM) can lead to an improvement in GDM-related complications of pregnancy such as preeclampsia and macrosomia.^4,5

Studies performed outside pregnancy have shown that telemedicine monitoring systems can help to improve blood glucose control and lower glycated hemoglobin (HbA1c) levels in patients with diabetes.^6

–9 In the pregestational and gestational settings, the use of telemedicine could offer the possibility of increasing the access to health care and help to maintain an adequate glycemic control during a relatively short period of time.^10,11 However, there is little information on the efficacy and efficiency of telemedicine applied to pregnant women with diabetes,^12

–18 with the information available for Web-based telemedicine systems for monitoring glucose control in pregnant women with diabetes being anecdotal.^9,11 We hypothesized that a Web-based telemedicine system for monitoring glucose control during pregnancy in women with diabetes can help to maintain an adequate glucose control, without affecting maternal or neonatal outcomes but reducing the number of outpatient visits to healthcare centers.

Research Design and Methods

Research design

We designed a prospective, single-center, interventional study with two parallel groups to examine the impact of a Web-based telemedicine system for monitoring glucose control in pregnant women with diabetes on healthcare visits, metabolic control, and maternal and neonatal outcomes compared with standard care.

Sample characteristics

One hundred four pregnant women with diabetes (77 with GDM, 16 with type 1 diabetes mellitus, and 11 with type 2 diabetes mellitus), 33.8±4.6 years of age, were consecutively recruited among patients assisted at the GDU of the Endocrinology Department of Puerto Real University Hospital (Cadiz, Spain). The inclusion criteria were age over 18 years with diabetes mellitus diagnosed before pregnancy (PGDM) or diabetes diagnosed in the current pregnancy (GDM) referred to our GDU before week 30 of pregnancy. Because, in our area, not all women have access to the Internet at home or feel comfortable using a Web-based telemedicine system to communicate with the hospital, the participants under study could choose to be included in one of two different glucose monitoring groups: the control group (CG), which was managed only by regular visits to hospital (to the GDU and a nurse educator), and the telemedicine group (TMG), which was managed both by more spaced hospital visits and by a Web-based telemedicine system. The study protocol was approved by the local ethical committees and was carried out according to the Declaration of Helsinki. Written informed consent was obtained from each patient.

Methodology

At baseline, all patients were instructed by a nurse educator to follow a personal diet and to self-monitor capillary blood glucose values (between three and six times per day), with goals before meals of <95 mg/dL and 2 h after meals of <120 mg/dL, based on recommendations from the Fifth International Workshop-Conference on GDM.² The need to start insulin therapy was established when, despite the dietary treatment, capillary blood glucose values were higher than established goals twice or more times a week.¹⁹ Glucose control in women in the CG was evaluated personally at our GDU every 2 or 3 weeks until the time of delivery, whereas in women in the TMG, glucose control was evaluated every 2 weeks on a Web-based telemedicine system called “DiabeTIC” and personally at the GDU every 6–8 weeks. All patients were reevaluated in a face-to-face visit between 6 to 12 weeks after delivery. The obstetric care during pregnancy and the decisions on the timing and type of delivery and newborn care were made in the Obstetrics and Paediatrics Departments of Puerto Real University Hospital, regardless of our study.

Telematic diabetes control was conducted through “DiabeTIC,” a Web site specifically designed for monitoring people with diabetes (https://www.diabeticservicios.es). This Web site allows remote and bidirectional communication between health professionals and patients with diabetes, offering the patient the possibility of sending blood glucose values (before and after each meal), insulin doses administered, carbohydrate rations consumed, and other health data, which can then be evaluated remotely by doctors and nurses in an asynchronous manner. Patients and healthcare professionals can write and reply messages, view and modify insulin treatment, obtain metabolic control statistics or treatment reports, and download documents of interest from the Web site library. Furthermore, the system alerts the professional every 2 weeks for monitoring glucose control of patients, and at that time the healthcare professional can decide whether to maintain or modify the treatment of the patient; this decision is always communicated to the patient by e-mail and phone message.

At Visit 0, patient data were collected on age, height, weight before pregnancy and current weight, body mass index (BMI), level of studies, race/ethnicity, Internet access at home, current job, city of residence, duration of diabetes, insulin dose, hypertension and other comorbidities, obstetric history (number of pregnancies, miscarriages, and GDM in previous pregnancies), and use of medications. At each GDU visit, body weight, blood pressure, capillary blood glucose, insulin dose, and HbA1c level were assessed. At the final visit (Week 6–12 after delivery) data were collected on maternal outcomes (weight gain during pregnancy, pregnancy-induced hypertension, insulin treatment, week and type of delivery, hospital stay), neonatal outcome (sex, height, weight, miscarriages, neonatal hypoglycemia, and other metabolic complications), metabolic outcome (medium HbA1c value during pregnancy and HbA1c value after delivery), and healthcare visits outcome (number of patients' visits to the GDU, obstetrics department, nurse educator, acute admissions, ambulatory nurse, general practitioner, and online visits). Neonatal hypoglycemia was defined as a blood glucose level of <40 mg/dL. Infants were considered large or small for gestational age when the birth weight was greater than the 90^th percentile or lower than the 10^th percentile, respectively.

Statistical analysis

Sample size was estimated by assuming the hypothesis that the telemedicine intervention would not be inferior to standard therapy. A primary end-point difference was detecting more than a 20% difference in HbA1c of patients achieving HbA1c values <5.7%. Given these assumptions, 38 patients per group were needed to ensure a statistical power of 80% (α=0.05). Taking into account a dropout rate of 5%, 40 patients per group had to be enrolled. Data were coded, entered, and analyzed using SPSS version 12.0 for Windows software (SPSS, Inc., Chicago, IL). The descriptive analysis of qualitative variables was performed by calculating frequencies and percentages, and by quantitative variables was determined including the mean, SD, median, and range. After verification of the normality assumption in the sample by the Shapiro–Wilk test, the following tests were performed: to compare quantitative variables between independent groups, Student's t test (two groups) or analysis of variance (more than two groups); and to compare qualitative variables between independent groups, the χ² test and, when indicated, Fisher's exact test. All significant values refer to the two-tailed test, considering that the association is statistically significant if P<0.05.

Results

One hundred four pregnant women with diabetes gave their informed consent and initiated the study; 38.5% of patients (n=40) were included in the TMG, and 61.5% of patients (n=64) were included in the CG (face-to-face at the GDU). Data collection occurred over a 18-month period, from March 2012 to August 2013. Ninety-three patients (89.4%) completed the study, with similar losses between groups (nine losses from the CG vs. two losses from the TMG; P=0.144), including four miscarriages (two in each group). Most patients had GDM (n=77; 74% of patients), half of them were primiparous (n=54; 51.4% of patients), and most of them lived at a considerable distance from the hospital (22.8±18.4 km average from the city where the patient lived to the hospital). Basal clinical characteristic are shown in Table 1.

Table 1.

Characteristics of Patients Participating in the Study (n=104)

Clinical characteristic	Total (n=104)	TMG (n=40)	CG (n=64)	P
Mean age (years)	33.8±4.6	34.9±3.9	33.2±4.9	0.054
Race/ethnicity				0.385
White	100 (96.2%)	39 (97.5%)	61 (95.2%)
Hispanic	2 (1.9%)	1 (2.5%)	1 (1.6)
North African	2 (1.9%)	0 (0.0%)	2 (3.2%)
Type of diabetes				0.677
Pregestational type 1 diabetes	16 (15.4%)	7 (17.5%)	9 (14.1%)
Pregestational type 2 diabetes	11 (10.6%)	3 (7.5%)	8 (12.5)
GDM	77 (74.0%)	30 (75.0%)	47 (73.4%)
Mean diabetes evolution (years)^a	9.9±8.4	10.7±9.2	9.4±8.2	0.718
University studies (%)	23 (22.1%)	14 (35.0%)	14 (21.8%)	0.013
Internet at home	98 (94.2)	40 (100%)	58 (90.6%)	0.673
Currently working (%)	39 (37.5%)	16 (40.0%)	23 (35.9%)	0.446
Distance from patient's home to hospital (km)	22.9±17.3	25.4±19.8	21.3±15.6	0.245
Prepregnancy BMI (kg/m²)	28.5±7.7	27.7±8.9	28.9±6.8	0.457
Hypertension (%)	5 (4.8%)	4 (10.0%)	1 (1.6%)	0.076
Primiparous (%)	54 (51.9%)	19 (47.5%)	32 (51.6%)	0.420
Prior GDM (%)	20 (19.2%)	7 (24.1%)	13 (27.7%)	0.476
Prior miscarriages (%)	36 (34.6%)	12 (30.0%)	24 (37.5%)	0.247
Visit 0 at GDU (week of pregnancy)	21.1±9.6	22.3±9.8	20.2±9.5	0.292

Results are expressed as mean±standard deviation values.

Only for patients with pregestational diabetes.

BMI, body mass index; CG, control group; GDM, gestational diabetes mellitus; GDU, Gestational Diabetes Unit; TMG, telemedicine group.

Globally, there were no significant differences in mean HbA1c during pregnancy (5.6±0.6% vs. 5.6±0.5%; P=0.821) or after delivery (5.7±0.6% vs. 5.7±0.7%; P=0.966) between groups or among patients with GDM or PGDM included in the CG or TMG (Table 2). However, women with GDM in the TMG required insulin therapy less frequently than women in the CG (15% vs. 32.8%; P=0.023) (Table 3).

Table 2.

Metabolic Control During Pregnancy and After Delivery in the Study (n=104)

	HbA1c values (%)
Patient group	Baseline	Medium during pregnancy	After delivery
All (n=104)	5.8±0.8	5.6±0.5	5.7±0.6
TMG (n=40)	5.7±0.7	5.6±0.6	5.7±0.6
CG (n=64)	5.8±0.9	5.6±0.5	5.7±0.7
GDM (n=77)	5.4±0.4	5.4±0.3	5.5±0.3
TMG (n=30)	5.4±0.3	5.4±0.3	5.4±0.3
CG (n=47)	5.4±0.4	5.4±0.4	5.4±0.3
PGDM (n=27)	6.8±0.8	6.2±0.6	6.3±0.3
TMG (n=10)	6.6±0.6	6.3±0.6	6.3±0.5
CG (n=17)	6.8±0.9	6.1±0.5	6.3±0.7

CG, control group; GDM, gestational diabetes mellitus; HbA1c, glycated hemoglobin; PGDM, diabetes mellitus diagnosed before pregnancy; TMG, telemedicine group.

Table 3.

Maternal, Neonatal, and Visit Outcomes in Patients of the Study (n=104)

Outcome	Total (n=104)	TMG (n=40)	CG (n=64)	P
Maternal
Time of delivery (gestational weeks)	38.2±1.7	37.8±2.1	38.4±1.4	0.083
Delivery before 37 weeks (%)	8 (7.7%)	3 (7.5%)	5 (7.8%)	0.175
Cesarean delivery (%)	38 (36.5%)	12 (30.0%)	26 (40.6%)	0.164
Weight gain (kg)	8.8±6.5	8.4±6.5	9.0±6.6	0.644
GDM with insulin treatment (%)	27 (25.9%)	6 (15.0%)	21 (32.8%)	0.023
Pregnancy-induced HT (%)	5 (4.8%)	2 (5.0%)	3 (4.7%)	0.966
Hospital stay (days)	4.7±3.6	4.8±4.0	4.6±3.4	0.879
Neonatal
Miscarriages (%)	2 (1.9%)	2 (5.0%)	0 (0.0%)	0.093
Birth weight (g)	3,159±481	3,077±570	3,213±411	0.195
Large for gestational age (%)	11 (10.6%)	5 (12.5%)	6 (9.4%)	0.660
Small for gestational age (%)	6 (5.8%)	3 (7.5%)	3 (4.7%)	0.581
Newborn males (%)	50 (48.1%)	18 (45.0%)	32 (50.0%)	0.695
Hypoglycemia (%)	3 (2.9%)	1 (2.5%)	2 (3.1%)	0.646
Other neonatal complications (%)	3 (2.9%)	0 (0.0%)	3 (4.7%)	0.189
Health visits (n) to
GDU	4.8±2.7	3.2±2.3	5.9±3.2	<0.001
Nurse educator	2.5±1.6	1.7±1.3	3.0±1.7	<0.001
Obstetric service	6.7±2.4	6.4±2.7	7.0±2.3	0.263
Hospital emergency	2.7±1.9	2.3±1.5	2.9±1.1	0.184
General practitioner	4.4±2.7	3.7±2.0	4.9±2.8	0.034
Ambulatory nurse	6.1±1.6	6.4±1.8	5.9±1.5	0.215
Online	2.2±4.7	6.3±6.1	0.0±0.0	<0.001

Results are expressed as mean±SD values or number (%) as indicated.

CG, control group; GDM, gestational diabetes mellitus; GDU, Gestational Diabetes Unit; HT, hypertension; TMG, telemedicine group.

Table 3 shows main maternal, neonatal, and healthcare visits outcomes. We did not detect differences in maternal or neonatal outcomes between groups globally or for type of diabetes. Rates of cesarean delivery were increased in both groups but were higher among women in the CG, although this difference did not reach statistical significance (P=0.164). Neonates born from mothers in the TMG group tended to have fewer metabolic complications than neonates from mothers in the CG, but none of these differences was statistically significant.

Finally, patients included in the TMG had a significantly lower number of visits to the GDU (3.2±2.3 vs. 5.9±2.3 visits; P<0.001), nurse educator (1.7±1.3 vs. 3.0±1.7 visits; P<0.001), and general practitioner (4.9±2.8 vs. 3.7±2.0 visits; P<0.001) than patients included in the CG. Globally, patients included in the TMG had more visits for assessment of glycemic control (visits to the GDU and nurse educator and online visits) than women included in the CG, although this difference was not statistically significant (10.9±7.9 vs. 9.0±3.5; P=0.123).

Discussion

A woman with GDM is generally diagnosed at approximately 24–28 weeks of gestation, leaving only 12–16 weeks to obtain an adequate metabolic control, with being this interval theoretically greater in women with PGDM. Although the frequency of follow-ups in these women has not yet been standardized, generally an intensive glucose assessment with visits every 1 or 2 weeks is recommended.^2,19 In this short period of time, application of telemedicine to achieve an strict glycemic control might be an useful and complementary tool to face-to-face assessments, by reducing the number of outpatient clinic visits, especially in women who have difficulty accessing healthcare centers for social or professional reasons.^10,20

In our study, women in the TMG used an specific Web site that allowed the transmission of glucose values, clinical information, or messages directly to their healthcare team, and they could receive information and advice about glucose control and treatment in an asynchronous manner, whereas women in the CG reported their blood glucose records in logbook format, which were reviewed at the GDU visits. Both groups of women achieved similar levels of glycemic control as well as maternal and neonatal outcomes, but women in the TMG had a significant lower outpatient clinic visits to the GDU, nurse educator, and general practitioners than women in the CG. Our results are consistent with previous studies that also found no impact on the use of technology on maternal or neonatal outcomes in women with GDM^13

–16 or PGDM.^12,17,21 However, most of these studies used telephones, modems, or glucometers capable of transmitting data via the Internet, and the telemedicine studies performed with a specific Web site designed for patients with diabetes are exceptional.^9,11,13 Homko et al.¹³ reported, in a group of 80 women who were randomized to either the Internet intervention group (in a Web site) or the CG, no significant differences in pregnancy outcomes between the two groups, but system utilization and contact between women with GDM and their healthcare providers were increased. A Spanish study from 2010¹⁴ also displayed no benefit from their intervention group versus a CG with their designed telemedicine system based on weekly transmission of capillary glucose data and text messages with professional feedback. There was, however, a large reduction in the number of face-to-face visits of 62% and 82.7% in the subgroups of insulin-treated patients.²²

Interactive Internet systems have been demonstrated to be beneficial in glycemic control, as well as a motivational support.²⁰ In this sense, other studies have reported that pregnant women using telemedicine system support had significantly higher feelings of diabetes self-efficacy and patient satisfaction.^23
–25 We did not examine the impact of our telemedicine system on patient satisfaction, but in a previous study using the same Web-based telemedicine system we demonstrated that patients with diabetes followed by the Web site “DiabeTIC” communicated a high degree of satisfaction.⁹ It is possible that the increased and facilitated contact and feedback with the healthcare team through telemedicine systems would enhance patient satisfaction and adherence to the diabetes self-management regimen, leading to improved glucose control,^9,10,20 and perhaps this is the main reason for a lower insulin treatment rate observed in our patients with GDM included in the TMG. Furthermore, patients with diabetes using telemedicine systems greatly benefit from a supervised diabetes self-management as well as a reinforcement of the decisions regarding diabetes treatment, such as insulin dose adjustments.^9,13,25

Our study has several limitations. First of all, the sample size is small, and the selected women were not randomized and could choose between the CG and TMG. In our area, although there are facilities for computers and Internet access, gaps still exists, particularly among rural or more disadvantaged populations. Other women, particularly those with a lower educational level, do not feel comfortable using a Web-based telemedicine system to communicate with the hospital and prefer being directly assisted at the GDU, coinciding with the visit to the obstetric clinic. Despite this limitation, there was no difference in basal clinical or metabolic characteristics between groups or in obstetric monitoring (although income was not evaluated), which could have interfered the study results, despite having more frequently secondary school studies. In this sense, other studies have also reported that the extent of the use of the telemedicine system is highly dependent on the woman's cultural and social level.²⁰ Second, we cannot prove that our telemedicine system, which is totally Internet based, is better than other systems based simply on telephone calls or glucometers capable of transmitting data. However, a telemedicine system based on a diabetes-specific Web site has important benefits as it enables viewing or modifying the treatment schedule by both the patient and the healthcare team, obtaining metabolic control statistics or treatment reports, downloading documents of interest from the Web site library, or being able to send automatic reminders if women failed to transmit their data as scheduled.¹³ We need large prospective randomized studies to check the optimal communication and monitoring system for patients with diabetes.

We conclude that a Web-based telemedicine system can be a tool facilitating the management of pregnant diabetes patients requiring tight glycemic control, as a complement to conventional outpatient clinic visits, especially in cases with difficulties in accessing the medical center, and could contribute to reducing the number of outpatient visits.

Footnotes

Author Disclosure Statement

No competing financial interests exist.

Acknowledgments

This study was partially supported by a research grant titled “Innovation in chronic patient care” from the laboratory of Dr. A. Esteve.

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