**Abstract**

Since the beginning of the 1990s, several telemedicine projects and studies focused on type 1 and type 2 diabetes have been developed, including very few elderly diabetic patients. Several of these projects specifically concerned elderly subjects (n = 4). Mainly, these projects and studies show that telemonitoring diabetes results in improved blood glucose control—a significant reduction in HbA1c, improved patient ownership of the disease, greater patient adherence to therapeutic and hygiene-dietary measures, positive impact on comorbidities (hypertension, weight, dyslipidemia), improved quality of life for patients, and at least good patient receptivity and accountability. To date, the magnitude of its effects remains debatable, especially with the variation in patients' characteristics (e.g., background, ability for self-management, medical condition), sample selection, and approach for treatment of control groups. Over the last 5 years, numerous telemedicine projects based on connected objects and new information and communication technologies (ICT) (elements defining telemedicine 2.0) have emerged or are still under development.

**Keywords:** elderly patient, telemedicine, telemonitoring, diabetes, artificial intelligence, information and communication technology, Web, heart failure, chronic disease

#### **1. Introduction**

Intensive glucose control has been shown to delay or prevent the development of micro- and macrovascular complications related to diabetes, even in elderly diabetic patients. However, it is estimated that 43.2–55.6% of diabetic patients with type 2 diabetes do not meet the reference target for glycemic control (hemoglobin A1c [HbA1c] < 7.0%) [1]. Factors that may contribute to suboptimal blood glucose (BG) control include inadequate home BG monitoring, nonadherence or noncompliance with medications or lifestyle changes (nutrition and sport), suboptimal patient education about the disease, and limited access to health professionals [1–3]. In the absence of timely and accurate data on home BG values, healthcare professionals may be reluctant, rightly so, to aggressively intensify oral hypoglycemic agents or insulin treatments for fear of hypoglycemia [4].

This is particularly true in the elderly, where hypoglycemia can have dramatic consequences, such as myocardial infarction (MI), falls, etc. These patients have a high mortality rate, with 20% of deaths occurring within 5 years after the first cardiovascular event. In this context, patients are often hospitalized, with prolonged and iterative hospitalization [2].

In practice, the main causes of diabetes required medical intervention are related to the following: nontherapeutic adherence and compliance, poor nutrition, and poor adherence to prescribed lifestyle changes and therapy, the decompensation of diabetic comorbidities and macrovascular complication, and community-based infections [2]. In this context, telemedicine may be an effective approach in solving problems of education, compliance, and monitoring and provider access [2, 5]. BG control could be safely improved by basing drug changes on home BG readings and transmitting them in near real time to providers, particularly in elderlies. In this setting, telemedicine may also be an effective solution to monitor the complications of the diabetes, especially macrovascular complications (e.g., MI, heart failure [HF], etc.) and comorbidities (e.g., arterial hypertension).

In this article, we review the literature in the field of telemonitoring (remote monitoring) of diabetic patients, with a focus on elderly diabetic patients.

### **2. First-generation telemedicine projects and studies in the field of diabetes**

Since the early 1990s to the end of 2010, numerous telemedicine projects and studies have been developed in the field of diabetes [6–27]. Practically all of them have investigated *telemonitoring* or *telephone follow*-*up* (defined terms in **Table 1**), especially to monitor BG levels. For the majority of them, they were conducted on specific population of poor controlled type 1 and type 2 diabetic patients, including very few elderly diabetic patients. Several of these projects include specifically elderly diabetic patients (< 80 years old) (n = 1) [21, 27]. Mainly these projects have been developed in children and young people (n = 3), young or mild-age patients with intensified therapy (n = 2), young or mild-age patients under insulin pump therapy (n = 1), and patients with complicated or complex diabetes, including several elderly patients (n = 2) [6–27].

To our knowledge, to date, no project has been published on *tele*-*consultation* and *teleexpertise* (defined terms in **Table 1**) in the area of diabetes domain, as defined under European or French legislation [28]. Several of such projects have been developed, but no formal scientific conclusions are currently available about the usefulness of these telemedicine technologies [29].

It is worth bearing in mind that these projects and studies [6–27], particularly the earlier ones, more closely resembled as a telephone follow-up with care providers (such as a nurse) traveling to the diabetic patient's home rather than telemedicine use as we think of it nowadays with nonintrusive, automated, smart telemonitoring employing remote sensors via modern communication technology (e.g., smartphone) or even artificial intelligence (AI) (**Table 1**) [29]. Thus, they characterize in our opinion *first*-*generation* telemedicine projects and studies.

Using *PubMed* database and *Google Scholar*, we have identified more than 20 reports of first-generation telemonitoring studies in the field of diabetes, including type 1 and type 2 diabetic patients, involving the upload and direct transmission of BG data by diabetic patients to providers via cellular telephone, telephone landline, or a Web-based program [6–27]. The results of these studies were mixed, perhaps because many studies did not target diabetic patients with poor baseline BG control or the interval between glucose transmission and follow-up was delayed or unspecified or mainly with no therapeutic intervention (therapeutic inertia). None of these

**63**

*State of Art of Telemonitoring in Patients with Diabetes Mellitus, with a Focus on Elderly Patients*

**-Telemedicine**: provision of remote patient care and consultation using telecommunication technologies. **-Telemonitoring**: this telemedicine practice allows a healthcare professional to remotely interpret the data necessary for the patient's medical follow-up in order to make decisions about his / her care. Remote data collection from a patient through a connected device or questionnaires to monitor his/her vital parameters

**-Teleexpertise**: this practice of telemedicine consists, for a medical professional, to seek the opinion of one or more medical professional experts regarding elements of the patient's medical file. Remote seeking by a health professional of a second medical opinion via sending of images (scanner, X-ray, eye fundus, etc.) and


**-Artificial intelligence**: this concept makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks. These processes include learning (the acquisition of information and rules for using the information), reasoning (using the rules to reach approximate or definite conclusions) and self-correction. Particular applications of AI include expert systems, speech recognition, and machine vision.

reports evaluated the intensity of intervention required to sustain achieved reduc-

As with CHF, the results of these first-generation telemedicine projects differed from study to study, with fairly inconclusive results as to their potential clinical benefits in terms of balancing diabetes and the associated metabolic problems, re-hospitalization, and decreased morbidity or mortality, particularly regarding the statistical significance of the results [29, 30]. As a consequence, experts have shared now widely divergent opinions on the actual utility of telemedicine in diabetic

To our knowledge, it should be emphasized that the first-generation studies and

• Inappropriate methodologies, involving unsuitable patient groups (such as well-balanced diabetic patients, diabetic patients without any complication) of small-sized patient samples and with very short follow-up periods (between

• Not well-structured follow-up organization, with nonspecialized staff to

• Several alarms arising too late, without therapeutic response (no specified

• The absence of a human interface or contact between the telemedicine solution

Moreover, most of these studies were only based on glycemic control, without including other warning or monitoring parameters related to comorbidities or diabetic complication (e.g., tensiometer, heart rate, balance), with an underutilization

alarms, or without any association of patients' general practitioners, specialists of diabetes management, or endocrinologists nor any optimized management

trials on telemedicine in diabetic patients were at times conducted with [29]:

tions in HbA1c after the implementation of home telemonitoring.

patient management [29, 30].

**Table 1.**

3 months and 1 year)

process or algorithm

and the patients

therapeutic protocol available)

• No associated educational programs

*DOI: http://dx.doi.org/10.5772/intechopen.83384*

and symptoms at home on a daily basis.

sometimes exchange by Internet-based videoconference.

*Glossary of terms and definitions in the field of telemedicine [29].*

is referred to as "Health 2.0" or "Medicine 2.0," and "telemedicine 2.0."

**-Telemedicine**: provision of remote patient care and consultation using telecommunication technologies. **-Telemonitoring**: this telemedicine practice allows a healthcare professional to remotely interpret the data necessary for the patient's medical follow-up in order to make decisions about his / her care. Remote data collection from a patient through a connected device or questionnaires to monitor his/her vital parameters and symptoms at home on a daily basis.

**-Teleexpertise**: this practice of telemedicine consists, for a medical professional, to seek the opinion of one or more medical professional experts regarding elements of the patient's medical file. Remote seeking by a health professional of a second medical opinion via sending of images (scanner, X-ray, eye fundus, etc.) and sometimes exchange by Internet-based videoconference.


**-Artificial intelligence**: this concept makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks. These processes include learning (the acquisition of information and rules for using the information), reasoning (using the rules to reach approximate or definite conclusions) and self-correction. Particular applications of AI include expert systems, speech recognition, and machine vision.

#### **Table 1.**

*Geriatric Medicine and Gerontology*

**diabetes**

longed and iterative hospitalization [2].

etc.) and comorbidities (e.g., arterial hypertension).

usefulness of these telemedicine technologies [29].

This is particularly true in the elderly, where hypoglycemia can have dramatic consequences, such as myocardial infarction (MI), falls, etc. These patients have a high mortality rate, with 20% of deaths occurring within 5 years after the first cardiovascular event. In this context, patients are often hospitalized, with pro-

In practice, the main causes of diabetes required medical intervention are related to the following: nontherapeutic adherence and compliance, poor nutrition, and poor adherence to prescribed lifestyle changes and therapy, the decompensation of diabetic comorbidities and macrovascular complication, and community-based infections [2]. In this context, telemedicine may be an effective approach in solving problems of education, compliance, and monitoring and provider access [2, 5]. BG control could be safely improved by basing drug changes on home BG readings and transmitting them in near real time to providers, particularly in elderlies. In this setting, telemedicine may also be an effective solution to monitor the complications of the diabetes, especially macrovascular complications (e.g., MI, heart failure [HF],

In this article, we review the literature in the field of telemonitoring (remote

monitoring) of diabetic patients, with a focus on elderly diabetic patients.

**2. First-generation telemedicine projects and studies in the field of** 

Since the early 1990s to the end of 2010, numerous telemedicine projects and studies have been developed in the field of diabetes [6–27]. Practically all of them have investigated *telemonitoring* or *telephone follow*-*up* (defined terms in **Table 1**), especially to monitor BG levels. For the majority of them, they were conducted on specific population of poor controlled type 1 and type 2 diabetic patients, including very few elderly diabetic patients. Several of these projects include specifically elderly diabetic patients (< 80 years old) (n = 1) [21, 27]. Mainly these projects have been developed in children and young people (n = 3), young or mild-age patients with intensified therapy (n = 2), young or mild-age patients under insulin pump therapy (n = 1), and patients with complicated or complex diabetes, including several elderly patients (n = 2) [6–27].

To our knowledge, to date, no project has been published on *tele*-*consultation* and *teleexpertise* (defined terms in **Table 1**) in the area of diabetes domain, as defined under European or French legislation [28]. Several of such projects have been developed, but no formal scientific conclusions are currently available about the

It is worth bearing in mind that these projects and studies [6–27], particularly the earlier ones, more closely resembled as a telephone follow-up with care providers (such as a nurse) traveling to the diabetic patient's home rather than telemedicine use as we think of it nowadays with nonintrusive, automated, smart telemonitoring employing remote sensors via modern communication technology (e.g., smartphone) or even artificial intelligence (AI) (**Table 1**) [29]. Thus, they characterize in our opinion *first*-*generation* telemedicine projects and studies. Using *PubMed* database and *Google Scholar*, we have identified more than 20 reports of first-generation telemonitoring studies in the field of diabetes, including type 1 and type 2 diabetic patients, involving the upload and direct transmission of BG data by diabetic patients to providers via cellular telephone, telephone landline, or a Web-based program [6–27]. The results of these studies were mixed, perhaps because many studies did not target diabetic patients with poor baseline BG control or the interval between glucose transmission and follow-up was delayed or unspecified or mainly with no therapeutic intervention (therapeutic inertia). None of these

**62**

*Glossary of terms and definitions in the field of telemedicine [29].*

reports evaluated the intensity of intervention required to sustain achieved reductions in HbA1c after the implementation of home telemonitoring.

As with CHF, the results of these first-generation telemedicine projects differed from study to study, with fairly inconclusive results as to their potential clinical benefits in terms of balancing diabetes and the associated metabolic problems, re-hospitalization, and decreased morbidity or mortality, particularly regarding the statistical significance of the results [29, 30]. As a consequence, experts have shared now widely divergent opinions on the actual utility of telemedicine in diabetic patient management [29, 30].

To our knowledge, it should be emphasized that the first-generation studies and trials on telemedicine in diabetic patients were at times conducted with [29]:


Moreover, most of these studies were only based on glycemic control, without including other warning or monitoring parameters related to comorbidities or diabetic complication (e.g., tensiometer, heart rate, balance), with an underutilization

**Figure 1.** *Results of IDEAtel trial (n = 1665 diabetic elderly patients) (adapted from [21, 27]).*

**65**

**diabetes**

*State of Art of Telemonitoring in Patients with Diabetes Mellitus, with a Focus on Elderly Patients*

of the deployed device [29, 30]. Thus in our opinion, these facts explain that the demonstration of any benefits with these first-generation studies was "illusory," in

Besides these medical considerations, it is worth noting that an economical aspect must be investigated and consolidated in future telemedicine projects to promote the development of telemedicine in diabetes and legitimize it, especially in regard of the budgetary constraints affecting insurance and mutual health insurance companies. Things are less advanced than in the field of chronic heart failure telemonitoring [29]. To our knowledge, only Biermann's study is dedicated to this

To date, none of the learned societies (e.g., *American Diabetes Association* [ADA], *European Society of Diabetes* [ESD]) involved in the topic of diabetes has, to our knowledge, made any formal recommendation as to whether or not telemedicine is of benefit to type 1 or type 2 diabetic patients. This is not the case in the setting of CHF, where factual data and medico-economic studies are more numerous, better documented, and consolidated (more mature field) [29]. In fact, the 2016 *European Society of Cardiology* (ESC) guidelines for the diagnosis and treatment of acute and chronic heart failure have recommended telemonitoring of heart failure

patients with a recommendation grade of IIb and level of evidence B [31].

In the setting of diabetic patients, Shea et al. have conducted the first telemedicine study specifically dedicated to "elderly" diabetic patients (aged 55 years or greater) [21, 27]. It is a randomized, controlled trial comparing telemedicine case management to usual care, with blinding of those obtaining outcome data, in 1665 Medicare recipients with diabetes. In the intervention group (n = 844), mean HbA1c improved over 1 year from 7.35 to 6.97% and from 8.35 to 7.42% in the subgroup with baseline HbA1c ≥ 7% (n = 353) [21]. In the usual care group (n = 821), mean HbA1c improved over 1 year from 7.42 to 7.17%. Adjusted net reductions (1 year minus baseline mean values in each group, compared between groups) favoring the intervention were as follows (all principal criteria): HbA1c, 0.18% (*p* = 0.006); systolic and diastolic blood pressure, 3.4 (*p* = 0.001) and 1.9 mmHg (*p* < 0.001); and LDL cholesterol, 9.5 mg/dL (*p* < 0.001) (**Figure 1**). In the subgroup with baseline HbA1c ≥ 7%, net adjusted reduction in HbA1c favoring the intervention group was 0.32% (*p* = 0.002). Mean LDL cholesterol level in the intervention group at 1 year was 95.7 mg/dL. Mortality was not different between the groups, although power was limited. There were 176 deaths in the intervention group and 169 in the usual care group (hazard ratio 1.01 [0.82, 1.24]).

**3. Second-generation telemedicine projects and studies in the field of** 

Over the last 10 years, *second-generation* telemedicine projects and studies have been developed in the setting of diabetes management, especially in the setting of telemonitoring [32–38], as defined in **Table 1**. These projects and studies have main objectives to evaluate the use of technology to implement medical and cost-effective healthcare management on a large scale for diabetes management. These projects include very few elderly patients. One project, the DiaTel study, was dedicated to elderly diabetic patients (<80 years old) [32]. Compared to the aforementioned project, most of the second-generation projects related to diabetes telemonitoring (for type 1 diabetic patients, n = 1; for type 2, n = 5) incorporate the following [32–38]:

• Self-administered medical questionnaires or forms on symptoms and signs of

diabetes decompensation and BG levels

*DOI: http://dx.doi.org/10.5772/intechopen.83384*

particular in terms of statistical significance.

theme of economical aspect [11].

#### *State of Art of Telemonitoring in Patients with Diabetes Mellitus, with a Focus on Elderly Patients DOI: http://dx.doi.org/10.5772/intechopen.83384*

of the deployed device [29, 30]. Thus in our opinion, these facts explain that the demonstration of any benefits with these first-generation studies was "illusory," in particular in terms of statistical significance.

Besides these medical considerations, it is worth noting that an economical aspect must be investigated and consolidated in future telemedicine projects to promote the development of telemedicine in diabetes and legitimize it, especially in regard of the budgetary constraints affecting insurance and mutual health insurance companies. Things are less advanced than in the field of chronic heart failure telemonitoring [29]. To our knowledge, only Biermann's study is dedicated to this theme of economical aspect [11].

To date, none of the learned societies (e.g., *American Diabetes Association* [ADA], *European Society of Diabetes* [ESD]) involved in the topic of diabetes has, to our knowledge, made any formal recommendation as to whether or not telemedicine is of benefit to type 1 or type 2 diabetic patients. This is not the case in the setting of CHF, where factual data and medico-economic studies are more numerous, better documented, and consolidated (more mature field) [29]. In fact, the 2016 *European Society of Cardiology* (ESC) guidelines for the diagnosis and treatment of acute and chronic heart failure have recommended telemonitoring of heart failure patients with a recommendation grade of IIb and level of evidence B [31].

In the setting of diabetic patients, Shea et al. have conducted the first telemedicine study specifically dedicated to "elderly" diabetic patients (aged 55 years or greater) [21, 27]. It is a randomized, controlled trial comparing telemedicine case management to usual care, with blinding of those obtaining outcome data, in 1665 Medicare recipients with diabetes. In the intervention group (n = 844), mean HbA1c improved over 1 year from 7.35 to 6.97% and from 8.35 to 7.42% in the subgroup with baseline HbA1c ≥ 7% (n = 353) [21]. In the usual care group (n = 821), mean HbA1c improved over 1 year from 7.42 to 7.17%. Adjusted net reductions (1 year minus baseline mean values in each group, compared between groups) favoring the intervention were as follows (all principal criteria): HbA1c, 0.18% (*p* = 0.006); systolic and diastolic blood pressure, 3.4 (*p* = 0.001) and 1.9 mmHg (*p* < 0.001); and LDL cholesterol, 9.5 mg/dL (*p* < 0.001) (**Figure 1**). In the subgroup with baseline HbA1c ≥ 7%, net adjusted reduction in HbA1c favoring the intervention group was 0.32% (*p* = 0.002). Mean LDL cholesterol level in the intervention group at 1 year was 95.7 mg/dL. Mortality was not different between the groups, although power was limited. There were 176 deaths in the intervention group and 169 in the usual care group (hazard ratio 1.01 [0.82, 1.24]).
