**1. Introduction**

[14] Field MJ. Telemedicine: a guide to assessing telecommunication in healthcare. J Digit

Imaging. 1997;10 (3 Supp;1):28

42 Telemedicine

Worldwide, diabetes has become an overwhelming problem due to the increase of over‐ weightness and obesity. As estimated by WHO in 2011 [1], 346 million people globally suffer from diabetes and there is an approximate 3,4 million mortality rate from the consequences of DMT. WHO predicts that diabetes related deaths will double by 2030. Throughout the course of time, diabetes damages the heart, blood vessels, eyes, kidneys, and nerves. Indeed, 50% of people with diabetes die due to cardiovascular disease (primarily heart disease and stroke). Reduced blood flow and neuropathic pain can increases the chances of complications such as ulcers and even limb amputations. Diabetic retinopathy represents a significant cause of blindness, as a consequence of damage to blood vessels in the retina. 2% of diabetics become blind after 15 years. Diabetes can result in neuropathy, whose common symptoms are tingling, pain, numbness, or weakness both in feet and hands. Diabetes is the seventh leading cause of death in the US [2]. These complications are very important determinants of quality of life. Low QoL may, in turn, affect metabolic control by reducing regimen adherence. Treatment of diabetes involves lowering blood glucose and the levels of other known risk factors that could damage blood vessels. Lifestyle measures, such as the control of body weight, physical activity, a healthy diet and avoidance of tobacco use, have been shown to be effective in preventing the onset of type 2 diabetes.

In addition, estimated global healthcare expenditures to treat and prevent diabetes and its complications total at least \$376 billion in 2010. By 2030, this number is projected to exceed some USD490 billion. Expressed in International Dollars (ID), which correct for differences in purchasing power, estimated global expenditures on diabetes was ID418 billion in 2010, and it will be at least ID561 billion in 2030. An estimated average of USD703 (ID878) per person

© 2013 Corti et al.; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 Corti et al.; licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

will be spent on diabetes in 2010 globally [3]. Besides excess healthcare expenditure, diabetes also imposes large economic burdens in the form of lost productivity and foregone economic growth. The American Diabetes Association estimated that the US economy lost USD58 billion, equivalent to about half of the direct healthcare expenditure on diabetes in 2007, as a result of lost earnings due to lost work days, restricted activity days, lower productivity at work, mortality and permanent disability caused by diabetes [4]. The largest economic burden, therefore, is the monetary value associated with disability and loss of life as a result of the disease itself and its related complications. This economic burden, however, can be reduced by implementing many inexpensive, easy-to-use interventions, most of which are costeffective or cost-saving. Advancement in treatment for diabetes have resulted in reduced lengths of hospital stay and, in some cases, the avoidance of hospital visits, so the demand for home care services has increased [5]. Health-care providers can deliver home care services by visiting the patient at home or by using information and communication technology, also known as telehealth or telemedicine.

as hospitalization and mortality than are physiologic and metabolic measures (such as the presence of complications, BMI and HbA1c)[16]. Greater attention is now being devoted to evaluating the quality of health care and the economic value associated with new interventions. Managed care organizations have stimulated a growing effort to determine whether the costs associated with new or existing therapies and educational interventions are justified within fairly short time frames, often less than 3 years. Quality of life is a multidimensional construct comprising the individual's subjective perception of physical, emotional and social well-being, including both a cognitive component (e.g. satisfaction) and an emotional component (e.g. happiness)[17]. In addition to overall or global quality of life there are many specific subdomains (e.g. health, job, family, friends, community, etc.). Some research on the impact of health on quality of life has examined the impact of domain-specific satisfaction on global life satisfaction. There has been substantial research on the effect of objective health status on overall life satisfaction or on a global measure of health-related quality of life. Yet, while the objective dimension of health status (as assessed by physicians' reports of symptoms or the presence of complications, for instance) is important, the patient's subjective perceptions of health translate the objective facts of his or her health status into an actual quality of life experience. This view is generally endorsed by researchers in this field [18-20] who point out that since expectations regarding health and the ability to cope with limitations and disability can greatly affect a person's perception of health and satisfaction with life, two people with the same objective health status may have a very different quality of life [21]. There is also general consensus that various domains of functioning and well-being can each contribute independently to global quality of life, thus making multidimensional measurement of quality of life necessary [19]. Simply asking one question, such as 'please rate your overall healthrelated quality of life on a scale from 0 to 100', may provide a useful global assessment, but it does not identify the underlying dimensions which contribute to the overall or health-specific quality of life [21]. Thus, almost all quality of life research involving people with diabetes employs multidimensional assessment of quality of life and typically assesses several dimen‐

Quality of Life in Telemedicine-Based Interventions for Type-2 Diabetes Patients: The TECNOB Project

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45

sions, including physical, psychological, and social functioning and well-being.

Two broad approaches to health-related quality of life measurement have emerged – generic anddisease-specific.Thegenericapproachinvolves theuseofmeasuresapplicableacrosshealth and illness groups. The most widely used generic measure of quality of life in studies of people with diabetes is the Medical Outcomes Study (MOS) Short-Form General Health Survey [22], in its several forms (SF-36, SF-20, SF-12). The MOS instrument includes physical, social and role functioning scales to capture behavioural dysfunction caused by health problems. Measures of mental health, perceptions of overall health, and pain intensity reflect more subjective compo‐ nents of health and general well-being. The authors of this measure claim that these six health concepts are comprehensive in terms of those aspects of health considered most important to patients [23]. These instruments have been translated into many languages, and used in these forms in studies which include people with diabetes. The Rand Quality of Well-Being Self-Administered (QWB-SA) survey [24] is similar to the SF-36 in its aim to comprehensively assess health-related well-being or quality of life. It contains scales designed to measure acute and chronic emotional and physical symptoms, mobility, and physical activity. Other instruments used at least occasionally to assess general health status in people with diabetes include the

### **2. Quality of life in diabetic population**

In the past two decades, research has increasingly highlighted quality of life (QoL) as an important health outcome in diabetes, if not the 'ultimate goal' of treatment [6, 7]. In recent years, there has been a burgeoning interest in quality of life issues, and especially in healthrelated quality of life, fueled by several factors, including a growing body of evidence concerning the potent effect of psychosocial factors on physical health outcomes, and dramatic changes in the organization and delivery of health care. People with diabetes often feel challenged by their disease and its day-to-day management demands. And these demands are substantial. Patients must deal with their diabetes all day, every day, making countless decisions in an often futile effort to approximate the non-diabetic metabolic state. Diabetes therapy, such as taking insulin, can substantially affect quality of life either positively, by reducing symptoms of high blood sugar, for instance, or negatively, by increasing symptoms of low blood sugar, for example. The psychosocial toll of living with diabetes is often a heavy one, and this toll can often, in turn, affect self-care behaviour and, ultimately, long-term glycaemic control, the risk of developing long-term complications, and quality of life. Psycho‐ logical adjustment to chronic disease embraces emotional, cognitive and behavioural dimen‐ sions. Several adaptation tasks need to be accomplished, such as negative and positive affective self-regulation, daily functioning contingent to treatment needs and the reformulation of beliefs and expectancies about health and disease, self and others, life and death. It is a complex dynamic process for someone with a chronic disease [8-10]. The daily psychological stress of living with a chronic disease in a world with professional and interpersonal challenges and specific diabetes-related psychological distress, associated with repetitive intrusive treatment regimens or disabling chronic complications are two correlated sources of stress in people with DMT2 [11-13]. There is good evidence that psychosocial issues are critical to good diabetes care [14, 15]. Psychosocial factors often determine self-management behaviours, and psycho‐ social variables (such as depression) are often stronger predictors of medical outcomes such as hospitalization and mortality than are physiologic and metabolic measures (such as the presence of complications, BMI and HbA1c)[16]. Greater attention is now being devoted to evaluating the quality of health care and the economic value associated with new interventions. Managed care organizations have stimulated a growing effort to determine whether the costs associated with new or existing therapies and educational interventions are justified within fairly short time frames, often less than 3 years. Quality of life is a multidimensional construct comprising the individual's subjective perception of physical, emotional and social well-being, including both a cognitive component (e.g. satisfaction) and an emotional component (e.g. happiness)[17]. In addition to overall or global quality of life there are many specific subdomains (e.g. health, job, family, friends, community, etc.). Some research on the impact of health on quality of life has examined the impact of domain-specific satisfaction on global life satisfaction. There has been substantial research on the effect of objective health status on overall life satisfaction or on a global measure of health-related quality of life. Yet, while the objective dimension of health status (as assessed by physicians' reports of symptoms or the presence of complications, for instance) is important, the patient's subjective perceptions of health translate the objective facts of his or her health status into an actual quality of life experience. This view is generally endorsed by researchers in this field [18-20] who point out that since expectations regarding health and the ability to cope with limitations and disability can greatly affect a person's perception of health and satisfaction with life, two people with the same objective health status may have a very different quality of life [21]. There is also general consensus that various domains of functioning and well-being can each contribute independently to global quality of life, thus making multidimensional measurement of quality of life necessary [19]. Simply asking one question, such as 'please rate your overall healthrelated quality of life on a scale from 0 to 100', may provide a useful global assessment, but it does not identify the underlying dimensions which contribute to the overall or health-specific quality of life [21]. Thus, almost all quality of life research involving people with diabetes employs multidimensional assessment of quality of life and typically assesses several dimen‐ sions, including physical, psychological, and social functioning and well-being.

will be spent on diabetes in 2010 globally [3]. Besides excess healthcare expenditure, diabetes also imposes large economic burdens in the form of lost productivity and foregone economic growth. The American Diabetes Association estimated that the US economy lost USD58 billion, equivalent to about half of the direct healthcare expenditure on diabetes in 2007, as a result of lost earnings due to lost work days, restricted activity days, lower productivity at work, mortality and permanent disability caused by diabetes [4]. The largest economic burden, therefore, is the monetary value associated with disability and loss of life as a result of the disease itself and its related complications. This economic burden, however, can be reduced by implementing many inexpensive, easy-to-use interventions, most of which are costeffective or cost-saving. Advancement in treatment for diabetes have resulted in reduced lengths of hospital stay and, in some cases, the avoidance of hospital visits, so the demand for home care services has increased [5]. Health-care providers can deliver home care services by visiting the patient at home or by using information and communication technology, also

In the past two decades, research has increasingly highlighted quality of life (QoL) as an important health outcome in diabetes, if not the 'ultimate goal' of treatment [6, 7]. In recent years, there has been a burgeoning interest in quality of life issues, and especially in healthrelated quality of life, fueled by several factors, including a growing body of evidence concerning the potent effect of psychosocial factors on physical health outcomes, and dramatic changes in the organization and delivery of health care. People with diabetes often feel challenged by their disease and its day-to-day management demands. And these demands are substantial. Patients must deal with their diabetes all day, every day, making countless decisions in an often futile effort to approximate the non-diabetic metabolic state. Diabetes therapy, such as taking insulin, can substantially affect quality of life either positively, by reducing symptoms of high blood sugar, for instance, or negatively, by increasing symptoms of low blood sugar, for example. The psychosocial toll of living with diabetes is often a heavy one, and this toll can often, in turn, affect self-care behaviour and, ultimately, long-term glycaemic control, the risk of developing long-term complications, and quality of life. Psycho‐ logical adjustment to chronic disease embraces emotional, cognitive and behavioural dimen‐ sions. Several adaptation tasks need to be accomplished, such as negative and positive affective self-regulation, daily functioning contingent to treatment needs and the reformulation of beliefs and expectancies about health and disease, self and others, life and death. It is a complex dynamic process for someone with a chronic disease [8-10]. The daily psychological stress of living with a chronic disease in a world with professional and interpersonal challenges and specific diabetes-related psychological distress, associated with repetitive intrusive treatment regimens or disabling chronic complications are two correlated sources of stress in people with DMT2 [11-13]. There is good evidence that psychosocial issues are critical to good diabetes care [14, 15]. Psychosocial factors often determine self-management behaviours, and psycho‐ social variables (such as depression) are often stronger predictors of medical outcomes such

known as telehealth or telemedicine.

44 Telemedicine

**2. Quality of life in diabetic population**

Two broad approaches to health-related quality of life measurement have emerged – generic anddisease-specific.Thegenericapproachinvolves theuseofmeasuresapplicableacrosshealth and illness groups. The most widely used generic measure of quality of life in studies of people with diabetes is the Medical Outcomes Study (MOS) Short-Form General Health Survey [22], in its several forms (SF-36, SF-20, SF-12). The MOS instrument includes physical, social and role functioning scales to capture behavioural dysfunction caused by health problems. Measures of mental health, perceptions of overall health, and pain intensity reflect more subjective compo‐ nents of health and general well-being. The authors of this measure claim that these six health concepts are comprehensive in terms of those aspects of health considered most important to patients [23]. These instruments have been translated into many languages, and used in these forms in studies which include people with diabetes. The Rand Quality of Well-Being Self-Administered (QWB-SA) survey [24] is similar to the SF-36 in its aim to comprehensively assess health-related well-being or quality of life. It contains scales designed to measure acute and chronic emotional and physical symptoms, mobility, and physical activity. Other instruments used at least occasionally to assess general health status in people with diabetes include the

Sickness Impact Profile [25] and the Nottingham Health Profile [26]. Generic measures like the SF-36 are most useful for comparing quality of life in people with different diseases and the qualityoflifeinpeoplewhohavenodiseaseswiththequalityoflifeinpeoplewhohaveadisease. Some generic measures, such as the Quality of Well-Being Scale [24], generate a single utility index of overall quality of life. This index usually ranges from 0 to 100 and these values can be used to adjust for years of life by degree of health experience to yield a measure of 'qualityadjusted life years'. Such a measure can be used to assess cost-effectiveness and cost benefits acrossvariousinterventionsandillnesses.Manygenericmeasuresofemotionalstatushavebeen employed in studies which include people with diabetes. These include the Well-Being Questionnaire [27], the Profile of Mood States [28], the Symptom Checklist (SCL-90R) [29], the Mini-Mental Status Exam [30]. Depression in people with diabetes has been studied using the following scales:theBeckDepressionInventory [31] andtheZung Self-RatingDepressionScale [32].Anxietyinpeoplewithdiabeteshasbeenstudiedusingthefollowingscales:theBeckAnxiety Inventory [33], and the Zung Self-Rating Anxiety Scale [34]. Both depression and anxiety in people with diabetes have been studied using the Hospital Anxiety and Depression Scale [35]. Illness-specific quality of life measures can focus on the specific problems posed by an individ‐ ualillness.Forexample,evenawell-designedgenericqualityoflifescalewillnotaddress certain aspects of life with diabetes such as hypoglycaemia, insulin injections, self-monitoring of blood glucose (SMBG), and dietary restrictions, which may be critical to an individual's healthrelated quality of life. Generic measures may not be specific enough to detect effects in some areasoffunctioningamongsomepeoplewithdiabetes.Forexample,genericmeasuresofmental health may not identify fear of complications as an important contributing factor. More and more,researchershaveaddeddisease-specificassessmentstogenericones,toincreasetheability oftheirmeasurestoidentifythefactorsmostrelevanttothehealth-relatedqualityoflifeofpeople with a specific disease. Some [18] have even advocated a 3-level approach for clinical trials, incorporating generic and disease-specific measures and, finally, situation-specific questions thatapplytothespecificcondition(neuropathy,forexample)orinterventionbeinginvestigated.

provided further solid evidence of this fact, even when controlling for usual T2DM risk factors, such as BMI, sedentary lifestyle or family diabetes [45-49]. Two meta-analyses based on 9 [50] and 13 [48]) prospective studies, reported an increase of 37% risk of depressed adults or a global risk increase of 1.6 (CI 95% 1.37–1.88) which led to T2DM later on. In recent study by Pan [51], conduced on a total of more than 55'000 US women with a 10 years' follow-up, was shown that depression and diabetes are closely related to each other, and this reciprocal

Quality of Life in Telemedicine-Based Interventions for Type-2 Diabetes Patients: The TECNOB Project

http://dx.doi.org/10.5772/56009

47

Depressive symptoms and diabetes-specific distress correlate with each other, although only specific distress displays more links with behavioural markers, such as self-management. treatment adherence, exercise and glycaemic control [52-55]. Psychological adjustment to type 2 diabetes explains 48% of the variance in diabetes-specific distress [56]. Nevertheless, diabetes distress remains the most prevalent long-lasting factor associated with hyperglycaemia in DMT2 [53]. Predictors of diabetes stress are related to chronic complications, negative life events, chronic stress in daily life, setbacks in diet and exercise management and previous history of depression. Also, depressive symptoms emerge mostly when more intrusive kinds of treatment begin, such as insulin use [51, 57] or if some complications in late diabetes arise [58, 59]. Furthermore, it has been shown that diabetic patients with severe depressive symp‐ toms adhere less well to diet and medication regimes than patients with less severe or no depressive symptoms [60-63]. In particular, depressed mood in diabetic patients might lead to pessimism regarding perceived benefits and lowered self-efficacy, and could result in poor self-care and compliance [64]. The diabetes patient who has low adherence to their diabetes management, lipid, or blood pressure medication as a result of depression is placed at greater risk for both micro- and macrovascular comorbid events and retinopathy [65, 66]. Finally, the

course of depression is also more chronic and severe in people with diabetes [67].

**2.** an electronic medical record for data incorporation and remote transmission,

**5.** a system for automatically flagging and providing feedback for outlier data [69].

components of a sound telemedicine system include:

**3.** a set of protocols for distant data analysis,

care providers, and

**1.** a process for accurate data collection in digital format,

One of the most promising methods for the management of chronic illness and, in particular, diabetes and its consequences is represented by the use of Information and Communication Technology (ITC) tools [68]. Telemedicine includes timely transmission and remote interpre‐ tation of patient data for follow-up and preventative interventions. The main purpose of this approach is to facilitate a productive interaction between the patient and the health care provider in order to achieve improved treatment results and lower treatment costs. The five

**4.** a variety of communication tools to permit effective dialogue between patients and health

**3. Telemedicine**

association depends on the severity or span of these conditions

As shown in literature, individuals with DMT2 are known to have lower health-related quality of life (HRQOL) and more depressive symptomatology than those without diabetes [36-39]. The comorbidity of depression in patients with type 2 diabetes mellitus has been observed in several studies [40, 41]. Anderson [41] summarized 20 cross-sectional reports and found that the odds of depression in the diabetic group was twice that of the nondiabetic comparison group. In a population-based study of adults with and without DMT2, investigators found EQ-5D index scores and visual analogue scores were significantly lower for respondents with DMT2 and those with 3−5 risk factors for DMT2 than for those with 0−2 risk factors [42]. In a longitudinal analysis of EQ-5D data collected in 2004 and 2009 among SHIELD (Study to Help Improve Early Evaluation and management of risk factors Leading to Diabetes) respondents with DMT2, found their health status declined significantly, indicating that burden of disease has a long-term detrimental impact on the QoL of individuals living with DMT2 [43]. The high prevalence of depressive symptoms among people with diabetes can be explained by two scenarios: that depression may occur as a consequence of having diabetes or a risk factor for the onset of DMT2. The first prospective study where this association was suggested emerged from the work of Eaton and collaborators in 1996 [44]. Afterwards, several prospective studies provided further solid evidence of this fact, even when controlling for usual T2DM risk factors, such as BMI, sedentary lifestyle or family diabetes [45-49]. Two meta-analyses based on 9 [50] and 13 [48]) prospective studies, reported an increase of 37% risk of depressed adults or a global risk increase of 1.6 (CI 95% 1.37–1.88) which led to T2DM later on. In recent study by Pan [51], conduced on a total of more than 55'000 US women with a 10 years' follow-up, was shown that depression and diabetes are closely related to each other, and this reciprocal association depends on the severity or span of these conditions

Depressive symptoms and diabetes-specific distress correlate with each other, although only specific distress displays more links with behavioural markers, such as self-management. treatment adherence, exercise and glycaemic control [52-55]. Psychological adjustment to type 2 diabetes explains 48% of the variance in diabetes-specific distress [56]. Nevertheless, diabetes distress remains the most prevalent long-lasting factor associated with hyperglycaemia in DMT2 [53]. Predictors of diabetes stress are related to chronic complications, negative life events, chronic stress in daily life, setbacks in diet and exercise management and previous history of depression. Also, depressive symptoms emerge mostly when more intrusive kinds of treatment begin, such as insulin use [51, 57] or if some complications in late diabetes arise [58, 59]. Furthermore, it has been shown that diabetic patients with severe depressive symp‐ toms adhere less well to diet and medication regimes than patients with less severe or no depressive symptoms [60-63]. In particular, depressed mood in diabetic patients might lead to pessimism regarding perceived benefits and lowered self-efficacy, and could result in poor self-care and compliance [64]. The diabetes patient who has low adherence to their diabetes management, lipid, or blood pressure medication as a result of depression is placed at greater risk for both micro- and macrovascular comorbid events and retinopathy [65, 66]. Finally, the course of depression is also more chronic and severe in people with diabetes [67].
