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    Review

    The Contribution of Teleconsultation and Videoconferencing to Diabetes Care: A Systematic Literature Review

    1Department of Technical and Professional Communication, Faculty of Behavioral Sciences, University of Twente, Enschede, The Netherlands

    2Department of Psychology and Communication of Health, Faculty of Behavioral Sciences, University of Twente, Enschede, The Netherlands

    3Department of Marketing Communication and Consumer Psychology, Faculty of Behavioral Sciences, University of Twente, Enschede, The Netherlands

    Corresponding Author:

    Fenne Verhoeven, MSc

    Department of Technical and Professional Communication

    University of Twente

    Faculty of Behavioral Sciences

    PO Box 217

    7500 AE Enschede

    The Netherlands

    Phone: +31 53 489 4441

    Fax:+31 53 489 4259

    Email:


    ABSTRACT

    Background: A systematic literature review was carried out to study the benefits of teleconsultation and videoconferencing on the multifaceted process of diabetes care. Previous reviews focused primarily on usability of technology and considered mainly one-sided interventions.

    Objective: The objective was to determine the benefits and deficiencies of teleconsultation and videoconferencing regarding clinical, behavioral, and care coordination outcomes of diabetes care.

    Methods: Electronic databases (Medline, PiCarta, PsycINFO, ScienceDirect, Telemedicine Information Exchange, ISI Web of Science, Google Scholar) were searched for relevant publications. The contribution to diabetes care was examined for clinical outcomes (eg, HbA1c, blood pressure, quality of life), behavioral outcomes (patient-caregiver interaction, self-care), and care coordination outcomes (usability of technology, cost-effectiveness, transparency of guidelines, equity of care access). Randomized controlled trials (RCTs) with HbA1c as an outcome were pooled using standard meta-analytical methods.

    Results: Of 852 publications identified, 39 met the inclusion criteria for electronic communication between (groups of) caregivers and patients with type 1, type 2, or gestational diabetes. Studies that evaluated teleconsultation or videoconferencing not particularly aimed at diabetes were excluded, as were those that described interventions aimed solely at clinical improvements (eg, HbA1c). There were 22 interventions related to teleconsultation, 13 to videoconferencing, and 4 to combined teleconsultation and videoconferencing. The heterogeneous nature of the identified videoconferencing studies did not permit a formal meta-analysis. Pooled results from the six RCTs of the identified teleconsultation studies did not show a significant reduction in HbA1c (0.03%, 95% CI = - 0.31% to 0.24%) compared to usual care. There was no significant statistical heterogeneity among the pooled RCTs (χ27= 7.99, P = .33). It can be concluded that in the period under review (1994-2006) 39 studies had a scope broader than clinical outcomes and involved interventions allowing patient-caregiver interaction. Most of the reported improvements concerned satisfaction with technology (26/39 studies), improved metabolic control (21/39), and cost reductions (16/39). Improvements in quality of life (6/39 studies), transparency (5/39), and better access to care (4/39) were hardly observed. Teleconsultation programs involving daily monitoring of clinical data, education, and personal feedback proved to be most successful in realizing behavioral change and reducing costs. The benefits of videoconferencing were mainly related to its effects on socioeconomic factors such as education and cost reduction, but also on monitoring disease. Additionally, videoconferencing seemed to maintain quality of care while producing cost savings.

    Conclusions: The selected studies suggest that both teleconsultation and videoconferencing are practical, cost-effective, and reliable ways of delivering a worthwhile health care service to diabetics. However, the diversity in study design and reported findings makes a strong conclusion premature. To further the contribution of technology to diabetes care, interactive systems should be developed that integrate monitoring and personalized feedback functions.

    J Med Internet Res 2007;9(5):e37)

    doi:10.2196/jmir.9.5.e37

    KEYWORDS



    Introduction

    Diabetes mellitus (DM) is major chronic disease that demands teamwork from various caregivers for the delivery of high-quality care [1]. Consequently, an adequate communication structure is an important condition for optimal interaction and coordination among caregivers and between patients and caregivers [2]. Information and communication technology (ICT) is often seen as the solution for problems in the management of diabetes care because of its potential to enhance care coordination and support patient self-care [3]. It is expected that using ICT will reduce costs while maintaining high-quality health care and that ICT can respond to an increasing demand for care with a decreasing availability of personnel [4]. Previous reviews on diabetes care have found modest benefits of ICT-based care compared to conventional face-to-face care. However, these reviews focused primarily on the usability of technology and considered mainly one-sided interventions such as clinical improvements (glucose and diet) rather than looking at the multifaceted process of a diabetic patient, including relevant issues such as the influence of interactive technology on the process of care (patient-caregiver collaboration, care coordination, costs) and patient outcomes such as quality of life and self-care [2,4,5].

    ICT-based care is more than just a technological intervention—it includes a way of thinking about how to deliver health care with the aid of ICT [6]. The most important modalities of ICT-based care are teleconsultation and videoconferencing [1]. Teleconsultation is a kind of telemonitoring including patient-caregiver communication (monitoring and delivering feedback) via email, phone, automated messaging systems, other equipment without face-to-face contact, or the Internet [7]. Videoconferencing involves real-time face-to-face contact (image and voice) via videoconferencing equipment (television, digital camera, videophone, etc) to connect caregivers and one or more patients simultaneously, usually for instruction [8].

    The aim of this review is to obtain an overview of the existing empirical support for the alleged benefits of teleconsultation and videoconferencing on diabetes care. The benefits are evaluated by means of criteria for “good chronic care” [1,2]. The evaluation criteria are clinical outcomes, behavioral outcomes, and care coordination outcomes [1,2]. Clinical outcomes include metabolic control and of life. Behavioral outcomes include self-care and patient-caregiver interaction. Care coordination outcomes refer to cost-effectiveness, transparency of the care delivery process, equity of access to care, and usability of equipment to facilitate the care delivery process.

    Our review is intended to inform social scientists and practitioners about the potential of technology to improve diabetes care. We provide an overview of what is currently known about the benefits and deficits of teleconsultation and videoconferencing and how practical and worthwhile these services are [9].


    Methods

    Literature Search

    We collected publications (from May 2005 to December 2007) on empirical research on ICT-based interaction between caregivers and patients or groups of patients, or among caregivers or patients themselves, using the for systematic reviews developed by the Centre for Reviews and Dissemination [10]. The review was restricted to studies evaluating teleconsultation and/or videoconferencing developed for type 1, type 2, and/or gestational diabetes and to language publications published between 1994 and 2006.

    No restrictions were imposed on the quality of study design because assessment studies dealing with ICT-based care are scarce [9], and, in practice, reviews have been constrained by the availability of data. In particular, behavioral or care coordination aspects were seldom the focus of reviews on diabetes care. Most reviews focused solely on clinical values in randomized controlled trials (RCTs). In light of a holistic approach, we wanted to provide a broad range of information in order to facilitate decisions about implementing new technology in health care. We excluded studies dealing with broader target groups than diabetics, studies not aimed at patient-caregiver interaction but solely reporting technical aspects of the equipment used, and those that strived for clinical improvements only. We included studies that covered clinical outcomes plus one or more other outcomes (behavioral, care coordination).

    The following electronic databases on medicine, psychology, and telemedicine were searched: Medline, ScienceDirect, ISI Web of Science, Telemedicine Information Exchange, PsycINFO, PiCarta, Google Scholar, and journal indexes (Diabetes Care, Effective Health Care, Journal of Medical Internet Research, Journal of Medical Informatics, Telemedicine and E-health, Telemedicine and Telecare). Keyword sets combined “diabetes” and one of the following: “telemedicine,” “telecare,” “telehealth,” “e-health,” “teleconsultation,” “telemonitoring,” or “videoconferencing.” We used “telemedicine” because the terms “e-health” and “electronic care” were hardly used in the literature before 2004. In addition to the databases, the reference lists of the identified publications were hand-searched. Citation was reviewed and designated as “in,” “out,” or “uncertain” based on the aforementioned restrictions. Sources designated as “in” or “uncertain” were obtained for further review. Two of the authors independently reviewed titles and abstracts of the identified publications to decide whether they should be examined in full detail.

    Two authors completed data extraction forms developed by the Centre for Reviews and Dissemination [10] and recorded the following details: study design (evidence level and methods for measurement outcomes, patient selection, description of intervention and control groups), study population (type of diabetes, age group, number and recruitment of patients), and intervention details (care setting, technology used to support the care delivery process, duration of the intervention). Using the care levels previously mentioned (clinical, behavioral, and care coordination) [1,2], we developed a checklist to categorize the outcomes of the interventions (Table 1).

    Table 1. Checklist to classify the outcome measures related to the levels of diabetes care
    View this table

    Five levels [10] were used to categorize the methodological approaches of the studies (Table 2). Two authors independently rated the study designs. In case of disagreement, consensus was reached by discussion.

    Table 2. Checklist to categorize level of evidence of study design
    View this table

    Statistical Methods

    A quality assessment was completed for all RCTs using the Jadad scale [11]. This scale contains questions about randomization, blinding, and withdrawals that are scored by a yes (1) or no (0). In total, five points can be awarded, with higher points indicating higher study quality.

    Changes in HbA1c values were calculated from baseline and follow-up means and standard deviations. Only studies researching effects on adults were included in the meta-analysis. When the deviation of the mean difference was not available in the papers, the authors were contacted. In case of no response or no availability of the requested information, we estimated the variance by using (1) reported confidence intervals, (2) reported P values, or (3) an imputation technique [12]. A random-effects model was used for pooling the included studies because clinical heterogeneity between studies was expected. The between-study heterogeneity was tested using the chi-square statistic. In one study, three intervention groups and one control group were studied. In meta-analyses, all three intervention groups were compared with the same usual care group, resulting in two extra comparisons.


    Results

    Study Characteristics

    We identified 852 potentially relevant publications, 39 of which were included after the selection procedure described in the previous section (Figure 1).

    Figure 1. Study selection process
    View this figure

    Table 3 (teleconsultation) and Table 4 (videoconferencing) summarize the characteristics of the publications that were included. As can be seen, 22 interventions addressed teleconsultation [13-34], 13 addressed videoconferencing [35-47], and 4 addressed videoconferencing combined with teleconsultation [48-51]. The most frequently used methodological approach was observational (case series or before-after design), which was used in 19 studies; 11 studies were RCTs, and 6 were quasi-experimental. The other methodological approaches were used only incidentally (two cohort studies and one study based on expert interviews). Sample sizes included ≤ 20 (n = 9), ≤ 100 (n = 17), > 100 (n = 12), and one was not specified. Participants were selected by the research team [31,33,36,47,49,50], general practitioner [17,30,35,47], a specialist [15,17,22,24], or via convenience sampling [32,40].

    Data were gathered via interviews, focus groups, log files, and nonstandardized questionnaires. Validated questionnaires were used in 12 of the 39 studies to measure usability of technology, quality of life, and self-care. The Telemedicine Satisfaction Questionnaire [14,25,41,47] was used for measuring usability of technology. Quality of life was measured with various questionnaires: the World Health Organization Quality of Life-BREF [14], SF-12 [17,25,30], SF-36 [36,38,41,44,48,49], Diabetes Quality of Life [25,30,36,41,44], Depression Scale CES-D [30], Problem Areas in Diabetes Scale [41], and the Visual Analog Scale [26]. The Diabetes Knowledge Assessment [36], Diabetes Treatment Satisfaction Questionnaire [41], and the Appraisal of Diabetes Scale [41] were used to measure self-care.

    Table 3 and Table 4 present the improvements found in the studies, per outcome (clinical values, quality of life, patient-caregiver interaction, self-care, usability, cost reduction, transparency, and equity). Most of the studies reported improvements in usability of technology (n = 26; 15 teleconsultation and 11 videoconferencing), followed by clinical improvements (n = 21; 15 teleconsultation and 6 videoconferencing), cost reduction (n = 16; 5 teleconsultation and 11 videoconferencing), self-care (n = 14; 10 teleconsultation and 4 videoconferencing), and patient-caregiver interaction (n = 13; 10 teleconsultation and 3 videoconferencing). A minority of the studies reported improvements in quality of life (n = 6, 3 teleconsultation and 3 videoconferencing), transparency of care delivery guidelines (n = 5, 3 teleconsultation and 2 videoconferencing), and equity in access to health care (n = 4; all videoconferencing).

    The findings summarized in Table 3 and Table 4 were extracted from publications that varied in study design and data gathering methods, and the reported findings were often not substantiated with evidence, as can be seen in the tables. In the light of the purpose of our review, we took this heterogeneity in study characteristics into account.

    To get insight into the contribution of teleconsultation and videoconferencing to diabetes care, the results of these interventions were presented separately, describing care setting and intervention and clinical, behavioral, and care coordination outcomes. Improvements were reported and explained.

    Table 3. Overview of teleconsultation interventions (see Multimedia Appendix for full tables containing inclusion criteria and data gathering methods)
    View this table
    Table 4. Overview of videoconferencing and combined interventions
    View this table

    Studies on the Effects of Teleconsultation

    Settings and Interventions

    Interventions took place in secondary care settings [13,15,17,19,22,23,25,34] and in primary care [24,28,30-32] (see Table 3). To improve the reliability of monitoring, clinical data such as HbA1c and insulin dose were usually sent and analyzed automatically (18/22 studies). In most settings, glucose meters, palmtops, and/or cell phones were used to send data (n = 15). To enhance disease control, feedback was given via computer-generated reminders whenever values were alarming [13,14,20,21,26,27,32]. In some cases, caregivers provided personal feedback to instruct patients in case of alarming values [15,17,22,24,25,30,33,34].

    Inclusion of patients in the intervention groups included such criteria as being diagnosed with type 1 [13,15,18,19,22,23,25,28] or type 2 diabetes [24,26,30,32,33], being compliant with therapy [13,22,24], being motivated to take part in the intervention [14,15] having a caregiver taking part in the intervention [17,24,31,33,34], living in the region [17,21,30,32], demographics such as being younger than 30 years [19,22] and being economically disadvantaged [17,22,28,30,32], having insulin problems [15,19,25], and poor metabolic control (HbA1c> 8%) [19,22-25,31]. As well, certain conditions needed to be met, such as being able to handle the technique [15,17,18,20,26,30], having followed a structured diabetes education program [15], and having access to the Internet [14,20,26] or a (cell) phone [14,17,20,21,26,30].

    Though teleconsultation is generally assumed as the solution for better disease management and care coordination of diabetic patients, the preference for this kind of technology compared to other options has not been clearly stated. Teleconsultation is supposed to be cost-effective, to deliver continuous care, and to foster time-efficient communication between patients and caregivers [13,14,16,17,19,21,23,31]. Most teleconsultation interventions (n = 18) were aimed at improving clinical values, investigating usability of technology (n = 15), intensifying interaction by means of information exchange, either among caregivers or between patient and caregivers (n = 14), and enhancing self-care (n = 12).

    Effects of Teleconsultation at Clinical Level

    HbA1c levels were measured in eight RCTs [14,15,19,22,25,27,30,31], but only six were suitable for meta-analysis. One trial studied only children [22] and was therefore not included in the meta-analyses. Another trial [14] reported that the variance of HbA1c values was significantly lower in the experimental group compared to the control group. This study was excluded because using an imputation technique was unadvisable as data provided by the author differed from the published data. Changes in HbA1c values were calculated from baseline and follow-up means and standard deviations. The Jadad quality score of the trials was either 2 or 3 (Table 5).

    Table 5. Randomized controlled trials with HbA1c data (see Multimedia Appendix for full tables containing inclusion criteria and data gathering methods)
    View this table

    Table 5 presents the mean difference between the baseline and follow-up HbA1c values. These values were either reported in the paper or provided by the authors. None of the interventions were blinded since blinding of participants with respect to study status is almost impossible in clinical trials of behavioral interventions. The method of randomization was not clear in two of the six RCTs; a description of withdrawals and dropouts was given in five studies. The pooled reduction in HbA1c was not statistically significant (weighted mean difference [WMD] 0.03; 95% CI = −0.31 to 0.24). Figure 2 shows the mean difference and WMD of the mean difference between baseline and follow-up HbA1c values. There was no significant statistical heterogeneity among the pooled RCTs (χ27 = 7.99, P = .33). The pooled RCTs included patients with type 1 diabetes [13,15,19,25], type 2 diabetes [31], and unspecified diabetes [27,31]. Glucose monitoring took place via a telephone network [14,15,19,25,27], the Internet [14,30,31] in primary care [30,31], secondary care [15,19,25], or integrated care [14] settings, or the care setting was not specified [27]. None of the pooled RCTs showed a significant difference in HbA1c between intervention and control groups. The trials varied in duration from 3 to 12 months.

    Two RCTs reported a decrease in HbA1c values. In one study [14] (DM type 1, 2, or unspecified), both the intervention and control groups had significantly different variances after 6 months (F test, P < .05), confirmed by the results of the randomized subset of patients (t test, P < .05) (see Table 3, reported findings under a). The other study [22] analyzed the HbA1c values of children (DM type 1) (see Table 3, reported findings under a). There was no significant difference between the two groups and no significant within-group difference between initiation and completion of the study (6 months). Some observational or quasi-experimental studies showed improved metabolic control with respect to HbA1c [13,16,23,24,33,34], diabetes regulation [33], and glucose, lipid profiles, and blood pressure [31,33]. The improvements were not significant compared to the control group (usual care). The improvements with regard to metabolic control were achieved by means of Web-based care management programs providing patients (mostly DM type 1) who have poor metabolic control with automatic data transmission, educational modules, and messaging systems for communication and personal feedback.

    Figure 2. Comparison of changes in HbA1c control versus intervention
    View this figure

    Quality of life improved in three studies [17,25,30] (see Table 3, reported findings under b). These studies measured different aspects of quality of life. In one study [17], a mean improvement was realized in the mental and physical status of patients after 6 months of intervention. In the second study [25], an improvement was observed in quality of life (DQOL) and in knowledge (DQK2) in the intervention and control group (usual care). In the third study [30], a slight improvement was reported in psychological well-being, especially in the personal self-management and combined condition.

    Effects of Teleconsultation at Behavioral Level

    Ten studies [13,16,17,18,22,23,27,28,30,32] reported improvements in patient-caregiver interactions (see Table 3, reported findings under c) with respect to a higher frequency of information exchange (about treatment) and increased metabolic data transmission [16,17,23,30]. In study 16, the intervention was compared to usual care, while in study 17 and 23, the effects were demonstrated in the intervention phase of a cross-over design. In study 30, two of the four care conditions (personal self-management and personal self-management combined with peer support) showed a significant improvement in patient-caregiver interaction. A communication network improved the availability and completeness of data among caregivers [16,23]. Intensity of contacts increased [17,23,30] via daily monitoring and automatic feedback when values were alarming [17], via personal feedback to patients’ requests for advice [23] or via an Internet-based program for self-management and social support [30].

    Improved self-care was observed in 10 studies [17,18,20,23,25,26,28,31,32,33] (see Table 3, reported findings under d). Patients checked their blood glucose more often [18,31], experienced a better understanding of their medical condition [17,26], and were better able to manage their disease after using the technology [17,18,20,23,25,28,32,33]. Better self-care was achieved in interventions with personal feedback [17,18,20,23,25,26,28] and/or education [28,31,32]. In one study [31], the improvement was significant compared to usual care. Regular data uploads were more likely to achieve and maintain reductions in patients’ HbA1c.

    Effects of Teleconsultation at Care Coordination Level

    In general, most patients were satisfied with the technology (see Table 3, reported findings under e). The technology (eg, glucose meters, hand-held electronic diary) was acceptable for patients [13,23,28,29], was reliable and helpful for caregivers [13,28,33], and appeared easy to use [15,17,21,27,34]. Technical problems and unfulfilled expectations frustrated patients [32]. The availability of metabolic data and the possibility of consulting a caregiver within minimal time and without traveling enhanced patients’ feeling of security [15].

    Adoption of the technology was demonstrated by a significant increased proportion of transmitted blood glucose data in the intervention group [19]. In most cases, patients were trained to master the equipment [15,17,18,19,20,22,23,25,26,28,30]. Two studies [18,23] reported on the implications of implementing technology in diabetes care. Web-based management of diabetes care [18] changed tasks and duties of the diabetes team as the system required extra competency of nurses in insulin dose adjustments. Electronic communication and frequent blood glucose transmission led to more changes in therapy compared to usual care [23].

    Five studies [15,17,21,24,25] reported cost reductions (see Table 3, reported findings under f). Cost reductions concerned saving of consultation time compared to usual care [15,25]. However, teleconsultation significantly increased physician’s time since patients tended to call more often [15] and more time was needed to handle technical problems [25]. Costs for technical equipment, telephone, and data transfer were compensated by the cost savings [15]. Costs were calculated as savings per year per patient, reduction of overall utilization and charges after one year, and treatment time required of caregivers. Costs were measured by means of interviews, nonstandardized questionnaires, and by retrieving data from visit logs. A cost analysis was carried out in one study [15] with an estimation of total costs of teleconsultation in an optimized scenario, including a comparison to usual care.

    Enhanced transparency was realized in three studies [24,28,33] (see Table 3, reported findings under g). Clinical guidelines for altering diabetes care (a treatment algorithm for metabolic control) resulted in a reduction in HbA1c in patients with poorly controlled diabetes; however, the difference in reduction between intervention and control groups (usual care, actively managed comparator group) was not significant [24]. Protocol-driven data transfer between caregiver and laboratory provided more complete patient records and a significant decrease in metabolic values (HbA1c, lipid profiles, and blood pressure) [33]. Online education of school personal enhanced compliance with school health plans [28].

    Studies on the Effects of Videoconferencing and Combined Interventions

    Settings and Interventions

    Interventions took place in secondary care settings [36,37,40,42,43,45,46] and in primary care [35,38,39,41,44,47,48,49,50,51]. Combined interventions [48-51] were all used in primary care settings, often in underserved or remote areas, to allow videoconferencing to supplement teleconsultation by enabling direct interaction between patient and caregiver(s) [49,50]. Videoconferencing involved real-time contact between the patient at home [37,38,39,40,44,45] or in a local clinic or center [35,36,41,42,43,46,47] and a caregiver in the hospital or diabetes center via video equipment. In 11 cases, patients had contact with one caregiver, while in six cases a team of various caregivers interacted with patients. In studies aimed at patient education [36,41,43,47], consultation took place between patient groups and caregiver(s). Videoconferencing was used for ulcer treatment [35,37,46], for patients discharged from hospital but still needing care [38], for injections and blood sugar control [43],and for general diabetes management [40,42,45]. Feedback was provided mostly during the video sessions or in combined interventions by telephone [49,50] or email [51].

    Inclusion criteria for the videoconferencing and combined interventions (see Table 4) included being diagnosed with DM type 2 [35,36,44,47], age [36,39,41,44,47,48,49,50], being treated longer than 1 year [35], being (frequently) referred to a diabetes specialist [47], having a complex medical condition [39,48,49,50], poor metabolic control [39], being at high risk of expensive service visits [48,49,50], being a pediatric patient [42,43], having limited mobility [36], having a caregiver taking part in the intervention [38,39,40,41,45], not having had diabetes education for at least 1 year [41], and having phone access [50]. Three studies did not mention inclusion criteria [37,46,51].

    Videoconferencing was chosen because it permitted experts from the hospital to be present in the patient’s home while maintaining the continuity and quality of treatment to support disabled or underserved patients [39-41,43,46,49,50]. Combining the two modalities was motivated by the fact that videoconferencing supplements teleconsultation by enabling direct interaction. It was expected that through videoconferencing it would be possible to explain the effects of teleconsultation more accurately [48]. Videoconferencing (and combined) interventions were mainly aimed at cost reduction (n = 14), clinical improvement (n = 11), usability of technology (n = 8), self-care (n = 8), and quality of life (n = 7).

    Effects of Videoconferencing and Combined Interventions at Clinical Level

    Improved metabolic control was observed in six studies [35,36,39,41,44,49] (see Table 4, reported findings under a).

    HbA1c decreased [35,36,39,41,44,49], systolic and diastolic blood pressure decreased [35], total calorie intake decreased, body mass index and glycemic control improved [36], and low density lipoprotein cholesterol decreased [41]. Due to the fact that data regarding standard deviations could not be retrieved, a meta-analysis could not be conducted on the RCTs reporting HbA1c levels.

    HbA1c decreased via therapeutic counseling by videoconferencing [35] and by means of daily monitoring of food intake and blood sugar levels via videophone, email, or phone [39].

    A comparable reduction in HbA1c was found as a result of educational sessions by videoconferencing with patients in remote areas compared to in-person education (no statistically significant difference between intervention and control groups) [41] and also by monitoring metabolic values and dietary behavior from patient’s home with videophone and email (no statistically significant difference between intervention and control groups) [44]. In another study, a hand-held in-home messaging device (Health Buddy), a two-way audio-video link, and a videophone were used to compare weekly monitoring (with a care coordinator) to daily monitoring (with the home message system). HbA1c decreased in both groups (no statistically significant difference between groups) [49].

    Most interventions were directed at patients with DM type 2, with poor metabolic control, or with complex medication conditions and a high risk of expensive service visits.

    Improvement in quality of life was reported in three studies [36,41,48] (see Table 4, reported findings under b). Two studies [36,41] concerned educational interventions. In one, videoconferencing (video and digital camera) took place in a community center with patients who had limited mobility and skin and foot care (wounds) problems [36]. In the other study, patients at a remote site were connected by videoconferencing, digital camera, and personal computer to a diabetes center [41]. One intervention [48] consisted of a home message system that allowed monitoring and communication by videophone. Quality of life improvements were reported for physical functioning [36,48], general health [36], emotional well-being [36], stress reduction [41], and social functioning [36,48]. Only in one study a control group was used, but no significant difference was observed between the intervention (tele-education) and control groups (education in person) [41].

    Effects of Videoconferencing and Combined Interventions at Behavioral Level

    Patient-caregiver interaction improved in three observational studies [36,45,47] (see Table 4, reported findings under c). Patients developed a wider social network, creating bonds with both other patients and with caregivers. An interactive ongoing collaboration between patient and caregiver was found to be important for the effectiveness of self-management therapy [45]. Videoconferencing enabled communication between caregivers, to provide education in small groups [47].

    Self-care improved in four studies [36,39,41,47] (see Table 4, reported findings under d). Self-care improved by management of blood sugar transfer [39] and increased knowledge allowing patients to cope with diabetes in a better way, thus improving self-care [36]. Patients developed a more positive view of their diabetes [41]. Education via videoconferencing appeared highly acceptable for patients [47]. The improvements in self-care [36,41,47] took place in care settings that were particularly directed at (group) education.

    Effects of Videoconferencing and Combined Interventions at Care Coordination Level

    Equipment for videoconferencing consisted of a personal computer with video card [35,38,41], equipment with a television [36,42,43,46,47], or a videophone [37,39,44]. A document camera or visualizer was used to show patient records, x-ray images [36,41,43,46], blood sugar values, and pictures of foot ulcers, skin conditions, and wounds. A hand-held camera was used for showing body sites (eg, ulcers) [36,38,42,46,50]. The combined interventions used hand-held in-home messaging devices (Health Buddy) and a videophone for monitoring glucose [48-50].

    Videoconferencing equipment [35-37,39-42, 46,47,48,51] appeared convenient and easy to use; caregivers found the photographic images reliable and valid [46] (see Table 4, reported findings under e). seven studies, patients and caregivers were trained to use the equipment [37,38,42,47,49,50,51].

    Satisfaction with videoconferencing depended on education and training [51], assistance while using the equipment, and age; the older the patient, the higher the level of satisfaction with videoconferencing [47].

    Cost reduction was reported in 11 studies [35,37,38,42,43,45,46,47,48,49,50] (see Table 4, reported findings under f). Cost savings concerned reduced health care utilization [35,38,42,48,49,50], lower treatment costs [38,42], more need-based primary care clinic visits (permitting just-in-time preventive care instead of just-in-case care) [48,49,50], and reduced travel costs for patients [37,46,48] and caregivers [43].

    Reduction in health care utilization costs was achieved with respect to hospital admissions [35,49] emergency department visits [42,48,50], hospitalizations [38,42,48], number of bed days of care [48,49], and discharges to home care [38]. Lower treatment costs refer to the potential of videoconferencing to provide the same number of patient encounters at lower cost, decrease patient referrals [38], and replace conventional visits by videoconferencing [42]. Videoconferencing also reduced unscheduled primary care visits [48,49,50]. Studies also associated lower costs with more reliable and valid metabolic control [49,50].

    The reductions in costs were found in observational studies without a control group [35,37,42,43,45,47,48]. Costs were calculated during the intervention period and were compared to the costs before the intervention took place (see Table 4, reported findings under f). In three studies [38,49,50], cost reductions were compared to a control group. In one study [38], an economic analysis was carried out on direct and indirect costs occurring at the home health agency level, including labor costs for both the intervention and control groups (skilled nursing home visits only) and costs associated with the implementation of the videoconferencing system. There were no significant differences between intervention and control groups in staff costs (time spent by training, video visits). Total costs per patient per episode were lower for the videoconferencing group, including hospitalization, than for the control group. In two combined interventions [49,50], lower costs were related to more reliable and valid metabolic control. One of these combined studies [49] showed effects of differences in home care monitoring intensities (weekly or daily monitoring) on service costs and clinical outcomes; daily monitoring (transmission via home telehealth technology) significantly reduced the unscheduled primary care clinic visits, the hospital admission rate, and the days of hospitalization. Patients in the daily monitoring group performed better than the weekly (instant camera) monitoring group because of more reliable and valid metabolic control. Although the service cost was reduced, no difference could be found in the clinical outcomes between groups. In the second of these combined studies [50], there were reported differences in health care service use between videoconferencing and conventional care with reference to outpatient services; a difference between intervention and control groups was observed in need-based primary care visits, which increased in the intervention group and decreased in the control group. The likelihood of one or more emergency department visits decreased both in intervention group and control groups, but the intervention group had a lower relative likelihood of having one or more hospitalizations than the control group. Patients who had higher HbA1c levels spent a greater number of days in hospital.

    Although videoconferencing saved money, the development and implementation costs (including training of staff) of a new technology are often high, and all kinds of technical problems (and costs) should be taken into consideration. In two studies [38,42], cost savings were compensated by staff training and system costs (including costs of technical deficits). Even when system costs were included, videoconferencing saved money [42] or was estimated to save money on the basis of cost analysis [38].

    Enhanced transparency in treatment programs was reported in two studies [37,45] (see Table 4, reported findings under g). Shared documentation via an online ulcer record system enhanced coordination in the treatment of diabetic foot ulcers [37]. A long-term quality improvement program (including national diabetes standards) with an interactive feedback system between patient and caregiver resulted in structured use of staff time [45]. Better access to specialized health care in underserved areas was reported in three studies [42,45,46] and in patients with complex medical conditions in one study [50] (see Table 4, reported findings under e).

    Reported Shortcomings of the Studies

    Several publications reported shortcomings concerning disappointing or unexpected study results and problems with implementing the intervention. The most frequently mentioned shortcomings were the lack of a significant difference between the intervention and control groups [14,15,19,24-27,30,33, 35,36,41,46], the inability to measure long-term effects of the intervention [14,17,19,30,44], and the fact that interventions sometimes inherently led to improved results because of a selection bias. Some patient groups benefited more from the intervention than others (eg, patients with poor metabolic control [33], high use of health care [50], motivated patients [22], or inexperienced patients [15,33,48]).

    Some publications reported problems with ICT-based care, generally caused by the absence of adequate infrastructure [14,16,27,29,47,50,51] or the logistical difficulties involved in organizing online consultations, with all parties having to agree on a suitable time [50]. Patient-caregiver interaction suffered from the lack of a protocol that could guarantee high-quality communication, leading to information overload [16,17,18,29,33,51]. In some cases, patients considered the technology too complex to master [21,23,30,47,50,51], too time consuming [15,23,30,33], or too costly [21], and some patients were reluctant to cooperate, resulting in unreliable clinical data transmissions [15,18,26,35,47,51]. ICT-based care was thought to reduce the trust and confidential relationship between patients and caregivers [15,18,32,51].


    Discussion

    As far as we know, our review is the first to evaluate the benefits of teleconsultation and videoconferencing for diabetes care, in particular with respect to clinical, behavioral, and care coordination aspects. Earlier reviews have focused on usability and costs of technology or considered mainly clinical (glucose and diet) outcomes [2,4,5]. A systematic search and selection process produced only 39 studies. This may appear low, but it is comparable with previous reviews on ICT-based care [3,4,52].

    We can conclude that in the period under review (1994-2006), 39 studies had a scope broader than clinical outcomes and involved interventions allowing patient-caregiver interaction. Most of the reported findings concerned satisfaction with technology (26/39 studies), improved metabolic control (21/39), and cost reductions (16/39). Improvements in quality of life (6/39), transparency (5/39), and better access to care (4/39) were hardly observed. In 19 of 39 studies the control group was more or less comparable with the intervention group (see Table 3 and Table 4). It appeared that ICT-based care improved diabetes care compared to usual care; however, the improvements were mostly not statistically significant. In a sense it could be argued that technology did not compromise the care delivery process.

    Only a minority of the studies (12/39) considered care settings involving teamwork of various caregivers (eg, nurses, case manager, psychologist, physician, general practitioner), which should be expected in integrated chronic care settings [1,53]. Training was given when implementing the technology, but this was restricted to handling equipment and did not address the technology to solve health care problems, which is a prerequisite for eHealth literacy [54].

    The contribution of teleconsultation and videoconferencing to patients’ quality of life and ability to control their disease was not substantial (clinical and statistical), because of a limited intervention period and various shortcomings in research design and in implementing ICT-based care. Although previous reviews have indicated that the impact of technology on behavioral change (interaction and self-care) and on care coordination (cost savings) needs to be clarified to support decisions about the use of technology to supplement care [3,5,52], only limited progress was observed. A possible reason that ICT-based care has not shown a high impact on diabetes care could be the absence of a long-term view on the potential of technology to reduce fragmentation and to improve diabetes care at acceptable costs. In most studies, patients’ perspectives with respect to emotional and social well-being (quality of life) and ability to cope with diabetes are underexposed, just as the feasibility, appropriateness, and meaningfulness of the interventions for care practice are [55]. Moreover, the choice of a specific technology was mostly based on convenience arguments (access to a computer for instance, living in an underserved area) and not related to preferences and specific needs of patients or caregivers to manage diabetes. For example, a study on the attitude toward videoconferencing [40] showed that patients prefer video visits while nurses wanted to deliver hands-on care in patients’ homes. Therefore, it is not certain that the most appropriate technology was used in the most effective way [9], and, consequently, it might be rather premature to say that teleconsultation or videoconferencing as such is the best option to deliver cost-effective and worthwhile services.

    Although these shortcomings can be seen as an inevitable part of innovating chronic care, one must consider the benefits of specific technologies to diabetes care to make progress. Based on our review, the benefits of teleconsultation concern the three levels of care. At the clinical level, this implies improvement of metabolic control. Improvements at the behavioral and care coordination level refer to reliable transmission of clinical data (eg, HbA1c), intensified patient-caregiver interaction, and enhanced self-care as a result of an improved understanding of the medical condition and higher quality of feedback (quicker response from caregivers and education about self-management).

    Teleconsultation interventions [16,17,19,24,25,31] with improvements in clinical, behavioral, and care coordination outcomes can be characterized as Web-based care management programs providing automatic transmission of clinical values, educational modules, and a messaging system for communication and personal feedback (warning messages and instruction). Conditions for implementing the technology were reported in some of these studies, such as using computer-based patient records for electronic data interchange between caregivers; guidelines for writing medical records; a close cooperation between patient, general practitioners, and specialists [16]; access to a care manager to manage diabetes care with technology; and patients who favor ICT-based care [31]. The technology was found not advanced enough to be sufficiently practical and cost-effective [25], and more intensive techniques (like computerized decision support systems) are needed to help patients change their health behavior [19].

    Most of the studies reported none or limited information about preference for and persistence of technology for specific patient groups. The observed improvements were based on interventions directed at patients who were able to use the equipment (eg, having experience with cell phones and SMS) [14,17,18,20,21,26], who were well motivated to take part in the intervention [13,14,15,31,33,34], who already had a caregiver taking part in the intervention [17,24], who were economically disadvantaged [17,28], or who had type 1 diabetes that required strict monitoring of blood glucose levels [22,23,25,28]. This might confound the practicability of the results [55,56].

    The benefits of videoconferencing can be particularly demonstrated at the usability level (convenient and easy to use) and care coordination level. Videoconferencing appeared to maintain quality of care while producing cost savings in patient at-home care settings. Real-time communication appeared particularly successful in group education, allowing patients to take more proactive roles in managing their diabetes, helping them to feel happier and to develop wider social networks. Monitoring combined with videoconferencing enabled “just-in-time preventive care” instead of more expensive “just-in-case care” and significantly reduced unscheduled clinic visits, hospital admissions, and days spent in hospital. Cost savings should be offset by increased staff costs and the costs of the development and implementation. For instance, increased patient-caregiver interactions or increased need-based primary care may imply an increase in workload. In two [38,42] of the 11 studies on cost savings, the cost reductions were compared to increased system costs.

    The results were based on interventions directed at patients in underserved or remote areas, with complex medical conditions (elderly, immobile, or with poor metabolic control), or meeting some practical conditions, such as having access to a physician in the intervention setting, which should be taken into account when implementing videoconferencing in practice, for reasons of selection bias [55,56].

    Successful interventions [38,41,48,49] with improvements in clinical, behavioral, or care coordination levels included programs aimed at teaching patients to cope with and control their diabetes, mostly settings in which patients at home consulted with their caregivers at hospitals or diabetes centers via video. Reported conditions for implementing these interventions were training of patients and staff throughout the implementation to learn to deal with the equipment [38], alternative markets to reduce investment costs, like purchasing “used” equipment at reduced costs [38], and a health care system that has an ongoing and well supported clinical infrastructure to support professionals competent to deal with ICT-based care [48].

    The observed benefits are consistent with prior reviews regarding cost savings, efficacy of applications, and improved communication between primary and secondary health care providers [4,5,9,52,57]. The scope of the reviews differs from our study, which is particularly aimed at diabetes care.

    Some Limitations of Our Study

    Due to the diversity and variance in study designs, inclusion criteria, and a lack of required data, a meta-analysis could not be conducted on the RCTs reporting HbA1c levels (videoconferencing) and other outcomes (quality of life, behavior, and care coordination). In particular, studies on quality of life, behavior, and care coordination used different outcome measures or calculated the same outcome (eg, well-being) in different ways. Lack of required data hampered a statistical combination and therefore may have biased the review’s results. To avoid spurious preciseness, we did not combine observational studies for a meta-analysis.

    To evaluate the contribution of technology to diabetes care, we developed a checklist based on principles for chronic care [1,53,58] because existing evaluation systems are directed at usability and acceptability of equipment rather than care service delivery [9]. Future research should validate this checklist. We reported the outcomes of the interventions per level of care, although they are interdependent in a chronic care setting; the usability of the equipment influences the reliability of monitoring and patient-caregiver interaction, which can influence behavior and care coordination [1].

    We chose to review various systems of teleconsultation and videoconferencing to shed light on different functions of the systems (monitoring, information exchange, communication) to support diabetes care. This might increase the heterogeneity in our study results.

    Future Research

    When patient self-care and care coordination are the focus of the intervention, we need to evaluate the process of implementation more thoroughly (eg, which patients persist and which drop out) and the quality of communication. We observed that patients need more help with self-care than they received in the intervention settings, and online training and personal assistance might be necessary in cases of ICT-based care. A supportive health policy environment (and appropriate financing) is necessary to guarantee continuity after a pilot period. Successful diabetes management systems should integrate several functions to provide collaborative care and to meet the needs of patients and caregivers. Moreover, the shift from hospital to community centers or home care requires technology that integrates lifestyle and education functions for simultaneous group education and for encouraging self-care. Future research should be directed at the development of patient-centered technology personalized to specific needs and capacities. More rigorous methods are needed to measure the effects of an intervention on quality of life, well-being, and organizational issues such as cost effectiveness to make decisions on implementation and to encourage better care coordination. By means of usability tests and log files, patients’ needs for care and technology support can be measured, and test results can be linked to education and behavior changes [59]. By means of critical incidents techniques [60], the conditions that permit technology to be implemented successfully can be assessed. More transparency is needed in reporting economic evaluations. The costs included in the studies varied so that comparison of the reported savings is hardly possible, which is also demonstrated in a former review [57]. Cost effects should be studied with a clear perspective that reflects the purpose of the evaluation and the viewpoint of analysis (eg, cost-benefit, cost-effectiveness analysis).

    We conclude that further assessment studies are needed to evaluate the contribution of ICT-based care to diabetes management. Future research should examine the potential of technology to enhance self-efficacy with the aim of making life worth living for someone with certain limitations, in cases where the disease is incurable. Technology can easily overstress the negative aspects of disease and illness because of the focus on collecting health data (eg, food intake). In the end, self-efficacy and social support are possibly the main conditions for changing health behavior [61].

    Conflicts of Interest

    None declared.

    Multimedia Appendix

    Extended Tables 3 and 5 (containing inclusion criteria and data gathering methods): Overview of videoconferencing and combined interventions PDF file (Adobe Acrobat), 196 KB


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    Abbreviations

    DM: diabetes mellitus
    HbA1c: glycosylated hemoglobin
    ICT: information and communication technology
    RCT: randomized controlled trial


    Edited by G. Eysenbach; submitted 15.06.07; peer-reviewed by T Paul; comments to author 29.06.07; revised version received 27.08.07; accepted 12.10.07; published 14.12.07

    © Fenne Verhoeven, Lisette van Gemert-Pijnen, Karin Dijkstra, Nicol Nijland, Erwin Seydel, Michaël Steehouder. Originally published in the Journal of Medical Internet Research (http://www.jmir.org, 14.12.2007). Except where otherwise noted, articles published in the Journal of Medical Internet Research are distributed under the terms of the Creative Commons Attribution License (http://www.creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited, including full bibliographic details and the URL (see "please cite as" above), and this statement is included.