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Journal of Diabetes Science and Technology logoLink to Journal of Diabetes Science and Technology
. 2021 Dec 26;17(3):794–825. doi: 10.1177/19322968211064633

The Effectiveness of Telemedicine Solutions for the Management of Type 2 Diabetes: A Systematic Review, Meta-Analysis, and Meta-Regression

Stine Hangaard 1,2,, Sisse H Laursen 1,3, Jonas D Andersen 1, Thomas Kronborg 1,2, Peter Vestergaard 2,4,5, Ole Hejlesen 1, Flemming W Udsen 1
PMCID: PMC10210100  PMID: 34957864

Abstract

Background:

Previous systematic reviews have aimed to clarify the effect of telemedicine on diabetes. However, such reviews often have a narrow focus, which calls for a more comprehensive systematic review within the field. Hence, the objective of the present systematic review, meta-analysis, and meta-regression is to evaluate the effectiveness of telemedicine solutions versus any comparator without the use of telemedicine on diabetes-related outcomes among adult patients with type 2 diabetes (T2D).

Methods:

This review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We considered telemedicine randomized controlled trials (RCT) including adults (≥18 years) diagnosed with T2D. Change in glycated hemoglobin (HbA1c, %) was the primary outcome. PubMed, EMBASE, and the Cochrane Library Central Register of Controlled Trials (CENTRAL) were searched on October 14, 2020. An overall treatment effect was estimated using a meta-analysis performed on the pool of included studies based on the mean difference (MD). The revised Cochrane risk-of-bias tool was applied and the certainty of evidence was graded using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach.

Results:

The final sample of papers included a total of 246, of which 168 had sufficient information to calculate the effect of HbA1c%. The results favored telemedicine, with an MD of −0.415% (95% confidence interval [CI] = −0.482% to −0.348%). The heterogeneity was great (I2 = 93.05%). A monitoring component gave rise to the higher effects of telemedicine.

Conclusions:

In conclusion, telemedicine may serve as a valuable supplement to usual care for patients with T2D. The inclusion of a telemonitoring component seems to increase the effect of telemedicine.

Keywords: telemedicine, diabetes mellitus, type 2, systematic review, meta-analysis, meta-regression, Denmark

Introduction

Diabetes is one of the most common chronic diseases and a major health care problem worldwide.1,2 In 2017, an estimated 8.4% of the adult global population had diabetes, which is expected to increase to approximately 9.9% (700 million) in 2045, primarily due to an increase in unhealthy dietary habits, obesity, and sedentary lifestyle.1,2 The global prevalence is predicted to increase mostly in low- and middle-income countries. 3 The economic impact of diabetes is considerable, spans health care services, and affects individuals, families, and national productivity.1,4

Type 2 diabetes (T2D) constitutes approximately 90% to 95% of diabetes cases.1,5 The T2D is a progressive disease associated with significant premature mortality, morbidity, and several complications, such as cardiovascular disease, nephropathy, neuropathy, and retinopathy.6,7 Diabetes patient care is a multifaceted and complex process, mainly aimed at attaining optimal glycemic control to prevent and control diabetes-related complications. 8 However, sustaining optimal glycemic control for people with diabetes is both demanding and challenging because it requires numerous daily self-management decisions and care activities. 9 These challenges include estimating the appropriate diabetes medication dosage to avoid hypoglycemic and hyperglycemic events and adherence to obstacles in terms of following the recommended guidelines.8,9 Adherence to the complex T2D treatment regimen is difficult to maintain 10 and medial adherence rates have been reported to range from 36% to 93%. 11

Self-management strategies are considered an essential part of diabetes treatment and are associated with improvements in health-related outcomes. 9 A potential solution to support ongoing diabetes self-management support is the use of telemedicine, 12 which has been suggested as a promising but unproven approach to support people with diabetes in the management of their disease. 13 Telemedicine can be defined as the delivery of health care services over a distance using information and communication technologies. 14 However, no definitive definition exists. 14 Telemedicine solutions may include a variety of different technologies and various delivery forms, including monitoring, education, consultative services, coaching, and counseling tasks.13,15-17 Telemedicine interventions constitute different constellations, such as simple reminders via text messaging, video consultation, and transmission of patient data (eg, blood glucose, blood pressure, dietary and medication intake, and physical activity) with feedback from health care professionals via web portals or via telephone.13,15,16 As diabetes predominantly needs to be managed outside health care facilities and to a large extent requires self-management, telemedicine holds the potential to provide sufficient self-management support to people with T2D.18,19

Previous systematic reviews have aimed to clarify the effect of telemedicine on diabetes.15-17,20-28 However, these previous reviews have often focused on a specific type of telemedicine, a specific outcome, and/or a specific comparator, which calls for a more comprehensive and inclusive systematic review seeking to compare and synthesize findings for treatment outcomes while adjusting for different study characteristics. In addition, the field of telemedicine is developing rapidly; thus, a large number of studies likely have been published recently, calling for an updated review. 29 Hence, the objective of the present systematic review, meta-analysis, and meta-regression was to evaluate the effectiveness of telemedicine solutions versus any comparator without the use of telemedicine on diabetes-related outcomes among adult patients with T2D.

Methods

Study Design

This systematic review, meta-analysis, and meta-regression was conducted and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. 30 A comprehensive search protocol was published elsewhere 31 and PROSPERO-registered with identification CRD42020123565 on April 2020. The search was part of a comprehensive search that included T2D as well as type 1 diabetes (T1D) and gestational diabetes 31 , which will be reported separately.

Eligibility Criteria

Studies were considered if they included adults (≥18 years) diagnosed with T2D. Studies that included mixed populations (eg, T1D and T2D) were only included if the data for the T2D population were reported separately. Studies were excluded if only participants at risk of diabetes or participants with prediabetes were included. Furthermore, the studies must have included telemedicine interventions that were substituted for usual practice or served as an alternative to usual practice. The telemedicine interventions had to include remote feedback/communication between a patient and health care professional(s). Alternatively, feedback/communication could occur between the patient and a trained peer. Telemedicine interventions that were wholly automatic were also considered.

Studies that reported on any relevant patient diabetes-related outcome were included. The primary outcome was change in glycated hemoglobin (HbA1c, %).

We only considered randomized controlled trials (RCTs)—both parallel and crossover designs. Studies published in English, Danish, Norwegian, and Swedish as peer-reviewed full-text papers were included. All studies published before October 14, 2020, were considered.

Information Sources

The search was performed in PubMed, EMBASE, the Cochrane Library Central Register of Controlled Trials (CENTRAL), and CINAHL. Two authors performed the database searches (S.H.L. and S.H.). A research librarian assisted. Additional citation searches were performed in the Web of Science, SCOPUS, and Google Scholar.

Search Strategy

Initially, an unstructured search was performed in PubMed, CINAHL, and Google Scholar to identify relevant search terms and thus qualify the systematic search. The systematic search followed the initial search. The search strategy was adapted for each database. The search terms included various synonyms, near-synonyms, acronyms, and spellings for all keywords and index terms. A variety of search functions were applied, including thesaurus, Boolean operators, abstract/title/keywords, phrase, truncation, free text, and advanced search. Citation searches were applied to identify additional studies.

Selection Process

First, all of the identified papers were uploaded into RefWorks (ProQuest RefWorks 2.0, 2010). Second, duplicates were removed using the functions Exact duplicates and Close duplicates. Third, titles and abstracts were screened by two authors with respect to the eligibility criteria of the review (S.H. and S.H.L.). Fourth, the remaining studies underwent full review by three authors with respect to the eligibility criteria of the review (S.H., S.H.L., and J.D.A.). Disagreement between the authors was resolved through discussion by the three authors alone or by inclusion of other authors. During the full review, the reasons for exclusion of studies were recorded, and afterward, a final sample of papers was identified.

Data Extraction

Data were extracted by three independent authors (S.H., S.H.L., and J.D.A.) using a standardized sheet in Microsoft Excel (2016). Extracted data included trial characteristics (author, publication year, country, sample size, and study duration), patient characteristics (age, sex, and body mass index [BMI]), and HbA1c outcomes. In addition, the characteristics of the telemedicine interventions were extracted, including the frequency of contact, implementation setting (primary care, hospital, specialized outpatient clinic, university, community or cross-sectional), peripherals (eg, glucometers, pedometers, blood pressure monitors, and scales), and the general purpose of intervention components (monitoring, consultation, counseling, coaching, education, mentoring, and reminding). Disagreements between the authors were resolved through discussion. Additional authors were included in the discussions when necessary.

Risk of Bias Assessment

The revised Cochrane risk-of-bias tool was applied. 32 Four reviewers (J.D.A., S.H., T.K., and F.W.U.) assessed the included studies independently and resolved potential disagreements by discussion.

Data Synthesis

All statistical analyses were performed in Stata 16 (Stata Statistical Software: Release 16, StataCorp 2019.; StataCorp LLC, College Station, Texas). Reported medians, interquartile ranges, ranges, and confidence intervals were transformed to means and standard deviations by traditional methods33,34 and scaled to HbA1c% when relevant (eg, if outcome was reported as mmol/mol). An overall treatment effect was estimated with a meta-analysis of the pool of included studies based on the mean difference (MD). Heterogeneity was assessed statistically using I2 tests. The results were combined with a random-effects model (due to heterogeneity, ie, an I2 statistic > 50%). Univariate a priori subgroup analyses based on meta-regression of the telemedicine characteristics were conducted and combined with post hoc analyses of the association of study and patient characteristics with the treatment effect of telemedicine. Publication bias was evaluated using visual inspection of the funnel plot and Egger test.

Certainty Assessment

The Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach was applied. A summary of findings (SoF) table was created using GRADEPro GDT 2015 (McMaster University, Ontario, Canada),35,36 which presents the absolute risks for the groups (treatment and control), estimates of relative risk, and ranking of the quality of the evidence, which is based on the risk of bias, 37 indirectness, 38 imprecision, 39 inconsistency, 40 and risk of publication bias. 41

Results

The flowchart in Figure 1 describes our selection of studies. In the literature search, 16 309 studies were found and 1125 eligible studies were assessed by full-text reading after screening titles and abstracts. After full-text assessment, 246 articles met our inclusion criteria.

Figure 1.

Figure 1.

Flowchart.

Abbreviation: RCT, randomized controlled trial.

The characteristics of the individual studies are presented in Table 1. One study was multinational, 88 articles were conducted in North America (36%), 84 in Asia (35%), 44 in Europe (18%), 16 in Australia/New Zealand (7%), five in Africa (2%), and five in South America (5%). Four studies were published before 2000 (2%), 50 in the 2000s (21%), 165 in the 2010s (68%), and 24 (10%) in 2020. Sample sizes ranged from 17 to 4078, with an average of 251 participants per study. The study duration ranged from one to 96 months, with a study average of 8.5 months. Across studies, the mean proportion of men was 50.4% (range = 15%-100%), the average age at baseline was 57 (range = 37-73) years, and the baseline mean BMI was 30 (range = 22-40). The average baseline HbA1c% levels ranged from 5.70% to 11.05%, with an average of 8.33%.

Table 1.

Study and Participant Characteristics.

Study Publication year Country Sample size Duration (months) Mean age years Male % Baseline BMI Baseline HbA1c
Abaza and Marschollek 42 2017 Egypt 90 3 52 44 NA 9.66
Agarwal et al 43 2019 Canada 50 4 64 55 NA 7.44
Agarwal et al 44 2019 Canada 240 3 52 52 NA 8.96
Aguiar et al 45 2018 Brazil 80 12 62 67 NA 8.95
Akinci et al 46 2018 Turkey 66 2 52 36 32 8.34
Al Omar et al 47 2020 United Arab Emirates 218 6 42 42 NA 8.45
Alanzi et al 48 2018 Saudi Arabia 20 6 NA 75 NA 8.53
Albikawi et al 49 2016 Jordan 168 3 51 46 NA NA
Alghafri et al 50 2018 Oman 232 3 44 43 33 7.96
Ali et al 51 2016 India & Pakistan 1146 30 54 46 27 9.90
Ali et al 52 2020 India 404 24 53 41 27 9.15
Aliha et al 53 2013 Iran 61 3 53 50 28 9.70
Alonso-Domínguez et al 54 2019 Spain 204 3 61 54 30 6.85
Alotaibi et al 55 2016 Saudi Arabia 20 6 45 NA NA 8.55
Anderson et al 56 2009 USA 310 24 56 41 34 7.48
Anderson et al 57 2010 USA 295 12 NA 42 35 8.00
Anderson-Loftin et al 58 2005 USA 97 6 57 23 35 7.90
Andreae et al 59 2020 USA 230 3 59 20 NA 8.29
Anzaldo-Campos et al 60 2016 Mexico 301 10 52 38 31 11.05
Arora et al 61 2014 USA 128 6 51 36 NA 10.10
Asante et al 62 2020 Ghana 60 3 56 22 28 8.95
Avdal et al 63 2011 Turkey 122 6 52 49 NA 8.07
Azizi et al 64 2016 Iran 72 4 55 50 NA NA
Benson et al 65 2018 USA 120 12 60 55 37 8.20
Blackberry et al 66 2013 Australia 473 18 63 57 NA 8.06
Bluml et al 67 2019 USA 446 3 54 41 37 10.25
Boels et al 12 2019 Netherlands 230 6 59 60 32 8.20
Bogner et al 68 2012 USA 182 3 57 32 34 7.10
Bohingamu Mudiyanselage et al 69 2018 Australia 177 12 70 53 NA 5.70
Lashkari et al 70 2013 Iran 50 3 NA NA 29 9.68
Browning et al 71 2016 China 711 12 64 52 26 10.45
Bujnowska-Fedak et al 72 2011 Poland 100 6 55 54 25 7.65
Buysse et al 73 2019 Belgium 153 24 37 50 NA 8.30
Capozza et al 74 2015 USA 156 6 53 37 NA 9.11
Carter et al 75 2011 USA 47 9 51 36 36 8.91
Castelnuovo et al 76 2011 Italy 72 12 52 52 NA NA
Chao et al 77 2019 Taiwan 121 3 NA NA 25 8.70
Chen et al 78 2008 Taiwan 78 6 59 44 26 9.61
Chen et al 79 2018 China 233 NA 59 51 NA NA
Chiu et al 80 2016 Taiwan 182 8 65 52 26 7.65
Cho et al 81 2006 Korea 80 30 53 54 23 7.60
Cho et al 82 2017 Korea 484 6 53 64 26 7.84
Choe et al 83 2005 USA 80 14 52 47 NA 10.15
Choudhry et al 84 2018 USA 4078 12 60 55 NA 9.65
Clark et al 85 2004 UK 100 12 60 58 31 8.42
Crowley et al 86 2013 USA 369 12 61 28 NA 8.00
Crowley et al 87 2016 USA 50 6 60 96 NA 10.45
Dale et al 88 2009 UK 231 6 NA 60 NA 8.56
Dario et al 89 2017 Italy 299 12 73 56 NA 7.94
Davis et al 90 2010 USA 165 12 60 25 37 8.96
Del Prato et al 91 2012 Italy 291 5.5 58 52 30 8.86
Delahanty et al 92 2019 USA 211 12 62 45 35 7.70
Doupis et al 7 2019 Greece 457 8 63 51 31 7.85
Dugas et al 93 2018 USA 27 3 NA 89 NA 9.23
Duruturk and Özköslü 94 2019 Turkey 50 1.5 53 NA 31 7.36
Döbler et al 95 2018 Germany 249 12 52 70 36 7.70
Eakin et al 96 2013 Australia 302 6 58 56 33 7.45
Eakin et al 97 2014 Australia 302 24 58 56 33 7.45
Egede et al 98 2017 USA 113 6 54 19 36 10.10
Egede et al 99 2018 USA 90 12 63 98 NA 7.11
Estey et al 100 1990 Canada 60 4 NA 46 NA 6.21
Faridi et al 101 2008 USA 30 3 56 37 36 6.45
Farsaei et al 102 2011 Iran 172 3 53 34 NA 9.10
Fernandes et al 103 2016 Brazil 219 6 63 31 29 8.07
Fortmann et al 104 2017 USA 126 6 48 25 32 9.55
Fottrell et al 105 2019 Bangladesh 2470 18 NA 47 22 NA
Fountoulakis et al 106 2015 Greece 80 12 62 69 30 9.80
Franc et al 107 2020 France 665 12 39 48 26 9.10
Franciosi et al 108 2011 Italy 62 6 49 74 31 7.90
Frosch et al 109 2011 USA 201 6 55 52 33 9.60
García et al 110 2015 USA 72 6 50 33 36 8.60
Garg et al 111 2017 USA 184 12 64 60 35 9.05
Gagliardino et al 112 2013 Argentina 198 12 61 49 33 7.21
Wasif Gillani 113 2016 Malaysia 150 6 53 55 28 9.89
Gimbel et al 114 2020 USA 240 12 63 62 33 7.55
Glasgow et al 115 2006 USA 327 2 62 50 32 7.45
Glasgow et al 116 2006 USA 327 2 61 55 33 7.25
Glasgow and Toobert 117 2000 USA 320 6 59 39 NA 7.60
Glasgow et al 118 2002 USA 320 12 59 39 NA 7.59
Glasgow et al 119 2005 USA 886 12 63 49 NA 7.32
Goodarzi et al 120 2012 Iran 100 3 54 22 28 7.87
Goodarzi et al 121 2018 Iran 76 3 57 100 NA NA
Graziano and Gross 122 2009 USA 120 3 62 55 NA 8.65
Griffin et al 123 2014 UK 478 12 60 62 33 7.12
Gupta et al 124 2020 India 81 4 50 52 28 8.45
Haider et al 125 2019 Australia 229 6 59 83 31 NA
Hansen et al 126 2017 Denmark 165 8 58 64 34 9.30
Hare et al 127 2011 Australia 223 33 55 56 32 7.55
Hee-Sung 128 2007 South Korea 60 3 50 42 24 6.82
Heisler et al 129 2019 USA 290 6 63 98 NA 9.10
Hidrus et al 130 2020 Malaysia 100 3 NA 50 NA NA
Hokanson et al 131 2006 USA 114 6 54 57 33 8.60
Holbrook et al 132 2009 Canada 511 6 61 51 32 7.05
Holmen et al 133 2014 Norway 151 12 57 55 31 8.25
Hordern et al 134 2009 Australia 223 12 56 55 32 7.55
Huang et al 135 2019 Singapore 50 3 52 49 29 8.65
Huizinga et al 136 2010 USA 165 24 56 60 34 6.64
Hunt et al 137 2014 USA 17 3 NA 41 NA 6.59
Iljaž et al 138 2017 Slovenia 120 12 55 30 32 6.95
Islam et al 139 2019 Bangladesh 239 6 48 46 NA NA
Jahangard-Rafsanjani et al 140 2015 Iran 101 5 57 50 29 7.56
Jain et al 141 2018 India 299 6 57 57 24 8.16
Jarab et al 142 2012 Jordan 171 6 64 57 33 8.45
Jennings et al 143 2014 Australia 436 8 58 52 33 NA
Jeong et al 144 2018 Korea 338 6 53 67 25 8.30
Jiwani et al 145 2020 USA 26 6 58 30 39 9.30
Kardas et al 146 2016 Poland 62 1.5 59 60 31 6.81
Kassavou et al 147 2020 UK 135 3 NA 54 NA NA
Kempf et al 148 2017 Germany 202 12 59 54 36 8.30
Keogh et al 149 2011 Ireland 121 6 59 63 32 9.18
Kim and Utz 150 2019 South Korea 155 3 51 48 NA 9.14
Kim 151 2007 Korea 60 3 47 43 24 7.84
Kim and Jeong 152 2007 Korea 60 6 47 43 24 7.84
Kim and Song 153 2008 Korea 40 12 47 47 25 7.85
Kim and Kim 154 2008 Korea 40 6 47 47 25 7.85
Kim and Oh 155 2003 Korea 50 3 60 30 24 8.50
Kim et al 156 2005 Korea 35 3 61 36 24 8.60
Kim and Kang 157 2006 Korea 73 3 55 53 NA 7.94
Kim et al 158 2009 USA 83 6.5 56 56 26 9.25
Kim et al 159 2010 Korea 100 3 48 50 24 9.80
Kim et al 160 2015 Korea 70 6 66 50 25 8.55
Kim et al 161 2016 China 220 6 54 48 26 7.95
King et al 162 2006 USA 335 2 61 49 32 NA
Kirkman et al 163 1994 USA 275 12 64 99 NA 10.70
Kleinman et al 164 2017 India 91 6 48 70 29 9.25
Krein et al 165 2004 USA 246 18 61 97 NA 9.25
Ku et al 166 2020 Australia 40 3 50 35 28 8.95
Kusnanto et al 167 2019 Indonesia 30 3 NA 43 NA 8.46
Kwon et al 168 2004 Korea 110 3 54 61 24 7.39
Lauffenburger et al 169 2019 USA 1400 12 55 63 NA 9.35
Lazo-Porras et al 170 2020 Peru 172 18 61 37 28 8.55
Lee et al 171 2017 Malaysia 85 3 53 51 30 8.74
Lee et al 172 2020 South Korea 72 6 NA NA 26 7.44
Lee et al 173 2019 Malaysia 240 12 56 54 NA 9.00
Li et al 174 2016 China 53 6 62 53 24 7.73
Liebreich et al 175 2009 Canada 49 3 54 41 34 NA
Lim et al 176 2011 Korea 154 6 68 21 25 7.85
Lim et al 177 2016 Korea 100 6 65 75 26 8.00
Lorig et al 178 2010 USA 761 6 54 29 NA 6.41
Lujan et al 179 2007 USA 150 6 58 22 NA 7.96
Luley et al 180 2011 Germany 70 6 58 49 35 7.55
Lutes et al 181 2017 USA 200 12 53 NA 38 9.09
Lynch et al 182 2014 USA 61 6 54 33 36 7.65
MacPhail et al 183 2014 Australia 87 4 68 NA 31 NA
Marios et al 184 2012 Australia 39 6 63 53 33 7.73
Maslakpak et al 185 2017 Iran 90 3 50 60 29 8.00
Mayberry et al 186 2020 USA 379 6 57 46 NA 8.13
McEwen et al 187 2017 USA 157 9 54 35 33 9.93
McKay et al 188 2001 USA 78 2 52 47 NA NA
McKay et al 189 2002 USA 160 3 59 45 NA 7.48
McKee et al 190 2011 USA 55 6 60 33 33 8.22
McMahon et al 191 2012 USA 152 12 61 93 34 9.85
Mease 192 2000 USA 28 3 63 39 NA 9.50
Mons et al 193 2013 Germany 204 18 68 61 NA 8.10
Moriyama et al 194 2009 Japan 75 12 66 46 NA 7.47
Mwangi et al 195 2020 Kenya 104 3 62 32 25 NA
Namjoo Nasab et al 196 2017 Iran 64 3 52 48 27 NA
Nesari et al 197 2010 Iran 61 3 51 28 28 9.26
Nicolucci et al 198 2015 Italy 302 12 58 65 29 7.95
Niswender et al 199 2014 Several 611 6 57 51 34 7.95
O’Neil et al 200 2016 USA 563 12 NA 29 NA 8.32
Odegard and Christensen 201 2012 USA 165 12 63 48 NA NA
Odnoletkova et al 202 2016 Belgium 574 18 63 62 30 7.00
Oh et al 203 2003 Korea 50 3 61 36 25 8.55
Orsama et al 204 2013 Finland 56 10 62 54 32 6.98
Owolabi et al 205 2019 South Africa 216 6 NA 16 32 NA
Parsons et al 206 2019 UK 446 12 62 57 33 8.60
Patja et al 207 2012 Finland 1535 12 65 57 32 7.57
Peasah et al 208 2019 USA 78 3 62 53 35 8.20
Peimani et al 209 2016 Iran 150 3 52 53 28 7.41
Piette et al 210 2011 USA 339 12 56 49 38 7.60
Plotnikoff et al 211 2013 Canada 287 12 62 51 30 7.16
Presley et al 212 2020 USA 120 6 55 28 35 9.98
Quinn et al 213 2017 USA 142 12 52 51 35 9.59
Quinn et al 214 2011 USA 213 12 53 51 35 9.24
Raj and Mathews 215 2020 India 50 6 69 54 NA 10.26
Ralston et al 216 2009 USA 83 12 57 51 NA 8.05
Ramadas et al 217 2018 Malaysia 132 12 51 69 NA 9.00
Rasmussen et al 218 2016 Denmark 40 6 63 68 32 8.55
Rodríguez-Idígoras et al 219 2009 Spain 328 12 64 52 NA 7.51
Ruggiero et al 220 2014 USA 270 12 53 32 33 8.63
Sacco et al 221 2009 USA 62 6 52 42 36 8.50
Sacco et al 222 2012 USA 62 6 52 42 36 8.50
Samuel-Hodge et al 223 2009 USA 201 12 59 36 35 7.78
Sarayani et al 224 2018 Iran 100 9 55 58 30 7.95
Saslow et al 225 2020 USA 64 12 NA NA NA NA
Sazlina et al 226 2015 Malaysia 69 8 64 57 27 8.20
Schillinger et al 227 2009 USA 339 12 56 39 31 9.35
Shahid et al 228 2015 Pakistan 440 4 49 61 27 9.97
Shahsavari and Bakhshandeh Bavarsad 229 2020 Iran 60 3 NA 15 29 8.93
Shetty et al 230 2011 India 215 12 50 NA 27 9.00
Shreck et al 231 2014 USA 526 12 56 33 NA 8.65
Sigurdardottir et al 232 2009 Iceland 58 6 61 68 32 7.99
Skelly et al 233 2009 USA 180 9 67 NA NA 8.37
Sone et al 234 2002 Japan 2205 36 59 55 23 7.74
Sone et al 235 2010 Japan 2033 96 59 46 23 7.85
Song and Kim 236 2009 Korea 49 3 50 43 25 9.20
Spencer et al 237 2018 USA 222 6 49 39 33 7.93
Steventon et al 238 2014 England 513 12 65 58 31 8.42
Sun et al 239 2019 China 91 6 68 46 23 7.86
Sunil Kumar et al 240 2020 India 300 6 65 60 NA 7.60
Takenga et al 241 2014 Democratic Republic of Congo 40 2 NA 73 NA 8.63
Tamban et al 242 2013 Philippines 104 6 50 27 28 7.84
Tan et al 243 2018 Singapore 142 2 62 NA NA 9.72
Tang et al 244 2013 USA 415 12 54 60 NA 9.26
Teston et al 245 2017 Brazil 134 5 NA 32 NA NA
Thom et al 246 2013 USA 299 6 55 48 34 9.99
Torbjørnsen et al 247 2014 Norway 164 4 58 59 32 7.85
Tu et al 248 1993 USA 31 3 65 33 NA NA
Van Dyck et al 249 2013 Belgium 92 12 62 69 30 7.30
Van Dyck et al 250 2011 Belgium 92 12 62 NA 30 NA
Van Vugt et al 251 2016 The Netherlands 132 6 68 53 30 6.59
Varney et al 252 2014 Australia 94 12 62 68 32 8.35
Vaughan et al 253 2020 USA 89 6 55 28 34 8.86
Vervloet et al 254 2014 The Netherlands 604 24 55 55 NA NA
Vinithia et al 255 2019 India 248 24 43 68 27 9.50
Von Storch et al 256 2019 Germany 2441 3 59 81 31 6.99
Wakefield et al 257 2011 USA 302 12 68 94 33 7.15
Wakefield et al 258 2012 USA 302 12 68 94 33 7.15
Wakefield et al 259 2014 USA 108 6 60 44 NA 7.30
Waki et al 260 2014 Japan 54 3 57 76 27 7.05
Walker et al 261 2011 USA 527 12 56 33 31 8.65
Wang et al 262 2020 Mongolia 171 12 55 48 26 9.15
Wang et al 263 2019 China 120 6 45 32 NA 8.65
Wang et al 264 2017 China 212 6 54 55 25 7.95
Warren et al 265 2018 Australia 157 6 61 55 34 8.27
Weinberger et al 266 1995 USA 275 12 64 99 NA 10.70
Whittemore et al 267 2004 USA 53 6 58 NA 35 7.65
Wichit et al 268 2017 Thailand 140 3 58 27 27 6.65
Wild et al 269 2016 UK 321 9 61 67 33 8.85
Williams et al 270 2012 Australia 120 6 57 65 33 8.55
Williams et al 271 2017 New Zealand 138 6 55 38 40 8.15
Wolever et al 272 2010 USA 56 6 53 23 NA 7.93
Wolf et al 273 2004 USA 147 12 53 40 38 7.70
Wu et al 274 2017 Australia & Taiwan 181 1 66 61 NA NA
Yang et al 275 2020 South Korea 401 3 56 51 26 7.96
Yasmin et al 276 2020 Bangladesh 320 12 52 23 NA NA
Yoo et al 277 2009 Korea 123 3 58 59 26 7.50
Yoon and Kim 278 2008 South Korea 60 12 47 43 24 7.83
Young et al 279 2005 UK 591 12 67 58 30 7.93
Yu et al 280 2019 China 185 6 52 28 26 8.60
Zamanzadeh et al 281 2017 Iran 66 3 49 41 NA NA
Zhou et al 282 2014 China 114 3 NA NA 24 8.33

Abbreviations: BMI, body mass index; HbA1c, glycated hemoglobin; NA, not available.

Table 2 illustrates the telemedicine technologies implemented across studies. Seventy-one studies (29%) were conducted in a hospital setting, 58 studies (24%) in the primary care sector, 37 in communities (15%), 34 in specialized outpatient clinics (14%), 14 in a university setting (6%), and four in cross-sectorial implementations (2%). The frequency of contact with patients across studies was daily (30 studies, 12%), weekly (83 studies, 34%), every two weeks (26 studies, 11%), monthly (40 studies, 16%), and more rarely (12 studies, 5%). Twenty-four (10%) of the studies reported a “tailored” number of contacts with participants (10%). Across studies, the explicitly reported peripherals were scales (13 studies, 5%), glucometers (45 studies, 19%), blood pressure monitors (19 studies, 8%), and pedometers (16 studies, 7%).

Table 2.

Telemedicine Intervention Characteristics.

Study Publication year Setting Frequency of contact Included peripherals Intervention components
Glucometer Pedometer BP monitor Scale Monitoring Consultation Counseling Coaching Education Mentoring Reminding
Abaza and Marschollek 42 2017 Hospital Daily x x x x
Agarwal et al 43 2019 Community Weekly x
Agarwal et al 44 2019 Hospital Daily x x
Aguiar et al 45 2018 Hospital Once x
Akinci et al 46 2018 University x
Al Omar et al 47 2020 Primary Daily x
Alanzi et al 48 2018 Community x x
Albikawi et al 49 2016 Specialized Once x
Alghafri et al 50 2018 Primary Monthly x
Ali et al 51 2016 Specialized Monthly x
Ali et al 52 2020 Hospital Weekly x
Aliha et al 53 2013 Specialized Weekly x
Alonso-Domínguez et al 54 2019 Primary Daily x
Alotaibi et al 55 2016 Hospital Weekly x x x
Anderson et al 56 2009 Community Monthly x
Anderson et al 57 2010 Community Tailored x x
Anderson-Loftin et al 58 2005 Primary Weekly x x
Andreae et al 59 2020 Community Weekly x
Anzaldo-Campos et al 60 2016 Primary x x x
Arora et al 61 2014 Hospital Daily x x
Asante et al 62 2020 Specialized Weekly x
Avdal et al 63 2011 University x x
Azizi et al 64 2016 Specialized x x
Benson et al 65 2018 Primary Monthly x x
Blackberry et al 66 2013 Primary Monthly x
Bluml et al 67 2019 Primary Weekly x x
Boels et al 12 2019 Hospital Daily x
Bogner et al 68 2012 Primary Twice x x
Bohingamu Mudiyanselage et al 69 2018 Community Daily x
Lashkari et al 70 2013 Weekly x
Browning et al 71 2016 Community Monthly x
Bujnowska-Fedak et al 72 2011 Primary Weekly x x
Buysse et al 73 2019 Hospital Monthly x
Capozza et al 74 2015 Primary Daily x x
Carter et al 75 2011 Primary Weekly x x x x x
Castelnuovo et al 76 2011 Hospital Fortnight x x x
Chao et al 77 2019 Hospital x
Chen et al 78 2008 Hospital Weekly x
Chen et al 79 2018 Hospital Weekly x
Chiu et al 80 2016 Community Weekly x
Cho et al 81 2006 Hospital Weekly x
Cho et al 82 2017 Specialized Weekly x x x
Choe et al 83 2005 University Monthly x
Choudhry et al 84 2018 Primary x
Clark et al 85 2004 Specialized Fortnight x
Crowley et al 86 2013 Primary Monthly x
Crowley et al 87 2016 Hospital Fortnight x x
Dale et al 88 2009 Primary Tailored x x
Dario et al 89 2017 Tailored x x
Davis et al 90 2010 Community Monthly x x
Del Prato et al 91 2012 x x
Delahanty et al 92 2019 Community Weekly x
Doupis et al 7 2019 Specialized Weekly x
Dugas et al 93 2018 Specialized Daily x x x
Duruturk and Özköslü 94 2019 Hospital Weekly x
Döbler et al 95 2018 Specialized Monthly x
Eakin et al 96 2013 Primary Fortnight x x x
Eakin et al 97 2014 Primary Fortnight x x x
Egede et al 98 2017 Community Weekly x x x
Egede et al 99 2018 Community
Estey et al 100 1990 University Fortnight x x
Faridi et al 101 2008 Community Daily x x
Farsaei et al 102 2011 Specialized Weekly x
Fernandes et al 103 2016 Primary Monthly x
Fortmann et al 104 2017 Community Daily x x x
Fottrell et al 105 2019 Community Weekly x
Fountoulakis et al 106 2015 Hospital Tailored x x
Franc et al 107 2020 Primary Daily x
Franciosi et al 108 2011 Specialized Monthly x x
Frosch et al 109 2011 Primary Tailored x
García et al 110 2015 Community Fortnight x x
Garg et al 111 2017 Hospital Weekly x x
Gagliardino et al 112 2013 Specialized Tailored x
Wasif Gillani 113 2016 Hospital Twice x x
Gimbel et al 114 2020 Primary Daily x x
Glasgow et al 115 2006 Primary care Twice x
Glasgow et al 116 2006 Twice x
Glasgow and Toobert 117 2000 Specialized Fortnight x
Glasgow et al 118 2002 Specialized Fortnight x
Glasgow et al 119 2005 Primary care x
Goodarzi et al 120 2012 Tailored x
Goodarzi et al 121 2018 University Weekly x
Graziano and Gross 122 2009 Cross-sectional Daily x x
Griffin et al 123 2014 Primary Monthly x
Gupta et al 124 2020 Hospital Weekly x x
Haider et al 125 2019 Hospital Weekly x
Hansen et al 126 2017 Hospital Monthly x x
Hare et al 127 2011 Hospital Tailored x
Hee-Sung 128 2007 Hospital Monthly x x x
Heisler et al 129 2019 Hospital Monthly x
Hidrus et al 130 2020 Hospital Daily x
Hokanson et al 131 2006 Specialized Tailored x
Holbrook et al 132 2009 Primary x
Holmen et al 133 2014 Primary Monthly x x
Hordern et al 134 2009 Hospital Tailored x x
Huang et al 135 2019 Specialized Daily x
Huizinga et al 136 2010 University Monthly x
Hunt et al 137 2014 Specialized Weekly x
Iljaž et al 138 2017 Primary Tailored x x x
Islam et al 139 2019 Hospital Daily x
Jahangard-Rafsanjani et al 140 2015 Community Monthly x
Jain et al 141 2018 Community Weekly x x
Jarab et al 142 2012 Specialized Weekly x
Jennings et al 143 2014 x
Jeong et al 144 2018 Hospital Twice x x x
Jiwani et al 145 2020 Community Weekly x
Kardas et al 146 2016 Primary x x x x x
Kassavou et al 147 2020 Primary Weekly x
Kempf et al 148 2017 Specialized Weekly x
Keogh et al 149 2011 Specialized Once x
Kim and Utz 150 2019 Hospital Weekly x x
Kim 151 2007 Hospital Weekly x x
Kim and Jeong 152 2007 Hospital Weekly x x
Kim and Song 153 2008 Hospital Weekly x x
Kim and Kim 154 2008 Hospital Weekly x x
Kim and Oh 155 2003 Hospital Weekly x x
Kim et al 156 2005 Hospital Weekly x x
Kim and Kang 157 2006 Hospital Tailored x
Kim et al 158 2009 Community Monthly x x x x
Kim et al 159 2010 Hospital Daily x x x
Kim et al 160 2015 Hospital x
Kim et al 161 2016 Hospital Tailored x
King et al 162 2006 Primary Twice x
Kirkman et al 163 1994 Primary Monthly x
Kleinman et al 164 2017 Specialized x x
Krein et al 165 2004 Specialized x
Ku et al 166 2020 Hospital Weekly x x x
Kusnanto et al 167 2019 Primary Daily x
Kwon et al 168 2004 Hospital Tailored x x
Lauffenburger et al 169 2019 Weekly x x
Lazo-Porras et al 170 2020 Hospital Weekly x x
Lee et al 171 2017 Community x x x x
Lee et al 172 2020 Hospital Weekly x x
Lee et al 173 2019 Primary Weekly x x
Li et al 174 2016 Hospital Monthly x x
Liebreich et al 175 2009 Weekly x x
Lim et al 176 2011 Hospital x x
Lim et al 177 2016 Hospital x x x
Lorig et al 178 2010 Weekly x
Lujan et al 179 2007 Community Fortnight x x
Luley et al 180 2011 Hospital Weekly x x x
Lutes et al 181 2017 Primary Monthly x x x x
Lynch et al 182 2014 Community Weekly x
MacPhail et al 183 2014 Primary Twice x
Marios et al 184 2012 Primary Weekly x x
Maslakpak et al 185 2017 Weekly x
Mayberry et al 186 2020 Primary Monthly x
McEwen et al 187 2017 Community Tailored x
McKay et al 188 2001 Weekly x x
McKay et al 189 2002 Primary Weekly x
McKee et al 190 2011 Community x x x x
McMahon et al 191 2012 Tailored x x x
Mease 192 2000 Primary Weekly x x
Mons et al 193 2013 Primary Monthly x
Moriyama et al 194 2009 Hospital Fortnight x x
Mwangi et al 195 2020 Hospital Monthly x x
Namjoo Nasab et al 196 2017 Community Weekly x
Nesari et al 197 2010 Specialized Weekly x x
Nicolucci et al 198 2015 Primary Monthly x x x x x
Niswender et al 199 2014 Cross-sectional Fortnight x
O’Neil et al 200 2016 University Weekly x x
Odegard and Christensen 201 2012 Community Monthly x x
Odnoletkova et al 202 2016 Fortnight x
Oh et al 203 2003 Hospital Weekly x x
Orsama et al 204 2013 Community Tailored x x x x x
Owolabi et al 205 2019 Primary Daily x x x
Parsons et al 206 2019 Primary Weekly x x
Patja et al 207 2012 Primary Monthly x
Peasah et al 208 2019 Primary Weekly x x
Peimani et al 209 2016 Hospital Weekly x
Piette et al 210 2011 Community Weekly x
Plotnikoff et al 211 2013 Community Tailored x
Presley et al 212 2020 Community Weekly x x
Quinn et al 213 2017 Community Tailored x x
Quinn et al 214 2011 Community Tailored x x
Raj and Mathews 215 2020 Hospital Weekly x x
Ralston et al 216 2009 Hospital Weekly x
Ramadas et al 217 2018 Hospital x x
Rasmussen et al 218 2016 Specialized x
Rodríguez-Idígoras et al 219 2009 Community Tailored x x
Ruggiero et al 220 2014 Primary Monthly x
Sacco et al 221 2009 University Weekly x
Sacco et al 222 2012 University Weekly x
Samuel-Hodge et al 223 2009 Community Monthly x
Sarayani et al 224 2018 Weekly x
Saslow et al 225 2020 University Daily x
Sazlina et al 226 2015 Primary x x
Schillinger et al 227 2009 Weekly x
Shahid et al 228 2015 Specialized Weekly x x x
Shahsavari and Bakhshandeh Bavarsad 229 2020 Specialized Weekly x
Shetty et al 230 2011 Specialized Weekly x
Shreck et al 231 2014 Fortnight x
Sigurdardottir et al 232 2009 Specialized Weekly x
Skelly et al 233 2009 Cross-sectional Fortnight x x
Sone et al 234 2002 Specialized Fortnight x x
Sone et al 235 2010 Specialized Fortnight x x x
Song and Kim 236 2009 Specialized Weekly x x
Spencer et al 237 2018 Community Fortnight x x
Steventon et al 238 2014 Cross-sectional Daily x x x x
Sun et al 239 2019 Hospital Daily x x x x
Sunil Kumar et al 240 2020 Hospital Daily x x x
Takenga et al 241 2014 Hospital x
Tamban et al 242 2013 Weekly x
Tan et al 243 2018 Primary Fortnight x
Tang et al 244 2013 x x x
Teston et al 245 2017 Fortnight x
Thom et al 246 2013 Community Fortnight x x
Torbjørnsen et al 247 2014 Monthly x x
Tu et al 248 1993 Hospital Weekly x x
Van Dyck et al 249 2013 Hospital Fortnight x x x
Van Dyck et al 250 2011 Hospital Fortnight x x x
Van Vugt et al 251 2016 Primary x x
Varney et al 252 2014 Hospital Monthly x
Vaughan et al 253 2020 Primary Weekly x x
Vervloet et al 254 2014 x
Vinithia et al 255 2019 Hospital Weekly x x
Von Storch et al 256 2019 Weekly x x x
Wakefield et al 257 2011 Primary Daily x x x x
Wakefield et al 258 2012 Primary Daily x x x x
Wakefield et al 259 2014 University Tailored x x x
Waki et al 260 2014 University Tailored x x x x x
Walker et al 261 2011 Specialized Monthly x
Wang et al 262 2020 Hospital Weekly x
Wang et al 263 2019 Hospital Weekly x x
Wang et al 264 2017 Hospital Fortnight x x x
Warren et al 265 2018 Primary Daily x x x x
Weinberger et al 266 1995 Primary Monthly x x
Whittemore et al 267 2004 Specialized Monthly x
Wichit et al 268 2017 Hospital Once x x
Wild et al 269 2016 Primary x x x x
Williams et al 270 2012 Hospital Weekly x
Williams et al 271 2017 Primary Monthly x
Wolever et al 272 2010 Weekly x
Wolf et al 273 2004 Primary Monthly x x
Wu et al 274 2017 University Once x x
Yang et al 275 2020 Primary Daily x x
Yasmin et al 276 2020 Hospital Fortnight x x x
Yoo et al 277 2009 University Tailored x x x x x
Yoon and Kim 278 2008 Hospital Weekly x x
Young et al 279 2005 Primary Monthly x x
Yu et al 280 2019 Hospital Daily x x
Zamanzadeh et al 281 2017 Daily x
Zhou et al 282 2014 Hospital Fortnight x x x x x

Abbreviation: BP, blood pressure.

The final sample included 86 studies (35%) with a monitoring component in the telemedicine intervention, 22 studies with a consultation opportunity (9%), 53 studies with a counseling purpose (22%), 63 studies with an opportunity for patients to receive coaching (26%), 81 studies with a patient education component (33%), and eight studies with the possibility of mentoring (3%). Furthermore, 38 studies were able to send reminders (16%).

The evaluation of risk of bias is described for each study in Online Appendix 1 and across studies in Figure 2. Overall, there was a high risk of bias in 45% of the included studies, a moderate risk in 38% and a low risk in 17%. This result was largely attributed to two factors. First were missing outcomes at follow-up, where a high proportion of studies (43%) only reported results of a complete case or per-protocol analysis without appropriate consideration of the relationship with covariates and missingness (ie, tests for missing completely at random or an assumption of missing at random with imputation and/or tests for association with baseline variables and missingness and/or adjusted analyses). Second, there were some concerns regarding the risk of selecting published results, especially due to a lack of registered or published research protocols in the majority of studies (72%).

Figure 2.

Figure 2.

Summary of risk of bias assessment.

Effect on HbA1c%

Of the 243 studies, 168 had sufficient information to calculate an MD with standard errors for the effect on HbA1c% and reported treatment effects of telemedicine from one to 96 months. Figure 3 and Table 3 present the results from the individual studies and the meta-analysis. Overall, the results favored telemedicine, with an MD of −0.415%, which was statistically significant (95% confidence interval [CI] = −0.482% to −0.348%). The heterogeneity was great (I2 = 93.05%).

Figure 3.

Figure 3.

Forest plot of the meta-analysis (magenta line is effect size difference of 0).

Table 3.

Meta-Analysis Summary.

Study MD Lower 95% CI Higher 95% CI Weight
Abaza and Marschollek 42 −0.11 −0.72 0.50 0.47
Aguiar et al 45 −0.63 −1.08 −0.18 0.57
Akinci et al 46 −0.57 −1.21 0.07 0.45
Alanzi et al 48 −1.25 −2.14 −0.36 0.33
Ali et al 51 −0.40 −0.59 −0.22 0.73
Aliha et al 53 −1.30 −1.88 −0.72 0.49
Alotaibi et al 55 −0.74 −1.56 0.08 0.36
Anderson et al 56 −0.29 −0.60 0.02 0.66
Anderson-Loftin et al 58 −1.00 −1.56 −0.44 0.50
Anzaldo-Campos et al 60 −1.37 −1.81 −0.94 0.58
Arora et al 61 −0.13 −0.56 0.31 0.58
Avdal et al 63 −0.69 −1.04 −0.35 0.64
Azizi et al 64 −0.40 −0.55 −0.25 0.74
Blackberry et al 66 −0.06 −0.27 0.15 0.72
Bogner et al 68 −1.20 −1.52 −0.88 0.65
Lashkari et al 70 −0.99 −1.62 −0.36 0.46
Browning et al 71 0.03 −0.16 0.22 0.73
Bujnowska-Fedak et al 72 −0.06 −0.71 0.59 0.45
Chen et al 78 −0.76 −1.33 −0.19 0.49
Cho et al 81 −0.70 −1.16 −0.24 0.56
Cho et al 82 −0.15 −0.32 0.02 0.74
Choe et al 83 −1.30 −1.88 −0.72 0.49
Crowley et al 86 −0.10 −0.17 −0.04 0.76
Crowley et al 87 −1.00 −1.35 −0.65 0.64
Dale et al 88 0.10 −0.23 0.43 0.65
Dario et al 89 0.01 −0.23 0.25 0.70
Davis et al 90 −0.70 −0.90 −0.50 0.72
Del Prato et al 91 0.00 −0.06 0.06 0. 77
Dugas et al 93 0.18 −0.87 1.23 0.27
Döbler et al 95 −0.80 −1.11 −0.49 0.66
Eakin et al 96 0.00 −0.29 0.29 0.67
Estey et al 100 −0.20 −0.77 0.37 0.49
Faridi et al 101 −0.40 −0.98 0.18 0.49
Farsaei et al 102 −1.50 −1.85 −1.15 0.64
Fortmann et al 104 −0.90 −1.34 −0.46 0.58
Fountoulakis et al 106 −0.70 −1.16 −0.24 0.56
Franciosi et al 108 −0.50 −0.74 −0.26 0.70
Frosch et al 109 −0.30 −0.42 −0.18 0.75
García et al 110 −1.20 −1.45 −0.95 0.69
Garg et al 111 −0.30 −0.65 0.05 0.64
Gagliardino et al 112 −0.20 −0.51 0.11 0.66
Glasgow and Toobert 117 0.10 −0.27 0.47 0.62
Glasgow et al 118 −0.20 −0.55 0.15 0.64
Glasgow et al 119 0.01 −0.13 0.15 0.74
Glasgow et al 115 −0.20 −0.48 0.08 0.68
Glasgow et al 116 0.00 −0.27 0.27 0.68
Goodarzi et al 120 −0.46 −0.88 −0.04 0.59
Graziano and Gross 122 −0.07 −0.45 0.31 0.62
Griffin et al 123 −0.01 −0.18 0.16 0.73
Hare et al 127 −0.10 −0.41 0.21 0.66
Hee-Sung 128 −0.43 −0.81 −0.05 0.62
Holbrook et al 132 −0.50 −0.71 −0.30 0.72
Holmen et al 133 −0.20 −0.68 0.28 0.55
Hordern et al 134 −0.70 −0.99 −0.41 0.67
Iljaž et al 138 −0.30 −0.69 0.09 0.61
Jahangard-Rafsanjani et al 140 −0.40 −0.89 0.09 0.54
Jarab et al 142 −0.90 −1.46 −0.34 0.50
Jeong et al 144 −0.12 −0.40 0.16 0.68
Kardas et al 146 −0.03 −0.51 0.45 0.55
Kempf et al 148 −0.60 −0.91 −0.29 0.66
Keogh et al 149 −0.39 −0.78 0.00 0.61
Kim and Oh 155 −1.20 −1.74 −0.66 0.51
Kim et al 156 −1.00 −1.63 −0.38 0.46
Kim and Kang 157 −0.90 −1.58 −0.22 0.43
Kim 151 −0.72 −1.22 −0.22 0.54
Kim and Jeong 152 −0.66 −1.20 −0.12 0.51
Kim and Song 153 −1.52 −2.02 −1.02 0.54
Kim and Kim 154 −0.59 −1.21 0.03 0.46
Kim et al 158 −0.90 −1.40 −0.40 0.54
Kim et al 159 −0.40 −0.74 −0.06 0.64
Kim et al 160 −0.70 −1.13 −0.27 0.58
Kim et al 161 −0.70 −0.96 −0.44 0.69
Kleinman et al 164 −0.30 −0.77 0.17 0.56
Krein et al 165 0.10 −0.28 0.48 0.62
Kwon et al 168 −0.68 −0.82 −0.55 0.75
Lee et al 171 −0.93 −1.49 −0.37 0.50
Li et al 174 −0.35 −0.95 0.25 0.48
Lim et al 176 −0.40 −0.79 −0.01 0.61
Lim et al 177 −0.60 −1.00 −0.20 0.60
Lorig et al 178 −0.11 −0.26 0.05 0.74
Lujan et al 179 −0.25 −0.68 0.18 0.58
Luley et al 180 −1.00 −1.33 −0.67 0.65
Lutes et al 181 −0.26 −0.66 0.14 0.60
Marios et al 184 0.49 −0.25 1.23 0.40
Maslakpak et al 185 −0.50 −1.09 0.09 0.48
McEwen et al 187 −0.01 −0.46 0.44 0.57
McKay et al 189 0.36 −0.17 0.89 0.52
McKee et al 190 −0.60 −1.39 0.19 0.37
McMahon et al 191 −0.10 −0.56 0.36 0.56
Nesari et al 197 −1.56 −2.18 −0.94 0.46
Nicolucci et al 198 −0.34 −0.57 −0.11 0.71
Niswender et al 199 −0.13 −0.17 −0.10 0.77
Odnoletkova et al 202 −0.10 −0.27 0.07 0.73
Oh et al 203 −1.30 −1.88 −0.72 0.49
O’Neil et al 200 −0.39 −0.59 −0.19 0.72
Orsama et al 204 −0.44 −0.88 0.01 0.58
Peimani et al 209 −0.49 −0.95 −0.03 0.56
Piette et al 210 0.00 −0.28 0.28 0.68
Plotnikoff et al 211 0.21 0.13 0.29 0.76
Quinn et al 214 −0.80 −1.26 −0.34 0.56
Ramadas et al 217 0.10 −0.39 0.59 0.55
Rodríguez-Idígoras et al 219 0.05 −0.18 0.28 0.70
Sacco et al 221 −0.40 −0.95 0.15 0.51
Samuel-Hodge et al 223 −0.10 −0.19 −0.01 0.76
Sarayani et al 224 −0.30 −0.80 0.20 0.54
Schillinger et al 227 −0.30 −0.66 0.06 0.63
Shahid et al 228 −0.73 −0.94 −0.52 0.72
Sigurdardottir et al 232 0.25 −0.26 0.76 0.53
Sone et al 234 −0.17 −0.26 −0.08 0.76
Sone et al 235 0.10 0.01 0.20 0.76
Song and Kim 236 −1.50 −2.13 −0.87 0.46
Tamban et al 242 −0.35 −0.71 0.01 0.63
Tan et al 243 −0.38 −0.77 0.01 0.61
Tang et al 244 −0.23 −0.48 0.02 0.69
Thom et al 246 −0.57 −0.90 −0.24 0.65
Torbjørnsen et al 247 0.00 −0.41 0.41 0.60
Tu et al 248 0.43 −0.65 1.51 0.26
Van Dyck et al 249 −0.30 −0.79 0.19 0.55
Varney et al 252 −0.20 −0.65 0.25 0.57
Wakefield et al 259 −0.10 −0.26 0.06 0.74
Waki et al 260 −0.40 −0.91 0.11 0.53
Walker et al 261 0.10 0.04 0.16 0.77
Wang et al 264 −0.60 −0.87 −0.33 0.68
Warren et al 265 −0.57 −0.89 −0.24 0.65
Weinberger et al 266 −0.60 −0.74 −0.46 0.74
Whittemore et al 267 0.00 −0.56 0.56 0.50
Wichit et al 268 −0.30 −0.68 0.08 0.62
Wild et al 269 −0.50 −0.75 −0.25 0.69
Williams et al 270 −0.80 −1.22 −0.38 0.59
Wolever et al 272 −0.50 −1.22 0.22 0.41
Yoo et al 277 −0.50 −0.84 −0.17 0.65
Yoon and Kim 278 −1.63 −2.11 −1.15 0.55
Zhou et al 282 −0.76 −1.20 −0.32 0.58
Agarwal et al 43 0.80 0.13 1.47 0.44
Alghafri et al 50 0.30 −0.01 0.61 0.66
Al Omar et al 47 −0.70 −1.05 −0.35 0.63
Andreae et al 59 −0.10 −0.46 0.26 0.63
Asante et al 62 −1.30 −2.02 −0.58 0.41
Bluml et al 67 0.00 −0.25 0.25 0.69
Boels et al 12 −0.20 −0.52 0.12 0.66
Bohingamu Mudiyanselage et al 69 −0.21 −0.41 −0.01 0.72
Buysse et al 73 −0.10 −0.67 0.47 0.49
Chao et al 77 −0.90 −1.35 −0.45 0.57
Choudhry et al 84 0.10 0.02 0.19 0.76
Delahanty et al 92 0.00 −0.37 0.37 0.62
Doupis et al 7 0.10 −0.04 0.24 0.74
Duruturk and Özköslü 94 −1.99 −2.80 −1.18 0.36
Gupta et al 124 −0.52 −0.98 −0.06 0.56
Haider et al 125 −0.40 −0.75 −0.05 0.64
Huang et al 135 −0.40 −1.18 0.38 0.37
Jain et al 141 0.26 −0.08 0.60 0.64
Jiwani et al 145 −2.20 −3.26 −1.14 0.26
Kim and Utz 150 0.24 −0.18 0.66 0.59
Ku et al 166 −1.20 −1.91 −0.49 0.41
Kusnanto et al 167 −0.27 −1.02 0.48 0.39
Lauffenburger et al 169 −0.06 −0.21 0.09 0.74
Lee et al 172 −0.50 −0.94 −0.06 0.58
Parsons et al 206 −0.97 −1.20 −0.74 0.71
Peasah et al 208 0.00 −0.52 0.52 0.53
Presley et al 212 0.50 0.00 1.00 0.54
Shahsavari and Bakhshandeh Bavarsad 229 −1.38 −1.89 −0.87 0.53
Sun et al 239 −0.38 −0.75 −0.01 0.62
Sunil Kumar et al 240 −0.87 −1.11 −0.63 0.70
Vaughan et al 253 −0.67 −1.24 −0.10 0.49
Vinithia et al 255 −0.40 −0.71 −0.10 0.66
Von Storch et al 256 −0.37 −0.45 −0.29 0.76
Wang et al 263 −0.80 −1.32 −0.28 0.53
Yu et al 280 −0.40 −0.92 0.12 0.53
Overall −0.42 −0.48 −0.35 100.00

Abbreviations: CI, confidence interval; MD, mean difference.

A series of univariate meta-regressions are illustrated in Table 4 and were assessed with a 5% significance level. Compared with North American studies (the reference), Asian studies reported larger effects of telemedicine (difference in MD = −0.287, P = .000), as did studies with higher baseline HbA1c% levels (difference in MD = −0.086 per %, P = .008). Compared with primary care settings (reference), hospital settings were also associated with an increase in the effect of telemedicine (difference in MD = −0.290, P = .004). Furthermore, a monitoring component gave rise to greater effects of telemedicine (difference in MD = −0.195, P = .004). Treatment effects of telemedicine were lesser for studies with longer duration (difference in MD = 0.008 per month, P = .015) and for studies with higher proportions of men (difference in MD = 0.005 per %, P = .035) and higher age (difference in MD = 0.022 per year, P = .000). A coaching component led to a lower effect (difference in MD = 0.215, P = .007). There were no statistically significant associations between the effect of telemedicine on HbA1c% levels and publication date, baseline BMI, contact frequency, the included peripherals, or risk of bias.

Table 4.

Association Between Study Covariates and Effect of Telemedicine on HbA1c% (Meta-Regression).

Covariate N Difference in MD (SE) P value I2 (%)
Study characteristics
 Publication decade
  Before 2020 4 Reference 92.86
  2020s 50 −0.175 (0.287) .542
  2010s 165 −0.082 (0.281) .769
  2020 24 −0.418 (0.312) .180
 Continent
  North America 88 Reference 91.15
  Europe 44 −0.037 (0.095) .696
  South America 5 −0.104 (0.303) .731
  Africa 5 −0.366 (0.362) .312
  Asia 84 −0.287 (0.078) .000*
  Australia/New Zealand 16 −0.040 (0.140) .773
 Study duration (range = 1-96 months) 168 0.008 per month (0.003) .015* 92.60
 Proportion of men (range = 15%-100%) 159 0.005 per % (0.002) .035* 93.05
 Age (range = 37-73 years) 157 0.022 per year (0.006) .000* 92.64
 Baseline BMI (range = 22-40) 123 0.018 per score (0.010) .066 92.51
 Baseline HbA1c% (range = 5.70%-11.05%) 165 −0.093 per % (0.035) .007* 92.80
Telemedicine characteristics
 Setting
  Primary care 58 Reference 90.25
  Community 37 −0.019 (0.116) .868
  Hospital 71 −0.290 (0.100) .004*
  Specialized outpatient clinic 34 −0.148 (0.114) .194
  University 14 −0.180 (0.169) .287
  Cross-sectorial 4 0.203 (0.301) .500
 Contact frequency
  Daily 30 Reference 91.42
  Weekly 83 −0.150 (0.129) .246
  Every two weeks 26 0.045 (0.157) .776
  Monthly 40 0.101 (0.144) .481
  More seldom 12 −0.006 (0.199) .977
  Tailored 24 0.076 (0.148) .611
 Included peripherals
  Glucometer 45 −0.052 (0.081) .523 92.81
  Pedometer 16 0.102 (0.132) .440 92.96
  BP monitor 19 −0.008 (0.132) .953 93.09
  Scale 13 0.014 (0.137) .919 93.12
 Intervention components
  Monitoring 86 −0.195 (0.068) .004* 92.30
  Consultation 22 −0.015 (0.114) .895 92.25
  Counseling 53 −0.030 (0.083) .720 92.95
  Coaching 63 0.215 (0.080) .007* 92.44
  Education 81 −0.125 (0.072) .085 92.76
  Mentoring 8 0.265 (0.201) .188 93.03
  Reminding 38 −0.151 (0.092) .100 92.87
 Risk of bias
  Low 33 Reference 92.82
  Some concerns 76 −0.101 (0.100) .310
  High 88 −0.067 (0.100) .492

Abbreviations: HbA1c%, glycated hemoglobin; MD, mean difference; BMI, body mass index; BP, blood pressure.

*

Statistically significant at a 5% level.

Certainty of the Evidence

Table 5 summarizes the findings. Overall, the certainty of evidence of the calculated effect on HbA1c% was judged as low due to serious problems with the risk of bias and inconsistency.

Table 5.

Summary of Findings Table.

Certainty assessment No of patients Effect Certainty Importance
No of studies Study design Risk of bias Inconsistency Indirectness Imprecision Other considerations Telemedicine Usual practice Relative (95% CI) Absolute (95% CI)
HbA1c%
243 Randomized trials Serious a Serious b Not serious Not serious None 29 671 27 465 MD 0.415 lower (0.482 lower to 0.348 lower) ⨁⨁◯◯ LOW IMPORTANT

Abbreviations: CI, confidence interval; HbA1c%, glycated hemoglobin; MD, mean difference.

a

The size of the review implies that no single study contributes dominant weights in the meta-analysis. Indeed, study weights range from 0.26 to 0.77. The correlation between effect size, that is, the MD, and risk of bias across studies was low and insignificant (Spearman ρ = −0.06, P = .3961). However, only 17% of the studies were evaluated to have a low risk of bias. Consequently, the risk of bias was downgraded to one level and assessed as serious.

b

Effect size point estimates vary widely between studies, with significant effects favoring both alternatives. I2 was high, both with and without controlling for statistically significant study covariates simultaneously in the meta-regression (I2 = 87.8% and I2 = 93%).

Discussion

This review aimed to evaluate the effectiveness of telemedicine solutions among adult patients with T2D. Overall, the results favored telemedicine. Asian studies, studies with higher baseline HbA1c% levels, and studies in hospital settings reported larger effects of telemedicine. Moreover, inclusion of a monitoring component in the telemedicine solution gave rise to a higher effect of telemedicine, whereas inclusion of a coaching component led to a lower effect. The results reflect the findings from previous systematic reviews, which have found significant reductions in HbA1c favoring telemedicine.13,22,283,284 In line with our findings, Faruque et al and Wu et al found a larger effect among studies with a higher baseline HbA1c.13,283 In contrast to our findings, Faruque et al found a larger effect in studies that used web portals or text messaging. 13 In terms of telemonitoring, Hanlon et al found improved glycemic control in studies that included telemonitoring with feedback 17 and Jaana et al found significantly reduced HbA1 through telemonitoring. 22 Hence, the ideal telemedicine setup remains to be determined, although the inclusion of a telemonitoring component seems advisable.

The heterogeneity of the included studies was large (I2 = 93.05%), which is often seen in reviews of telemedicine.13,15,284-286 In the before-mentioned systematic review by Faruque et al, the heterogeneity (I2) ranged from 58% to 75% depending on the time point Hba1c was measured. 13 A systematic review and meta-analysis by Tchero found a heterogeneity (I2) of 99% in studies comparing telemedicine with usual care in T2D. 284 Hence, the large heterogeneity found in the present review is not unusually large when compared with similar reviews. The large heterogeneity found in the present review may be explained by differences in the inclusion criteria and context of studies that vary greatly in terms of patient subgroup, provider, technology, organization, communication frequency, outcome, and so on. Moreover, the inclusion of studies from the 1990s and 2000s may have added to the heterogeneity. Telemedicine interventions in diabetes have evolved significantly during the last decades due to technological advances and differences in the interventions are thus expected to have affected heterogeneity. However, the inclusion of studies from the 1990s and 2000s has maintained the broad and inclusive scope that was intended for the present review.

The certainty of the evidence was judged as poor. First, most of the evidence (45%) stems from studies with a high risk of bias and only 17% stems from studies with a low risk of bias. However, the size of the review implies that no single study contributed dominant weights in the meta-analysis, where study weights ranged from 0.26 to 0.77. The correlation between effect size, that is, the MD, and risk of bias across studies was low and nonsignificant (Spearman ρ = −0.06, P = .3961). Taken together, the certainty of evidence was downgraded one level due to risk of bias. Second, imprecision was assessed as not serious, as the effect size was statistically significant, and the MD and lower confidence limit (MD = −0.415, 95% CI = −0.482% to −0.348%) were both clinically relevant, and all were comparable with expected effects for other quality improvement strategies, 287 which is also why no upgrading due to large effects was conducted. The total number of patients (N = 57 136) included in the review was also much higher than the optimal information size threshold (the OIS criterion). Third, inconsistency was assessed as serious. Although confidence intervals overlap considerably, effect size point estimates vary widely between studies, with significant effects favoring both alternatives. I2 was high both with and without controlling for statistically significant study covariates simultaneously in the meta-regression (I2 = 87.8% and I2 = 93%). Fourth, indirectness was not serious in this review, as all included studies were head-to-head experimental trials assessing the same outcome, and the inclusion criteria for both the population and type of intervention were broad. Fifth, although publication bias cannot be rejected with high confidence, the risk of publication bias was evaluated as undetected. Less than 100 participants were included in 35% of the studies. The Egger test for small-study effects was statistically significant (P < .000) and the funnel plot in Figure 4 reveals studies reporting both significant and insignificant positive and negative effects. The funnel plot is somewhat asymmetrical, with more studies demonstrating significant effects favoring telemedicine than negative effects. Of the 243 included studies, 32 reported industry sponsorship and 44 studies did not report whether there were sponsorships or other relevant conflicts of interest. However, the relationship between disclosed industry sponsorship and/or undisclosed relationships with both study size (above/below 100 participants) and MD (above/below mean effect across studies) was statistically nonsignificant (Fisher exact test = 0.31 and 0.11, respectively). Finally, no dose-response gradient was detected, as the contact frequency was insignificant in the meta-regression (Table 4).

Figure 4.

Figure 4.

Funnel plot.

Abbreviation: CI, confidence interval.

The present systematic review has some limitations. First, more baseline data, such as diabetes years, blood pressure, cholesterol levels, and medication, could have been extracted. However, due to differences in reporting style, such an extraction would have resulted in a high proportion of missing data in the analysis. Second, we could have contacted the authors of the individual studies to minimize the amount of missing HbA1c data. However, due to the large sample of included papers, such a search for data was deemed too time-consuming. Third, relevant studies may have been overlooked. Although a very broad search was conducted, the search was still limited to English and Scandinavian.

Conclusion

Telemedicine may serve as an effective supplement to usual care for patients with T2D. The inclusion of a telemonitoring component seems to increase the effect of telemedicine. It seems that those with a higher HbA1c are more likely to benefit from telemedicine. Patients with poor glycemic control may benefit more from telemedicine interventions, as a high HbA1c level leaves further room for improvement. However, the ideal glycemic target group for telemedicine in T2D remains to be determined.

Supplemental Material

sj-docx-1-dst-10.1177_19322968211064633 – Supplemental material for The Effectiveness of Telemedicine Solutions for the Management of Type 2 Diabetes: A Systematic Review, Meta-Analysis, and Meta-Regression

Supplemental material, sj-docx-1-dst-10.1177_19322968211064633 for The Effectiveness of Telemedicine Solutions for the Management of Type 2 Diabetes: A Systematic Review, Meta-Analysis, and Meta-Regression by Stine Hangaard, Sisse H. Laursen, Jonas D. Andersen, Thomas Kronborg, Peter Vestergaard, Ole Hejlesen and Flemming W. Udsen in Journal of Diabetes Science and Technology

Acknowledgments

The authors would like to thank the research librarian Connie Skrubbeltrang, who assisted in the literature search.

Footnotes

Abbreviations: GRADE, The Grading of Recommendations, Assessment, Development and Evaluation; HbA1c, glycated hemoglobin A1c; MD, mean difference; PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses; RCT, randomized controlled trial; T1D, type 1 diabetes; T2D, type 2 diabetes.

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This is an independent manuscript commissioned and jointly funded by the Steno Diabetes Center North Denmark and Aalborg University.

Supplemental Material: Supplemental material for this article is available online.

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Supplementary Materials

sj-docx-1-dst-10.1177_19322968211064633 – Supplemental material for The Effectiveness of Telemedicine Solutions for the Management of Type 2 Diabetes: A Systematic Review, Meta-Analysis, and Meta-Regression

Supplemental material, sj-docx-1-dst-10.1177_19322968211064633 for The Effectiveness of Telemedicine Solutions for the Management of Type 2 Diabetes: A Systematic Review, Meta-Analysis, and Meta-Regression by Stine Hangaard, Sisse H. Laursen, Jonas D. Andersen, Thomas Kronborg, Peter Vestergaard, Ole Hejlesen and Flemming W. Udsen in Journal of Diabetes Science and Technology


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