Effectiveness of telemonitoring intervention on glycaemic control in patients with type 2 diabetes mellitus: a systematic review and meta-analysis
Open accessAbstract
Background Type 2 diabetes mellitus (T2DM) is a rising global health concern that requires long-term treatment and close monitoring. Telemonitoring has been shown to be a promising tool to facilitate patient-physician interaction and improve glycaemic control.Method Randomised controlled trials (RCT) of telemonitoring in T2DM published between 1990 and 2021 were searched through multiple electronic databases. The primary outcome variables included HbA1c and fasting blood glucose (FBG), and BMI was a secondary outcome variable.Results Thirty RCT with a total of 4,678 participants were included in this study. Twenty-six studies reported on HbA1c, which was shown to be significantly lower in participants on telemonitoring when compared to conventional care. Ten studies investigated FBG which collectively showed no statistically significant difference. Subgroup analysis demonstrated the effect of telemonitoring on glycaemic control is influenced by a range of factors concerning system practicality, user engagement, patient characteristics and disease education.Conclusion Telemonitoring exhibited a great potential to improve T2DM management. Several technical features and patient factors may influence the effectiveness of telemonitoring. Further studies are needed to verify the findings and address limitations before its implementation into routine practice.
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Glucometers and CGMs demonstrated a symmetrical distribution between workflow and literacy challenges, illustrating the dual burden of learning invasive or semi-invasive peripheral operation alongside data-logging routines.
“Glucometers and CGMs demonstrated a symmetrical distribution between workflow and literacy challenges [2,4], illustrating the dual burden of learning invasive or semi-invasive peripheral operation alongside data-logging routines.”
From Clinical Efficacy and Patient Adherence Hurdles of Remote Patient Monitoring (RPM) Frameworks in Managing Hypertension and Type 2 Diabetes: A Scoping Review (2026) · cites this paper as [4]
Section 2.6 (page unavailable) describes manual data input and education in self-measurement skills, which relate to the claimed data-logging and learning tasks. Neither that section nor the Discussion (page unavailable) reports a symmetrical distribution of workflow and literacy challenges for glucometers and CGMs, or characterizes device operation and logging as a dual burden. (LLM, conf=0.76)
Experimental — accuracy not yet measuredThe clinical value proposition of RPM systems is well-documented; systematically tracking physiological metrics allows for early detection of clinical deterioration, optimization of pharmacological regimens, and reduction of emergency department utilization.
“The clinical value proposition of these systems is well-documented; systematically tracking physiological metrics allows for the early detection of clinical deterioration, optimization of pharmacological regimens, and reduction of emergency department utilization [2,4].”
From Clinical Efficacy and Patient Adherence Hurdles of Remote Patient Monitoring (RPM) Frameworks in Managing Hypertension and Type 2 Diabetes: A Scoping Review (2026) · cites this paper as [4]
Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
Experimental — accuracy not yet measuredThe lack of seamless architectural interoperability between hardware modalities and proprietary cloud infrastructure often forces reliance on fragmented data synchronization models, compounding operational inefficiencies.
“the lack of seamless architectural interoperability between hardware modalities and proprietary cloud infrastructure often forces reliance on fragmented data synchronization models, compounding operational inefficiencies [4,11].”
From Clinical Efficacy and Patient Adherence Hurdles of Remote Patient Monitoring (RPM) Frameworks in Managing Hypertension and Type 2 Diabetes: A Scoping Review (2026) · cites this paper as [4]
Section 2.6 (page unavailable) describes Wi-Fi, Bluetooth, and cellular transmission to a cloud server, while Section 4.2 notes variation in telemonitoring systems’ technical features. Neither passage addresses lack of interoperability, proprietary infrastructure, fragmented synchronization, or resulting operational inefficiencies; searches for those terms and related integration barriers found no supporting passage. (LLM, conf=0.75)
Experimental — accuracy not yet measured
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Cited by
Sorted by citations
- Authors
- Cai, J., Xu, H., Jiang, S., Sung, J., Sawhney, R., Broadley, S., & Sun, J.
- Affiliations
- Griffith University (AU)
- Corresponding author
- Cai, Jinxuan
- Xu, Huaying
- Jiang, Stephen
- Sung, Jerry
- Sawhney, Rakshat
- Broadley, Simon
- Sun, Jing
- Venue
- Diabetes Research and Clinical Practice
- Publisher
- Elsevier BV
- Published
- 2023-07
- Volume
- 201
- Pages
- 110727
- ISSN
- 0168-8227 (ISSN-L)
- OpenAlex
- W4377141862
- Cited by
- 8
- References
- 61
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 1 · 2023: 1
- FWCI
- 0.40
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Diabetes Research and Clinical Practice (publishedVersion)
- PubMed (publishedVersion)
- Griffith Research Online (submittedVersion, cc-by-nc-nd)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Keywords
- remote patient monitoring, type 2 diabetes, glycemic control, HbA1c, fasting blood glucose, body mass index, patient engagement, disease education
- MeSH terms
- Glycemic Control, Blood Glucose, Diabetes Mellitus, Type 2, Glycated Hemoglobin, Humans
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