OBJECTIVE: This scientometric investigation aims to examine collaborative research networks, dominant research themes and disciplines, and seminal research studies that have contributed most to the field of telemedicine. This information is vital for scientists, institutions, and policy stakeholders to evaluate research areas where more infrastructural or scholarly contributions are required.
METHODS: For analyses, we used CiteSpace (version 4.0 R5; Drexel University), which is a Java-based software that allows scientometric analysis, especially visualization of collaborative networks and research themes in a specific field.
RESULTS: We found that scholarly activity has experienced a significant increase in the last decade. Most important works were conducted by institutions located in high-income countries. A discipline-specific shift from radiology to telestroke, teledermatology, telepsychiatry, and primary care was observed. The most important innovations that yielded a collaborative influence were reported in the following medical disciplines, in descending order: public environmental and occupational health, psychiatry, pediatrics, health policy and services, nursing, rehabilitation, radiology, pharmacology, surgery, respiratory medicine, neurosciences, obstetrics, and geriatrics.
CONCLUSIONS: Despite a continuous rise in scholarly activity in telemedicine, we noticed several gaps in the literature. For instance, all the primary and secondary research central to telemedicine was conducted in the context of high-income countries, including the evidence synthesis approaches that pertained to implementation aspects of telemedicine. Furthermore, the research landscape and implementation of telemedicine infrastructure are expected to see exponential progress during and after the COVID-19 era.
Methods: We searched seven databases up to July 2020 for randomized controlled trials investigating the effectiveness of telemedicine in the delivery of diabetes care in low- and middle-income countries. We extracted data on the study characteristics, primary end-points and effect sizes of outcomes. Using random effects analyses, we ran a series of meta-analyses for both biochemical outcomes and related patient properties.
Findings: We included 31 interventions in our meta-analysis. We observed significant standardized mean differences of -0.38 for glycated haemoglobin (95% confidence interval, CI: -0.52 to -0.23; I2 = 86.70%), -0.20 for fasting blood sugar (95% CI: -0.32 to -0.08; I2 = 64.28%), 0.81 for adherence to treatment (95% CI: 0.19 to 1.42; I2 = 93.75%), 0.55 for diabetes knowledge (95% CI: -0.10 to 1.20; I2 = 92.65%) and 1.68 for self-efficacy (95% CI: 1.06 to 2.30; I2 = 97.15%). We observed no significant treatment effects for other outcomes, with standardized mean differences of -0.04 for body mass index (95% CI: -0.13 to 0.05; I2 = 35.94%), -0.06 for total cholesterol (95% CI: -0.16 to 0.04; I2 = 59.93%) and -0.02 for triglycerides (95% CI: -0.12 to 0.09; I2 = 0%). Interventions via telephone and short message service yielded the highest treatment effects compared with services based on telemetry and smartphone applications.
Conclusion: Although we determined that telemedicine is effective in improving several diabetes-related outcomes, the certainty of evidence was very low due to substantial heterogeneity and risk of bias.