Evidence map›Paper›PMID 39889298›Full record

ArticleJournal of medical Internet research2025

Metrics for Evaluating Telemedicine in Randomized Controlled Trials: Scoping Review.

Yuka Sugawara, Yosuke Hirakawa, Masao Iwagami, Ryota Inokuchi, Rie Wakimizu, Masaomi Nangaku

Abstract readScoping Review
In one paragraph

Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Yuka SugawaraDivision of Nephrology and Endocrinology, The University of Tokyo, Tokyo, Japan.ORCID https://orcid.org/0000-0002-3022-1096
Yosuke HirakawaDivision of Nephrology and Endocrinology, The University of Tokyo, Tokyo, Japan.ORCID https://orcid.org/0000-0001-9238-650X
Masao IwagamiDepartment of Health Services Research, Institute of Medicine, University of Tsukuba, Ibaraki, Japan.ORCID https://orcid.org/0000-0001-7079-0640
Ryota InokuchiDepartment of Clinical Engineering, The University of Tokyo Hospital, Tokyo, Japan.ORCID https://orcid.org/0000-0001-6343-2298
Rie WakimizuDepartment of Child Health and Development Nursing, Institute of Medicine, University of Tsukuba, Ibaraki, Japan.ORCID https://orcid.org/0000-0003-2464-6028
Masaomi NangakuDivision of Nephrology and Endocrinology, The University of Tokyo, Tokyo, Japan.ORCID https://orcid.org/0000-0001-7401-2934

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTelemedicine involves medical, diagnostic, and treatment-related services using telecommunication technology. Not only does telemedicine contribute to improved patient quality of life and satisfaction by reducing travel time and allowing patients to be seen in their usual environment, but it also has the potential to improve disease management by making it easier for patients to see a doctor. Recently, owing to IT developments, research on telemedicine has been increasing; however, its usefulness and limitations in randomized controlled trials remain unclear because of the multifaceted effects of telemedicine. Furthermore, the specific metrics that can be used as cross-disciplinary indicators when comparing telemedicine and face-to-face care also remain undefined.

objectiveThis review aimed to provide an overview of the general and cross-disciplinarity metrics used to compare telemedicine with in-person care in randomized controlled trials. In addition, we identified previously unevaluated indicators and suggested those that should be prioritized in future clinical trials.

methodsMEDLINE and Embase databases were searched for publications that met the inclusion criteria according to PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analysis Extension for Scoping Reviews). Original, English-language articles on randomized controlled trials comparing some forms of telemedicine with face-to-face care from January 2019 to March 2024 were included, and the basic information and general metrics used in these studies were summarized.

resultsOf the 2275 articles initially identified, 79 were included in the final analysis. The commonly used metrics that can be used across medical specialties were divided into the following 3 categories: (1) patient-centeredness (67/79, 85%), including patient satisfaction, workload, and quality of life; (2) patient outcomes (57/79, 72%), including general clinical parameters such as death, admission, and adverse events; and (3) cost-effectiveness (40/79, 51%), including cost assessment and quality-adjusted life year. Notably, only 25 (32%) of 79 studies evaluated all the 3 categories. Other metrics, such as staff convenience, system usability, and environmental impact, were extracted as indicators in different directions from the three categories above, although few previous reports have evaluated them (staff convenience: 8/79, 10%; system usability: 3/79, 4%; and environmental impact: 2/79, 3%).

conclusionsA significant variation was observed in the metrics used across previous studies. Notably, general indicators should be used to enhance the understandability of the results for people in other areas, even if disease-specific indicators are used. In addition, indicators should be established to include all three commonly used categories of measures to ensure a comprehensive evaluation: patient-centeredness, patient outcomes, and cost-effectiveness. Staff convenience, system usability, and environmental impact are important indicators that should be used in future trials. Moreover, standardization of the evaluation metrics is desired for future clinical trials and studies.

trial registrationOpen Science Forum Registries YH5S7; https://doi.org/10.17605/OSF.IO/YH5S7.

Indexed as

Randomized Controlled Trials as TopicTelemedicineHumansPatient SatisfactionQuality of Lifeclinical parametercost-effectivenessdatabaseeHealthevaluation metricshealth caremetricsmHealthmobile healthmobile phonepatient-centerednesspatient experiencepatient outcomepatient-reported outcomepatient satisfactionquality-adjusted life yearquality of lifereviewscoping reviewsystematic reviewtelecommunicationstelehealthtelemedicine

Identifiers

PMID39889298
PMCPMC11829184

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.