Evidence map›Paper›PMID 36465986›Full record

ArticleDigital health

Access, charge and quality of tele-dermatology e-consults in China: A standardized patients study.

Rui Guo, Mengchi Hou, Yangyang Han, Xing Lin Feng

Abstract read
In one paragraph

Article in Digital health. 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. Article
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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

4 authors.

Rui GuoSchool of Public Health, Capital Medical University, Beijing, China.
Mengchi HouChina Aerospace Science & Industry Corporation 731 Hospital, Beijing, China.
Yangyang HanBeijing Chinese Medical Hospital Affiliated to Capital Medical University, Beijing, China.
Xing Lin FengDepartment of Health Policy and Management, School of Public Health, Peking University, Beijing, China.ORCID https://orcid.org/0000-0003-3588-1859

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Direct-to-consumer telemedicine is rapidly changing the way that patients seek medical care. This study provided the first report on access, cost and quality of text- and image-based tele-dermatology e-consults, in China. Methods: We adopted the Standardized Patients approach to evaluate the services of tele-dermatology e-consults in two metropolitan cities, that is, Beijing and Hangzhou, in China. We measured quality from four dimensions: service process, diagnosis accuracy, prescription and treatment comprehensiveness, based on China's national clinical guidelines. We performed logistic regressions to investigate factors that were associated with high-quality care. Results: For 114 physicians eligible for inclusion, we succeeded in 87 (76%) validated visits. The median waiting time was 100 minutes (IQR 19-243 minutes) and the median length of consultation was 636 minutes (about 10 hours, IQR 188-1528 minutes). Per visit costs varied from $0 to $38, with a median of $8 (IQR 4-9). Among all, 15% of visits showed high quality in service process, 84% arrived in the correct diagnosis, 24% provided high-quality prescriptions and 71% provided comprehensive treatment. Providing images was associated with high quality in service process (OR 7.22, 95% CI 1.49-34.88). Visits in metropolitan Beijing and on non-work days had better prescription quality than that in metropolitan Hangzhou (OR 6.05, 95% CI 1.75-20.95) and that on workdays (OR 3.75, 95%CI 1.27-11.04), respectively. Conclusions: Tele-dermatology e-consults seem to be easy to access and less expensive in China. However, great efforts are warranted to ensure that service processes and prescriptions adhere to clinical guidelines.

Indexed as

Digital healthqualitystandardized patientstele-dermatology

Identifiers

PMID36465986
PMCPMC9716584

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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 OpenQuestion graph.