Evidence map›Paper›PMID 36011092›Full record

ArticleHealthcare (Basel, Switzerland)2022

Doctors' Preferences in the Selection of Patients in Online Medical Consultations: An Empirical Study with Doctor-Patient Consultation Data.

Yingjie Lu, Qian Wang

Open access · goldAbstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.3field-weighted citation impact, top 8% of its field
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

7 citing papers in PubMed, 17 citations in OpenAlex.

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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

2 authors at 1 institution in 1 country.

Yingjie LuSchool of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, China.ORCID 0000-0001-9607-3607
Qian WangSchool of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, China.
Beijing University of Chemical Technology · CN

Funding

the Fundamental Research Funds for the Central Universities PT2204the Funds for First-class Discipline Construction XK1802-5the National Social Science Fund of China 20BTQ080the Social Science Foundation of Beijing 19GLC064
6 · The paper itself

Abstract

Online medical consultation (OMC) allows doctors and patients to communicate with each other in an online synchronous or asynchronous setting. Unlike face-to-face consultations in which doctors are only passively chosen by patients with appointments, doctors engaging in voluntary online consultation have the option of choosing patients they hope to treat when faced with a large number of online questions from patients. It is necessary to characterize doctors' preferences for patient selection in OMC, which can contribute to their more active participation in OMC services. We proposed to exploit a bipartite graph to describe the doctor-patient interaction and use an exponential random graph model (ERGM) to analyze the doctors' preferences for patient selection. A total of 1404 doctor-patient consultation data retrieved from an online medical platform in China were used for empirical analysis. It was found that first, mildly ill patients will be prioritized by doctors, but the doctors with more professional experience may be more likely to prefer more severely ill patients. Second, doctors appear to be more willing to provide consultation services to patients from urban areas, but the doctors with more professional experience or from higher-quality hospitals give higher priority to patients from rural and medically underserved areas. Finally, doctors generally prefer asynchronous communication methods such as picture/text consultation, while the doctors with more professional experience may be more willing to communicate with patients via synchronous communication methods, such as voice consultation or video consultation.

Indexed as

doctor–patient interactiondoctors’ selection of patientsexponential random graph modelInternet healthcareonline medical consultation

Identifiers

PMID36011092
PMCPMC9408688
OpenAlexW4289133933

What OpenQuestion 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 OpenQuestion graph.