Evidence map›Paper›PMID 38885498›Full record

ArticleJMIR formative research2024

The Relationship Between Static Characteristics of Physicians and Patient Consultation Volume in Internet Hospitals: Quantitative Analysis.

Ye Wang, Changjing Shi, Xinyun Wang, Hua Meng, Junqiang Chen

Abstract read
In one paragraph

Article in JMIR formative research, 2024. 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

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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.

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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

5 authors.

Ye WangInternet Hospital Operation Department, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.ORCID https://orcid.org/0009-0007-3653-9111
Changjing ShiInternet Hospital Operation Department, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.ORCID https://orcid.org/0009-0007-0202-6561
Xinyun WangInternet Hospital Operation Department, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.ORCID https://orcid.org/0009-0009-0466-3905
Hua MengInformation Center, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.ORCID https://orcid.org/0009-0009-9018-8679
Junqiang ChenDepartment of Gastrointestinal Gland Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.ORCID https://orcid.org/0000-0002-2615-3537

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInternet medical treatment, also known as telemedicine, represents a paradigm shift in health care delivery. This contactless model allows patients to seek medical advice remotely, often before they physically visit a doctor's clinic. Herein, physicians are in a relatively passive position, as patients browse and choose their health care providers. Although a wealth of experience is undoubtedly a draw for many patients, it remains unclear which specific facets of a doctor's credentials and accomplishments patients prioritize during their selection process.

objectiveOur primary aim is to delve deeper into the correlation between physicians' static characteristics-such as their qualifications, experiences, and profiles on the internet-and the number of patient visits they receive. We seek to achieve this by analyzing comprehensive internet hospital data from public hospitals. Furthermore, we aim to offer insights into how doctors can present themselves more effectively on web-based platforms, thereby attracting more patients and improving overall patient satisfaction.

methodsWe retrospectively gathered web-based diagnosis and treatment data from the First Affiliated Hospital of Guangxi Medical University in 2023. These data underwent rigorous analysis, encompassing basic descriptive statistics, correlation analyses between key factors in doctors' internet-based introductions, and the number of patient consultation visits. Additionally, we conducted subgroup analyses to ascertain the independence of these vital factors. To further distill the essence from these data, we used nonnegative matrix factorization to identify crucial demographic characteristics that significantly impact patient choice.

resultsThe statistical results suggested that there were significant differences in the distribution of consultation volume (P<.001), and the correlation analysis results suggested that there was a strong correlation between the two groups of data (ρ=0.93; P<.001). There was a correlation between the richness of a profile and popularity (P<.001). Patients were more interested in physicians with advanced titles, doctoral degrees, social activities, and scientific achievements (P<.001) as well as other institutional visit experiences (P=.003). More prosperous social activities, scientific achievements, experiences of other institutional visits, and awards were more common among people with advanced professional titles. Doctoral degrees remained attractive to patients when data were limited to senior physicians (P<.001). Patients trusted the medical staff with advanced titles, social activities, scientific achievements, and doctoral degrees (P<.001).

conclusionsPatient preferences for choosing a health care provider differed significantly between free and paid consultations. Notably, patients tended to trust doctors with advanced professional titles more and were more likely to seek out those with doctoral qualifications over other professional ranks. Additionally, physicians who actively participated in social events and scientific endeavors often had an advantage in attracting new patients. Given these insights, doctors who invest in enhancing their personal and professional experiences within these domains are likely to see increased popularity and patient satisfaction.

Indexed as

internet hospitalsonline consultationpatientphysicianstatic characteristics of physiciansstatistical analysisteleconsultationtelemedicineweb-based consultation

Identifiers

PMID38885498
PMCPMC11217713

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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.