Evidence map›Paper›PMID 38024131›Full record

ArticleJournal of multidisciplinary healthcare2023

Developing a Quality Evaluation Index System for E-Consultation Doctor-Patient Communication Using the Delphi Method.

Jing Liao, Mengyao Jiang, Jiaxiu Liu, Xiaoyu Zhou, Zuyue Zhang, Qingmao Rao, Li Bai, Xiaorong Hou

Abstract read
In one paragraph

Article in Journal of multidisciplinary healthcare, 2023. 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

8 authors.

Jing LiaoCollege of Medical Informatics, Chongqing Medical University, Chongqing, 400016, People's Republic of China.ORCID 0000-0002-0397-5589
Mengyao JiangCollege of Medical Informatics, Chongqing Medical University, Chongqing, 400016, People's Republic of China.
Jiaxiu LiuCollege of Medical Informatics, Chongqing Medical University, Chongqing, 400016, People's Republic of China.
Xiaoyu ZhouCollege of Medical Informatics, Chongqing Medical University, Chongqing, 400016, People's Republic of China.
Zuyue ZhangChengdu Blood Center, Chengdu, 610041, People's Republic of China.
Qingmao RaoEducational Affairs Office, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, 610065, People's Republic of China.
Li BaiHospital of Zigong Mental Health Central, Zigong, Sichuan, People's Republic of China.
Xiaorong HouCollege of Medical Informatics, Chongqing Medical University, Chongqing, 400016, People's Republic of China.ORCID 0000-0003-0381-9110

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: E-consultation medical services have become popular globally, which offers patients more options, regardless of time or location. However, research indicates a prevalent issue with the communication quality in e-consultations, leading to sub-optimal patient experiences. Objective: This study aims to design an evaluation system for e-consultation quality. The developed scale guides operators in improving services and users in assessing their experience. It aids in selecting e-consultation services, saving costs, and assisting doctors in making informed decisions. Methods: This study combines existing scales, literature analysis, and expert consultation to form preliminary evaluation indicators. Fourteen experts were invited using stratified purposive sampling. Two rounds of Delphi method were conducted to exclude indicators that did not meet basic conditions. The final evaluation system was determined through expert discussions and revisions. The Analytic Hierarchy Process (AHP) quantified indicator weights. Results: Both rounds of the questionnaire saw compelling response rates of 100% (14 out of 14) and 92.86% (13 out of 14), respectively. Meanwhile, the Expert Authority Coefficient (Cr) was recorded at 0.89 and 0.88, respectively, while the Kendall Consistency Coefficient (Kendall W) for all level indicators fluctuated between 0.133 and 0.37 (P<0.05). The ultimate indicator system formulated includes three primary indicators, ten secondary indicators, and thirty-two tertiary indicators. The highest to lowest weighted first-level indicators were 'Joint Decision-Making between Doctors and Patients' (0.6232), 'Patient Responsiveness' (0.2395), and "Interpersonal Relationship between Doctors and Patients" (0.1373). Weights for the second-level and third-level indicators were also determined. Conclusion: A scientific scale for e-consultation quality evaluation has been created, which effectively captures the essence of online medical communication and patient experiences. It enriches the theoretical framework for evaluating e-consultation quality, broadens perspectives in Internet medicine, provides practical guidance for network medical service managers and users and the development of the "Internet + medical health" service model.

Indexed as

doctor-patient relationshipe-consultationmedical staffquality assessment scaleuser perception

Identifiers

PMID38024131
PMCPMC10658931

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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.