Evidence map›Paper›PMID 41639825›Full record

ArticleBMC psychiatry2026

A structured approach to designing the minimum data set for telepsychiatry systems.

Shahabedin Rahmatizadeh, Zeinab Kohzadi, Jamal Shams, Zahra Kohzadi, Akbar Bolvardi, Amir Maziar Niaei, Reza Shahghadami

Abstract read
In one paragraph

Article in BMC psychiatry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Shahabedin RahmatizadehDepartment of Health Information Technology and Management, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.ORCID 0000-0003-2429-1642
Zeinab KohzadiArtificial Intelligence in Health Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran. z.kohzadi96@gmail.com.ORCID 0000-0001-8038-5454
Jamal ShamsBehavioral Sciences Research Center & Psychiatric Department, Imam Hossein Hospital, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Zahra KohzadiIlam County Health Center, Ilam University of Medical Sciences, Ilam, Iran.
Akbar BolvardiEducational Development Center, EDC, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Amir Maziar NiaeiEducational Development Center, EDC, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Reza ShahghadamiDepartment of Medical Engineering and Physics, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Funding

Behavioral Sciences Research Center, Shahid Beheshti University of Medical Sciences 43009740
6 · The paper itself

Abstract

introductionThe increasing demand for mental health services, coupled with challenges such as a shortage of specialists, the geographical dispersion of treatment centers, and the need for continuous care, has led to telepsychiatry systems being considered an innovative and effective solution. However, the development of such systems necessitates precise and standardized information infrastructures. This study aimed to design a Minimum Data Set (MDS) for a telepsychiatry system, adopting a native approach based on specialists’ consensus.

methodsThis study was conducted using a mixed-methods approach in two phases. In the first phase, an initial list of required data elements related to telepsychiatry services was identified through a review of scientific literature and databases, and subsequently categorized into primary domains. In the second phase, the final set of data elements was agreed upon through two rounds of the Delphi technique, with the participation of specialists.

findingsThe final data set comprised 103 data elements across 6 main domains: Demographic Information (20 items), Medical and Medication History (19 items), Paraclinical Tests (18 items), Psychosocial Functioning (7 items), Clinical Symptoms, Assessment, and Diagnosis (28 items), and Treatment Plan and Follow-up (11items). This dataset represents various dimensions of the information required for the structured and analyzable delivery of telepsychiatry services.

conclusionThe compiled dataset provides a standardized framework for recording, exchanging, and analyzing psychiatric data within digital health systems. This framework can serve as the foundation for designing national telepsychiatry systems, contributing to the improvement of quality, coordination, and integration of mental health services. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

Datasets as TopicMental Health ServicesPsychiatryTelemedicineDelphi TechniqueHumansMental Health TeletherapyDelphi techniqueMental healthMinimum data setTelepsychiatry

Identifiers

PMID41639825
PMCPMC12958497

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LicenceCC BY-NC-ND
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Registered trials

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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.