Evidence map›Paper›PMID 36670481›Full record

ArticleBMC medical informatics and decision making2023

Data management system for diabetes clinical trials: a pre-post evaluation study.

Aynaz Nourani, Haleh Ayatollahi, Masoud Solaymani-Dodaran

Abstract readEvaluation Study
In one paragraph

Article in BMC medical informatics and decision making, 2023. 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

3 authors.

Aynaz NouraniDepartment of Health Information Technology, Urmia University of Medical Sciences, Urmia, Iran.
Haleh AyatollahiHealth Management and Economics Research Center, Health Management Research Institute, Iran University of Medical Sciences, Tehran, Iran. ayatollahi.h@iums.ac.ir.
Masoud Solaymani-DodaranDepartment of Epidemiology, Iran University of Medical Sciences, Tehran, Iran.

Funding

Iran University of Medical Sciences IUMS/SHMIS_95/9321481003
6 · The paper itself

Abstract

backgroundData management system for diabetes clinical trials is used to support clinical data management processes. The purpose of this study was to evaluate the quality and usability of this system from the users' perspectives.

methodsThis study was conducted in 2020, and the pre-post evaluation method was used to examine the quality and usability of the designed system. Initially, a questionnaire was designed and distributed among the researchers who were involved in the diabetes clinical trials (n = 30) to investigate their expectations. Then, the researchers were asked to use the system and explain their perspectives about it by completing two questionnaires.

resultsThere was no statistically significant differences between the users' perspectives about the information quality, service quality, achievements, and communication before and after using the system. However, in terms of the system quality (P = 0.042) and users' autonomy (P = 0.026), the users' expectations were greater than the system performance. The system usability was at a good level based on the users' opinions.

conclusionIt seems that the designed system largely met the users' expectations in most areas. However, the system quality and users' autonomy need further attentions. In addition, the system should be used in multicenter trials and re-evaluated by a larger group of users.

Indexed as

Data ManagementDiabetes MellitusClinical Trials as TopicDatabase Management SystemsHumansSurveys and QuestionnairesClinical trialData management systemDiabetesPre- post evaluationUsability

Identifiers

PMID36670481
PMCPMC9854045

What OpenQuestion holds

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LicenceCC BY
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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.