Evidence map›Paper›PMID 32010449›Full record

ArticleDigital health

Minimum data set development for a drug poisoning registry system.

Sadrieh Hajesmaeel-Gohari, Kambiz Bahaadinbeigy, Shahrad Tajoddini, Sharareh R Niakan Kalhori

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 pooled it
–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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
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  8. Review
  9. Supervised Machine Learning Approach to COVID-19 Detection Based on Clinical Data.Medical journal of the Islamic Republic of Iran · 2022
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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

4 authors.

Sadrieh Hajesmaeel-GohariDepartment of Health Information Management, Tehran University of Medical Sciences (TUMS), Tehran, Iran.ORCID https://orcid.org/0000-0001-5212-6148
Kambiz BahaadinbeigyMedical Informatics Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
Shahrad TajoddiniEmergency Medicine Department, Neuroscience Research Center, Institute of Neuropharmacology, Kerman University of Medical Sciences, Kerman, Iran.
Sharareh R Niakan KalhoriDepartment of Health Information Management, Tehran University of Medical Sciences (TUMS), Tehran, Iran.ORCID https://orcid.org/0000-0002-7577-1200

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveDrug poisoning is the most prevalent type of poisoning throughout the world that can occur intentional or unintentional. Standard way for data gathering with uniform definitions is a requirement for preventing, controlling and managing of drug poisoning management. The purpose of this study was to develop a minimum data set, as an initial step, for a drug poisoning registry system in Iran.

methodsThis was descriptive and cross-sectional study that was performed in 2019. As the first step a comprehensive literature review was performed to retrieve related resources in Persian and English languages. For the second step the medical records of drug poisoning patients at Afzalipour hospital affiliated to Kerman University of Medical Sciences were assessed. Related data from these two steps were gathered by a checklist. Finally, a questionnaire that was created based on the checklist data elements and had three columns of 'essential,' 'useful, but not essential', and 'not essential' was used to reach a consensus on the data elements. Then the content validity ratio and the mean of experts' judgments were calculated for each data element. The Cronbach's alpha value for the entire questionnaire was obtained 0.9.

resultsThe minimum data set of a drug poisoning registry system was categorised into the administrative part with three sections including 32 data elements, and clinical parts with six sections including 81 data elements.

conclusionThis study provides a minimum data set for development of a drug poisoning registry system. Collecting this minimum data set is critical for helping policy makers and healthcare providers to prevent, control and manage drug poisoning.

Indexed as

DatasetdrugIranpoisoningregistry system

Identifiers

PMID32010449
PMCPMC6967198

What OpenQuestion holds

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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.