Evidence map›Paper›PMID 32766319›Full record

ArticleJournal of education and health promotion2020

Improving hypertension surveillance from a data management prospective: Data requirements for implementation of population-based registry.

Mostafa Shanbehzadeh, Hadi Kazemi-Arpanahi, Arezo Arzani-Birgani, Azimeh Karimyan, Fatemeh Mobasheri

Abstract read
In one paragraph

Article in Journal of education and health promotion, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 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

5 authors.

Mostafa ShanbehzadehDepartment of Health Information Technology, School of Paramedical, Ilam University of Medical Sciences, Ilam, Iran.
Hadi Kazemi-ArpanahiDepartment of Health Information Technology, Abadan Faculty of Medical Sciences, Abadan, Iran.
Arezo Arzani-BirganiDepartment of Health Information Technology, Abadan Faculty of Medical Sciences, Abadan, Iran.
Azimeh KarimyanDepartment of Public Health, Abadan Faculty of Medical Sciences, Abadan, Iran.
Fatemeh MobasheriDepartment of Health Information Technology, Abadan Faculty of Medical Sciences, Abadan, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHypertension (HTN) has become a major public health problem which can cause serious complications when it is not well-controlled. Prevention and effective care of HTN require a population-based registry. Thus, establishing this registry can be used to collect comprehensive, timely, and reliable data on epidemiology cases. The aim is to create a registry for the collection of highly required prospective data that will present an in-depth analysis of the characteristics of all individuals with HTN and track them over a particular chronological interval. MATERIALS AND

methodsThe study was divided into three phases: At first, a comprehensive literature review was conducted to determine the proposed data classes and data fields. Then, the final minimum data set was designed by a two-round Delphi consensus approach of 20 experts of cardiologists, nephrologists, nutritionist, and health information management. Finally, a web-based registry system was developed by a Structured Query Language environment.

resultsA total of two clinical and nonclinical data categories with nine data classes and 68 data fields were selected for their inclusion in the registry following the consensus phase. A web-based registry was designed with a modular and layered architecture.

conclusionsThis study provides an appropriate information infrastructure for active tracing and monitoring of individuals with HTN. It has provided a practical information system allowing quality improvement, aggregate reporting for planning, and research purposes.

Indexed as

Hypertensionminimum data setregistry system

Identifiers

PMID32766319
PMCPMC7377147

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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.