Evidence map›Paper›PMID 36249477›Full record

ArticleDigital health

Design, implementation, and evaluation of an innovative intelligence information management system for premature infants.

Shahrbanoo Pahlevanynejad, Navid Danaei, Reza Safdari

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 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. Review
  2. Article
  3. Review
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.

Shahrbanoo PahlevanynejadDepartment of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.ORCID https://orcid.org/0000-0003-0450-3556
Navid DanaeiDepartment of Pediatric, Semnan University of Medical Sciences, Semnan, Iran.
Reza SafdariDepartment of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Low birth weight is the most important condition of neonatal community health and the main cause of neonates' mortality. Identifying the indexes associated with this condition, and factors to prevent, and managing related data can help reduce the birth of premature infants to reduce the mortality rate due to this condition. The goal of present study was to design, implement and evaluate an innovative intelligence information management system for premature infants. Material and method: The present study was a multidisciplinary research that was done in 2019 to 2021 in four integrated phases in Iran. The first phase aimed to compare the current status of registration systems of premature infants through a systematic review and semi-structured interviews by using the Delphi model Then the minimum data set was determined and was designed a proposed model based on it. In the second phase, the structure and how the user interacts with the system were determined, and, using Microsoft Visio software, Unified Modeling Language diagrams were drawn to define the logical relationship of data. In the third phase, the system was developed, and finally in the last phase, in three methods, users' views on the usability of the system were evaluated. Results: The findings of this study included 233 essential data elements that were placed in two main groups of essential data, and the system was approved by end users for 87.73% consent and 67.19% satisfaction for SUMI (Software Usability Measurement Inventory) and 7.97 of 9 in QUIS questionnaire. Conclusion: This research's results can be beneficial and functional such as a complete sample for design and development of other systems concerned to health systems.

Indexed as

health information managementneonatal registrypremature birth systemPremature infantprematuritysystem evaluation

Identifiers

PMID36249477
PMCPMC9554115

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.