Evidence map›Paper›PMID 36311153›Full record

ArticleActa informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH2022

Towards a Model of Big Health Care Data Analytics in Panama: Chronic Kidney Disease.

Denis Cedeno-Moreno, Gaspar DA Costa-Foster, Miguel Vargas-Lombardo

Abstract read
In one paragraph

Article in Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH, 2022. 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.

Denis Cedeno-MorenoCentro Regional de Panamá Oeste, Universidad Tecnológica de Panamá , La Chorrera, Panamá.
Gaspar DA Costa-FosterMinisterio de Salud, MINSA Penonomé, Coclé , Panamá.
Miguel Vargas-LombardoGises-CIDITiC, Universidad Tecnológica de Panamá, Panamá, Panamá.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: A growing number of mobile applications have been designed for the chronic disease patient as the primary user. Mobile health applications for self-care have the potential to help patients living with chronic conditions such as kidney disease, and can be used to manage aspects such as the consumption of substances that are harmful to health. Chronic kidney disease causes significant morbidity throughout Panama, and is also responsible for an increase in cardiovascular disease. Objective: In this paper, we present a review of the applications offered by the Android store, based on a search and selection of the most efficient options that fulfill a set of criteria and functionalities. Methods: We evaluate a big health data model in terms of its usefulness for studies, research and projections of Panamanian patients with this chronic disease. Results and Discusion: We present a mobile application based on the most important standards and functionalities for the Panamanian population affected by this disease. Our analysis also highlights the importance of mobile applications for the self-care of chronic diseases and their usefulness to both patients and health care providers, since they can support better health habits and give good results in terms of following a diet, promoting a healthy lifestyle, and encouraging physical activity. The analysis presented here will form the basis for the development of an application that will be simple, user-friendly and powerful, in the sense that it will empower patients with the resources they need for self-care. . Conclusion: Mobile applications are found to show promise for the self-care of chronic conditions, and can improve the quality of life of Panamanian patients. In addition, we intend to develop a data repository for scientific research within Central America.

Indexed as

big health dataChronic kidney diseasehealthmobile applicationsself-care of health

Identifiers

PMID36311153
PMCPMC9559994

What Socratic holds

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LicenceCC BY-NC
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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 Socratic graph.