ReviewYearbook of medical informatics2014
Challenges and potential solutions for big data implementations in developing countries.
Review in Yearbook of medical informatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Making the most of big qualitative datasets: a living systematic review of analysis methods.Frontiers in big data · 2024Pooled it
- Self-monitoring and psychoeducation in bipolar patients with a smart-phone application (SIMPLe) project: design, development and studies protocols.BMC psychiatry · 2015Trial
- Challenges and opportunities of big data analytics in healthcare.Health care science · 2023Review
- Proceedings from the CIHLMU 2022 Symposium: "Availability of and Access to Quality Data in Health".BMC proceedings · 2023Article
- A global perspective on data powering responsible AI solutions in health applications.AI and ethics · 2023Article
- A novel approach to model traffic on road segments of large-scale urban road networks.MethodsX · 2019Article
- Health-Enabling and Ambient Assistive Technologies: Past, Present, Future.Yearbook of medical informatics · 2016Article
- Towards exergaming commons: composing the exergame ontology for publishing open game data.Journal of biomedical semantics · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe volume of data, the velocity with which they are generated, and their variety and lack of structure hinder their use. This creates the need to change the way information is captured, stored, processed, and analyzed, leading to the paradigm shift called Big Data.
objectivesTo describe the challenges and possible solutions for developing countries when implementing Big Data projects in the health sector.
methodsA non-systematic review of the literature was performed in PubMed and Google Scholar. The following keywords were used: "big data", "developing countries", "data mining", "health information systems", and "computing methodologies". A thematic review of selected articles was performed.
resultsThere are challenges when implementing any Big Data program including exponential growth of data, special infrastructure needs, need for a trained workforce, need to agree on interoperability standards, privacy and security issues, and the need to include people, processes, and policies to ensure their adoption. Developing countries have particular characteristics that hinder further development of these projects.
conclusionsThe advent of Big Data promises great opportunities for the healthcare field. In this article, we attempt to describe the challenges developing countries would face and enumerate the options to be used to achieve successful implementations of Big Data programs.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.