ArticleBMC family practice2019
Are big data analytics helpful in caring for multimorbid patients in general practice? - A scoping review.
Article in BMC family practice, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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.
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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.
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Who cites it
7 citing papers in PubMed.
- Identifying Predictors of Nursing Home Admission by Using Electronic Health Records and Administrative Data: Scoping Review.JMIR aging · 2023Article
- Data Analytics in Healthcare: A Tertiary Study.SN computer science · 2023Review
- Age and Ageing journal 50th anniversary commentary seriesWhy illness is more important than disease in old age.Age and ageing · 2022Article
- Autonomous Tool for Monitoring Multi-Morbidity Health Conditions in UAE and India.Frontiers in artificial intelligence · 2022Review
- Health information technology to improve care for people with multiple chronic conditions.Health services research · 2021Review
- E-Health Practices and Technologies: A Systematic Review from 2014 to 2019.Healthcare (Basel, Switzerland) · 2021Review
- Big data analysis techniques to address polypharmacy in patients - a scoping review.BMC family practice · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe treatment of multimorbid patients is one crucial task in general practice as multimorbidity is highly prevalent in this setting. However, there is little evidence how to treat these patients and consequently there are but a few guidelines that focus primarily on multimorbidity. Big data analytics are defined as a method that obtains results for high volume data with high variety generated at high velocity. Yet, the explanatory power of these results is not completely understood. Nevertheless, addressing multimorbidity as a complex condition might be a promising field for big data analytics. The aim of this scoping review was to evaluate whether applying big data analytics on patient data does already contribute to the treatment of multimorbid patients in general practice.
methodsIn January 2018, a review searching the databases PubMed, The Cochrane Library, and Web of Science, using defined search terms for "big data analytics" and "multimorbidity", supplemented by a search of grey literature with Google Scholar, was conducted. Studies were not filtered by type of study, publication year or language. Validity of studies was evaluated independently by two researchers.
resultsIn total, 2392 records were identified for screening. After title and abstract screening, six articles were included in the full-text analysis. Of those articles, one reported on a model generated with big data techniques to help caring for one group of multimorbid patients. The other five articles dealt with the analysis of multimorbidity clusters. No article defined big data analytics explicitly.
conclusionsAlthough the usage of the phrase "Big Data" is growing rapidly, there is nearly no practical use case for big data analysis techniques in the treatment of multimorbidity in general practice yet. Furthermore, in publications addressing big data analytics, the term is rarely defined. However, possible models and algorithms to address multimorbidity in the future are already published.
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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.