ArticleJournal of medical Internet research2021
Impact of Big Data Analytics on People's Health: Overview of Systematic Reviews and Recommendations for Future Studies.
Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 5 of them syntheses 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
27 citing papers in PubMed, 5 syntheses or guidelines pooled it, 81 citations in OpenAlex.
- A foundation systematic review of natural language processing applied to gastroenterology & hepatology.BMC gastroenterology · 2025Pooled it
- Synergistic review of automation impact of big data, AI, and ML in current data transformative era.F1000Research · 2025Pooled it
- Pooled it
- Systematic review of current natural language processing methods and applications in cardiology.Heart (British Cardiac Society) · 2022Pooled it
- Process Improvement Approaches for Increasing the Response of Emergency Departments against the COVID-19 Pandemic: A Systematic Review.International journal of environmental research and public health · 2021Pooled it
- Application of artificial intelligence in oral health management: challenges and opportunities.Frontiers in medicine · 2026Review
- An Overview of Reviews on Telemedicine and Telehealth in Dementia Care: Mixed Methods Synthesis.JMIR mental health · 2025Review
- Management of neuropsychiatric, motor and non-motor symptoms in Parkinson´s disease after long distance air travel: a consensus view.Journal of neural transmission (Vienna, Austria : 1996) · 2025Review
- Transformative Impact of the Internet on the Boundaries for the Physician Profession: Why Materiality Matters.Journal of medical Internet research · 2025Article
- Spatio-Temporal Modelling and Forecasting of the Prolonged Measles Outbreak in Romania: Insights and Challenges.Healthcare (Basel, Switzerland) · 2025Article
- "I Believe That AI Will Recognize the Problem Before It Happens": Qualitative Study Exploring Young Adults' Perceptions of AI in Mental Health Care.JMIR mental health · 2025Article
- Medical and Biomedical Students' Perspective on Digital Health and Its Integration in Medical Curricula: Recent and Future Views.International journal of environmental research and public health · 2025Article
- Clinical Implications of Antidepressants and Associated Risk of Bleeding: A Narrative Review.Current pain and headache reports · 2025Review
- Mapping patient encounters to identify recruitment timepoints after brain tumour surgery: a cohort and cross-sectional study.BMJ open quality · 2025Article
- Navigating Neurodegeneration: Integrating Biomarkers, Neuroinflammation, and Imaging in Parkinson's, Alzheimer's, and Motor Neuron Disorders.Biomedicines · 2025Article
- Using Healthcare Big Data Analytics to Improve Women's Health: Benefits, Challenges, and Perspectives.China CDC weekly · 2024Article
- A Scenario for a Model of Excellence in Comprehensive Cancer Care.Asian Pacific journal of cancer prevention : APJCP · 2024Article
- Article
- Unveiling the Comorbidities of Chronic Diseases in Serbia Using ML Algorithms and Kohonen Self-Organizing Maps for Personalized Healthcare Frameworks.Journal of personalized medicine · 2023Article
- Potential and limitations of machine meta-learning (ensemble) methods for predicting COVID-19 mortality in a large inhospital Brazilian dataset.Scientific reports · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 4 institutions in 6 countries.
Funding
Abstract
backgroundAlthough the potential of big data analytics for health care is well recognized, evidence is lacking on its effects on public health.
objectiveThe aim of this study was to assess the impact of the use of big data analytics on people's health based on the health indicators and core priorities in the World Health Organization (WHO) General Programme of Work 2019/2023 and the European Programme of Work (EPW), approved and adopted by its Member States, in addition to SARS-CoV-2-related studies. Furthermore, we sought to identify the most relevant challenges and opportunities of these tools with respect to people's health.
methodsSix databases (MEDLINE, Embase, Cochrane Database of Systematic Reviews via Cochrane Library, Web of Science, Scopus, and Epistemonikos) were searched from the inception date to September 21, 2020. Systematic reviews assessing the effects of big data analytics on health indicators were included. Two authors independently performed screening, selection, data extraction, and quality assessment using the AMSTAR-2 (A Measurement Tool to Assess Systematic Reviews 2) checklist.
resultsThe literature search initially yielded 185 records, 35 of which met the inclusion criteria, involving more than 5,000,000 patients. Most of the included studies used patient data collected from electronic health records, hospital information systems, private patient databases, and imaging datasets, and involved the use of big data analytics for noncommunicable diseases. "Probability of dying from any of cardiovascular, cancer, diabetes or chronic renal disease" and "suicide mortality rate" were the most commonly assessed health indicators and core priorities within the WHO General Programme of Work 2019/2023 and the EPW 2020/2025. Big data analytics have shown moderate to high accuracy for the diagnosis and prediction of complications of diabetes mellitus as well as for the diagnosis and classification of mental disorders; prediction of suicide attempts and behaviors; and the diagnosis, treatment, and prediction of important clinical outcomes of several chronic diseases. Confidence in the results was rated as "critically low" for 25 reviews, as "low" for 7 reviews, and as "moderate" for 3 reviews. The most frequently identified challenges were establishment of a well-designed and structured data source, and a secure, transparent, and standardized database for patient data.
conclusionsAlthough the overall quality of included studies was limited, big data analytics has shown moderate to high accuracy for the diagnosis of certain diseases, improvement in managing chronic diseases, and support for prompt and real-time analyses of large sets of varied input data to diagnose and predict disease outcomes.
trial registrationInternational Prospective Register of Systematic Reviews (PROSPERO) CRD42020214048; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=214048.
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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.