ArticleHeliyon2023
Big data-driven public health policy making: Potential for the healthcare industry.
Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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
24 citing papers in PubMed, 55 citations in OpenAlex.
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- Modeling and forecasting neonatal mortality in Ethiopia: a comparative study using statistical, machine learning, and deep learning approaches.Archives of public health = Archives belges de sante publique · 2026Article
- Understanding the community management of long-term physical and mental health conditions in Bolivia, Colombia and Guatemala: a situational analysis.BMJ global health · 2026Article
- Defining Competencies for Policymaking in Public Health: A Scoping Review on the State-of- The-Art.Public health reviews · 2026Review
- Medical Artificial Intelligence: Opportunities and Challenges In Infectious Disease Management.Current medicinal chemistry · 2026Review
- The Complex Task of Translating Health Research into Health Policy in the Philippines.Acta medica Philippina · 2026Article
- Economic Burden and Clinical Epidemiology of Dialysis: A Cross-Sectional Analysis of Chronic Kidney Disease Patients.Cureus · 2025Article
- Pediatrics 4.0: the Transformative Impacts of the Latest Industrial Revolution on Pediatrics.Health care analysis : HCA : journal of health philosophy and policy · 2025Article
- Real-World Characteristics and Treatment Patterns of Patients With Transthyretin Amyloid Cardiomyopathy: Protocol for a Multicountry Disease Registry Study.JMIR research protocols · 2025Article
- Review
- Leveraging Administrative Health Databases to Address Health Challenges in Farming Populations: Scoping Review and Bibliometric Analysis (1975-2024).JMIR public health and surveillance · 2025Article
- Enhancing oral health outcomes through public health policy reform.Frontiers in oral health · 2025Article
- Post-pandemic era: global trends, benefits, and barriers in integrating artificial intelligence into public health education.Frontiers in public health · 2025Review
- Article
- Data Analytics to Support Policy Making for Noncommunicable Diseases: Scoping Review.Online journal of public health informatics · 2024Article
- Bridging Real-World Data Gaps: Connecting Dots Across 10 Asian Countries.JMIR medical informatics · 2024Article
- Citizens' digital footprints to support health promotion at the local level-PUHTI study, Finland.European journal of public health · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The use of healthcare data analytics is anticipated to play a significant role in future public health policy formulation. Therefore, this study examines how big data analytics (BDA) may be methodically incorporated into various phases of the health policy cycle for fact-based and precise health policy decision-making. So, this study explores the potential of BDA for accurate and rapid policy-making processes in the healthcare industry. A systematic review of literature spanning 22 years (from January 2001 to January 2023) has been conducted using the PRISMA approach to develop a conceptual framework. The study introduces the emerging topic of BDA in healthcare policy, goes over the advantages, presents a framework, advances instances from the literature, reveals difficulties and provides recommendations. This study argues that BDA has the ability to transform the conventional policy-making process into data-driven process, which helps to make accurate health policy decision. In addition, this study contends that BDA is applicable to the different stages of health policy cycle, namely policy identification, agenda setting as well as policy formulation, implementation and evaluation. Currently, descriptive, predictive and prescriptive analytics are used for public health policy decisions on data obtained from several common health-related big data sources like electronic health reports, public health records, patient and clinical data, and government and social networking sites. To effectively utilize all of the data, it is necessary to overcome the computational, algorithmic and technological obstacles that define today's extremely heterogeneous data landscape, as well as a variety of legal, normative, governance and policy limitations. Big data can only fulfill its full potential if data are made available and shared. This enables public health institutions and policymakers to evaluate the impact and risk of policy changes at the population level.
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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.