ReviewHealthcare (Basel, Switzerland)2018
A Systematic Review on Healthcare Analytics: Application and Theoretical Perspective of Data Mining.
Review in Healthcare (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 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
52 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Deep learning visual analysis in laparoscopic surgery: a systematic review and diagnostic test accuracy meta-analysis.Surgical endoscopy · 2021Pooled it
- Exploring data reduction strategies in the analysis of continuous pressure imaging technology.BMC medical research methodology · 2023Trial
- Leveraging data to transform surgical outcomes and precision in orthopaedics.Journal of clinical orthopaedics and trauma · 2025Review
- Towards robust electronic health record systems: integrating formal verification and process modeling techniques.BMC medical research methodology · 2025Article
- From Stories to Solutions: A Research Cycle Framework for Enhancing Trustworthiness in Studies of Online Patient Narratives.Journal of medical Internet research · 2025Article
- Estimating hip impact velocity and acceleration from video-captured falls using a pose estimation algorithm.Scientific reports · 2025Article
- Data Mining Models in Prediction of Vancomycin-IntermediateMicroorganisms · 2025Article
- Conceptually Funded Usability Evaluation of an Application for Leveraging Descriptive Data Analysis Models for Cardiovascular Research.Diagnostics (Basel, Switzerland) · 2024Article
- Getting More Out of Clinical Documentation: Can Clinical Dashboards Yield Clinically Useful Information?Administration and policy in mental health · 2024Article
- Bibliometric Analysis of Development Trends and Research Hotspots in the Study of Data Mining in Nursing Based on CiteSpace.Journal of multidisciplinary healthcare · 2024Review
- Survey of Transfer Learning Approaches in the Machine Learning of Digital Health Sensing Data.Journal of personalized medicine · 2023Review
- Accounting for clustering in automated variable selection using hospital data: a comparison of different LASSO approaches.BMC medical research methodology · 2023Article
- Skills and competencies in health data analytics for health professionals: a scoping review protocol.BMJ open · 2023Article
- Evaluation of a Machine Learning-Based Dysphagia Prediction Tool in Clinical Routine: A Prospective Observational Cohort Study.Dysphagia · 2023Observational
- A Predictive Model of Ischemic Heart Disease in Middle-Aged and Older Women Using Data Mining Technique.Journal of personalized medicine · 2023Article
- Combining text mining with clinical decision support in clinical practice: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Framework for Classifying Explainable Artificial Intelligence (XAI) Algorithms in Clinical Medicine.Online journal of public health informatics · 2023Article
- Comparing the Discussion of Telehealth in Two Social Media Platforms: Social Listening Analysis.Telemedicine reports · 2023Article
- Application of machine learning methods in predicting schizophrenia and bipolar disorders: A systematic review.Health science reports · 2023Article
- Data Analytics in Healthcare: A Tertiary Study.SN computer science · 2023Review
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
The growing healthcare industry is generating a large volume of useful data on patient demographics, treatment plans, payment, and insurance coverage—attracting the attention of clinicians and scientists alike. In recent years, a number of peer-reviewed articles have addressed different dimensions of data mining application in healthcare. However, the lack of a comprehensive and systematic narrative motivated us to construct a literature review on this topic. In this paper, we present a review of the literature on healthcare analytics using data mining and big data. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we conducted a database search between 2005 and 2016. Critical elements of the selected studies—healthcare sub-areas, data mining techniques, types of analytics, data, and data sources—were extracted to provide a systematic view of development in this field and possible future directions. We found that the existing literature mostly examines analytics in clinical and administrative decision-making. Use of human-generated data is predominant considering the wide adoption of Electronic Medical Record in clinical care. However, analytics based on website and social media data has been increasing in recent years. Lack of prescriptive analytics in practice and integration of domain expert knowledge in the decision-making process emphasizes the necessity of future research.
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.