ReviewFrontiers in oncology2016
Review of Developments in Electronic, Clinical Data Collection, and Documentation Systems over the Last Decade - Are We Ready for Big Data in Routine Health Care?
Review in Frontiers in oncology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Development of a digitalization concept for assessing patient-reported outcomes in the context of a University Cancer Center - a model for use in clinical routine.Journal of patient-reported outcomes · 2025Article
- A database for oncological research and quality assurance: implementation and first experiences with the University Clinical Cancer Registry Regensburg.BMC medical research methodology · 2024Article
- Applying Data Warehousing to a Phase III Clinical Trial From the Fondazione Italiana Linfomi Ensures Superior Data Quality and Improved Assessment of Clinical Outcomes.JCO clinical cancer informatics · 2019Article
- Reliability of Paper-Based Routine Documentation in Psychiatric Inpatient Care and Recommendations for Further Improvement.Frontiers in psychiatry · 2019Article
- [Big data in imaging].Zeitschrift fur Rheumatologie · 2018Review
- Use of Multicenter Data in a Large Cancer Registry for Evaluation of Outcome and Implementation of Novel Concepts.Frontiers in oncology · 2017Article
- Big Data in Designing Clinical Trials: Opportunities and Challenges.Frontiers in oncology · 2017Article
- A critical review of recent developments in radiotherapy for non-small cell lung cancer.Radiation oncology (London, England) · 2016Review
- The big data effort in radiation oncology: Data mining or data farming?Advances in radiation oncologyReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recently, information availability has become more elaborate and widespread, and treatment decisions are based on a multitude of factors, including imaging, molecular or pathological markers, surgical results, and patient's preference. In this context, the term "Big Data" evolved also in health care. The "hype" is heavily discussed in literature. In interdisciplinary medical specialties, such as radiation oncology, not only heterogeneous and voluminous amount of data must be evaluated but also spread in different styles across various information systems. Exactly this problem is also referred to in many ongoing discussions about Big Data - the "three V's": volume, velocity, and variety. We reviewed 895 articles extracted from the NCBI databases about current developments in electronic clinical data management systems and their further analysis or postprocessing procedures. Few articles show first ideas and ways to immediately make use of collected data, particularly imaging data. Many developments can be noticed in the field of clinical trial or analysis documentation, mobile devices for documentation, and genomics research. Using Big Data to advance medical research is definitely on the rise. Health care is perhaps the most comprehensive, important, and economically viable field of application.
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.