ArticleJournal of applied clinical medical physics2021
Automated data abstraction for quality surveillance and outcome assessment in radiation oncology.
Article in Journal of applied clinical medical physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Operational Ontology for Oncology (O3): A Professional Society-Based, Multistakeholder, Consensus-Driven Informatics Standard Supporting Clinical and Research Use of Real-World Data From Patients Treated for Cancer.International journal of radiation oncology, biology, physics · 2023Guideline
- The complementary roles of oversight, education, and collaboration in the responsible integration of artificial intelligence in radiation medicine: White paper of CADRA.Journal of applied clinical medical physics · 2026Review
- Exploring Technological Solutions for Interoperability Between Patient Electronic Medical Records and Clinical Registries: Scoping Review.Journal of medical Internet research · 2026Article
- Automated extraction of temporalized tumor evolution from oncology EMRs using natural language processing.ESMO real world data and digital oncology · 2026Article
- Implementation of a comprehensive clinical quality assurance system in radiation oncology.Radiation oncology (London, England) · 2025Article
- Leveraging Radiotherapy Data for Precision Oncology: Veterans Affairs Granular Radiotherapy Information Database.JCO clinical cancer informatics · 2025Article
- Perceptions on and roadblocks to implementation of standardized nomenclature in radiation oncology: A survey from TG-263U1.Journal of applied clinical medical physics · 2024Article
- Infrastructure tools to support an effective Radiation Oncology Learning Health System.Journal of applied clinical medical physics · 2023Article
- Incorporating Patient Similarity and Clinical Temporality in Disease Prognostic Modeling.IEEE transactions on computational biology and bioinformaticsArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Rigorous radiotherapy quality surveillance and comprehensive outcome assessment require electronic capture and automatic abstraction of clinical, radiation treatment planning, and delivery data. We present the design and implementation framework of an integrated data abstraction, aggregation, and storage, curation, and analytics software: the Health Information Gateway and Exchange (HINGE), which collates data for cancer patients receiving radiotherapy. The HINGE software abstracts structured DICOM-RT data from the treatment planning system (TPS), treatment data from the treatment management system (TMS), and clinical data from the electronic health records (EHRs). HINGE software has disease site-specific "Smart" templates that facilitate the entry of relevant clinical information by physicians and clinical staff in a discrete manner as part of the routine clinical documentation. Radiotherapy data abstracted from these disparate sources and the smart templates are processed for quality and outcome assessment. The predictive data analyses are done on using well-defined clinical and dosimetry quality measures defined by disease site experts in radiation oncology. HINGE application software connects seamlessly to the local IT/medical infrastructure via interfaces and cloud services and performs data extraction and aggregation functions without human intervention. It provides tools to assess variations in radiation oncology practices and outcomes and determines gaps in radiotherapy quality delivered by each provider.
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.