ArticleJournal of clinical oncology : official journal of the American Society of Clinical Oncology2020
Status Update on Data Required to Build a Learning Health System.
Article in Journal of clinical oncology : official journal of the American Society of Clinical Oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 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
18 citing papers in PubMed.
- Leveraging Data Science for Conducting Observational Studies: Highlighting Advantages and Limitations Throughout the Evaluation of a Use Case.Mayo Clinic proceedings. Digital health · 2026Article
- From Network Governance to Real-World-Time Learning: A High-Reliability Operating Model for Rare Cancers.Cancers · 2026Article
- Challenges in Automating Extraction of Real-World Radiographic Images and Adverse Events: Lessons From the ICAREdata Initiative.JCO clinical cancer informatics · 2025Article
- Towards a shared understanding of the learning health system in a large academic-based health system: A qualitative analysis.Health services management research · 2025Article
- Article
- Organizational Factors in Clinical Data Sharing for Artificial Intelligence in Health Care.JAMA network open · 2023Article
- Overview of approaches to estimate real-world disease progression in lung cancer.JNCI cancer spectrum · 2023Review
- Risk factors of early mortality in patients with small cell lung cancer: a retrospective study in the SEER database.Journal of cancer research and clinical oncology · 2023Article
- Prioritizing Measures That Matter Within a Person-Centered Oncology Learning Health System.JNCI cancer spectrum · 2022Article
- Electronic Health Record Data in Cancer Learning Health Systems: Challenges and Opportunities.JCO clinical cancer informatics · 2022Review
- Making Diabetes Electronic Medical Record Data Actionable: Promoting Benchmarking and Population Health Improvement Using the T1D Exchange Quality Improvement Portal.Clinical diabetes : a publication of the American Diabetes Association · 2022Article
- The OpenDeID corpus for patient de-identification.Scientific reports · 2021Article
- Leveraging Clinical Informatics Tools to Extract Cumulative Anthracycline Exposure, Measure Cardiovascular Outcomes, and Assess Guideline Adherence for Children With Cancer.JCO clinical cancer informatics · 2021Article
- Correlation Between Surrogate End Points and Overall Survival in a Multi-institutional Clinicogenomic Cohort of Patients With Non-Small Cell Lung or Colorectal Cancer.JAMA network open · 2021Article
- Challenges and opportunities to developing a frailty index using electronic health record data.Journal of geriatric oncology · 2021Article
- The Prospective Dutch Colorectal Cancer (PLCRC) cohort: real-world data facilitating research and clinical care.Scientific reports · 2021Article
- Apples and Oranges? Considerations for EHR-Based Analyses Aggregating Data From Interventional Clinical Trials and Point-of-Care Encounters in Oncology.JCO clinical cancer informatics · 2021Article
- Improving Cancer Data Interoperability: The Promise of the Minimal Common Oncology Data Elements (mCODE) Initiative.JCO clinical cancer informatics · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Wide adoption of electronic health records (EHRs) has raised the expectation that data obtained during routine clinical care, termed "real-world" data, will be accumulated across health care systems and analyzed on a large scale to produce improvements in patient outcomes and the use of health care resources. To facilitate a learning health system, EHRs must contain clinically meaningful structured data elements that can be readily exchanged, and the data must be of adequate quality to draw valid inferences. At the present time, the majority of EHR content is unstructured and locked into proprietary systems that pose significant challenges to conducting accurate analyses of many clinical outcomes. This article details the current state of data obtained at the point of care and describes the changes necessary to use the EHR to build a learning health system.
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.