ArticleConvergent science physical oncology2018
Secondary use of electronic medical records for clinical research: Challenges and Opportunities.
Article in Convergent science physical oncology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Integrating NLP to Enhance Algorithmic Identification of Metastatic and Castration-Resistant Prostate Cancer in Large Claims-Based Studies.Cancer medicine · 2025Article
- Autoencoder-Based Representation Learning for Similar Patients Retrieval From Electronic Health Records: Comparative Study.JMIR medical informatics · 2025Article
- Prediction of adverse pregnancy outcomes using machine learning techniques: evidence from analysis of electronic medical records data in Rwanda.BMC medical informatics and decision making · 2025Article
- Undercounting diagnoses in Australian general practice: a data quality study with implications for population health reporting.BMC medical informatics and decision making · 2024Article
- Cardiovascular Care Innovation through Data-Driven Discoveries in the Electronic Health Record.The American journal of cardiology · 2023Review
- pyPheWAS Explorer: a visualization tool for exploratory analysis of phenome-disease associations.JAMIA open · 2023Article
- Identifying primary care datasets and perspectives on their secondary use: a survey of Australian data users and custodians.BMC medical informatics and decision making · 2022Article
- Association of Physician Referrals with Timely Cancer Care Using Tumor Registry and Claims Data.Health equity · 2022Article
- Comparison of orthogonal NLP methods for clinical phenotyping and assessment of bone scan utilization among prostate cancer patients.Journal of biomedical informatics · 2019Article
- Optimizing scalable approaches for early detection of cognitive impairment in primary care.Alzheimer's & dementia (Amsterdam, Netherlands)Article
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
Abstract
With increasingly ubiquitous electronic medical record (EMR) implementation accelerated by the adoption of the HITECH Act, there is much interest in the secondary use of collected data to improve outcomes and promote personalized medicine. A plethora of research has emerged using EMRs to investigate clinical research questions and assess variations in both treatments and outcomes. However, whether because of genuine complexities of modeling disease physiology or because of practical problems regarding data capture, data accuracy, and data completeness, the state of current EMR research is challenging and gives rise to concerns regarding study accuracy and reproducibility. This work explores challenges in how different experimental design decisions can influence results using a specific example of breast cancer patients undergoing excision and reconstruction surgeries from EMRs in an academic hospital and the Veterans Health Administration (VHA) We discuss emerging strategies that will mitigate these limitations, including data sharing, application of natural language processing, and improved EMR user design.
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.