ArticleClinical epidemiology2011
Use of electronic medical records (EMR) for oncology outcomes research: assessing the comparability of EMR information to patient registry and health claims data.
Article in Clinical epidemiology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
What it found
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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.
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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
27 citing papers in PubMed.
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- Enabling realistic health data re-identification risk assessment through adversarial modeling.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Renal response in real-world carfilzomib- vs bortezomib-treated patients with relapsed or refractory multiple myeloma.Blood advances · 2021Article
- Cohort Identification for Translational Bioinformatics Studies.Methods in molecular biology (Clifton, N.J.) · 2021Article
- A Conceptual Model of an Oncology Information System.Cancer management and research · 2020Article
- Appropriateness of granulocyte colony-stimulating factor use in patients receiving chemotherapy by febrile neutropenia risk level.Journal of oncology pharmacy practice : official publication of the International Society of Oncology Pharmacy Practitioners · 2019Article
- Relevant Word Order Vectorization for Improved Natural Language Processing in Electronic Health Records.Scientific reports · 2019Article
- Linkage between Utah All Payers Claims Database and Central Cancer Registry.Health services research · 2019Article
- Electronic Health Record-Based Registries: Clinical Research Using Registries in Colon and Rectal Surgery.Clinics in colon and rectal surgery · 2019Review
- Change in Survival in Metastatic Breast Cancer with Treatment Advances: Meta-Analysis and Systematic Review.JNCI cancer spectrum · 2018Article
- How Confounder Strength Can Affect Allocation of Resources in Electronic Health Records.Perspectives in health information managemen · 2018Article
- Challenges in Personalized Nutrition and Health.Frontiers in nutrition · 2018Article
- Biases introduced by filtering electronic health records for patients with "complete data".Journal of the American Medical Informatics Association : JAMIA · 2017Article
- Estimation of State-Level Prevalence of Hepatitis C Virus Infection, US States and District of Columbia, 2010.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2017Article
- Increasing use of radical prostatectomy for locally advanced prostate cancer in the USA and Germany: a comparative population-based study.Prostate cancer and prostatic diseases · 2017Article
- -Omic and Electronic Health Record Big Data Analytics for Precision Medicine.IEEE transactions on bio-medical engineering · 2017Review
- Complex temporal topic evolution modelling using the Kullback-Leibler divergence and the Bhattacharyya distance.EURASIP journal on bioinformatics & systems biology · 2016Article
- Burden of symptoms associated with development of metastatic bone disease in patients with breast cancer.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2016Article
- Development of a large urban longitudinal HIV clinical cohort using a web-based platform to merge electronically and manually abstracted data from disparate medical record systems: technical challenges and innovative solutions.Journal of the American Medical Informatics Association : JAMIA · 2016Article
- Patients with bone metastases from solid tumors initiating treatment with a bone-targeted agent in 2011: a descriptive analysis using oncology clinic data in the US.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2014Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
unlabelledElectronic medical records (EMRs) are used increasingly for research in clinical oncology, epidemiology, and comparative effectiveness research (CER).
objectiveTo assess the utility of using EMR data in population-based cancer research by comparing a database of EMRs from community oncology clinics against Surveillance Epidemiology and End Results (SEER) cancer registry data and two claims databases (Medicare and commercial claims). STUDY DESIGN AND
settingDEMOGRAPHIC, CLINICAL, AND TREATMENT PATTERNS IN THE EMR, SEER, MEDICARE, AND COMMERCIAL CLAIMS DATA WERE COMPARED USING SIX TUMOR SITES: breast, lung/bronchus, head/neck, colorectal, prostate, and non-Hodgkin's lymphoma (NHL). We identified various challenges in data standardization and selection of appropriate statistical procedures. We describe the patient and clinic inclusion criteria, treatment definitions, and consideration of the administrative and clinical purposes of the EMR, registry, and claims data to address these challenges.
resultsSex and 10-year age distributions of patient populations for each tumor site were generally similar across the data sets. We observed several differences in racial composition and treatment patterns, and modest differences in distribution of tumor site.
conclusionOur experience with an oncology EMR database identified several factors that must be considered when using EMRs for research purposes or generalizing results to the US cancer population. These factors were related primarily to evaluation of treatment patterns, including evaluation of stage, geographic location, race, and specialization of the medical facilities. While many specialty EMRs may not provide the breadth of data on medical care, as found in comprehensive claims databases and EMR systems, they can provide detailed clinical data not found in claims that are extremely important in conducting epidemiologic and outcomes research.
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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.