ArticleJournal of oncology practice2013
Physician inter-annotator agreement in the Quality Oncology Practice Initiative manual abstraction task.
Article in Journal of oncology practice, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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.
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
6 citing papers in PubMed.
- Artificial Intelligence Clinical Evidence Engine for Automatic Identification, Prioritization, and Extraction of Relevant Clinical Oncology Research.JCO clinical cancer informatics · 2021Article
- Researching the Appropriateness of Care in the Complementary and Integrative Health Professions Part 5: Using Patient Records: Selection, Protection, and Abstraction.Journal of manipulative and physiological therapeutics · 2019Observational
- Next-generation long-term transplant clinics: improving resource utilization and the quality of care through health information technology.Bone marrow transplantation · 2016Review
- Comparison of Quality Oncology Practice Initiative (QOPI) Measure Adherence Between Oncology Fellows, Advanced Practice Providers, and Attending Physicians.Journal of cancer education : the official journal of the American Association for Cancer Education · 2015Article
- Delivering High-Quality Cancer Care: The Critical Role of Quality Measurement.Healthcare (Amsterdam, Netherlands) · 2014Article
- Evolution of the Quality Oncology Practice Initiative supportive care quality measures portfolio and conformance at a Veterans Affairs medical center.Journal of oncology practice · 2013Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThe Quality Oncology Practice Initiative (QOPI) relies on the accuracy of manual abstraction of clinical data from paper-based and electronic medical records (EMRs). Although there is no "gold standard" to measure manual abstraction accuracy, measurement of inter-annotator agreement (IAA) is a commonly agreed-on surrogate. We quantified the IAA of QOPI abstractions on a cohort of cancer patients treated at Beth Israel Deaconess Medical Center.
methodsThe EMR charts of 49 patients (20 colorectal cancer; 18 breast cancer; 11 non-Hodgkin lymphoma) were abstracted by separate physician abstractors in the fall 2010 and fall 2011 QOPI abstraction rounds. Cohen's kappa (κ) was calculated for encoded data; raw levels of agreement and magnitude of discrepancies were calculated for numeric and dated data.
resultsOne hundred two data elements with 2,035 paired entries were analyzed. Overall IAA for the 1,496 coded entries was κ = 0.75; median IAA for n = 85 individual coded elements was κ = 0.84 (interquartile range, 0.30 to 1.00). Overall IAA for the 421 dated entries was 73%; median IAA for n = 17 individual dated elements was 67% (interquartile range, 61% to 86%).
conclusionThis study establishes a baseline level of IAA for a complex medical abstraction task with clear relevance for the oncology community. Given that the observed κ is considered only fair IAA, and that the rate of date discrepancy is high, caution is necessary in interpreting the results of QOPI and other manual abstractions of clinical oncology data. The accuracy of automated data extraction efforts, possibly including a future evolution of QOPI, will also need to be carefully evaluated.
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