ArticleApplied clinical informatics2021
Lessons Learned for Identifying and Annotating Permissions in Clinical Consent Forms.
Article in Applied clinical informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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.
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Who cites it
2 citing papers in PubMed.
- Pediatric Consent on FHIR.Applied clinical informatics · 2024Article
- Evaluating and Extending the Informed Consent Ontology for Representing Permissions from the Clinical Domain.Applied ontology · 2022Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
backgroundThe lack of machine-interpretable representations of consent permissions precludes development of tools that act upon permissions across information ecosystems, at scale.
objectivesTo report the process, results, and lessons learned while annotating permissions in clinical consent forms.
methodsWe conducted a retrospective analysis of clinical consent forms. We developed an annotation scheme following the MAMA (Model-Annotate-Model-Annotate) cycle and evaluated interannotator agreement (IAA) using observed agreement (
resultsThe final dataset included 6,399 sentences from 134 clinical consent forms. Complete agreement was achieved for 5,871 sentences, including 211 positively identified and 5,660 negatively identified as permission-sentences across all three annotators (
conclusionOur findings point to the complexity of identifying permission-sentences within the clinical consent forms. We present our results in light of lessons learned, which may serve as a launching point for developing tools for automated permission extraction.
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Registered trials
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