ArticleMedicine2020
Medical error professionals' perspectives on Inter-system Medical Error Discovery (IMED): Consensus, divergence, and uncertainty.
Article in Medicine, 2020. 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
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
6 citing papers in PubMed.
- The Relationship Between Barriers to Medical Error Disclosure and Patient Safety Culture: A Cross-Sectional Study.Journal of nursing management · 2026Article
- Anesthesi̇a students' behavi̇ors towards a medi̇cal errors: a phenomenologi̇cal quali̇tati̇ve scenari̇o study.BMC anesthesiology · 2025Article
- Just Culture in a Fragmented System: Ethical and Quality Imperatives in Cross-Institutional Tracheostomy Care.Tracheostomy (Warrenville, Ill.) · 2025Article
- Disclosure of medical errors to patients by medical professionals: a protocol for a qualitative systematic review.BMJ open · 2024Article
- How to HEEAL: A Patient and Peer-Centric Simulation Curriculum for Medical Error Disclosure.MedEdPORTAL : the journal of teaching and learning resources · 2024Article
- Nonsurgical Treatment of Carpal Tunnel Syndrome: A Survey of Hand Surgeons.Plastic and reconstructive surgery. Global open · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Best practices for how to respond are unclear when a medical error is discovered in a different system (inter-system medical error discovery or IMED). This qualitative study explored medical error professionals' views on disclosure, feedback, and reporting in these scenarios.We conducted semi-structured telephone interviews from January to September 2018 with 15 medical error professionals from 5 regions of the United States. Interview guides addressed perspectives on best practice, minimum obligations, and mediating factors with respect to IMED. Each transcript was coded independently by two investigators. Analysis followed the inductive approach of interpretive description.Medical error professionals expressed diverse views about minimum obligations and best practices for physicians when responding to IMED events. All cited practical barriers to disclosure, feedback, and reporting in these scenarios. There was general consensus that clear-cut, harmful errors should be disclosed to patients, and most advised investigation and feedback prior to disclosure. Respondents diverged in recommended best practices and thresholds for taking action. All noted the lack of guidance specific to IMED scenarios but differed in how they would extrapolate from more general guidance.While medical error professionals expressed consensus regarding obligations to disclose obvious errors, they differed on particulars. Guidelines or an algorithm could be very useful. Efforts to develop clear guidelines for IMED must take into account these factors, as well as practical and political challenges to communication about errors discovered across systems.
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.