ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2016
A Novel Schema to Enhance Data Quality of Patient Safety Event Reports.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Enhancing Patient Safety Event Reporting. A Systematic Review of System Design Features.Applied clinical informatics · 2017Pooled it
- A prototype of knowledge-based patient safety event reporting and learning system.BMC medical informatics and decision making · 2018Article
- Initializing and Growing a Database of Health Information Technology (HIT) Events by Using TF-IDF and Biterm Topic Modeling.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
The most important knowledge in the field of patient safety is regarding the prevention and reduction of patient safety events (PSEs). It is believed that PSE reporting systems could be a good resource to share and to learn from previous cases. However, the success of such systems in healthcare is yet to be seen. One reason is that the qualities of most PSE reports are unsatisfactory due to the lack of knowledge output from reporting systems which makes reporters report halfheartedly. In this study, we designed a PSE similarity searching model based on semantic similarity measures, and proposed a novel schema of PSE reporting system which can effectively learn from previous experiences and timely inform the subsequent actions. This system will not only help promote the report qualities but also serve as a knowledge base and education tool to guide healthcare providers in terms of preventing the recurrence of PSEs.
Indexed as
Identifiers
28269943PMC5333227What 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.