Effects on wrong-patient errors by limiting access to concurrently open ERH charts: A preliminary systematic mapping and synthesis review
Bibliographic record
Abstract
Abstract Background Several recent outcome studies have been published looking at the effects of restricting electronic health record (EHR) user interfaces to limit the number of concurrently accessible patient records. Strong recommendations have been in place for several years to have user interfaces constrained to only display one patient chart at a time in order to reduce the risk of data (documentation, orders) being entered on the wrong patient (Joint Commission, 2015; ONC, 2016). This recommendation was made based on expert opinion rather than objective information, raising the question whether the accumulating evidence supports continued implementation of such chart access restrictions. Objectives This work reports a systematic mapping and synthesis review addressing research questions, “What is the evidence that restricting the number of concurrently open records reduces errors? (RQ1), “How effective is restriction of concurrently open charts at reducing wrong-patient errors? (RQ2), and “What additional inquiry is needed to make evidence-based policy decisions about restricting concurrent chart access? (RQ3). Methods A systematic search of CINAHL, PubMed, and Web of Science databases was performed with full search string specification to retrieve a result set that is the conjunction of result sets for concepts of EHR, concurrently open charts , and medical error . Of 407 studies identified and screened, five were eligible for inclusion in the qualitative synthesis review, and three were amenable to data extraction and pooled effect size calculation. Results None of the studies included for review found evidence of statistically significant change in wrong-patient error rates associated with implementing restriction in the number of patient records allowed to be open concurrently in the EHR. The combined OR for the pooled studies was 1.02 (95% CI 0.90 – 1.15) with low estimates for inter-study heterogeneity and no indication of publication bias. Conclusion There is no evidence that restricting the number of concurrently open records reduces errors (RQ1). It is not possible to definitively answer RQ2, but the magnitude of any yet to be detected beneficial effect that might be lost with lifting of chart access restriction can be no greater than an absolute risk increase of 33 errors per 100,000 ordering sessions. While it has been claimed that restricting the number of concurrently open EHR records is necessary for patient safety, the present review demonstrates that it is insufficient to attain a measurable improvement in error rates. Additional investigation of the usability and human factors aspects of EHR configuration decisions as well as knowledge of the impacts on clinical workflows will be necessary to provide policymakers, operational leaders, and practitioners with insight into the nature of the threats and opportunities with respect to safety, as well as the strengths and weaknesses of potential interventions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.055 | 0.205 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.016 |
| Bibliometrics | 0.020 | 0.015 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".