Effects of Electronic Medical Record Downtime on Patient Safety, Downtime Mitigation, and Downtime Plans
Bibliographic record
Abstract
The purpose of this article is to examine the extent and nature of the published electronic medical record (EMR) downtime, downtime mitigation and downtime planning research in healthcare. The article will also summarize some of the major themes and recommendations found in published research focused on downtime and healthcare. In this study, data was extracted from the research publications. Three major themes emerged: patient safety, contingency planning, and mitigation. These overarching themes were further expanded into 13 subthemes. Healthcare organizations, now with mature EMR deployments, are well aware of the importance of contingency plans for both planned and unintended downtime situations. The literature is encouraging. Organizations are updating and evolving their contingency plans. Research suggests clinical staff (e.g. physicians, nurses) benefit from more training. Clinical staff also benefited from first-hand knowledge and experience in downtime scenarios, either in live situations or in the form of downtime drills.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".