Prevalence of information gaps in the emergency department and the effect on patient outcomes.
Bibliographic record
Abstract
BACKGROUND: Information gaps occur when previously collected information is unavailable to a physician who is currently treating a patient. In this study we measured the prevalence of physician-reported information gaps for patients presenting to an emergency department at a teaching hospital. METHODS: For 1002 visits to the emergency department made by 983 patients, we recorded all information gaps identified by the emergency physician immediately after the patient was assessed. When an information gap was present, the physician was asked to identify the required information, why it was required and how important it was to the patient's care. We reviewed the patient charts to measure severity of illness and to determine whether the patient was referred to the emergency department by a community physician. Multiple linear regression analysis was used to determine whether information gaps were associated with length of stay in the emergency department. RESULTS: At least 1 information gap was identified in 323 (32.2%) of the 1002 visits (95% confidence interval 29.4%-35.2%). Information gaps were associated with severity of illness, being significantly more common in patients who had serious chronic illnesses, those who arrived by ambulance, those who had visited the emergency department or had been in hospital recently, patients in monitored areas in the emergency department and older patients. Information gaps most commonly comprised medical history (58%) and laboratory test results (23.3%) and were felt to be essential to patient care in 47.8% of the cases. The presence of information gaps was not associated with admission to hospital. After adjusting for important confounders, including patient sex, previous hospital admissions, diagnosis and severity of illness, we found that stays in the emergency department were 1.2 hours longer on average for patients with an information gap than for those without one. INTERPRETATION: Information gaps were present in almost one-third of the visits to our emergency department. They were more common in sicker patients and were independently associated with a prolonged stay in the emergency department.
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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 | 0.007 | 0.075 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".