Feasibility of using emergency department patient experience surveys as a proxy for equity of care
Bibliographic record
Abstract
Collecting and examining equity data can help inform quality improvement initiatives but is a relatively new practice in health care. The overall goal of this study was to assess different methods of administering patient experience surveys as a feasible starting point in measuring equity in an urban Emergency Department (ED) that serves a diverse patient population. Socio-demographic characteristics of patients visiting an ED were compared with those of patients who responded to provincial patient experience surveys routinely administered by mail. Patient experience survey data were collected over an 11-week period in an urban ED using different survey administration methods (face-to-face interviews vs. handout) among study participants from vulnerable populations (elderly, low income, homeless, and mental health or substance use issues). Patient populations receiving care in the ED were shown to be different from those who responded to routinely mailed patient experience surveys with elderly patients over-represented, and contrarily, low income, mental health or substance use and homeless/unstable housing populations under-represented in survey responses. From a total of 111 study participants, the response rate for face-to-face surveys was significantly higher than for surveys that were handed out (p = 0.002), but no significant difference in the percentage of positive responses was evident. Delivering patient experience surveys immediately upon discharge is an effective way of capturing unique responses from patients in vulnerable populations, supporting a valuable means of assessing equity in the ED. Survey administration method poses important implications when used to inform quality improvement efforts and performance measurement.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".