Factors That Influence Line Managers' Perceptions of Hospital Performance Data
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Bibliographic record
Abstract
OBJECTIVE: To design and test a model of the factors that influence frontline and midlevel managers' perceptions of usefulness of comparative reports of hospital performance. STUDY SETTING: A total of 344 frontline and midlevel managers with responsibility for stroke and medical cardiac patients in 89 acute care hospitals in the Canadian province of Ontario. STUDY DESIGN: Fifty-nine percent of managers responded to a mail survey regarding managers' familiarity with a comparative report of hospital performance, ratings of the report's data quality, relevance and complexity, improvement culture of the organization, and perceptions of usefulness of the report. EXTRACTION METHODS: Exploratory factor analysis was performed to assess the dimensionality of performance data characteristics and improvement culture. Antecedents of perceived usefulness and the role of improvement culture as a moderator were tested using hierarchical regression analyses. PRINCIPAL FINDINGS: Both data characteristics variables including data quality, relevance, and report complexity, as well as organizational factors including dissemination intensity and improvement culture, explain significant amounts of variance in perceptions of usefulness of comparative reports of hospital performance. The total R2 for the full hierarchical regression model = .691. Improvement culture moderates the relationship between data relevance and perceived usefulness. CONCLUSIONS: Organizations and those who fund and design performance reports need to recognize that both report characteristics and organizational context play an important role in determining line managers' response to and ability to use these types of data.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it