Return on investment of a LEED platinum hospital: the influence of healthcare facility environments on healthcare employees and organizational effectiveness
Bibliographic record
Abstract
Objective: The purpose of this research study was to link hospital environments to the quality of care and the associated cost of care by examining the relationship among hospital environments and healthcare employee engagement, turnover, illness and injury. Methods: This study used a multi-method research design and quantitative analysis of data sets from participating hospitals. Data included employee survey responses and human resource employee data provided by the hospital system. All statistical tests used an alpha level of .05. The analysis of the survey and human resource employee data tested for significant differences among employees at the participating hospitals; and used correlations and regression analysis to determine the direction and strength of the relationships where significant differences were evident. Results: Results from the survey indicated that perceptions of the built environment affect employee engagement and health and well-being up to 14%. Turnover and injury reductions were significant and resulted in substantial cost differences; $2.17M cost reduction based on the facility replaced and annual cost avoidance of $2.24M when compared to the two newer hospitals that were not Leadership in Energy and Environmental Design (LEED) certified. Conclusions: This study demonstrates that the quality of the hospital environment has social, environmental, and cost implications that aligns with the intention of sustainable design as defined by the United States Green Building Council (USGBC). Developing a built environment that supports productivity, efficiency, safety, and engagement contributes to the prosperity of the healthcare organization.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".