Optimizing senior’s surgical care - Elder-friendly Approaches to the Surgical Environment (EASE) study: rationale and objectives
Bibliographic record
Abstract
BACKGROUND: It is estimated that seniors (≥65 years old) account for >50% of acute inpatient hospital days and are presenting for surgical evaluation of acute illness in increasing numbers. Unfortunately, conventional acute care models rarely take into account needs of the elderly population. The failure to consider these special needs have resulted in poor outcomes, longer lengths of hospital stay and have likely increased the need for institutional care. Acute Care for the Elderly models on medical wards have demonstrated decreased cost, length of hospital stay, readmissions and improved cognition, function and patient/staff satisfaction. We hypothesize that specific Elder-friendly Approaches to the Surgical Environment (EASE) interventions will similarly improve health outcomes in a cost-effective manner. METHODS/DESIGN: Prospective, before-after study with a concurrent control group. Four cohorts of 140 consecutively-screened older patients (≥65 years old) will be enrolled (560 patients in total). The EASE interventions involves co-locating all older surgical patients on a single unit, involving an interdisciplinary care team (including a geriatric specialist) in the development of individual care plans, implementing evidence-informed elder-friendly practices, use of a reconditioning program, and optimizing discharge planning. Subjects will be followed via chart review for their hospital stay, and will then complete in-person or telephone interviews at 6 weeks and 6 months after discharge. Measured outcomes include clinical (postoperative major in-hospital complication or death [primary composite outcome]; death or readmission within 30-days of initial discharge; length of hospital stay), humanistic (quality of life; functional, cognitive, and nutritional status) and economic (health care resource utilization and costs) endpoints. Within-site mean change scores will be computed for the composite primary outcome and the overall covariate-adjusted between-site pre-post difference will be the dependent variable analyzed using generalized linear mixed model procedures including adjustment for clustering. DISCUSSION: Our findings will generate new knowledge on outcomes from acute surgical care in older patients and validate a novel elder-friendly surgical model including assessment of both clinical and economic benefits. If effective, we expect the EASE initiatives to be generalizable to other surgical centres. TRIAL REGISTRATION: Clinicaltrials.govidentifier: NCT02233153.
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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 | 0.008 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".