American journal of surgery · 2026
Reliability of a rating rubric to assess quality of preoperative goals of care notes.
СтатьяНазвание и аннотация: Перевод в очереди
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Kern Caelie E, Cribbin Morgan P, Piazza Kirstin M, Whiteside Phoebe G, Pelcher Lindsay R, Peeples Amanda D, Goodman Octavia K, Pascal Caroline F, Arnold Robert M, Shrake Kaitlyn M, Hall Daniel E
Аннотация
BACKGROUND: High-quality preoperative goals of care (GOC) documentation should address prognosis, goals and values, treatment options, and justification of a preferred treatment option. A reproducible method for evaluating note quality is critical for quality improvement. We sought to adapt a pre-existing rating rubric for preoperative GOC documentation and evaluate its interrater reliability (IRR).
METHODS: We analyzed preoperative GOC notes from frail Veterans considering elective outpatient surgery at 5 Veterans Affairs Medical Centers. IRR was assessed using percent agreement and Cohen's kappa across 4 domains and overall quality.
RESULTS: 215 notes (April 2022 - July 2023) were included. Cohen's kappa ranged from 0.66 to 0.91 with percent agreement of 80.1% to 94.0%. The pooled kappa across domains was 0.82, indicating substantial to almost perfect agreement.
CONCLUSIONS: Iterative refinement produced a reliable rubric with at least substantial IRR, supporting its use for independent rating and quality improvement. Domain-specific variability highlights opportunities for further rubric refinement and rater training.
METHODS: We analyzed preoperative GOC notes from frail Veterans considering elective outpatient surgery at 5 Veterans Affairs Medical Centers. IRR was assessed using percent agreement and Cohen's kappa across 4 domains and overall quality.
RESULTS: 215 notes (April 2022 - July 2023) were included. Cohen's kappa ranged from 0.66 to 0.91 with percent agreement of 80.1% to 94.0%. The pooled kappa across domains was 0.82, indicating substantial to almost perfect agreement.
CONCLUSIONS: Iterative refinement produced a reliable rubric with at least substantial IRR, supporting its use for independent rating and quality improvement. Domain-specific variability highlights opportunities for further rubric refinement and rater training.