Optimizing Surgical Quality Datasets to Care for Older Adults: Lessons from the American College of Surgeons NSQIP Geriatric Surgery Pilot

摘要

Background Surgical quality datasets can be better tailored toward older adults. The American College of Surgeons (ACS) NSQIP Geriatric Surgery Pilot collected risk factors and outcomes in 4 geriatric-specific domains: cognition, decision-making, function, and mobility. This study evaluated the contributions of geriatric-specific factors to risk adjustment in modeling 30-day outcomes and geriatric-specific outcomes (postoperative delirium, new mobility aid use, functional decline, and pressure ulcers). Study Design Using ACS NSQIP Geriatric Surgery Pilot data (January 2014 to December 2016), 7 geriatric-specific risk factors were evaluated for selection in 14 logistic models (morbidities/mortality) in general-vascular and orthopaedic surgery subgroups. Hierarchical models evaluated 4 geriatric-specific outcomes, adjusting for hospitals-level effects and including Bayesian-type shrinkage, to estimate hospital performance. Results There were 36,399 older adults who underwent operations at 31 hospitals in the ACS NSQIP Geriatric Surgery Pilot. Geriatric-specific risk factors were selected in 10 of 14 models in both general-vascular and orthopaedic surgery subgroups. After risk adjustment, surrogate consent (odds ratio [OR] 1.5; 95% CI 1.3 to 1.8) and use of a mobility aid (OR 1.3; 95% CI 1.1 to 1.4) increased the risk for serious morbidity or mortality in the general-vascular cohort. Geriatric-specific factors were selected in all 4 geriatric-specific outcomes models. Rates of geriatric-specific outcomes were: postoperative delirium in 12.1% (n?= 3,650), functional decline in 42.9% (n?= 13,000), new mobility aid in 29.7% (n?= 9,257), and new or worsened pressure ulcers in 1.7% (n?= 527). Conclusions Geriatric-specific risk factors are important for patient-centered care and contribute to risk adjustment in modeling traditional and geriatric-specific outcomes. To provide optimal patient care for older adults, surgical datasets should collect measures that address cognition, decision-making, mobility, and function.