Redefining Quality of Surgical Care for the Frail Elderly

Identifying high-risk surgical patients: A study of older adults whose code status changed to Do-Not-Resuscitate

BACKGROUND

There is a paucity of data on older adults (age ≥65 years) undergoing surgery who had an inpatient do-not-resuscitate (DNR) order, and the association between timing of DNR order and outcomes.

METHODS

This was a retrospective analysis of 1976 older adults in the American College of Surgeons National Surgical Quality Improvement Program geriatric-specific database (2014-2018). Patients were stratified by institution of a DNR order during their surgical admission ("new-DNR" vs. "no-DNR"), and matched by age (±3 years), frailty score (range: 0-1), and procedure. The main outcome of interest was occurrence of death or hospice transition (DoH) ≤30 postoperative days; this was analyzed using bivariate and multivariable methods.

RESULTS

One in 36 older adults had a new-DNR order. After matching, there were 988 new-DNR and 988 no-DNR patients. Median age and frailty score were 82 years and 0.2, respectively. Most underwent orthopedic (47.6%), general (37.6%), and vascular procedures (8.4%). Overall DoH rate ≤30 days was 44.4% for new-DNR versus 4.0% for no-DNR patients (p < 0.001). DoH rate for patients who had DNR orders placed in the preoperative, day of surgery, and postoperative setting was 16.7%, 23.3%, and 64.6%, respectively (p < 0.001). In multivariable analysis, compared to no-DNR patients, those with a new-DNR order had a 28-fold higher adjusted odds of DoH (odds ratio [OR] 28.1, 95% confidence interval: 13.0-60.1, p < 0.001); however, odds were 10-fold lower if the DNR order was placed preoperatively (OR: 5.8, p = 0.003) versus postoperatively (OR: 52.9, p < 0.001). Traditional markers of poor postoperative outcomes such as American Society of Anesthesiologists class and emergency surgery were not independently associated with DoH.

CONCLUSIONS

An inpatient DNR order was associated with risk of DoH independent of traditional markers of poor surgical outcomes. Further research is needed to understand factors leading to a DNR order that may aid early recognition of high-risk older adults undergoing surgery.

The Prognostic Performance of Frailty for Delirium and Functional Decline in Vascular Surgery Patients

BACKGROUND

Frailty in older vascular surgery patients is associated with increased mortality, hospital stay, and morbidity. The association of frailty with hospital-acquired geriatric syndromes such as delirium and functional decline has not been well studied.

OBJECTIVES

To investigate the association between frailty and hospital-acquired geriatric syndromes in older hospitalized vascular surgery patients, and to evaluate the prognostic performance of the frailty index (FI) and the Clinical Frailty Scale (CFS) for delirium and functional decline.

DESIGN

Prospective cohort study.

SETTING

Acute care academic hospital.

PARTICIPANTS

Patients aged 65 years or more admitted to a tertiary vascular surgery unit (N=150).

MEASUREMENTS

Frailty was assessed using the FI and CFS. The adjusted association of frailty status with delirium and functional decline was assessed using logistic regression analysis. The prognostic performance of FI and CFS was determined by assessing C-statistic and positive and negative predictive values (PPV and NPV).

RESULTS

Of 150 participants, FI identified 34 (23%) and CFS identified 45 (30%) as frail. Frailty was an independent predictor of delirium (FI adjusted odds ratio, odds ratio (OR) = 5.66, 95% confidence interval (CI) = 1.53-21.03; CFS adjusted OR = 4.07, 95% CI = 1.14-14.50), but not functional decline. FI and CFS showed acceptable prognostic performance for delirium (C-statistic 0.74), but not functional decline (C-statistic 0.63-0.64). For both outcomes, the FI and CFS had high NPV (86-96%), and low PPV (22-29%).

CONCLUSION

Frail older vascular surgery patients are more likely to develop hospital-acquired geriatric syndromes. The FI and CFS have acceptable prognostic performance for predicting delirium but not all individuals who are identified as frail develop delirium. Ongoing research is needed to identify interventions that improve outcomes in patients who screen positive for frailty.

Postoperative Delirium as a Target for Surgical Quality Improvement

OBJECTIVE

To explore hospital-level variation in postoperative delirium using a multi-institutional data source.

BACKGROUND

Postoperative delirium is closely related to serious morbidity, disability, and death in older adults. Yet, surgeons and hospitals rarely measure delirium rates, which limits quality improvement efforts.

METHODS

The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) Geriatric Surgery Pilot (2014 to 2015) collects geriatric-specific variables, including postoperative delirium using a standardized definition. Hierarchical logistic regression models, adjusted for case mix [Current Procedural Terminology (CPT) code] and patient risk factors, yielded risk-adjusted and smoothed odds ratios (ORs) for hospital performance. Model performance was assessed with Hosmer-Lemeshow (HL) statistic and c-statistics, and compared across surgical specialties.

RESULTS

Twenty thousand two hundred twelve older adults (≥65 years) underwent inpatient operations at 30 hospitals. Postoperative delirium occurred in 2427 patients (12.0%) with variation across specialties, from 4.7% in gynecology to 13.7% in cardiothoracic surgery. Hierarchical modeling with 20 risk factors (HL = 9.423, P = 0.31; c-statistic 0.86) identified 13 hospitals as statistical outliers (5 good, 8 poor performers). Per hospital, the median risk-adjusted delirium rate was 10.4% (range 3.2% to 27.5%). Operation-specific risk and preoperative cognitive impairment (OR 2.9, 95% confidence interval 2.5-3.5) were the strongest predictors. The model performed well across surgical specialties (orthopedic, general surgery, and vascular surgery).

CONCLUSION

Rates of postoperative delirium varied 8.5-fold across hospitals, and can feasibly be measured in surgical quality datasets. The model performed well with 10 to 12 variables and demonstrated applicability across surgical specialties. Such efforts are critical to better tailor quality improvement to older surgical patients.