Faculty Bibliography

IMPORTANCE:Various clinical societies and patient advocacy organizations continue to encourage minimum volume standards at hospitals that perform certain high-risk operations. Although many clinicians and quality and safety experts believe this can improve outcomes, the extent to which hospitals have responded to these discretionary standards remains unclear. OBJECTIVE:To evaluate the association between short-term clinical outcomes and hospitals' adherence to the Leapfrog Group's minimum volume standards for high-risk cancer surgery. DESIGN, SETTING, AND PARTICIPANTS:Longitudinal cohort study using 100% of the Medicare claims for 516 392 patients undergoing pancreatic, esophageal, rectal, or lung resection for cancer between January 1, 2005, and December 31, 2016. Data were accessed between December 1, 2018, and April 30, 2019. EXPOSURES:High-risk cancer surgery in hospitals meeting and not meeting the minimum volume standards. MAIN OUTCOMES AND MEASURES:Patients having surgery in hospitals meeting the volume standard and 30-day and in-hospital mortality and complication rates. RESULTS:Overall, a total of 516 392 procedures (47 318 pancreatic resections, 29 812 esophageal resections, 116 383 rectal resections, and 322 879 lung resections) were included in the study, and patient mean (SD) age was 73.1 (7.5) years. Outcomes improved over time in both hospitals meeting and not meeting the minimum volume standards. Mortality after pancreatic resection decreased from 5.5% in 2005 to 4.8% in 2016 (P for trend <.001). Mortality after esophageal resection decreased from in 6.7% 2005 to 5.0% in 2016 (P for trend <.001). Mortality after rectal resection decreased from 3.6% in 2005 to 2.7 % in 2016 (P for trend <.001). Mortality after lung resection decreased from 4.2% in 2005 to 2.7 % in 2016 (P for trend <.001). Throughout the study period, there were no statistically significant differences in risk-adjusted mortality between hospitals meeting and not meeting the volume standards for esophageal, lung, and rectal cancer resections. Mortality rates after pancreatic resection were consistently lower at hospitals meeting the volume standard, although mortality at all hospitals decreased over the study period. For example, in 2016, risk-adjusted mortality rates for hospitals meeting the volume standard were 3.8% (95% CI, 3.3%-4.3%) compared with 5.7% (95% CI, 5.1%-6.5%) for hospitals that did not. Although an increasing majority of patients underwent surgery in hospitals meeting the Leapfrog volume standards over time, the overall proportion of hospitals meeting the standards in 2016 ranged from 5.6% for esophageal resection to 23.3% for pancreatic resection. CONCLUSIONS AND RELEVANCE:Although volume remains an important factor for patient safety, the Leapfrog Group's minimum volume standards did not differentiate hospitals based on mortality for 3 of the 4 high-risk cancer operations assessed, and few hospitals were able to meet these standards. These findings highlight important tradeoffs between setting effective volume thresholds and practical expectations for hospital adherence and patient access to centers that meet those standards.

INTRODUCTION:Surgery accounts for almost half of inpatient spending, much of which is concentrated in a subset of high-cost patients. To study the effects of surgeon and hospital characteristics on surgical expenditures, a way to adjust for patient characteristics is essential. DESIGN:Using 100% Medicare claims data, we identified patients aged 66-99 undergoing elective inpatient surgery (coronary artery bypass grafting, colectomy, and total hip/knee replacement) in 2014. We calculated price-standardized Medicare payments for the surgical episode from admission through 30 days after discharge (episode payments). On the basis of predictor variables from 2013, that is, Elixhauser comorbidities, hierarchical condition categories, Medicare's Chronic Conditions Warehouse (CCW), and total spending, we constructed models to predict the costs of surgical episodes in 2014. RESULTS:All sources of comorbidity data performed well in predicting the costliest cases (Spearman correlation 0.86-0.98). Models on the basis of hierarchical condition categories had slightly superior performance. The costliest quintile of patients as predicted by the model captured 35%-45% of the patients in each procedure's actual costliest quintile. For example, in hip replacement, 44% of the costliest quintile was predicted by the model's costliest quintile. CONCLUSIONS:A significant proportion of surgical spending can be predicted using patient factors on the basis of readily available claims data. By adjusting for patient factors, this will facilitate future research on unwarranted variation in episode payments driven by surgeons, hospitals, or other market forces.

The Hospital Readmissions Reduction Program, announced in 2010 to penalize excess readmissions for patients with selected medical diagnoses, was expanded in 2013 to include targeted surgical diagnoses, beginning with hip and knee replacements. Whether these surgical penalties reduced procedure-specific readmissions is not well understood. Using Medicare claims, we evaluated the penalty announcements' effects on risk-adjusted readmission rates, episode payments, lengths-of-stay, and observation status use. Risk-adjusted readmission rates declined for both procedures from 7.6 percent in 2008 to 5.5 percent in 2016. These rates were decreasing before the program was announced, but the rate of reductions doubled after the announcement of medical penalties in March 2010 (from -0.05 percentage points to -0.10 percentage points per quarter). After targeted surgical penalties were announced in August 2013, readmission reductions returned to near the baseline trend. During the same time period, mean episode payments and lengths-of-stay decreased substantially, and trends in observation status were unchanged. This suggests that medical readmission penalties led to readmission reductions for surgical patients as well, that targeted surgical penalties did not have an additional effect, and that readmission reductions are approaching a "floor" below which further reductions may be unlikely.

Calls to repeal the Affordable Care Act (ACA) have become increasingly frequent. Most attempts to repeal the ACA have targeted specific policies rather than the ACA as a whole. This article describes the specific policies under debate and the ramifications of repealing each of them. Specific attention is given to insurance coverage, individual premiums, and budgetary impact. Based on the literature regarding the ACA's impact to date, the impact of ACA repeal on Surgical oncology care is predicted.

OBJECTIVE:To identify pre-operative risk factors predicting complications following adenotonsillectomy in children with severe OSA. METHODS:Retrospective chart review in an academic tertiary care center. Children with symptoms of OSA with overnight polysomnography (PSG) revealing apnea-hypopnea index (AHI) >10, who underwent adenotonsillectomy with overnight postoperative observation between 2008 and 2012. Univariate logistic regression was used to assess odds ratio (OR) of individual risk factors versus postoperative complications such as overnight desaturations <90%, length of stay (LOS)>24 h, supplemental oxygen requirement, and transfer to a higher level of care. RESULTS:All patients (n=157) with severe OSA were observed overnight. Mean age was 5.3±3.7 years. Twenty-five (15.9%) patients had LOS>24 h. Forty-two (26.8%) had overnight desaturations <90%. AHI ≥15 and O2 saturation nadir <80% on preop polysomnography (PSG) were independent predictors of post-op O2 saturation <90% and LOS>24 h. (p<0.05). PSG minimum saturation <80% was the strongest predictor of all variables examined with an OR of 6.98 (3.15-15.48, 95% CI) for desaturation <90% and 5.19 (2.11-12.75, 95% CI) for LOS>24 h. Preop PSG O2 saturation<90% predicted overnight post op oxygen requirement with an OR of 3.38 (1.39-8.25, 95%CI). CONCLUSIONS:Preoperative polysomnography yields significant independent predictors of post-op complications in children with OSA. While AHI is a significant independent predictor, minimum O2 saturation on preop PSG appeared the strongest predictor when <80%. Patients with these risk factors, especially low O2 on PSG, warrant overnight observation with continuous pulse oximetry.