Correlation of perioperative risk scores with hospital costs in neurosurgical patients

2020 ◽  
Vol 132 (3) ◽  
pp. 818-824
Author(s):  
Sasha Vaziri ◽  
Joseph M. Abbatematteo ◽  
Max S. Fleisher ◽  
Alexander B. Dru ◽  
Dennis T. Lockney ◽  
...  

OBJECTIVEThe American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) online surgical risk calculator uses inherent patient characteristics to provide predictive risk scores for adverse postoperative events. The purpose of this study was to determine if predicted perioperative risk scores correlate with actual hospital costs.METHODSA single-center retrospective review of 1005 neurosurgical patients treated between September 1, 2011, and December 31, 2014, was performed. Individual patient characteristics were entered into the NSQIP calculator. Predicted risk scores were compared with actual in-hospital costs obtained from a billing database. Correlational statistics were used to determine if patients with higher risk scores were associated with increased in-hospital costs.RESULTSThe Pearson correlation coefficient (R) was used to assess the correlation between 11 types of predicted complication risk scores and 5 types of encounter costs from 1005 health encounters involving neurosurgical procedures. Risk scores in categories such as any complication, serious complication, pneumonia, cardiac complication, surgical site infection, urinary tract infection, venous thromboembolism, renal failure, return to operating room, death, and discharge to nursing home or rehabilitation facility were obtained. Patients with higher predicted risk scores in all measures except surgical site infection were found to have a statistically significant association with increased actual in-hospital costs (p < 0.0005).CONCLUSIONSPrevious work has demonstrated that the ACS NSQIP surgical risk calculator can accurately predict mortality after neurosurgery but is poorly predictive of other potential adverse events and clinical outcomes. However, this study demonstrates that predicted high-risk patients identified by the ACS NSQIP surgical risk calculator have a statistically significant moderate correlation to increased actual in-hospital costs. The NSQIP calculator may not accurately predict the occurrence of surgical complications (as demonstrated previously), but future iterations of the ACS universal risk calculator may be effective in predicting actual in-hospital costs, which could be advantageous in the current value-based healthcare environment.

2018 ◽  
Vol 128 (3) ◽  
pp. 942-947 ◽  
Author(s):  
Sasha Vaziri ◽  
Jacob Wilson ◽  
Joseph Abbatematteo ◽  
Paul Kubilis ◽  
Saptarshi Chakraborty ◽  
...  

OBJECTIVEThe American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) universal Surgical Risk Calculator is an online decision-support tool that uses patient characteristics to estimate the risk of adverse postoperative events. Further validation of this risk calculator in the neurosurgical population is needed; therefore, the object of this study was to assess the predictive performance of the ACS NSQIP Surgical Risk Calculator in neurosurgical patients treated at a tertiary care center.METHODSA single-center retrospective review of 1006 neurosurgical patients treated in the period from September 2011 through December 2014 was performed. Individual patient characteristics were entered into the NSQIP calculator. Predicted complications were compared with actual occurrences identified through chart review and administrative quality coding data. Statistical models were used to assess the predictive performance of risk scores. Traditionally, an ideal risk prediction model demonstrates good calibration and strong discrimination when comparing predicted and observed events.RESULTSThe ACS NSQIP risk calculator demonstrated good calibration between predicted and observed risks of death (p = 0.102), surgical site infection (SSI; p = 0.099), and venous thromboembolism (VTE; p = 0.164) Alternatively, the risk calculator demonstrated a statistically significant lack of calibration between predicted and observed risk of pneumonia (p = 0.044), urinary tract infection (UTI; p < 0.001), return to the operating room (p < 0.001), and discharge to a rehabilitation or nursing facility (p < 0.001). The discriminative performance of the risk calculator was assessed using the c-statistic. Death (c-statistic 0.93), UTI (0.846), and pneumonia (0.862) demonstrated strong discriminative performance. Discharge to a rehabilitation facility or nursing home (c-statistic 0.794) and VTE (0.767) showed adequate discrimination. Return to the operating room (c-statistic 0.452) and SSI (0.556) demonstrated poor discriminative performance. The risk prediction model was both well calibrated and discriminative only for 30-day mortality.CONCLUSIONSThis study illustrates the importance of validating universal risk calculators in specialty-specific surgical populations. The ACS NSQIP Surgical Risk Calculator could be used as a decision-support tool for neurosurgical informed consent with respect to predicted mortality but was poorly predictive of other potential adverse events and clinical outcomes.


2020 ◽  
Vol 86 (8) ◽  
pp. 958-964
Author(s):  
Alexander S. Rosemurgy ◽  
Kenneth Luberice ◽  
Emily Krill ◽  
Miguel Castro ◽  
Gabriel Rivera Espineira ◽  
...  

Introduction This study was undertaken to examine 100 consecutive robotic distal pancreatectomies with splenectomies, and to compare our outcomes to predicted outcomes as calculated using the American college of surgeons national surgical quality improvement program (ACS NSQIP) Surgical Risk Calculator and to the outcomes contained within NSQIP. Methods Outcomes were compared with predicted outcomes, calculated using the ACS NSQIP Surgical Risk Calculator, and with outcomes documented in NSQIP for distal pancreatectomy. For illustrative purposes, data are presented as median (mean ± SD). Results Patients who underwent robotic distal pancreatectomy were of age 67 (63 ± 13.4) years with a BMI of 29 (29 ± 6.3) kg/m2, with 49% being women. Operative duration was 242 (265 ± 112.2) minutes and estimated blood loss was 110 (211 ± 233.9) mL. Predicted outcomes were similar to those reported in NSQIP. Our actual outcomes were significantly superior to the predicted outcomes for serious complication, any complication, surgical site infection, sepsis, and length of stay. Compared to NSQIP outcomes, our actual outcomes for serious complication, any complication, surgical site infection, sepsis, and delayed gastric emptying were significantly superior. Twelve percent of operations were converted to “open.” There were 3 deaths within 30 days, similar to predicted outcomes. Deaths were due to sepsis (2) and respiratory failure (1). Conclusion Our patients’ predicted outcomes were the same as national outcomes; our patients were not a select group. However, their actual outcomes were like or significantly superior than those predicted by NSQIP or reported in NSQIP. We believe that the robot has the future of distal pancreatectomy with or without splenectomy.


2020 ◽  
Vol 86 (2) ◽  
pp. 83-89
Author(s):  
Andrea M. Long ◽  
Amy N. Hildreth ◽  
Patrick T. Davis ◽  
Rebecca Ur ◽  
Ashley T. Badger ◽  
...  

The ACS NSQIP Surgical Risk Calculator is designed to estimate the chance of an unfavorable outcome after surgery. Our goal was to evaluate the accuracy of the calculator in our emergency general surgery population. Surgical outcomes were compared to predicted risk. The risk was calculated with surgeon adjustment scores (SASs) of 1 (no adjustment), 2 (risk somewhat higher), and 3 (risk significantly higher than estimate). Two hundred and twenty-seven patients met the inclusion criteria. An SAS of 1 or 2 accurately predicted risk of mortality (5.7% and 8.5% predicted versus 7.9% actual), whereas a risk adjustment of 3 indicated significant overestimation of mortality rate (14.8% predicted). There was good overall prediction performance for most variables with no clear preference for SAS 1, 2, or 3. Poor correlation was seen with SSI, urinary tract infection, and length of stay variables. The ACS NSQIP Surgical Risk Calculator yields valid predictions in the emergency general surgery population, and the data support its use to inform conversations about outcome expectations.


2020 ◽  
Vol 41 (S1) ◽  
pp. s157-s157
Author(s):  
Kelly Baekyung Choi ◽  
John Conly ◽  
Blanda Chow ◽  
Joanne Embree ◽  
Bonita Lee ◽  
...  

Background: Surgical site infection (SSI) after cerebrospinal fluids (CSF) shunt surgery is thought to be acquired intraoperatively. Biomaterial-associated infection can present up to 1 year after surgery, but many national systems have shortened follow-up to 90 days. We compared 3- versus 12-month follow-up periods to determine the nature of case ascertainment in the 2 periods. Methods: Participants of any age with placement of an internal CSF shunt or revision surgical manipulation of an existing internal shunt identified in the Canadian Nosocomial Infection Surveillance Program (CNISP) participating hospitals between 2006 and 2018 were eligible. We excluded patients with external shunting devices or culture-positive CSF at the time of surgery. Patients were followed for 12 months after surgery for the primary outcome of a CSF infection with a positive CSF culture by review of laboratory and health records. Patients were categorized as adult (aged ≥18 years) or pediatric (aged < 18 years). The infection rate was expressed as the number of CSF shunt-associated infections divided by the number of shunt surgeries per 100 procedures. Results: In total, 325 patients (53% female) met inclusion criteria in 14 hospitals from 7 provinces were identified. Overall, 46.1% of surgeries were shunt revisions and 90.3% of shunts were ventriculoperitoneal. For pediatric patients, the median age was 0.7 years (IQR, 0.2–7.0). For adult patients, the median age was 47.9 years (IQR, 29.6–64.6). The SSI rates per 100 procedures were 3.69 for adults and 3.65 for pediatrics. The overall SSI rates per 100 procedures at 3 and 12 months were 2.74 (n = 265) and 3.48 (n = 323), respectively. By 3 months (90 days), 82% of infection cases were identified (Fig. 1). The median time from procedure to SSI detection was 30 days (IQR, 10–65). No difference was found in the microbiology of the shunt infections at 3- and 12-month follow-ups. The most common pathogens were coagulase-negative Staphylococcus (43.6 %), followed by S. aureus (24.8 %) and Propionibacterium spp (6.5 %). No differences in age distribution, gender, surgery type (new or revision), shunt type, or infecting organisms were observed when 3- and 12-month periods were compared. Conclusions: CSF-SSI surveillance for 3 versus 12 months would capture 82.0% (95% CI, 77.5–86.0) of cases, with no significant differences in the patient characteristics, surgery types, or pathogens. A 3-month follow-up can reduce resources and allow for more timely reporting of infection rates.Funding: NoneDisclosures: None


2021 ◽  
Vol 12 (8) ◽  
pp. S67
Author(s):  
H. Van der Hulst ◽  
J.W.T. Dekker ◽  
E. Bastiaannet ◽  
J. van der Bol ◽  
F. van den Bos ◽  
...  

Author(s):  
Neel P. Chudgar ◽  
Shi Yan ◽  
Meier Hsu ◽  
Kay See Tan ◽  
Katherine D. Gray ◽  
...  

HPB ◽  
2017 ◽  
Vol 19 (2) ◽  
pp. 147-153 ◽  
Author(s):  
Brian M. Cusworth ◽  
Bradley A. Krasnick ◽  
Timothy M. Nywening ◽  
Cheryl A. Woolsey ◽  
Ryan C. Fields ◽  
...  

HPB ◽  
2016 ◽  
Vol 18 ◽  
pp. e157 ◽  
Author(s):  
S. Madhavan ◽  
S.-L. Soong ◽  
S. Vishalkumar ◽  
W.W.L. Woon ◽  
J.K. Low ◽  
...  

2016 ◽  
Vol 8 (1) ◽  
pp. 7-12 ◽  
Author(s):  
Anthony A. Sochet ◽  
Alexander M. Cartron ◽  
Aoibhinn Nyhan ◽  
Michael C. Spaeder ◽  
Xiaoyan Song ◽  
...  

Background: Surgical site infection (SSI) occurs in 0.25% to 6% of children after cardiothoracic surgery (CTS). There are no published data regarding the financial impact of SSI after pediatric CTS. We sought to determine the attributable hospital cost and length of stay associated with SSI in children after CTS. Methods: We performed a retrospective, matched cohort study in a 26-bed cardiac intensive care unit (CICU) from January 2010 through December 2013. Cases with SSI were identified retrospectively and individually matched to controls 2:1 by age, gender, Risk Adjustment for Congenital Heart Surgery score, Society of Thoracic Surgeons–European Association for Cardiothoracic Surgery category, and primary cardiac diagnosis and procedure. Results: Of the 981 cases performed during the study period, 12 with SSI were identified. There were no differences in demographics, clinical characteristics, or intraoperative data. Median total hospital costs were higher in participants with SSI as compared to controls (US$219,573 vs US$82,623, P < .01). Children with SSI had longer median CICU length of stay (9 vs 3 days, P < .01), hospital length of stay (18 vs 8.5 days, P < .01), and duration of mechanical ventilation (2 vs 1 day, P < .01) and vasoactive administration (4.5 vs 1 day, P < .01). Conclusions: Children with SSI after CTS have an associated increase in hospital costs of US$136,950/case and hospital length of stay of 9.5 days/case. The economic burden posed by SSI stress the importance of infection control surveillance, exhaustive preventative measures, and identification of modifiable risk factors.


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