Effect of Present at Time of Surgery on Unadjusted and Risk-Adjusted Postoperative Complication Rate.

BACKGROUND: Present at the time of surgery (PATOS) is an important measure to collect in postoperative complication surveillance systems because it may affect a patient's risk of a subsequent complication and the estimation of postoperative complication rates attributed to the healthcare system. The American College of Surgeons (ACS) NSQIP started collecting PATOS data for 8 postoperative complications in 2011, but no one has used these data to quantify how this may affect unadjusted and risk-adjusted postoperative complication rates. STUDY DESIGN: This study was a retrospective observational study of the ACS NSQIP database from 2012 to 2018. PATOS data were analyzed for the 8 postoperative complications of superficial, deep, and organ space surgical site infection; pneumonia; urinary tract infection; ventilator dependence; sepsis; and septic shock. Unadjusted postoperative complication rates were compared ignoring PATOS vs taking PATOS into account. Observed to expected ratios over time were also compared by calculating expected values using multiple logistic regression analyses with complication as the dependent variable and the 28 nonlaboratory preoperative variables in the ACS NSQIP database as the independent variables. RESULTS: In 5,777,108 patients, observed event rates for each outcome were reduced by between 6.1% (superficial surgical site infection) and 52.5% (sepsis) when PATOS was taken into account. The observed to expected ratios were similar each year for all outcomes, except for sepsis and septic shock in the early years. CONCLUSIONS: Taking PATOS into account is important for reporting unadjusted event rates. The effect varied by type of complication-lowest for superficial surgical site infection and highest for sepsis and septic shock. Taking PATOS into account was less important for risk-adjusted outcomes (observed to expected ratios), except for sepsis and septic shock.

Relationships between predischarge and postdischarge infectious complications, length of stay, and unplanned readmissions in the ACS NSQIP database.

BACKGROUND: Postoperative complications, length of index hospital stay, and unplanned hospital readmissions are important metrics reflecting surgical care quality. Postoperative infections represent a substantial proportion of all postoperative complications. We examined the relationships between identification of postoperative infection prehospital and posthospital discharge, length of stay, and unplanned readmissions in the American College of Surgeons National Surgical Quality Improvement Program database across nine surgical specialties. METHODS: The 30-day postoperative infectious complications including sepsis, surgical site infections, pneumonia, and urinary tract infection were analyzed in the American College of Surgeons National Surgical Quality Improvement Program inpatient data during the period from 2012 to 2017. General, gynecologic, vascular, orthopedic, otolaryngology, plastic, thoracic, urologic, and neurosurgical inpatient operations were selected. RESULTS: Postoperative infectious complications were identified in 5.2% (137,014/2,620,450) of cases; 81,929 (59.8%) were postdischarge. The percentage of specific complications identified postdischarge were 73.4% of surgical site infections (range across specialties 63.7-93.1%); 34.9% of sepsis cases (27.4-58.1%); 26.5% of pneumonia cases (18.9%-36.3%); and 53.2% of urinary tract infections (48.3%-88.0%). The relative risk of readmission among patients with postdischarge versus predischarge surgical site infection, sepsis, pneumonia, or urinary tract infection was 5.13 (95% confidence interval: 4.90-5.37), 9.63 (8.93-10.40), 10.79 (10.15-11.45), and 3.32 (3.07-3.60), respectively. Over time, mean length of stay decreased but postdischarge infections and readmission rates significantly increased. CONCLUSION: Most postoperative infectious complications were diagnosed postdischarge. These were associated with an increased risk of readmission. The trend toward shorter length of stay over time was observed along with an increase both in the percentage of infections detected after discharge and the rate of unplanned related postoperative readmissions over time. Postoperative surveillance of infections should extend beyond hospital discharge of surgical patients.

Use of Surgical Risk Preoperative Assessment System (SURPAS) and Patient Satisfaction During Informed Consent for Surgery.

BACKGROUND: The objective of this study was to determine the effects of using the Surgical Risk Preoperative Assessment System (SURPAS) on patient satisfaction and surgeon efficiency in the surgical informed consent process, as compared to surgeons' "usual" consent process. STUDY DESIGN: Patient perception of the consent process was assessed via survey in 2 cohorts: 10 surgeons in different specialties used their "usual" consent process for 10 patients; these surgeons were then taught to use SURPAS, and they used it during the informed consent process of 10 additional patients. The data were compared using Fisher's exact test and the Cochran-Mantel-Haenszel test. RESULTS: One hundred patients underwent the "usual" consent process (USUAL), and 93 underwent SURPAS-guided consent (SURPAS). Eighty-two percent of SURPAS were "very satisfied" and 18% were "satisfied" with risk discussion vs 16% and 72% of USUAL, respectively. Of those who used SURPAS, 75.3% reported the risk discussion made them "more comfortable" with surgery vs 19% of USUAL, and 90.3% of SURPAS users reported "somewhat" or "greatly decreased" anxiety vs 20% of USUAL. All p values were <0.0001. Among SURPAS patients, 97.9% reported "enough time spent discussing risks" vs 72.0% of USUAL patients. CONCLUSIONS: The SURPAS tool improved the informed consent process for patients compared with the "usual" consent process, in terms of patient satisfaction, ie making patients feel more comfortable and less anxious about their impending operations. Providers should consider integrating the SURPAS tool into their preoperative consent process.

Accurate Preoperative Prediction of Discharge Destination Using 8 Predictor Variables: A NSQIP Analysis.

BACKGROUND: With inpatient length of stay decreasing, discharge destination after surgery can serve as an important metric for quality of care. Additionally, patients desire information on possible discharge destination. Adequate planning requires a multidisciplinary approach, can reduce healthcare costs and ensure patient needs are met. The Surgical Risk Preoperative Assessment System (SURPAS) is a parsimonious risk assessment tool using 8 predictor variables developed from the American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) dataset. SURPAS is applicable to more than 3,000 operations in adults in 9 surgical specialties, predicts important adverse outcomes, and is incorporated into our electronic health record. We sought to determine whether SURPAS can accurately predict discharge destination. STUDY DESIGN: A "full model" for risk of postoperative "discharge not to home" was developed from 28 nonlaboratory preoperative variables from ACS NSQIP 2012-2017 dataset using logistic regression. This was compared with the 8-variable SURPAS model using the C index as a measure of discrimination, the Hosmer-Lemeshow observed-to-expected plots testing calibration, and the Brier score, a combined metric of discrimination and calibration. RESULTS: Of 5,303,519 patients, 447,153 (8.67%) experienced a discharge not to home. The SURPAS model's C index, 0.914, was 99.24% of that of the full model's (0.921); the Hosmer-Lemeshow plots indicated good calibration and the Brier score was 0.0537 and 0.0514 for the SUPAS and full model, respectively. CONCLUSIONS: The 8-variable SURPAS model preoperatively predicts risk of postoperative discharge to a destination other than home as accurately as the 28 nonlaboratory variable ACS NSQIP full model. Therefore, discharge destination can be integrated into the existing SURPAS tool, providing accurate outcomes to guide decision-making and help prepare patients for their postoperative recovery.