Dataset Information

Effect of wound classification on risk adjustment in American College of Surgeons NSQIP.

ABSTRACT: Surgical wound classification has been used in risk-adjustment models. However, it can be subjective and could potentially improperly bias hospital quality comparisons. The objective is to examine the effect of wound classification on hospital performance risk-adjustment models.Retrospective review of the 2011 American College of Surgeons NSQIP database was conducted for the following wound classification categories: clean, clean-contaminated, contaminated, and dirty-infected. To assess the influence of wound classification on risk adjustment, 2 models were developed for all outcomes: 1 including and 1 excluding wound classification. For each model, hospital postoperative complications were estimated using hierarchical multivariable regression methods. Absolute changes in hospital rank, correlations of odds ratios, and outlier status agreement between models were examined.Of the 442,149 cases performed in 315 hospitals: 53.6% were classified as clean; 34.2% as clean-contaminated; 6.7% as contaminated; and 5.5% as dirty-infected. The surgical site infection rate was highest in dirty-infected (8.5%) and lowest in clean (1.8%) cases. For overall surgical site infection, the absolute change in risk-adjusted hospital performance rank between models, including vs excluding wound classification, was minimal (mean 4.5 of 315 positions). The correlations between odds ratios of the 2 performance models were nearly perfect (R = 0.9976, p < 0.0001), and outlier status agreement was excellent (? = 0.95ss08, p < 0.0001). Similar findings were observed in models of subgroups of surgical site infections and other postoperative outcomes.In circumstances where alternate information is available for risk adjustment, there appear to be minimal differences in performance models that include vs exclude wound classification. Therefore, the American College of Surgeons NSQIP is critically evaluating the continued use of wound classification in hospital performance risk-adjustment models.

SUBMITTER: Ju MH

PROVIDER: S-EPMC4143469 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

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Effect of wound classification on risk adjustment in American College of Surgeons NSQIP.

Ju Mila H MH Cohen Mark E ME Bilimoria Karl Y KY Latus Melissa S MS Scholl Lisa M LM Schwab Bradley J BJ Byrd Claudia M CM Ko Clifford Y CY Dellinger E Patchen EP Hall Bruce L BL

Journal of the American College of Surgeons 20140510 3

<h4>Background</h4>Surgical wound classification has been used in risk-adjustment models. However, it can be subjective and could potentially improperly bias hospital quality comparisons. The objective is to examine the effect of wound classification on hospital performance risk-adjustment models.<h4>Study design</h4>Retrospective review of the 2011 American College of Surgeons NSQIP database was conducted for the following wound classification categories: clean, clean-contaminated, contaminated ...[more]

PMID: 25053222

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Project description:BACKGROUND:In October 2012, The Centers for Medicare and Medicaid Services (CMS) began publicly reporting American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) surgical outcomes on its public reporting website, Hospital Compare. Participation in this CMS-NSQIP initiative is voluntary. Our objective was to compare CMS-NSQIP participating hospitals with ACS NSQIP hospitals that elected not to participate. STUDY DESIGN:Hospital Compare and American Hospital Association Annual Survey data were merged to compare CMS-NSQIP participants with nonparticipants. Regression models were developed to assess predictors of participation and to assess if hospitals differed on 32 process, 10 patient experience (Hospital Consumer Assessment of HealthCare Providers and Systems [HCAHPS]), and 16 outcomes (Hospital Compare and Agency for Healthcare Research Quality) measures. Additionally, performance on 2 waves of publicly reported ACS NSQIP surgical outcomes measures was compared. RESULTS:Of the 452 ACS NSQIP hospitals, 80 (18%) participated in CMS-NSQIP public reporting. Participating hospitals had more beds, admissions, operations, and were more often accredited (Commission on Cancer and the Council of Teaching Hospitals [COTH] [p < 0.05]). Only COTH membership remained significant in adjusted analyses (odds ratio 2.45, 95% CI 1.12 to 5.35). Hospital performance on process, HCAHPS, and outcomes measures were not associated with CMS-NSQIP participation for 54 of 58 measures examined. Hospitals with "better-than-average" performance were more likely to publicly report the Elderly Surgery measure (p < 0.05). In wave 2, an increased proportion of new participants reported "worse-than-average" outcomes. CONCLUSIONS:There were few measurable differences between CMS-NSQIP participating and nonparticipating hospitals. The decision to voluntarily publicly report may be related to the hospital's culture of quality improvement and transparency.

Project description:OBJECTIVES:The aim of this study was to develop and validate a risk adjustment model for 30-day mortality after transcatheter aortic valve replacement (TAVR) that accounted for both standard clinical factors and pre-procedural health status and frailty. BACKGROUND:Assessment of risk for TAVR is important both for patient selection and provider comparisons. Prior efforts for risk adjustment have focused on in-hospital mortality, which is easily obtainable but can be biased because of early discharge of ill patients. METHODS:Using data from patients who underwent TAVR as part of the Society of Thoracic Surgeons/American College of Cardiology TVT (Transcatheter Valve Therapy) Registry (June 2013 to May 2016), a hierarchical logistic regression model to estimate risk for 30-day mortality after TAVR based only on pre-procedural factors and access site was developed and internally validated. The model included factors from the original TVT Registry in-hospital mortality model but added the Kansas City Cardiomyopathy Questionnaire (health status) and gait speed (5-m walk test). RESULTS:Among 21,661 TAVR patients at 188 sites, 1,025 (4.7%) died within 30 days. Independent predictors of 30-day death included older age, low body weight, worse renal function, peripheral artery disease, home oxygen, prior myocardial infarction, left main coronary artery disease, tricuspid regurgitation, nonfemoral access, worse baseline health status, and inability to walk. The predicted 30-day mortality risk ranged from 1.1% (lowest decile of risk) to 13.8% (highest decile of risk). The model was able to stratify risk on the basis of patient factors with good discrimination (C = 0.71 [derivation], C = 0.70 [split-sample validation]) and excellent calibration, both overall and in key patient subgroups. CONCLUSIONS:A clinical risk model was developed for 30-day death after TAVR that included clinical data as well as health status and frailty. This model will facilitate tracking outcomes over time as TAVR expands to lower risk patients and to less experienced sites and will allow an objective comparison of short-term mortality rates across centers.

Project description:BackgroundGiven the rarity of pediatric surgical disease, it is important to consider available large-scale data resources as a means to better study and understand relevant disease-processes and their treatments. The Military Health System Data Repository (MDR) includes claims-based information for > 3 million pediatric patients who are dependents of members and retirees of the United States Armed Services, but has not been externally validated. We hypothesized that demographics and selected outcome metrics would be similar between MDR and the previously validated American College of Surgeons National Surgical Quality Improvement Program-Pediatric (NSQIP-P) for several common pediatric surgical operations.MethodsWe selected five commonly performed pediatric surgical operations: appendectomy, pyeloplasty, pyloromyotomy, spinal arthrodesis for scoliosis, and facial reconstruction for cleft palate. Among children who underwent these operations, we compared demographics (age, sex, and race) and clinical outcomes (length of hospital stay [LOS] and mortality) in the MDR and NSQIP-P, including all available overlapping years (2012-2014).ResultsAge, sex, and race were generally similar between the NSQIP-P and MDR. Specifically, these demographics were generally similar between the resources for appendectomy (NSQIP-P, n = 20,602 vs. MDR, n = 4363; median age 11 vs. 12 years; female 40% vs. 41%; white 75% vs. 84%), pyeloplasty (NSQIP-P, n = 786 vs. MDR, n = 112; median age 0.9 vs. 2 years; female 28% vs. 28%; white 71% vs. 80%), pyloromyotomy, (NSQIP-P, n = 3827 vs. MDR, n = 227; median age 34 vs. < 1 year, female 17% vs. 16%; white 76% vs. 89%), scoliosis surgery (NSQIP-P, n = 5743 vs. MDR, n = 95; median age 14.2 vs. 14 years; female 75% vs. 67%; white 72% vs. 75%), and cleft lip/palate repair (NSQIP-P, n = 6202 vs. MDR, n = 749; median age, 1 vs. 1 year; female 42% vs. 45%; white 69% vs. 84%). Length of stay and 30-day mortality were similar between resources. LOS and 30-day mortality were also similar between datasets.ConclusionFor the selected common pediatric surgical operations, patients included in the MDR were comparable to those included in the validated NSQIP-P. The MDR may comprise a valuable clinical outcomes research resource, especially for studying infrequent diseases with follow-up beyond the 30-day peri-operative period.

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Effect of wound classification on risk adjustment in American College of Surgeons NSQIP.

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Effect of wound classification on risk adjustment in American College of Surgeons NSQIP.

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