Literature DB >> 25723845

Improved Surgical Outcomes for ACS NSQIP Hospitals Over Time: Evaluation of Hospital Cohorts With up to 8 Years of Participation.

Mark E Cohen1, Yaoming Liu, Clifford Y Ko, Bruce L Hall.   

Abstract

BACKGROUND: The American College of Surgeons, National Surgical Quality Improvement Program (ACS NSQIP) surgical quality feedback models are recalibrated every 6 months, and each hospital is given risk-adjusted, hierarchical model, odds ratios that permit comparison to an estimated average NSQIP hospital at a particular point in time. This approach is appropriate for "relative" benchmarking, and for targeting quality improvement efforts, but does not permit evaluation of hospital or program-wide changes in quality over time. We report on long-term improvement in surgical outcomes associated with participation in ACS NSQIP. STUDY
DESIGN: ACS NSQIP data (2006-2013) were used to create prediction models for mortality, morbidity (any of several distinct adverse outcomes), and surgical site infection (SSI). For each model, for each hospital, and for year of first participation (hospital cohort), hierarchical model observed/expected (O/E) ratios were computed. The primary performance metric was the within-hospital trend in logged O/E ratios over time (slope) for mortality, morbidity, and SSI.
RESULTS: Hospital-averaged log O/E ratio slopes were generally negative, indicating improving performance over time. For all hospitals, 62%, 70%, and 65% of hospitals had negative slopes for mortality, morbidity, and any SSI, respectively. For hospitals currently in the program for at least 3 years, 69%, 79%, and 71% showed improvement in mortality, morbidity, and SSI, respectively. For these hospitals, we estimate 0.8%, 3.1%, and 2.6% annual reductions (with respect to prior year's rates) for mortality, morbidity, and SSI, respectively.
CONCLUSIONS: Participation in ACS NSQIP is associated with reductions in adverse events after surgery. The magnitude of quality improvement increases with time in the program.

Entities:  

Mesh:

Year:  2016        PMID: 25723845     DOI: 10.1097/SLA.0000000000001192

Source DB:  PubMed          Journal:  Ann Surg        ISSN: 0003-4932            Impact factor:   12.969


  44 in total

1.  Comparison of observed to predicted outcomes using the ACS NSQIP risk calculator in patients undergoing pancreaticoduodenectomy.

Authors:  Harveshp D Mogal; Nora Fino; Clancy Clark; Perry Shen
Journal:  J Surg Oncol       Date:  2016-05-04       Impact factor: 3.454

2.  Derivation, Validation and Application of a Pragmatic Risk Prediction Index for Benchmarking of Surgical Outcomes.

Authors:  Richard T Spence; David C Chang; Haytham M A Kaafarani; Eugenio Panieri; Geoffrey A Anderson; Matthew M Hutter
Journal:  World J Surg       Date:  2018-02       Impact factor: 3.352

Review 3.  Surgical research using national databases.

Authors:  Ram K Alluri; Hyuma Leland; Nathanael Heckmann
Journal:  Ann Transl Med       Date:  2016-10

4.  An Online Tool for Global Benchmarking of Risk-Adjusted Surgical Outcomes.

Authors:  Richard T Spence; David C Chang; Kathryn Chu; Eugenio Panieri; Jessica L Mueller; Matthew M Hutter
Journal:  World J Surg       Date:  2017-01       Impact factor: 3.352

5.  Evaluation of Postoperative Functional Health Status Decline Among Older Adults.

Authors:  Lindsey M Zhang; Melissa A Hornor; Thomas Robinson; Ronnie A Rosenthal; Clifford Y Ko; Marcia M Russell
Journal:  JAMA Surg       Date:  2020-10-01       Impact factor: 14.766

6.  Can surgical site infections be reduced with the adoption of a bundle of simultaneous initiatives? The use of NSQIP incidence data to follow multiple quality improvement interventions.

Authors:  Duncan Rozario
Journal:  Can J Surg       Date:  2018-02       Impact factor: 2.089

Review 7.  Perioperative Information Systems: Opportunities to Improve Delivery of Care and Clinical Outcomes in Cardiac and Vascular Surgery.

Authors:  Robert E Freundlich; Jesse M Ehrenfeld
Journal:  J Cardiothorac Vasc Anesth       Date:  2017-11-04       Impact factor: 2.628

8.  A Novel Model Demonstrates Variation in Risk-Adjusted Mortality Across Pediatric Cardiac ICUs After Surgery.

Authors:  Sarah Tabbutt; Jennifer Schuette; Wenying Zhang; Jeffrey Alten; Janet Donohue; J William Gaynor; Nancy Ghanayem; Jeffrey Jacobs; Sara K Pasquali; Ravi Thiagarajan; Justin B Dimick; Mousumi Banerjee; David Cooper; Michael Gaies
Journal:  Pediatr Crit Care Med       Date:  2019-02       Impact factor: 3.624

9.  Patient selection and perioperative outcomes are similar between targeted and nontargeted hospitals (in the National Surgical Quality Improvement Program) for abdominal aortic aneurysm repair.

Authors:  Peter A Soden; Sara L Zettervall; Klaas H J Ultee; Jeremy D Darling; John C McCallum; Allen D Hamdan; Mark C Wyers; Marc L Schermerhorn
Journal:  J Vasc Surg       Date:  2016-07-25       Impact factor: 4.268

10.  Risk factors for unplanned readmission within 30 days after pediatric neurosurgery: a nationwide analysis of 9799 procedures from the American College of Surgeons National Surgical Quality Improvement Program.

Authors:  Brandon A Sherrod; James M Johnston; Brandon G Rocque
Journal:  J Neurosurg Pediatr       Date:  2016-05-17       Impact factor: 2.375

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