Literature DB >> 19797283

Variation in hospital mortality associated with inpatient surgery.

Amir A Ghaferi1, John D Birkmeyer, Justin B Dimick.   

Abstract

BACKGROUND: Hospital mortality that is associated with inpatient surgery varies widely. Reducing rates of postoperative complications, the current focus of payers and regulators, may be one approach to reducing mortality. However, effective management of complications once they have occurred may be equally important.
METHODS: We studied 84,730 patients who had undergone inpatient general and vascular surgery from 2005 through 2007, using data from the American College of Surgeons National Surgical Quality Improvement Program. We first ranked hospitals according to their risk-adjusted overall rate of death and divided them into five groups. For hospitals in each overall mortality quintile, we then assessed the incidence of overall and major complications and the rate of death among patients with major complications.
RESULTS: Rates of death varied widely across hospital quintiles, from 3.5% in very-low-mortality hospitals to 6.9% in very-high-mortality hospitals. Hospitals with either very high mortality or very low mortality had similar rates of overall complications (24.6% and 26.9%, respectively) and of major complications (18.2% and 16.2%, respectively). Rates of individual complications did not vary significantly across hospital mortality quintiles. In contrast, mortality in patients with major complications was almost twice as high in hospitals with very high overall mortality as in those with very low overall mortality (21.4% vs. 12.5%, P<0.001). Differences in rates of death among patients with major complications were also the primary determinant of variation in overall mortality with individual operations.
CONCLUSIONS: In addition to efforts aimed at avoiding complications in the first place, reducing mortality associated with inpatient surgery will require greater attention to the timely recognition and management of complications once they occur. 2009 Massachusetts Medical Society

Entities:  

Mesh:

Year:  2009        PMID: 19797283     DOI: 10.1056/NEJMsa0903048

Source DB:  PubMed          Journal:  N Engl J Med        ISSN: 0028-4793            Impact factor:   91.245


  315 in total

1.  Body mass index and adverse perioperative outcomes following hepatic resection.

Authors:  Amit K Mathur; Amir A Ghaferi; Nicholas H Osborne; Timothy M Pawlik; Darrell A Campbell; Michael J Englesbe; Theodore H Welling
Journal:  J Gastrointest Surg       Date:  2010-06-08       Impact factor: 3.452

2.  Complications after the Norwood operation: an analysis of The Society of Thoracic Surgeons Congenital Heart Surgery Database.

Authors:  Christoph P Hornik; Xia He; Jeffrey P Jacobs; Jennifer S Li; Robert D B Jaquiss; Marshall L Jacobs; Sean M O'Brien; Eric D Peterson; Sara K Pasquali
Journal:  Ann Thorac Surg       Date:  2011-09-19       Impact factor: 4.330

3.  Association Between Physician Teamwork and Health System Outcomes After Coronary Artery Bypass Grafting.

Authors:  John M Hollingsworth; Russell J Funk; Spencer A Garrison; Jason Owen-Smith; Samuel A Kaufman; Francis D Pagani; Brahmajee K Nallamothu
Journal:  Circ Cardiovasc Qual Outcomes       Date:  2016-11-08

4.  [Anesthesiology: partner or competitor?].

Authors:  C M Körner; M A Weigand; E Martin
Journal:  Chirurg       Date:  2012-04       Impact factor: 0.955

5.  Variable impact of complications in general surgery: a prospective cohort study.

Authors:  Eelke Bosma; Eelco J Veen; Mariska A C de Jongh; Jan A Roukema
Journal:  Can J Surg       Date:  2012-06       Impact factor: 2.089

6.  Pancreatectomy risk calculator: an ACS-NSQIP resource.

Authors:  Purvi Parikh; Mira Shiloach; Mark E Cohen; Karl Y Bilimoria; Clifford Y Ko; Bruce L Hall; Henry A Pitt
Journal:  HPB (Oxford)       Date:  2010-09       Impact factor: 3.647

Review 7.  Lung cancer care: the impact of facilities and area measures.

Authors:  Christopher S Lathan
Journal:  Transl Lung Cancer Res       Date:  2015-08

Review 8.  Using existing data to address important clinical questions in critical care.

Authors:  Colin R Cooke; Theodore J Iwashyna
Journal:  Crit Care Med       Date:  2013-03       Impact factor: 7.598

9.  Association Between Hospital Staffing Models and Failure to Rescue.

Authors:  Sarah T Ward; Justin B Dimick; Wenying Zhang; Darrell A Campbell; Amir A Ghaferi
Journal:  Ann Surg       Date:  2019-07       Impact factor: 12.969

10.  Association of hospital volume with conditional 90-day mortality after cystectomy: an analysis of the National Cancer Data Base.

Authors:  Matthew E Nielsen; Katherine Mallin; Mark A Weaver; Bryan Palis; Andrew Stewart; David P Winchester; Matthew I Milowsky
Journal:  BJU Int       Date:  2014-05-22       Impact factor: 5.588

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.