Literature DB >> 18197450

Disparities in oncologic surgery.

Caprice C Greenberg1, Jane C Weeks, Steven C Stain.   

Abstract

Surgical oncology is one of the most frequently studied surgical specialties with regard to disparities in quality of care. There is variation in the care received according to nonclinical factors such as age, race and ethnicity, education, income, and even geographic region. Differences exist with regard to who gets treatment, what treatment is received, and the outcomes of those treatments. Although the existence of such disparities is no longer in doubt, the etiology is still being investigated. Ongoing research and quality improvement initiatives move beyond the mere description of existing disparities in one of three ways: (1) identifying and understanding the factors that lead to disparities; (2) advancing available methods to measure and track disparities; and (3) developing an approach to improvement. In this article, we start out by offering a framework to describe potential factors that lead to disparities, using examples from surgical oncology. We then describe the approaches to measuring and tracking disparities that are being used in research and quality improvement. Finally, we attempt to illustrate how all of these factors interact and offer some potential strategies to close the gap and alleviate disparities within the discipline.

Mesh:

Year:  2008        PMID: 18197450      PMCID: PMC4195237          DOI: 10.1007/s00268-007-9383-x

Source DB:  PubMed          Journal:  World J Surg        ISSN: 0364-2313            Impact factor:   3.352


  45 in total

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5.  Effects of health insurance and race on early detection of cancer.

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Journal:  J Natl Cancer Inst       Date:  1999-08-18       Impact factor: 13.506

6.  Persistent differences in sociodemographic determinants of breast conserving treatment despite overall increased adoption.

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Journal:  Med Care       Date:  2002-03       Impact factor: 2.983

7.  Surgery for colorectal cancer: Race-related differences in rates and survival among Medicare beneficiaries.

Authors:  G S Cooper; Z Yuan; C S Landefeld; A A Rimm
Journal:  Am J Public Health       Date:  1996-04       Impact factor: 9.308

8.  Disparities in cancer diagnosis and survival.

Authors:  C J Bradley; C W Given; C Roberts
Journal:  Cancer       Date:  2001-01-01       Impact factor: 6.860

9.  Patient race/ethnicity and quality of patient-physician communication during medical visits.

Authors:  Rachel L Johnson; Debra Roter; Neil R Powe; Lisa A Cooper
Journal:  Am J Public Health       Date:  2004-12       Impact factor: 9.308

10.  Socioeconomic status and comorbidity among newly diagnosed cancer patients.

Authors:  C T Schrijvers; J W Coebergh; J P Mackenbach
Journal:  Cancer       Date:  1997-10-15       Impact factor: 6.860

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  6 in total

1.  Disparities in access to basic laparoscopic surgery at U.S. academic medical centers.

Authors:  J Esteban Varela; Ninh T Nguyen
Journal:  Surg Endosc       Date:  2010-09-17       Impact factor: 4.584

Review 2.  The role of unconscious bias in surgical safety and outcomes.

Authors:  Heena P Santry; Sherry M Wren
Journal:  Surg Clin North Am       Date:  2011-12-06       Impact factor: 2.741

3.  Racial and socioeconomic correlates of treatment and survival among patients with meningioma: a population-based study.

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Journal:  J Neurooncol       Date:  2020-03-19       Impact factor: 4.130

4.  Impact of insurance on hospital course and readmission after resection of benign meningioma.

Authors:  Blake M Hauser; Saksham Gupta; Edward Xu; Kyle Wu; Joshua D Bernstock; Melissa Chua; Ayaz M Khawaja; Timothy R Smith; Ian F Dunn; Regan W Bergmark; Wenya Linda Bi
Journal:  J Neurooncol       Date:  2020-07-11       Impact factor: 4.130

5.  Changes in Racial Disparities in Mortality After Cancer Surgery in the US, 2007-2016.

Authors:  Miranda B Lam; Katherine Raphael; Winta T Mehtsun; Jessica Phelan; E John Orav; Ashish K Jha; Jose F Figueroa
Journal:  JAMA Netw Open       Date:  2020-12-01

6.  The population-based oncological health care study OVIS - recruitment of the patients and analysis of the non-participants.

Authors:  Ron Pritzkuleit; Annika Waldmann; Heiner Raspe; Alexander Katalinic
Journal:  BMC Cancer       Date:  2008-10-27       Impact factor: 4.430

  6 in total

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