Literature DB >> 27798750

Outcomes of physician patients after non-cardiac surgery: a registry analysis.

Krit Panjasawatwong1, Peirong Lin1, Nika Karimi1, Jing You1,2, Daniel I Sessler3.   

Abstract

OBJECTIVES: When physicians become patients, they may expect special privileges, extra attention from caregivers, and non-routine treatments. Consequently, physician patients may not be treated per routine-which possibly worsens care rather than improving it. We thus tested the primary hypothesis that in-hospital mortality and major complications after non-cardiac surgery are more common in physician patients than in non-physician patients. PATIENTS AND METHODS: Perioperative data were extracted for patients who had non-cardiac surgery at the Cleveland Clinic between 2005 and 2013. We used propensity score matching to identify comparable groups of physician and non-physician patients. Matched physician and non-physician patients were compared on a composite of in-hospital mortality and major postoperative complications using a generalized equation average relative effects model. Secondly, the matched patients were also compared on reoperation using logistic regression and on duration of hospitalization using Kaplan-Meier analysis with the log-rank test and Cox proportional hazards regression.
RESULTS: Among 21,173 qualifying patients, we matched 522 physician patients to 2448 non-physician controls. There were no significant differences between physician and non-physician patients in the composite of in-hospital mortality and major complications, with an estimated odds ratio across the outcome components (average relative effect) of 1.20 (95% confidence interval 0.77-1.87) for physicians vs. non-physicians, P = 0.41. There was also no difference in the risk of re-operation or duration of hospitalization.
CONCLUSIONS: A variety of important outcomes were similar in physician patients and matched non-physician patients after non-cardiac surgery.

Entities:  

Keywords:  Anesthesia; Health services; Mortality; Physician patient; Surgery; Visiting important person

Mesh:

Year:  2016        PMID: 27798750     DOI: 10.1007/s00540-016-2273-3

Source DB:  PubMed          Journal:  J Anesth        ISSN: 0913-8668            Impact factor:   2.078


  15 in total

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Authors:  Jorge A Guzman; Madhu Sasidhar; James K Stoller
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Authors:  Hsiu-Nien Shen; Chin-Li Lu; Chung-Yi Li
Journal:  Crit Care Med       Date:  2014-04       Impact factor: 7.598

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Authors:  James E. Groves; Barbara A. Dunderdale; Theodore A. Stern
Journal:  Prim Care Companion J Clin Psychiatry       Date:  2002-12

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Authors:  Peter C Austin
Journal:  Stat Med       Date:  2012-12-12       Impact factor: 2.373

10.  A comparison of 12 algorithms for matching on the propensity score.

Authors:  Peter C Austin
Journal:  Stat Med       Date:  2013-10-07       Impact factor: 2.373

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