Explaining the Gender Gap in Waiting Times for Scheduled Surgery in the Portuguese National Health Service

Objective: This paper evaluates the gender gap in waiting times for scheduled surgery, using information on 2.6 million surgical episodes in Portuguese National Health Service hospitals covering the period from 2011 to 2015. Methodology: We estimated the gross gender gap, i.e., the differential betw...

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Main Authors: Joana Cima, Paulo Guimarães, Álvaro Almeida
Format: Article
Language:English
Published: Karger Publishers 2021-02-01
Series:Portuguese Journal of Public Health
Subjects:
Online Access:https://www.karger.com/Article/FullText/514798
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spelling doaj-6395dd9769fb4817b1f87b85344207512021-03-18T13:19:50ZengKarger PublishersPortuguese Journal of Public Health2504-31372504-31452021-02-011810.1159/000514798514798Explaining the Gender Gap in Waiting Times for Scheduled Surgery in the Portuguese National Health ServiceJoana CimaPaulo GuimarãesÁlvaro AlmeidaObjective: This paper evaluates the gender gap in waiting times for scheduled surgery, using information on 2.6 million surgical episodes in Portuguese National Health Service hospitals covering the period from 2011 to 2015. Methodology: We estimated the gross gender gap, i.e., the differential between the waiting times of men and women, and then add several explanatory variables that can account for this difference to estimate an adjusted gender gap. The variables are added in a way that permits the most flexible parametric specification. Next, we used Gelbach’s decomposition to understand the contribution of each variable to the difference between the gross and the adjusted gender gaps. Results: The gross gender gap of 10% is reduced to a 3% adjusted gender gap after accounting for observable explanatory factors. Gelbach’s decomposition shows that patient priority and hospital-fixed effects are the variables that contribute the most to the explained component of the gap. The analysis suggests that men tend to be ranked with more severe priorities, and that there are hospital specificities that cause men to have shorter waiting times. Conclusions: Overall, we identified a gender bias against women in surgery waiting times, but the size of the bias is smaller than was previously suggested in the literature.https://www.karger.com/Article/FullText/514798waiting timesscheduled surgerygender gapgelbach’s decompositionportugal
collection DOAJ
language English
format Article
sources DOAJ
author Joana Cima
Paulo Guimarães
Álvaro Almeida
spellingShingle Joana Cima
Paulo Guimarães
Álvaro Almeida
Explaining the Gender Gap in Waiting Times for Scheduled Surgery in the Portuguese National Health Service
Portuguese Journal of Public Health
waiting times
scheduled surgery
gender gap
gelbach’s decomposition
portugal
author_facet Joana Cima
Paulo Guimarães
Álvaro Almeida
author_sort Joana Cima
title Explaining the Gender Gap in Waiting Times for Scheduled Surgery in the Portuguese National Health Service
title_short Explaining the Gender Gap in Waiting Times for Scheduled Surgery in the Portuguese National Health Service
title_full Explaining the Gender Gap in Waiting Times for Scheduled Surgery in the Portuguese National Health Service
title_fullStr Explaining the Gender Gap in Waiting Times for Scheduled Surgery in the Portuguese National Health Service
title_full_unstemmed Explaining the Gender Gap in Waiting Times for Scheduled Surgery in the Portuguese National Health Service
title_sort explaining the gender gap in waiting times for scheduled surgery in the portuguese national health service
publisher Karger Publishers
series Portuguese Journal of Public Health
issn 2504-3137
2504-3145
publishDate 2021-02-01
description Objective: This paper evaluates the gender gap in waiting times for scheduled surgery, using information on 2.6 million surgical episodes in Portuguese National Health Service hospitals covering the period from 2011 to 2015. Methodology: We estimated the gross gender gap, i.e., the differential between the waiting times of men and women, and then add several explanatory variables that can account for this difference to estimate an adjusted gender gap. The variables are added in a way that permits the most flexible parametric specification. Next, we used Gelbach’s decomposition to understand the contribution of each variable to the difference between the gross and the adjusted gender gaps. Results: The gross gender gap of 10% is reduced to a 3% adjusted gender gap after accounting for observable explanatory factors. Gelbach’s decomposition shows that patient priority and hospital-fixed effects are the variables that contribute the most to the explained component of the gap. The analysis suggests that men tend to be ranked with more severe priorities, and that there are hospital specificities that cause men to have shorter waiting times. Conclusions: Overall, we identified a gender bias against women in surgery waiting times, but the size of the bias is smaller than was previously suggested in the literature.
topic waiting times
scheduled surgery
gender gap
gelbach’s decomposition
portugal
url https://www.karger.com/Article/FullText/514798
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