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Decision support system for the operating room rescheduling problem

Overview of attention for article published in Health Care Management Science, June 2012
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#26 of 285)
  • High Attention Score compared to outputs of the same age (87th percentile)

Mentioned by

news
1 news outlet
twitter
1 X user

Citations

dimensions_citation
37 Dimensions

Readers on

mendeley
114 Mendeley
Title
Decision support system for the operating room rescheduling problem
Published in
Health Care Management Science, June 2012
DOI 10.1007/s10729-012-9202-2
Pubmed ID
Authors

J. Theresia van Essen, Johann L. Hurink, Woutske Hartholt, Bernd J. van den Akker

Abstract

Due to surgery duration variability and arrivals of emergency surgeries, the planned Operating Room (OR) schedule is disrupted throughout the day which may lead to a change in the start time of the elective surgeries. These changes may result in undesirable situations for patients, wards or other involved departments, and therefore, the OR schedule has to be adjusted. In this paper, we develop a decision support system (DSS) which assists the OR manager in this decision by providing the three best adjusted OR schedules. The system considers the preferences of all involved stakeholders and only evaluates the OR schedules that satisfy the imposed resource constraints. The decision rules used for this system are based on a thorough analysis of the OR rescheduling problem. We model this problem as an Integer Linear Program (ILP) which objective is to minimize the deviation from the preferences of the considered stakeholders. By applying this ILP to instances from practice, we determined that the given preferences mainly lead to (i) shifting a surgery and (ii) scheduling a break between two surgeries. By using these changes in the DSS, the performed simulation study shows that less surgeries are canceled and patients and wards are more satisfied, but also that the perceived workload of several departments increases to compensate this. The system can also be used to judge the acceptability of a proposed initial OR schedule.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 114 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 1 <1%
France 1 <1%
Sweden 1 <1%
India 1 <1%
Belgium 1 <1%
Unknown 109 96%

Demographic breakdown

Readers by professional status Count As %
Student > Master 22 19%
Student > Ph. D. Student 21 18%
Researcher 17 15%
Student > Bachelor 8 7%
Student > Doctoral Student 7 6%
Other 19 17%
Unknown 20 18%
Readers by discipline Count As %
Engineering 29 25%
Business, Management and Accounting 23 20%
Medicine and Dentistry 8 7%
Computer Science 5 4%
Mathematics 4 4%
Other 16 14%
Unknown 29 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 June 2016.
All research outputs
#2,919,392
of 22,671,366 outputs
Outputs from Health Care Management Science
#26
of 285 outputs
Outputs of similar age
#20,058
of 167,240 outputs
Outputs of similar age from Health Care Management Science
#2
of 3 outputs
Altmetric has tracked 22,671,366 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 285 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one has done particularly well, scoring higher than 90% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 167,240 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.