Evidence map›Paper›PMID 24590259›Full record

ArticleHealth care management science2015

Allocating operating room block time using historical caseload variability.

Narges Hosseini, Kevin M Taaffe

Abstract read
PubMed Publisher
In one paragraph

Article in Health care management science, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
5.7field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 36 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Observational
  5. Review
  6. Due time driven surgery scheduling.Health care management science · 2017
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 2 institutions in 1 country.

Narges HosseiniDepartment of Health Science Research, Center for the Science of Health Care Delivery, Mayo Clinic, 200 1st Street SW, Rochester, MN, 55905, USA. nhossei@g.clemson.edu.
Kevin M TaaffeDepartment of Industrial Engineering, Clemson University, 110 Freeman Hall, Clemson, SC, 29634, USA. taaffe@clemson.edu.
Clemson University · USWinnMed · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Operating room (OR) allocation and planning is one of the most important strategic decisions that OR managers face. The number of ORs that a hospital opens depends on the number of blocks that are allocated to the surgical groups, services, or individual surgeons, combined with the amount of open posting time (i.e., first come, first serve posting) that the hospital wants to provide. By allocating too few ORs, a hospital may turn away surgery demand whereas opening too many ORs could prove to be a costly decision. The traditional method of determining block frequency and size considers the average historical surgery demand for each group. However, given that there are penalties to the system for having too much or too little OR time allocated to a group, demand variability should play a role in determining the real OR requirement. In this paper we present an algorithm that allocates block time based on this demand variability, specifically accounting for both over-utilized time (time used beyond the block) and under-utilized time (time unused within the block). This algorithm provides a solution to the situation in which total caseload demand can be accommodated by the total OR resource set, in other words not in a capacity-constrained situation. We have found this scenario to be common among several regional healthcare providers with large OR suites and excess capacity. This algorithm could be used to adjust existing blocks or to assign new blocks to surgeons that did not previously have a block. We also have studied the effect of turnover time on the number of ORs that needs to be allocated. Numerical experiments based on real data from a large health-care provider indicate the opportunity to achieve over 2,900 hours of OR time savings through improved block allocations.

Indexed as

AlgorithmsHumansOperating RoomsOrganizational Case StudiesPersonnel Staffing and SchedulingResource AllocationSurgery Department, HospitalTime FactorsBlock allocationLinear programmingOperating roomOvertimeUnder timeUtilization

Identifiers

PMID24590259
OpenAlexW1997411066

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.