Evidence map›Paper›PMID 30094761›Full record

ArticleHealth care management science2019

The impact of specialization of hospitals on patient access to care; a queuing analysis with an application to a neurological hospital.

Saied Samiedaluie, Vedat Verter

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Health care management science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. 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.

Saied SamiedaluieAlberta School of Business, University of Alberta, Edmonton, Alberta, T6G 2R6, Canada. samiedal@ualberta.ca.ORCID http://orcid.org/0000-0002-2384-8907
Vedat VerterDesautels Faculty of Management, McGill University, 1001 Sherbrooke Street West, Montreal, Quebec, H3A 1G5, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We study the impact of specialization on the operational efficiency of a multi-hospital system. The mixed outcomes of recently increasing hospital mergers and system re-configuration initiatives have raised the importance of studying such organizational changes from all the relevant perspectives. We consider two configuration scenarios for a multi-hospital system. The first scenario assumes that all the hospitals in the system are general, which implies they can provide care to all types of patients. In the alternative configuration, we specialize each hospital in certain level of care, which means they serve only specific types of patients. By considering an extensive number of possible settings for a multi-hospital system, we characterize the situations in which one scenario outperforms the other in terms of extending access of patients to care. Our results show that whenever the percent of patients with shorter length of stay in the system increases, specialization of healthcare services can maximize the accessibility of care. Also, if the patient load is balanced between all hospitals in the system, it seems more likely that all hospitals benefit from specialization. We conclude that the strategic decision of designing a multi-hospital system requires careful consideration of patient mix among arrivals, relative length of stay of patients, and distribution of patient load between hospitals.

Indexed as

Hospital AdministrationLength of StayMulti-Institutional SystemsNeurologyResource AllocationComputer SimulationHealth Services AccessibilityHospitalsHospitals, UniversityHumansOrganizational Case StudiesQuebecSpecializationWaiting ListsHospital bed managementMulti-hospital systemsQueueing networksSpecialization

Identifiers

What OpenQuestion holds

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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.