Evidence map›Paper›PMID 29849748›Full record

ArticleComputational and mathematical methods in medicine2018

Online Appointment Scheduling for a Nuclear Medicine Department in a Chinese Hospital.

Qian Xiao, Li Luo, Shu-Zhen Zhao, Xiao-Bin Ran, Ya-Bing Feng

Abstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2018. 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
–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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Article
  6. 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

5 authors.

Qian XiaoInstitute of Hospital Management, West China Hospital, Sichuan University, Chengdu 610041, China.ORCID 0000-0003-0908-6341
Li LuoService Management Institute, Business School of Sichuan University, Chengdu 610064, China.ORCID 0000-0002-2007-7916
Shu-Zhen ZhaoOutpatient Department, West China Hospital, Sichuan University, Chengdu 610041, China.ORCID 0000-0002-7236-8440
Xiao-Bin RanService Management Institute, Business School of Sichuan University, Chengdu 610064, China.ORCID 0000-0002-3681-5864
Ya-Bing FengService Management Institute, Business School of Sichuan University, Chengdu 610064, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nuclear medicine, a subspecialty of radiology, plays an important role in proper diagnosis and timely treatment. Multiple resources, especially short-lived radiopharmaceuticals involved in the process of nuclear medical examination, constitute a unique problem in appointment scheduling. Aiming at achieving scientific and reasonable appointment scheduling in the West China Hospital (WCH), a typical class A tertiary hospital in China, we developed an online appointment scheduling algorithm based on an offline nonlinear integer programming model which considers multiresources allocation, the time window constraints imposed by short-lived radiopharmaceuticals, and the stochastic nature of the patient requests when scheduling patients. A series of experiments are conducted to show the effectiveness of the proposed strategy based on data provided by the WCH. The results show that the examination amount increases by 29.76% compared with the current one with a significant increase in the resource utilization and timely rate. Besides, it also has a high stability for stochastic factors and bears the advantage of convenient and economic operation.

Indexed as

Appointments and SchedulesEfficiency, OrganizationalChinaHospitalsHumansNuclear MedicineTime Factors

Identifiers

PMID29849748
PMCPMC5925036

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.