Evidence map›Paper›PMID 29417076›Full record

ArticleJournal of education and health promotion2018

Forecasting the shortage of neurosurgeons in Iran using a system dynamics model approach.

Sima Rafiei, Arman Daneshvaran, Sina Abdollahzade

Abstract read
In one paragraph

Article in Journal of education and health promotion, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Long-Range Forecasting for Emergency Care Systems in a Highly Dynamic Setting: A Singapore Case Study.Journal of the American College of Emergency Physicians open · 2025
    Article
  3. Article
  4. Article
  5. 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

3 authors.

Sima RafieiDepartment of Healthcare Management, School of Health, Qazvin University of Medical Sciences, Qazvin, Iran.
Arman DaneshvaranDepartment of Management, School of Management, Sharif University of Technology, Tehran, Iran.
Sina AbdollahzadeDepartment of Surgery, School of Medicine, Qazvin University of Medical Sciences, Qazvin, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

contextShortage of physicians particularly in specialty levels is considered as an important issue in Iran health system. Thus, in an uncertain environment, long-term planning is required for health professionals as a basic priority on a national scale.

aimsThis study aimed to estimate the number of required neurosurgeons using system dynamic modeling. SETTING AND

designSystem dynamic modeling was applied to predict the gap between stock and number of required neurosurgeons in Iran up to 2020. SUBJECTS AND

methodsA supply and demand simulation model was constructed for neurosurgeons using system dynamic approach. The demand model included epidemiological, demographic, and utilization variables along with supply model-incorporated current stock of neurosurgeons and flow variables such as attrition, migration, and retirement rate. STATISTICAL ANALYSIS USED: Data were obtained from various governmental databases and were analyzed by Vensim PLE Version 3.0 to address the flow of health professionals, clinical infrastructure, population demographics, and disease prevalence during the time.

resultsIt was forecasted that shortage in number of neurosurgeons would disappear at 2020. The most dominant determinants on predicted number of neurosurgeons were the prevalence of neurosurgical diseases, the rate for service utilization, and medical capacity of the region.

conclusionsShortage of neurosurgeons in some areas of the country relates to maldistribution of the specialists. Accordingly, there is a need to reconsider the allocation system for health professionals within the country instead of increasing the overall number of acceptance quota in training positions.

Indexed as

Demandforecastshortagesupplysystem dynamics

Identifiers

PMID29417076
PMCPMC5791429

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