ArticleHealth care management science2020
Characterization of the flow of patients in a hospital from complex networks.
Article in Health care management science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Clinical and operational insights from data-driven care pathway mapping: a systematic review.BMC medical informatics and decision making · 2022Pooled it
- Monitoring patient pathways at a secondary healthcare services through process mining via Fuzzy Miner.BMC medical informatics and decision making · 2025Article
- What has the appraisal for hospitals brought to job satisfaction of healthcare professionals? A cross-sectional survey in China.BMJ open · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
We study the efficiency of operations management in a hospital from the dynamics of the flow of patients. Our principal aim is to characterize strategic departments and seasonal patterns in a hospital from a complex networks approach. Process mining techniques are developed to track out-patients' pathways along different departments for the purpose of building weekly networks. In these networks, departments act as nodes with multiple out/in-going arrows connecting other departments. Strategic departments are classified into target and critical departments. On the one hand, target departments, which in this study belong to the oncology area, correspond to those affected by new management policies whose impact is to be assessed. On the other hand, critical departments correspond to the most active departments, the hubs of the networks. Using suitable networks parameters, strategic departments are shown to be highly efficient regardless of the season, which naturally translates into a high level of service offered to patients. In addition, our results show conformance with the new objectives concerning target departments. The methodology presented is shown to be successful in evaluating the efficiency of hospital services in order to enhance process performances, and moreover, it is suitable to be implemented in healthcare management systems at a greater scale and the service industry whenever the flow of clients or customers are involved.
Indexed as
Identifiers
30607802What OpenQuestion holds
Registered trials
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.