ArticleHealth care management science2019
Road map for progress and attractiveness of Iranian hospitals by integrating self-organizing map and context-dependent DEA.
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 1 paper.
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
1 citing paper in PubMed.
- The Core of Healthcare Efficiency: A Comprehensive Bibliometric Review on Frontier Analysis of Hospitals.Healthcare (Basel, Switzerland) · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hospitals play an important role in healthcare systems and usually stay on the end node of the healthcare chain. Thus, determining their road map to get close to the desired efficiency frontier and developing short-term and long-term plans could help to manage costs and resources, efficiently. As the efficiency frontier depends on the size of the hospital and the complexity of its structure, the homogeneity in benchmarking must be considered. For tackling this problem, the self-organizing map (SOM) is used to create homogeneous groups. On the other hand, data envelopment analysis (DEA) is a well-known methodology for evaluating decision-making units. Each unit obtains the efficiency score based on the ratio of weighted outputs to weighted inputs, where each unit can take the desirable weights for inputs and outputs to provide the maximum value. One of the problems of DEA is the selection of the reference set and distinguishing between the efficient hospitals. To overcome these problems, the context-depended DEA has been applied and the progress and attractiveness of hospitals are obtained. To evaluate the capability of the proposed approach, data of 288 Iranian hospitals are utilized. By applying SOM the hospitals are clustered into appropriate homogeneous groups and by applying context-dependent DEA, the road map for progress and attractiveness of each hospital is determined. In other words, using the proposed approach the hospitals are able to determine the short and long-term goals according to their strategic plans.
Indexed as
Identifiers
31081531What 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.