Evidence map›Paper›PMID 34075269›Full record

ArticleGeoJournal2022

Comparison of GIS-based AHP and fuzzy AHP methods for hospital site selection: a case study for Prayagraj City, India.

Ashutosh Kumar Tripathi, Sonam Agrawal, Rajan Dev Gupta

Abstract read
In one paragraph

Article in GeoJournal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

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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

10 citing papers in PubMed.

  1. Trial
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  7. Flood vulnerability of a few areas in the foothills of the Western Ghats: a comparison of AHP and F-AHP models.Stochastic environmental research and risk assessment : research journal · 2023
    Article
  8. Article
  9. Article
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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.

Ashutosh Kumar TripathiGIS Cell, Motilal Nehru National Institute of Technology Allahabad, Prayagraj, Uttar Pradesh 211004 India.ORCID 0000-0003-0683-0489
Sonam AgrawalGIS Cell, Motilal Nehru National Institute of Technology Allahabad, Prayagraj, Uttar Pradesh 211004 India.
Rajan Dev GuptaCivil Engineering Department, Motilal Nehru National Institute of Technology Allahabad, Prayagraj, Uttar Pradesh 211004 India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identification of hospital sites and their ranking is important for the planning and development of any country's health infrastructure. The site selection problem is a typical multi-criteria decision making problem involving multiple stakeholders and their interests. Multi-Criteria Decision Analysis (MCDA) is a promising approach to solve a location-based problem due to the constitution of various criteria involved in decision making. In this research, eleven criterion are chosen which are classified under three main criteria; socio-economic, geographical and environmental. This research aims to identify the appropriate MCDA method for the selection of a new hospital sites. Here, two MCDA methods named Analytical Hierarchy Process (AHP) and Fuzzy AHP (FAHP) are used. Further, Geographical Information System (GIS) based MCDA methodology is proposed in this paper. The results obtained with both AHP and FAHP methods are compared. This comparison is based on criterion rankings, proposed hospital locations and sensitivity analysis. The main difference in results is shown in the result of sensitivity analysis in which constant variation in site ranking is obtained when weight change analysis is performed using AHP. The FAHP result shows only one variation in site ranking after a change in weight from +10 to +20%. The result suggests that FAHP may be a better approach to the hospital site selection problem.

Indexed as

Analytic hierarchy process (AHP)Fuzzy AHP (FAHP)Geographic information system (GIS)Hospital site selectionMulti-criteria decision analysis (MCDA)Sensitivity analysis

Identifiers

PMID34075269
PMCPMC8159725

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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.