Evidence map›Paper›PMID 40597199›Full record

ArticleBMC health services research2025

Classification of medical imaging technologies: results from Türkiye.

Hakan Temiz, Tuncay Kara

Abstract read
In one paragraph

Article in BMC health services research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Hakan TemizDepartment of Computer Engineering, Artvin Coruh University, Artvin, Türkiye. htemiz@artvin.edu.tr.ORCID http://orcid.org/0000-0002-1351-7565
Tuncay KaraHealth Administration Department, Ankara, Türkiye.ORCID http://orcid.org/0000-0001-6308-3980

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRegional disparities in access to medical diagnostic imaging technologies (MDITs) present a significant barrier to achieving health equity, particularly in developing countries. Understanding how these technologies are distributed and utilized is essential for informing equitable health policy.

methodThis study examines the distribution and utilization of MDITs across Türkiye's 12 NUTS regions using a hierarchical clustering approach. Unlike previous studies, the analysis incorporates both technological capacity and utilization (CaU) variables, evaluated jointly and independently. Imaging modalities are also stratified based on their technological complexity and investment requirements to capture nuanced regional patterns.

resultsFindings indicate that although Türkiye demonstrates an overall balanced distribution of MDITs, notable regional disparities in utilization efficiency remain. Regions exhibiting similar usage patterns tend to cluster together irrespective of geographic proximity. Interestingly, the clusters often transcend geographical proximity; regions located at opposite ends of the country tend to cluster on the basis of similar utilization patterns. This may suggest that disparities between administrative centers and rural areas are less pronounced than previously assumed. These patterns imply that institutional capacity, healthcare workforce distribution, and demographic demand may have a stronger influence on utilization than spatial location.

conclusionThe study highlights a disconnect between capacity and actual use of diagnostic imaging technologies, underscoring the need for targeted policy interventions. It also suggests that regional utilization patterns may align more with functional similarities than with geographic proximity. Moreover, analyzing technological capacity and utilization variables separately-rather than as a combined index-yielded more transparent and objective insights into regional disparities. These findings contribute to optimizing health resource allocation and support evidence-based policymaking aimed at advancing equitable access to diagnostic services, aligning with Türkiye's commitment to universal health coverage.

Indexed as

Diagnostic ImagingHealthcare DisparitiesHealth Services AccessibilityCluster AnalysisDeveloping CountriesHumansCapacity and useDiagnostic imagingHealthcare utilizationHealth equityHierarchical clusteringRegional disparitiesTürkiye

Identifiers

PMID40597199
PMCPMC12211891

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LicenceCC BY-NC-ND
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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.