Spatial Distribution of Total Number of Medical Devices in Turkey: A Classification Analysis

Çınaroğlu, Songül; Başer, Onur

doi:10.5530/ijmedph.2017.2.20

Cited by 3 publications

(2 citation statements)

References 28 publications

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“…Such inefficiency can be explained by the fact that majority of inefficient provinces are in rural regions and people living in rural areas tend to use such services less than people in the urban regions [29][30][31]. The study by Cinaroglu and Baser [32] conducted to analyze the distribution of medical devices in public hospitals of Turkey showed that the provinces are grouped as urban and rural, and regarding the number of devices, there is a difference against the provinces in the rural regions. Also, Sonğur and Top [33] found that there were inequities in medical devices according to regions in Turkey.…”

Section: 2discussionmentioning

confidence: 99%

Türkiye’de Tıbbi Görüntüleme Cihazlarının Verimliliğini Etkileyen Faktörlerin Değerlendirilmesi: İki Aşamalı Veri Zarflama Analizi

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Konca

et al. 2022

Celal Bayar Üniversitesi Sağlık Bilimleri Enstitüsü Dergisi

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Objectives: Healthcare sector is observed to be both labour and technology concentrated. Particularly based on the technological developments, there is major increase in health expenditures. Technological devices, which make pressure on health expenditures, affect the whole world while making the technology managements become a global concern and long-term problem. This study aims to compare the efficiency in medical device use among 81 provinces in Turkey. The main objective of this study is to determine a national framework by reflecting the efficient and inefficient provinces in terms of medical device use, and to make various recommendations accordingly. Materials and Methods: The study is comprised of two-stage analysis. Firstly, the Data Envelopment Analysis (DEA) and then the Ordinary Least Squares (OLS) were utilised respectively. The efficient and inefficient provinces regarding the medical device use were identified through DEA while the factors affecting the efficiency of provinces through OLS. Results: 22 of provinces were found as efficient and 59 as inefficient among 81 provinces in total. According to the regression model, there is not any statistically significant effect of the variables as status of metropolitan, rate of university graduates and gross domestic product per capita on the efficiency score (p>0.05); the number of physician and old-age dependency rate has statistically significant effect on the efficiency score (p≤0.05). Conclusion: This study is considered to provide guiding information to health policy makers and planners through its results.

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Section: 2discussionmentioning

confidence: 99%

Türkiye’de Tıbbi Görüntüleme Cihazlarının Verimliliğini Etkileyen Faktörlerin Değerlendirilmesi: İki Aşamalı Veri Zarflama Analizi

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Konca

et al. 2022

Celal Bayar Üniversitesi Sağlık Bilimleri Enstitüsü Dergisi

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“…The number of FUO cases, the aetiology and the clinical manifestations of FUO have been changing over the years because of the improvement in the diagnostic procedures, vaccination policies, frequent use of antibiotics and infrastructure improvements in cities. As a part of Health Transformation Program in Turkey, both accessibility and the quality of the health system, especially the number of the state‐of‐the‐art technology medical devices like computerised tomography (CT), magnetic resonance imaging or PET‐CT, have incrementally increased since 2003 2,3 . On the other hand, some factors like increased number of elderly people, newly emerging or re‐emerging diseases, malignancies and AIDS epidemic in the World influence on FUO epidemiology.…”

Section: Introductionmentioning

confidence: 99%

Fever of unknown origin (FUO) on a land on cross‐roads between Asia and Europa; a multicentre study from Turkey

Yeni̇lmez

Kakalicoglu

Bozkurt

et al. 2021

Int J Clinical Practice

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Aims The differential diagnosis of Fever of Unknown Origin (FUO) is still a major clinical challenge despite the advances in diagnostic procedures. In this multicentre study, we aimed to reveal FUO aetiology and factors influencing the final diagnosis of FUO in Turkey. Methods A total of 214 patients with FUO between the years 2015 and 2019 from 13 tertiary training and research hospitals were retrospectively evaluated. Results The etiologic distribution of FUO was infections (44.9%), malignancies (15.42%), autoimmune/inflammatory (11.68%) diseases, miscellaneous diseases (8.41%) and undiagnosed cases (19.62%). Brucellosis (10.25%), extrapulmonary tuberculosis (6.54%) and infective endocarditis (6.54%) were the most frequent three infective causes. Solid malignancies (7.1%) and lymphoma (5.6%), adult‐onset still's disease (6.07%) and thyroiditis (5.14%) were other frequent diseases. The aetiological spectrum did not differ in elderly people (P < .05). Infections were less frequent in Western (34.62%) compared with Eastern regions of Turkey (60.71%) (P < .001, OR: 0.31, 95% Cl: 0.19 to 0.60). The ratio of undiagnosed aetiology was significantly higher in elderly people (p: 0.046, OR: 2.34, 95% Cl: 1.00 to 5.48) and significantly lower in Western Turkey (P: .004, OR: 3.07, 95% Cl: 1.39 to 6.71). Conclusions Brucellosis, extrapulmonary tuberculosis and infective endocarditis remain to be the most frequent infective causes of FUO in Turkey. Solid tumours and lymphomas, AOSD and thyroiditis are the other common diseases. The aetiological spectrum did not differ in elderly people, on the other hand, infections were more common in Eastern Turkey. A considerable amount of aetiology remained undiagnosed despite the state‐of‐the‐art technology in healthcare services.

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Tıbbi Cihaz Kullanım Durumunun Değerlendirilmesi: Türkiye ve Avrupa Birliği Ülkeleri Üzerine Bir Araştırma

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KOCA

2021

Erciyes Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi

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Bu çalışmada Türkiye ve Avrupa Birliği (AB) üyesi ülkelerde görüntüleme amaçlı kullanılan bilgisayarlı tomografi (BT) ile manyetik rezonans görüntüleme (MRG) cihazlarının kullanım oranlarını ve cihaz başına kullanım paylarını hesaplamak ve bu değişkenlere göre ülkeleri sınıflamak amaçlanmıştır. Araştırma kapsamında ilk olarak cihaz kullanım oranları ve cihaz başına kullanım payları hesaplanmıştır. Ardından, ülkeler hem BT hem de MRG cihazı için kullanım oranları ve payları açısından ayrı ayrı hiyerarşik kümeleme analiziyle gruplandırılmıştır. Yapılan hesaplamalar sonucunda BT ve MRG kullanım oranlarının sırayla Türkiye için 20,87, 32,84 ve AB ortalamalarının ise 3,44, 2,92 olduğu bulunmuştur. Kümeleme analizi sonucunda ise, BT cihazı açısından, Fransa ve Türkiye’nin birinci grupta diğer ülkelerin ikinci grupta; MRG cihazı açısından ise İspanya, Fransa, Birleşik Krallık ve Türkiye’nin birinci grupta diğer ülkelerin ikinci grupta yer aldığı bulunmuştur. Çalışmadan elde edilen sonuçların sağlık teknolojileri aracılığıyla sunulacak olan sağlık hizmetlerinin planlanmasında, cihaz sayılarının belirlenmesinde, cihazların verimli kullanımına ilişkin kararların alınmasında kanıta dayalı önemli bilgiler sunacağı düşünülmektedir

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Spatial Distribution of Total Number of Medical Devices in Turkey: A Classification Analysis

Cited by 3 publications

References 28 publications

Türkiye’de Tıbbi Görüntüleme Cihazlarının Verimliliğini Etkileyen Faktörlerin Değerlendirilmesi: İki Aşamalı Veri Zarflama Analizi

Türkiye’de Tıbbi Görüntüleme Cihazlarının Verimliliğini Etkileyen Faktörlerin Değerlendirilmesi: İki Aşamalı Veri Zarflama Analizi

Fever of unknown origin (FUO) on a land on cross‐roads between Asia and Europa; a multicentre study from Turkey

Tıbbi Cihaz Kullanım Durumunun Değerlendirilmesi: Türkiye ve Avrupa Birliği Ülkeleri Üzerine Bir Araştırma

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