Determination of Priority Strategies for Digitalisation of Family Health Centres with Machine Learning Based Approach

Objective: Family health centers are an important part of the health system. They are especially vital for the provision of preventive and primary care services. In the developing world, it is inevitable to provide these services through digitalization. It is an undeniable fact that digitalization of the processes of family health centers will contribute positively to the quality and sustainability of the service. However, there are many factors affecting the digitalization of these health institutions. This study aims to weight the factors affecting the digitalization of family health centers and identify priority strategies. Method: Factors affecting the digitalization process of family health centers are financial concerns, data security concerns, lack of infrastructure, legal processes, policy support and social acceptance of digitalization. These factors were weighted by machine learning-based Pythagorean Fuzzy DEMATEL method. Results: The results show that the most important factor affecting the digitalization of family health centers is financial concerns (w: 0.181). Social acceptance of digitalization (w: 0.160) and data security concerns (w: 0.159) were found to be other important issues affecting the digitalization of these centers. Conclusion: This study is thought to make a significant contribution to the literature on the digitalization of family health centers. The biggest limitation of the study is that it was conducted in family health centers. Future studies can be conducted for institutions providing services in the second and third level.

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Publication Details

Journal
Turkish Journal of Family Practice
Published
2024-09-30
DOI
https://doi.org/10.54308/tahd.2024.07088
Citations
1
Primary Topic
Data Mining and Machine Learning Applications
Type
article
Field-Weighted Citation Impact
0.78
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article

Determination of Priority Strategies for Digitalisation of Family Health Centres with Machine Learning Based Approach

Serkan Eti, Yeter Demir Uslu, Sefer Aygün, Umutcan Altun et al.
1 citations
Turkish Journal of Family Practice
Data Mining and Machine Learning Applications
0.78
article

Determination of Priority Strategies for Digitalisation of Family Health Centres with Machine Learning Based Approach

Serkan Eti, Yeter Demir Uslu, Sefer Aygün, Umutcan Altun, Yaşar Gökalp, Aybala Demirci Aksoy
article en
1 citations

Abstract

Objective: Family health centers are an important part of the health system. They are especially vital for the provision of preventive and primary care services. In the developing world, it is inevitable to provide these services through digitalization. It is an undeniable fact that digitalization of the processes of family health centers will contribute positively to the quality and sustainability of the service. However, there are many factors affecting the digitalization of these health institutions. This study aims to weight the factors affecting the digitalization of family health centers and identify priority strategies. Method: Factors affecting the digitalization process of family health centers are financial concerns, data security concerns, lack of infrastructure, legal processes, policy support and social acceptance of digitalization. These factors were weighted by machine learning-based Pythagorean Fuzzy DEMATEL method. Results: The results show that the most important factor affecting the digitalization of family health centers is financial concerns (w: 0.181). Social acceptance of digitalization (w: 0.160) and data security concerns (w: 0.159) were found to be other important issues affecting the digitalization of these centers. Conclusion: This study is thought to make a significant contribution to the literature on the digitalization of family health centers. The biggest limitation of the study is that it was conducted in family health centers. Future studies can be conducted for institutions providing services in the second and third level.

Turkish Journal of Family PracticeVol. 28(3)
Istanbul Topkapi University (TR), Istanbul Medipol University (TR), Hacettepe University (TR), Kastamonu University (TR)
Openalex Percentile: Top 21%
Data Mining and Machine Learning Applications
0.78
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