SAĞLIK HİZMETLERİNDE YAPAY ZEKA ENTEGRASYONU: SOSYO-TEKNİK FAKTÖRLERİN SWARA VE AHP YÖNTEMLERİ İLE DEĞERLENDİRİLMESİ

Abstract

Bu çalışmada, sağlık hizmetlerinde yapay zekanın entegrasyonunu etkileyen sosyo-teknik faktörlerin belirlenerek SWARA ve AHP yöntemleriyle önceliklendirilmesi ve yapay zekanın uyumlaştırılmasına yönelik çözüm önerilerinin sunulması amaçlanmıştır. Betimsel ve kesitsel nitelikte olan çalışmada literatür taraması sonucunda sağlık hizmetlerinde yapay zekanın entegrasyonunu etkileyen sosyo-teknik faktörler 10 ana başlık altında toplanmıştır. SWARA ve AHP sonuçlarına göre; sağlık hizmetlerinde yapay zeka entegrasyonunu etkileyen sosyo-teknik faktörlerden en önemlileri sırasıyla veri kalitesi ve güvenliği, teknolojik altyapı uygunluğu ve beceri ve eğitim olarak tespit edilmiştir. Sonuçlar, her iki yöntemin de benzer önceliklendirme çıktıları sunduğunu göstermiştir. Sağlık hizmet sunucuları öncelikli olarak bu faktörler doğrultusunda strateji geliştirerek kaynaklarını bu yöne tahsis etmelidir. Veri kalitesi ve güvenliğinin artırılması için elektronik sağlık kayıtları ve diğer veri kaynaklarının entegrasyonu sağlanmalı, eksik ya da hatalı verilerin önüne geçmek için veri doğrulama ve temizleme mekanizmaları oluşturulmalıdır. Bulut tabanlı veri saklama ve işleme sistemleri, yüksek performanslı bilişim altyapıları ve hızlı veri akışını sağlayan ağ sistemleri gibi teknolojik çözümlerin geliştirilmesi önemlidir. Yapay zeka teknolojilerine yönelik farkındalığını artırmak, yapay zeka okuryazarlığını geliştirmek ve sistemleri etkin kullanmalarını sağlamak için sürekli gelişimi teşvik eden mesleki eğitim programları düzenlenmelidir.

Keywords

• Sağlık Hizmeti
• Yapay Zeka
• Sosyo-teknik Faktörler
• SWARA
• AHP

INTEGRATION OF ARTIFICIAL INTELLIGENCE IN HEALTH SERVICES: EVALUATION OF SOCIO-TECHNICAL FACTORS USING SWARA AND AHP METHODS

Abstract

This study aims to determine the socio-technical factors affecting the integration of artificial intelligence (AI) in healthcare services, prioritize them with SWARA and AHP methods, and provide solution proposals for the harmonizing artificial intelligence. Designed as a descriptive and cross-sectional study, a literature review identified ten main categories of socio-technical factors influencing AI integration in healthcare. According to the results of the SWARA and AHP analyses; the most important socio-technical factors affecting the integration of artificial intelligence in healthcare services were determined to be data quality and security, suitability of technological infrastructure, and skills and education, respectively. The results showed that both methods offered similar prioritization outcomes. Healthcare service providers should primarily develop strategies in line with these factors and allocate their resources in this direction. In order to increase data quality and security, integration of electronic health records and other data sources should be ensured, and data verification and cleaning mechanisms should be established to prevent incomplete or incorrect data. It is important to develop technological solutions such as cloud-based data storage and processing systems, high-performance computing infrastructures, and network systems that provide fast data flow. Moreover, professional development programs that encourage continuous learning should be organized to increase awareness of artificial intelligence technologies, improve artificial intelligence literacy, and enable them to use the systems effectively.

Keywords

• Healthcare
• Artificial Intelligence
• Socio-Technical Factors
• SWARA
• AHP

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