Challenges for the Integration of Artificial Intelligence in Healthcare  Services: A Decision-Making Approach

Erman Gedikli

Makale detayları

Challenges for the Integration of Artificial Intelligence in Healthcare Services: A Decision-Making Approach

Yazarlar:

Erman Gedikli

Yayıncı:

İdeal Kent Yayınları

Ana Başlıklar:

Sosyal Politikada Bölgesel Gelişme ve Küreselleşme | Sağlık Sosyolojisi

Dergi:

OPUS Toplum Araştırmaları Dergisi Vol.22 Issue 1, pp.23-32

Belge Tipi:

Makale

Yayın Tarihi:

12/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001341182

pISSN:

2791-9862

Anahtar kelimeler:

Özet:

 This study aims to elucidate the interdependent effects of the challenges and risks of using artificial intelligence in the healthcare sector. The ten challenges and risks obtained by literature were assessed by five professionals involved in managing health. Participants were selected based on having at least ten years of academic or professional experience in health. The participants made their judgments on the topic of structured forms. DEMATEL The Decision-Making Trial and Evaluation Laboratory technique investigated the cause-effect relationships between the identified integration challenges. According to DEMATEL analysis results in terms of the degree of importance, safety and security risk SSR is ranked in the first place, and inadequate patient risk assessments IPRA, data quality risks DQR, verifiability risks VR, stakeholders perceived mistrust SPM, integration challenges IC, ethical considerations EC, algorithmdecision-making bias AMB and job displacement risks JDR are ranked in the following places. In addition, DQR, AMB, SSR, VR, IPRA, and DPR are causal variables; EC, IC, JDR, and SPM are regarded as effects. These factors highlight the need for robust mechanisms to ensure the integrity of data, the accuracy of risk assessments, and the transparency of the decision-making processes of AI. Negative impacts on ethics, inclusion, employment, and trust between stakeholders will likely be reduced by addressing the root causes, such as data quality, risk assessment, and algorithmic bias, and developing policies to address them.

 This study aims to elucidate the interdependent effects of the challenges and risks of using artificial intelligence in the healthcare sector. The ten challenges and risks obtained by literature were assessed by five professionals involved in managing health. Participants were selected based on having at least ten years of academic or professional experience in health. The participants made their judgments on the topic of structured forms. DEMATEL The Decision-Making Trial and Evaluation Laboratory technique investigated the cause-effect relationships between the identified integration challenges. According to DEMATEL analysis results in terms of the degree of importance, safety and security risk SSR is ranked in the first place, and inadequate patient risk assessments IPRA, data quality risks DQR, verifiability risks VR, stakeholders perceived mistrust SPM, integration challenges IC, ethical considerations EC, algorithmdecision-making bias AMB and job displacement risks JDR are ranked in the following places. In addition, DQR, AMB, SSR, VR, IPRA, and DPR are causal variables; EC, IC, JDR, and SPM are regarded as effects. These factors highlight the need for robust mechanisms to ensure the integrity of data, the accuracy of risk assessments, and the transparency of the decision-making processes of AI. Negative impacts on ethics, inclusion, employment, and trust between stakeholders will likely be reduced by addressing the root causes, such as data quality, risk assessment, and algorithmic bias, and developing policies to address them.

 This study aims to elucidate the interdependent effects of the challenges and risks of using artificial intelligence in the healthcare sector. The ten challenges and risks obtained by literature were assessed by five professionals involved in managing health. Participants were selected based on having at least ten years of academic or professional experience in health. The participants made their judgments on the topic of structured forms. DEMATEL The Decision-Making Trial and Evaluation Laboratory technique investigated the cause-effect relationships between the identified integration challenges. According to DEMATEL analysis results in terms of the degree of importance, safety and security risk SSR is ranked in the first place, and inadequate patient risk assessments IPRA, data quality risks DQR, verifiability risks VR, stakeholders perceived mistrust SPM, integration challenges IC, ethical considerations EC, algorithmdecision-making bias AMB and job displacement risks JDR are ranked in the following places. In addition, DQR, AMB, SSR, VR, IPRA, and DPR are causal variables; EC, IC, JDR, and SPM are regarded as effects. These factors highlight the need for robust mechanisms to ensure the integrity of data, the accuracy of risk assessments, and the transparency of the decision-making processes of AI. Negative impacts on ethics, inclusion, employment, and trust between stakeholders will likely be reduced by addressing the root causes, such as data quality, risk assessment, and algorithmic bias, and developing policies to address them.

 Bu çalışma, sağlık sektöründe yapay zekânın kullanımına özgü zorlukların ve risklerin birbirine bağlı etkilerini ortaya koymayı amaçlamaktadır. Literatürden elde edilen on farklı zorluk ve risk, sağlık yönetiminde yer alan beş uzman tarafından değerlendirilmiştir. Katılımcılar, sağlık alanında en az on yıllık akademik veya profesyonel deneyime sahip olmalarına göre seçilmiştir. Katılımcılar konuyla ilgili değerlendirmelerini yapılandırılmış formlar üzerinden yapmıştır. Belirlenen entegrasyon zorlukları arasındaki neden-sonuç ilişkilerini araştırmak için DEMATEL tekniği kullanılmıştır. DEMATEL analizi sonuçlarına göre önem derecesi açısından emniyet ve güvenlik riski SSR ilk sırada yer alırken, yetersiz hasta risk değerlendirmeleri IPRA, veri kalitesi riskleri DQR, doğrulanabilirlik riskleri VR, paydaşların algıladığı güvensizlikler SPM, entegrasyon zorlukları IC, etik hususlar EC, algoritmakarar verme yanlılığı AMB ve iş değiştirme riskleri JDR sonraki sıralarda yer almaktadır. Ek olarak, DQR, AMB, SSR, VR, IPRA, DPR nedensel değişken olarak; EC, IC, JDR ve SPM ise etki olarak değerlendirilmiştir. Bu faktörler, verilerin bütünlüğünü, risk değerlendirmelerinin doğruluğunu ve yapay zekanın karar alma süreçlerinin şeffaflığını sağlamak için güçlü argümanlara olan ihtiyacı vurgulamaktadır. Etik, kapsayıcılık, istihdam ve paydaşlar arasındaki güven üzerindeki olumsuz etkiler, veri kalitesi, risk değerlendirmesi ve algoritmalardaki yanlılıklar gibi temel nedenlerin ele alınması ve bunlara yönelik politikaların geliştirilmesi ile azaltılabilir.

Makale detayları

Challenges for the Integration of Artificial Intelligence in Healthcare Services: A Decision-Making Approach

Yazarlar:

Erman Gedikli

Yayıncı:

İdeal Kent Yayınları

Ana Başlıklar:

Sosyal Politikada Bölgesel Gelişme ve Küreselleşme | Sağlık Sosyolojisi

Dergi:

OPUS Toplum Araştırmaları Dergisi Vol.22 Issue 1, pp.23-32

Belge Tipi:

Makale

Yayın Tarihi:

12/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001341182

pISSN:

2791-9862

Decision making

digital health technology

health services administrationDijital sağlık teknolojisi

karar verme

sağlık hizmetleri yönetimi

Sayı

Makale detayları

Challenges for the Integration of Artificial Intelligence in Healthcare Services: A Decision-Making Approach

Yazarlar: Erman Gedikli

Yayıncı: İdeal Kent Yayınları

Ana Başlıklar: Sosyal Politikada Bölgesel Gelişme ve Küreselleşme | Sağlık Sosyolojisi

Dergi: OPUS Toplum Araştırmaları Dergisi Vol.22 Issue 1, pp.23-32

Belge Tipi: Makale

Yayın Tarihi: 12/2025

Belge Dili: İngilizce

Document ID (Org No.): 2001341182

pISSN: 2791-9862

Decision making

digital health technology

health services administrationDijital sağlık teknolojisi

karar verme

sağlık hizmetleri yönetimi

Sayı

Yazarlar:

Erman Gedikli

Yayıncı:

İdeal Kent Yayınları

Ana Başlıklar:

Sosyal Politikada Bölgesel Gelişme ve Küreselleşme | Sağlık Sosyolojisi

Dergi:

OPUS Toplum Araştırmaları Dergisi Vol.22 Issue 1, pp.23-32

Belge Tipi:

Makale

Yayın Tarihi:

12/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001341182

pISSN:

2791-9862