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

Erman Gedikli

doi:10.26466/opusjsr.1583315

EN TR

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

Abstract

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), algorithm/decision-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.

Keywords

Decision making , digital health technology , health services administration

Yapay Zekanın Sağlık Hizmetlerine Entegrasyonunda Karşılaşılan Zorluklar: Bir Karar Verme Yaklaşımı

Öz

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), algoritma/karar 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.

Anahtar Kelimeler

Dijital sağlık teknolojisi , karar verme , sağlık hizmetleri yönetimi

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Details

Primary Language

English

Subjects

Regional Development and Globalisation in Social Policy , Sociology of Health

Journal Section

Research Article

Authors

Erman Gedikli ^*
0000-0002-5508-194X
Türkiye

Early Pub Date

February 16, 2025

Publication Date

February 12, 2025

Submission Date

November 12, 2024

Acceptance Date

February 5, 2025

Published in Issue

Year 1970 Volume: 22 Number: 1

DOI

https://doi.org/10.26466/opusjsr.1583315

IZ

https://izlik.org/JA42MY66DM

APA

Gedikli, E. (2025). Challenges for the Integration of Artificial Intelligence in Healthcare Services: A Decision-Making Approach. OPUS Journal of Society Research, 22(1), 23-32. https://doi.org/10.26466/opusjsr.1583315

Cited By

Prioritization of Social Impacts of Artificial Intelligence-Based Automation Systems on Healthcare Workers in Healthcare Institutions Using the AHP Method

Verimlilik Dergisi

https://doi.org/10.51551/verimlilik.1746569