Ethical Data Mining in Healthcare: Toward a Professionally Grounded Framework

Öz

The use of data mining technology in healthcare provides effective tools for resource management, therapy customization, and diagnosis. But there are also difficult ethical issues with their use. By critically analyzing important issues such algorithmic bias, patient autonomy, data ownership, and informed permission, this study offers a conceptual framework for ethical data mining in the healthcare industry. The framework places a strong emphasis on responsibility, transparency, and equity while building upon the moral obligations of healthcare workers and the fundamental ideas of bioethics. The purpose of this work is to assist physicians, data scientists, and policymakers in using data mining techniques in medical settings while making morally correct choices.

Anahtar Kelimeler

• data mining
• healthcare ethics
• algorithmic bias
• informed consent
• data ownership
• professional responsibility
• medical AI

Sağlık Hizmetlerinde Etik Veri Madenciliği: Mesleki Temellere Dayalı Bir Çerçeveye Doğru

Öz

Veri madenciliği teknolojileri, günümüz sağlık hizmetlerinde klinik karar verme, bireyselleştirilmiş tedavi ve sağlık sistemlerinin optimizasyonunu kolaylaştırarak önemli bir nokta haline gelmiştir. Bununla birlikte, entegrasyonları, teknik performans ve yasal uyumlulukla sınırlı olmayan uzun süredir devam eden etik sorunları da beraberinde getirmektedir. Bu çalışma, biyomedikal etik, profesyonel tıp standartları ve bilgi etiğinde sunulan bilgilerin sentezi yoluyla, sağlık hizmetlerinde veri madenciliğine ilişkin kavramsal temelli bir etik çerçeve sunmaktadır. Son literatürün bütünleyici nitel bir incelemesine dayanan analiz, algoritmik önyargı, hasta özerkliğinin aşınması, bilgilendirilmiş onamın sınırlılıkları, veri sahipliği sorunları ve kurumsal hesap verebilirlik açıkları gibi tekrarlayan etik sorunların belirlenebileceğini ortaya koymaktadır. Bu sonuçlara dayanarak, önerilen çerçeve, etik hususların temel direkleri olarak profesyonel sorumluluk, tasarım yoluyla şeffaflık, bağlamsal onam ve eşitlik odaklı denetimi belirlemektedir. Araştırma, veri odaklı yeniliği hasta merkezli değerler ve etik sağlık hizmeti sunumuyla uyumlu hale getirmek için klinisyenler, veri bilimciler ve politika yapıcılar tarafından kullanılması gereken profesyonel temelli bir yol haritası sunmaktadır.

Anahtar Kelimeler

• Veri Madenciliği
• Sağlık Etiği
• Algoritmik Önyargı
• Bilgilendirilmiş Onam
• Veri Sahipliği
• Mesleki Sorumluluk
• Tıbbi Yapay Zekâ

Kaynakça

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