Would Artificial Intelligence Improve the Quality of Care of Patients With Rare Diseases?

Abstract

Rare diseases are characterized by low prevalence, they affect 4-5 patients per 10,000 people, which results in a lack of knowledge, guidelines, training, and diagnostic complexities among clinicians. This significantly burdens the healthcare systems and negatively hinders the quality and patient safety. There are 5000-8000 identified rare diseases affecting more than 350 million people worldwide; of these, 75% affect children, and 80% are genetically based. Most patients with rare diseases have experienced a diagnostic odyssey through the prolonged journey of late diagnosis, which can take several years and incur substantial cost estimated at $US 1 trillion. Nevertheless, the conclusion of their search for a diagnostic journey is usually followed by the beginning of another one, the "therapeutic odyssey"! A few examples of rare diseases are Huntington's disease, Sickle cell disease, Gaucher disease, and hemophilia. Neoplastic diseases are the most prevalent rare diseases (59%), followed by developmental, neurological, and circulatory diseases. Proper management of these diseases leads to early intervention, prevention of deterioration, and enhances patients' quality of life. This commentary aims to enlighten quality-focused clinicians on the substantial quality gap experienced by patients with rare diseases, and to explore the transformative power of artificial intelligence (AI) applications to improve the quality of healthcare services.

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