How prescriptive analytics influences decision making in precision medicine

• Autor(a) principal: Mosavi, Nasimsadat
• Data de Publicação: 2020
• Outros Autores: Santos, Manuel
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/1822/71877
• topic: Prescriptive; Precision Medicine; Healthcare; Analytics; Medical Decision Making; Healthcare analytics; Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática

Failure of the old model of medical decision making, “one-size-fits-all”, has encouraged the healthcare/medicine landscape to take advantage of big data and analytics for tailoring the treatments[1], based on individual patient’s differences in gen, environment, and lifestyle [2]. Whereas literature has demonstrated a strong contribution to the adoption of healthcare analytics over patient’s data, for better decision making [3], understanding the level and the degree that each type of analytics influences decision making, is crucial for addressing the type of problems [4]. While descriptive, diagnostic, and predictive analytics generate knowledge for decision support systems, prescriptive analytics recommends a proactive decision[5]. This study aims to highlight the influential and effective role of prescriptive analytics for fulfilling precision medicine which is defined as an emerging approach in medical decision making .