Modelling vital success factors in adopting personalized medicine system in healthcare technology and management

• Main Authors: Subhas C. Misra, Sandip Bisui
• Format: Article
• Language: English
• Published: Elsevier 2018-06-01
• Series: Engineering Science and Technology, an International Journal
• Online Access: http://www.sciencedirect.com/science/article/pii/S2215098616309995

Biomedical engineering has grown as a vast field of research that includes many areas of engineering and technology also. Personalized Medicine is an emerging approach in today’s medicare system. It bears a very strong potential to consolidate modern e-health systems fundamentally. Scientists have already discovered some of the personalized drugs that can shift the whole medicare system into a new dimension. However, bringing the change in the whole medicare system is not an easy task. There are several factors that can affect the successful adoption of Personalized Medicine systems in the healthcare management sector. This paper aims at identifying the critical factors with the help of an empirical study. A questionnaire was distributed amongst some clinicians, clinical researchers, practitioners in pharmaceutical industries, regulatory board members, and a larger section of patients. The response data collected thereby were analyzed by using appropriate statistical methods. Based on the statistical analysis, an attempt is made to prepare a list of critical success factors in the adoption of personalized medicine in healthcare management. The study indicates that eight of the thirteen hypothesized factors have statistical relationship with “Success”. The important success factors detected are: data management, team work and composition, privacy and confidentiality, mind-set, return on investment, sufficient time, R&D and alignment. To the best of our knowledge, this is the first academic paper in which an attempt has been made to model the vital critical factors for the successful implementation of Personalized Medicine in healthcare management. The study bears the promise of important applications in healthcare engineering and technology. Keywords: Healthcare management, Personalized medicine, E-health, Success factors, Medicare systems, Regression analysis