Healthcare Fusion: An Innovative Framework for Health Information Management

Authors

  • Kevin Zhai Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar https://orcid.org/0000-0003-2556-5641
  • Nasseer A. Masoodi Hamad Medical Corporation, Doha, Qatar
  • Lan Zhang BAE Systems Inc., Nashua, NH, USA
  • Mohammad S. Yousef Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
  • M. Walid Qoronfleh 21HealthStreet Company, London, UK

DOI:

https://doi.org/10.34190/ejkm.20.3.2968

Keywords:

healthcare fusion, big data, ROBIN, medical records, machine learning, artificial intelligence, cloud computing, precision medicine, population health

Abstract

Perhaps the main goal of healthcare management is the attainment of effective, efficient, equitable, timely, safe, and patient-centered care. At the core of this lies the need for an integrated pathway for healthcare data storage, analysis, and utilization. The potential exists for a centralized, cloud-based system that links physicians, hospitals, public health agencies, insurance and pharmaceutical companies, and most importantly, patients. Such a system could improve clinical quality management and support the delivery of consistent and effective treatments. Undoubtedly, massive integration of personalized health and large-scale epidemiological and molecular data, coupled with the use of artificial intelligence and machine learning, is already in process. Here, we envision the healthcare fusion framework, which unites all stakeholders in healthcare. This fusion aims to achieve culturally and demographically relevant outcomes in precision medicine and population health, in ways that are convincing to stakeholders and investors. In addition, the proposed framework may prove relevant in informing governmental and private sector responses to sudden public health crises. 

Downloads

Published

16 Dec 2022

Issue

Section

Special issue on A Brave Post Covid World