Page 86 - GHES-3-3

Global Health Economics and
Sustainability
Global health care during COVID-19

continues to impact healthcare systems, pharmaceutical Thus, healthcare systems are strongly advised to adopt
industries, insurance providers, and patients. advancements in clinical decision-making and electronic
health record (EHR) systems (Shahmoradi et al., 2017).
4. Advanced applications in healthcare
systems Health sectors contain both clinical and non-clinical
administrative records, generating large amounts of data
Smart health care is a unique notion in the healthcare within the healthcare industry. The use of current technical
paradigm that incorporates numerous concepts, such as advancements has significantly transformed healthcare
medical informatics, advanced communication systems, operations, leading to substantial improvements across the
electronics, and biotechnology (Solanas et al., 2017). health sector. EHRs have created vast amounts of global
These systems have proven to be efficient and effective in medical data. Similar to other industries, the integration
addressing major challenges in the healthcare industry. of artificial intelligence (AI) has had a tremendously
Notably, the application of smart healthcare practices progressive impact on the healthcare industry. Sensors
played a significant role in tackling the COVID-19 crisis. are also used in a variety of applications, including
In today’s healthcare landscape, integrating modern, environmental monitoring, transportation, and healthcare
multidisciplinary principles is essential for ensuring medical device operations. Advanced technical applications
smooth system functionality. One such approach is for various critical clinical equipment and instruments are
Knowledge Management (KM), which has the potential to an essential component of the biomedical system, which
reorganize competency frameworks and better coordinate generates and stores patient clinical data. Furthermore,
resource utilization (Karamitri et al., 2015). The healthcare these databases provide robust support for clinical
industry is increasingly exploring KM as a means of decision-making. One notable development is the ability to
fostering rapid and significant development. However, KM analyze vast datasets to extract actionable insights, which
is a multidimensional approach in health care that involves has become increasingly thought-provoking and vital in
the processes of gathering, sharing, and implementing today’s data-driven healthcare landscape. The proposed
knowledge. For KM to be effective, it must be structured Meta Cloud-Redirection (MC-R) scheme is designed
to allow for the swift identification and distribution of to collect data from sensor devices (Manogaran et al.,
relevant information to the appropriate stakeholders, 2017). Big Data Analytics (BDA) plays a significant role
thereby strengthening decision-making capabilities and in healthcare management. With the volume of medical
strategic vision. These KM practices represent a critical data constantly expanding, healthcare administrators
aspect of the technological advancements driving modern are actively seeking data science professionals to manage
healthcare systems (Bordoloi & Islam, 2012). From the and interpret this information effectively. BDA, as an
standpoint of decision-makers, knowledge management operational instrument in health sectors, analyzes massive
is crucial. By analyzing relevant case studies, healthcare population-based mass data or epidemiological data,
administrators and clinicians can apply context-specific aiding in the development of strategic improvements in
information in real-time decision-making scenarios. healthcare system management (Galetsi et al., 2020). It may
Physicians, for instance, rely on such information to make significantly enhance functional performance by enabling
timely and informed clinical choices based on current needs forecasts and structured responses to public health risks,
and circumstances. Knowledge and intelligence resources including epidemics and pandemics. Moreover, it supports
in healthcare systems play a role in shaping value-driven more effective allocation of health resources, leading to
strategies. As KM evolves, its primary focus remains on improvements in both care quality and financial planning
resolving practical problems through the integration of (Nambiar et al., 2013). Researchers also place high value
precise technical support. Information systems and KM on Big Data and Predictive Analytics for their strategic
frameworks thus form the backbone of healthcare system importance in healthcare operations (Gunasekaran
development, providing robust support for both clinical et al., 2017). The Technology Acceptance Model (TAM)
and administrative functions (Myllärniemi et al., 2012). is increasingly used to expand health informatics and is
The use of KM in the healthcare system for decision- expected to continue to improve health organizations.
making is relatively new. For it to succeed, appropriate
methodologies and sustainable systems are necessary. Telemedicine is an example of TAM that has expanded
When applied effectively, it can significantly improve the rapidly in recent years (Rahimi et al., 2018).
quality and safety of health care for patients in hospitals Medical data have been organized using Business
and at home. Globally, the move toward evidence-based Intelligence (BI) to enhance clinical and health
medical practice underscores the importance of KM in management. BI has become a vital tool for organizations,
delivering optimal care; KM is critical in such situations. enabling them to process information more efficiently

Volume 3 Issue 3 (2025) 78 https://doi.org/10.36922/ghes.8492