This chapter carried out a scoping review on cloud computing and its innovative possibilities in the use and application in medical laboratory services. While cloud computing offers numerous benefits including access to large laboratory data storage and large data processing power on demand, movement of electronic medical laboratory data through large data sets, data sharing, and access to medical laboratory results, especially to authorized medical laboratory clients and patients from different geographic locations, large data analysis public health actionable insights, and ample opportunity for retrospective and review studies on available laboratory data, the challenges such as interoperability and portability, security, and ethical issues must be addressed. Cloud brokers have emerged as mediators, linking cloud users and providers, and managing resource sharing while supporting interoperability and portability.
Top1. Introduction
Health systems around the globe are experiencing unprecedented challenges. These include human resource shortages, financial constraints, ageing populations often living with multiple non-communicable diseases (NCDs), and rising social inequalities that cause disparities in health risks and outcomes (WHO, 2010). Faced with these pressures, health system leaders are grappling with how to develop more resilient, sustainable and efficient health systems while simultaneously delivering person-centered, equitable and high-quality care to all. Also, the healthcare industry especially the Medical Laboratory Services including genomics, generates enormous amounts of data, which require effective handling, storage, and analysis. The exponential growth of technology-driven devices has resulted in an abundance of healthcare data, including data from mobile phones, sensors devices, electronic health records (EHR), and various other sources. This data has the potential to be used for preventive diagnostics and prognostics of disease occurrence and outcomes, significantly enhancing human welfare. However, managing and processing this data can be a daunting task.
The healthcare sector is complex and comprises various interconnected features, including health insurance, hospitals, clinics, medical laboratories, and doctor networks, among other healthcare professionals including medical laboratory scientists (Ahuja, Mani and Zambrano, 2012). This industry faces significant challenges, such as the need for data security to protect patients’ health records while complying with Health Insurance Portability and Accountability Act (HIPAA) regulations, as well as the increasing costs of healthcare solutions. The conventional healthcare architecture requires a shift to more innovative approaches to manage the growing volume of medical/ medical laboratory data that includes both homogeneous and heterogeneous data depicted (Benhlima, 2018).
Addressing these challenges requires an approach that is both comprehensive and data driven. Cloud technology (‘the cloud’) is a key enabler of this data-driven approach. This is important as both care delivery and health-related research are more data intensive and collaborative than ever, and the processes of collecting, combining, storing, analyzing and exchanging these data require computational power and speed that far exceed ordinary on-premises capabilities. According to Smith and Shirer (2018), cloud computing models have revolutionized several sectors, including the computer industry. As early as 2011, it was predicted that more than 80% of businesses worldwide would adopt cloud computing by 2020, and in 2019, ‘‘451 Research’’ reported that 90% of companies were already on the cloud, indicating its mainstream adoption (Goyal, 2014). Furthermore, International Data Corporation (IDC) statistics reveal the countries’ spending on cloud computing technologies in 2019.
The United States is considered one of the largest public cloud markets, with an estimated $124.6 billion in spending in 2019. The global cloud computing market is expected to reach $623.3 billion by 2023 (Goyal, 2014). Cloud computing offers a promising solution to these challenges. While cloud computing and bioinformatics can provide significant benefits and new opportunities in healthcare, data privacy, security, and management concerns are significant challenges that must be addressed. Not only does it offer significantly larger amounts of virtual capacity than on-premises systems, it also allows for a flexible approach to computing and data storage, offering scalability and efficiency.
Organizations must implement robust security measures to protect sensitive patient information and ensure regulatory compliance. Additionally, proper data management practices and training for healthcare professionals are necessary to maximize the potential of cloud computing in bioinformatics. Ultimately, the adoption of cloud computing in bioinformatics will pave the way for more personalized and effective healthcare, benefiting patients and healthcare professionals’ alike (Phillips et al., 2014).
Despite this potential, the adoption of cloud technology is at its infancy in healthcare compared with other sectors, and several barriers to optimizing its use remain. Lack of general knowledge and understanding of the cloud, as well as perceived risks related to privacy and security, are important first barriers to address. Hence, the need to review comprehensively on the innovative cloud computing for Medical laboratory data storage and analysis.