A mix of growing economic concerns, rising inflation and staff burnout, is leading healthcare organizations (HCOs) to invest heavily in IT system modernization. Cloud applications and services are bringing the benefits of the cloud to the healthcare industry including scalability to serve variable workloads, accelerating the speed of innovation, access to the latest security and infrastructure technology and big data diagnostics and analytics.
Cloud computing in healthcare: What is it?
Cloud computing in healthcare refers to the use of remote servers hosted on the Internet to store, manage, and process health data. This approach allows HCOs to access and utilize computing resources and data storage without the need for on-site hardware and infrastructure. One of the key advantages of cloud computing in healthcare is the ability to handle large volumes of data, such as patient records, medical imaging, and genomic information, in a scalable and cost-effective manner.
For example, a major hospital might use cloud-based services to store and analyze patient medical records, enabling doctors and nurses to remotely access real-time patient information. Cloud computing allows HCOs to offer telehealth services, where healthcare professionals can remotely diagnose and treat patients, making healthcare more accessible, especially in rural or underserved areas. Technical maturity in cloud healthcare will allow healthcare providers to accelerate innovation in areas such as genomic sequencing, drug discovery, health data exchange and more.
Key technology drivers of cloud computing in healthcare organizations
The adoption of cloud computing in healthcare is primarily driven by its ability to scale services according to demand, offer advanced data analytics capabilities, and reduce operational costs. However, this transition must carefully address critical issues such as ensuring robust data security to protect sensitive patient information, maintaining compliance with healthcare regulations like HIPAA, and guaranteeing reliable internet infrastructure for uninterrupted service delivery. These factors are key in leveraging cloud computing's full potential while safeguarding patient trust and the efficacy of healthcare services.
Let’s look at some of the key drivers of cloud computing in healthcare:
Data storage and scalability:
With the cloud, HCOs get access to scalable storage solutions, that are crucial to deal with electronic health records (EHRs), imaging files, and genomic data. The cloud's scalability allows for the storage of large datasets without the need for significant physical infrastructure investments. With cloud transformation, healthcare providers can introduce improvements in security, disaster recovery and business resilience without investing heavily in IT infrastructure.
Improved data analytics and AI integration:
Cloud for healthcare facilitates advanced data analytics and artificial intelligence (AI) capabilities. Healthcare providers can leverage cloud applications and services for predictive analytics, patient data analysis, and decision-making.
Enhanced collaboration and information sharing:
Presently, most healthcare data is unstructured, making it difficult to integrate and exchange data across multiple platforms. With digital health platforms, healthcare providers can seamlessly exchange data across healthcare systems, schedule events and interface with patients. This interoperability is crucial for collaborative research, sharing data from imaging systems, and aiding comprehensive patient care.
Cost efficiency:
HCOs are adopting the cloud to reduce upfront capital investments in hardware and infrastructure. Advanced virtualization technology allows multiple virtual machines to run on single physical hardware, optimizing resource usage and reducing the need for extensive physical infrastructure. Dynamic scalability of resource utilization, combined with containerization and microservices architecture, enables easier deployment, scaling, and management of applications. The pay-as-you-go model is cost-effective, especially for smaller healthcare providers or those looking to reduce IT expenditures.
Mobility and remote access:
Mobility and remote access in healthcare, facilitated by internet connectivity, allow healthcare professionals to retrieve patient data and utilize applications from any location. Leveraging IoT devices, edge computing, and cloud services, healthcare organizations can obtain real-time data crucial for managing assets, in-hospital patient care, ambulatory support, and supply chain management. This aspect of mobility is especially advantageous for telehealth services and delivering care in remote or underserved regions.
Regulatory compliance and data security:
Healthcare organizations (HCOs) are mandated to follow strict regulations like HIPAA in the U.S., and cloud providers support compliance by offering advanced security measures, including military-grade data encryption like AES and TLS to protect data both at rest and in transit. Cloud-native applications are specifically designed to securely manage and transmit sensitive patient data, incorporating strong encryption, rigorous access controls, and consistent security updates. Robust security and compliance in handling patient data is not just a regulatory necessity but instills trust and resilience in the digital healthcare landscape.
Healthcare cloud computing: Analysis and trends
Healthcare organizations (HCOs) are mandated to follow strict regulations like HIPAA in the U.S., and cloud providers support compliance by offering advanced security measures, including military-grade data encryption like AES and TLS to protect data both at rest and in transit. Cloud-native applications are specifically designed to securely manage and transmit sensitive patient data, incorporating strong encryption, rigorous access controls, and consistent security updates. Robust security and compliance in handling patient data is not just a regulatory necessity but instills trust and resilience in the digital healthcare landscape.
Edge computing
The introduction of edge computing is allowing HCOs to process data at the network's edge, speeding up data monitoring, tracking and analytics in real time. This proximity reduces latency and accelerates data processing, which is crucial in supplementing real-time applications such as patient monitoring and emergency response. By processing data in real time, edge computing minimizes the volume of sensitive patient data transmitted over a network, reducing exposure to potential breaches.
Edge computing's role in remote care and telemedicine is gaining prominence, where it speeds up data collection and analysis from IoT devices and biomedical equipment. This capability ensures that healthcare professionals can make quicker, more informed decisions, even in remote or resource-limited settings. In hospital environments, edge computing aids in real-time asset tracking and management, streamlining resource allocation and enhancing patient care efficiency. The synergy of edge computing with technologies like Kubernetes further empowers HCOs to collaborate with cloud technology providers for rapid innovation.
Philips partnered with AWS to shift from a traditional inpatient healthcare setting to a more efficient, home-based care model using cloud technology. By adopting AWS cloud services, Philips was able to connect devices, store and analyze health data more effectively, reducing hospitalizations, care costs, and improving patient care quality.
Enterprise health cloud
An enterprise health cloud is a specialized platform designed to meet the unique needs of healthcare organizations such as compliance with healthcare regulations, secure data management, and support for healthcare applications. Enterprise health clouds are integrated platforms that combine electronic health records, patient management systems, telemedicine, and other healthcare applications to streamline operations, improve patient care, and facilitate data sharing across different healthcare services. Enterprise health clouds help HCOs tackle common challenges, reduce CapEx and OpEx, and streamline communication between departments.
Cloud healthcare platforms offer advanced data analytics and AI capabilities for insights into patient data, improving diagnostic accuracy, personalizing treatment plans, and predicting patient outcomes. They provide scalable solutions that can adapt to the changing needs of healthcare organizations, accommodating fluctuating data volumes and patient loads without compromising performance.
Saudi Arabia has adopted a multi-cloud approach to modernize healthcare services for the ‘Vision 2030 and Health Sector Transformation Program’. Implementing VMware Cloud Foundation, a hybrid cloud platform, the Ministry of Health (MoH) has transformed IT operations across numerous healthcare facilities, enhancing system resilience and operational efficiency.
Predictive medical care
Predictive analytics uses patient data to tailor healthcare to individual needs through a combination of data analytics, machine learning, and artificial intelligence (AI), all hosted in the cloud. This wealth of patient data leads to faster and more accurate diagnoses and predictive models that can determine an individual's risk of hospitalization. By analyzing patterns in medical history, genetics, and lifestyle, healthcare providers can develop personalized treatment and prevention plans, improving patient outcomes. Cloud computing in healthcare has enabled HCOs to move past pen-and-paper-based methods and process thousands of data points every day with advanced analytical capabilities.
Cloud-based AI algorithms analyze large datasets of medical information to identify early signs of diseases like cancer or diabetes, often before symptoms are clinically apparent. This early detection can lead to more timely and less invasive treatments. In fact, predictive models also help optimize resource allocation by forecasting patient inflows, identifying potential high-risk patients, and preparing for epidemic outbreaks leading to better preparedness and efficiency in healthcare delivery.
The Department of Veteran Affairs’ partnership with Google’s Deepmind to enhance patient care through predictive analytics is an interesting case in point. This collaboration focused on analyzing 700,000 anonymized health records to develop an algorithm predicting acute kidney injuries' onset.
Cloud for healthcare: Use cases
According to Forrester’s Infrastructure Cloud Survey, 2022, 88% of HCO decision-makers globally are adopting cloud for healthcare. HCOs are leveraging cloud computing in healthcare to accelerate innovation and deliver use cases ranging from leading-edge research and remote patient monitoring to population health management and medical imaging. However, each use case brings its own set of challenges and ethical considerations, particularly around data security, privacy, accessibility and ethical use of data.
Edge computing
The introduction of edge computing is allowing HCOs to process data at the network's edge, speeding up data monitoring, tracking and analytics in real time. This proximity reduces latency and accelerates data processing, which is crucial in supplementing real-time applications such as patient monitoring and emergency response. By processing data in real time, edge computing minimizes the volume of sensitive patient data transmitted over a network, reducing exposure to potential breaches.
Edge computing's role in remote care and telemedicine is gaining prominence, where it speeds up data collection and analysis from IoT devices and biomedical equipment. This capability ensures that healthcare professionals can make quicker, more informed decisions, even in remote or resource-limited settings. In hospital environments, edge computing aids in real-time asset tracking and management, streamlining resource allocation and enhancing patient care efficiency. The synergy of edge computing with technologies like Kubernetes further empowers HCOs to collaborate with cloud technology providers for rapid innovation.
Philips partnered with AWS to shift from a traditional inpatient healthcare setting to a more efficient, home-based care model using cloud technology. By adopting AWS cloud services, Philips was able to connect devices, store and analyze health data more effectively, reducing hospitalizations, care costs, and improving patient care quality.
Enterprise health cloud
An enterprise health cloud is a specialized platform designed to meet the unique needs of healthcare organizations such as compliance with healthcare regulations, secure data management, and support for healthcare applications. Enterprise health clouds are integrated platforms that combine electronic health records, patient management systems, telemedicine, and other healthcare applications to streamline operations, improve patient care, and facilitate data sharing across different healthcare services. Enterprise health clouds help HCOs tackle common challenges, reduce CapEx and OpEx, and streamline communication between departments.
Cloud healthcare platforms offer advanced data analytics and AI capabilities for insights into patient data, improving diagnostic accuracy, personalizing treatment plans, and predicting patient outcomes. They provide scalable solutions that can adapt to the changing needs of healthcare organizations, accommodating fluctuating data volumes and patient loads without compromising performance.
Saudi Arabia has adopted a multi-cloud approach to modernize healthcare services for the ‘Vision 2030 and Health Sector Transformation Program’. Implementing VMware Cloud Foundation, a hybrid cloud platform, the Ministry of Health (MoH) has transformed IT operations across numerous healthcare facilities, enhancing system resilience and operational efficiency.
Predictive medical care
Predictive analytics uses patient data to tailor healthcare to individual needs through a combination of data analytics, machine learning, and artificial intelligence (AI), all hosted in the cloud. This wealth of patient data leads to faster and more accurate diagnoses and predictive models that can determine an individual's risk of hospitalization. By analyzing patterns in medical history, genetics, and lifestyle, healthcare providers can develop personalized treatment and prevention plans, improving patient outcomes. Cloud computing in healthcare has enabled HCOs to move past pen-and-paper-based methods and process thousands of data points every day with advanced analytical capabilities.
Edge computing's role in remote care and telemedicine is gaining prominence, where it speeds up data collection and analysis from IoT devices and biomedical equipment. This capability ensures that healthcare professionals can make quicker, more informed decisions, even in remote or resource-limited settings. In hospital environments, edge computing aids in real-time asset tracking and management, streamlining resource allocation and enhancing patient care efficiency. The synergy of edge computing with technologies like Kubernetes further empowers HCOs to collaborate with cloud technology providers for rapid innovation.
Philips partnered with AWS to shift from a traditional inpatient healthcare setting to a more efficient, home-based care model using cloud technology. By adopting AWS cloud services, Philips was able to connect devices, store and analyze health data more effectively, reducing hospitalizations, care costs, and improving patient care quality.
Cloud for healthcare: Use cases
According to Forrester’s Infrastructure Cloud Survey, 2022, 88% of HCO decision-makers globally are adopting cloud for healthcare. HCOs are leveraging cloud computing in healthcare to accelerate innovation and deliver use cases ranging from leading-edge research and remote patient monitoring to population health management and medical imaging. However, each use case brings its own set of challenges and ethical considerations, particularly around data security, privacy, accessibility and ethical use of data.
Predictive medical care
An EHR system is a centralized platform for storing and managing patient records. Cloud-based EHRs enable real-time access to patient records from any location, ensuring that critical health information is readily available during patient care. Healthcare facilities can adjust their storage needs based on patient volume, without needing to invest heavily in IT infrastructure for data storage.
In case of local data losses due to hardware failures or natural disasters, cloud data backup and recovery keep patient information secure. HCOs can integrate EHRs with analytics tools for valuable insights on patient data, disease tracking, population health management, and informed decision-making in healthcare policies and practices.
Telemedicine and remote patient monitoring
Healthcare providers leverage cloud healthcare to offer remote consultations and patient monitoring. This is particularly beneficial for patients in remote areas, those with mobility issues, or those who are immunocompromised and at higher risk of infection in public spaces.
For remote health monitoring, HCOs use IoT and biomedical devices to collect patient data, such as heart rate, blood pressure, and glucose levels, and transmit this information to care providers via cloud platforms. Telemedicine and remote patient monitoring play a vital role in managing chronic conditions, post-operative care, and elderly care, allowing for timely interventions.
During the COVID-19 pandemic, Teladoc Health, a telemedicine company, utilized cloud computing to provide virtual healthcare services. Teladoc’s cloud transformation allowed them to address rising demand and deliver virtual care to approximately 20,000 patients per day.
Medical imaging and analytics
With cloud-based platforms, healthcare professionals can store vast amounts of medical imaging data, such as X-rays, MRI scans, and CT scans in a centralized database. The computational power of the cloud, combined with AI/ML enables more accurate and faster image analyses, assisting in early and precise diagnoses. Cloud-based medical imaging systems can be integrated with EHRs to provide a comprehensive view of a patient's medical history and diagnostic information.
GE Healthcare's Edison platform embeds artificial intelligence and medical imaging capabilities within existing workflows for greater efficiency and increased access to care. The platform allows radiologists to remotely access and analyze medical images, generating clinical, operational and even financial insights.
Research and development
Access to the cloud has accelerated medical research by providing scalable and robust resources for handling extensive biomedical datasets, including genomic information, clinical trial data, and patient health records. Cloud services enable researchers to effectively manage and access large-scale biomedical data sets, facilitating complex analyses that were once constrained by computational limitations.
The cloud's capacity for efficient data sharing creates a more collaborative and open research environment, essential for multi-center studies and global health initiatives. Researchers can now engage in sophisticated tasks like bioinformatics, computational biology, and advanced modeling and simulations without the need for substantial IT infrastructure investments.
The National Institutes of Health (NIH) in the United States leverages cloud computing for its BRAIN Initiative. This project involves massive data collection and analysis to understand brain function, and cloud computing provides the necessary infrastructure to manage and analyze this data.
Population health management
Cloud-based analytics tools support population health management by processing and analyzing vast amounts of data from various sources, including EHRs, wearable devices, and social determinants of health.
- Population stratification: Health institutions are leveraging the cloud to segment the population into subgroups based on various health indicators and demographics, enabling targeted healthcare interventions and resource allocation.
- Risk stratification: Cloud-based analytics tools assist in stratifying populations based on risk factors, social determinants, and health behaviours. This enables healthcare organizations to tailor interventions to specific subgroups and allocate resources more efficiently.
- Chronic disease management: Population health analytics on the cloud support the identification of individuals with chronic conditions, facilitating targeted interventions, care coordination, and preventive measures. Continuous monitoring and data analysis are crucial for governments to effectively manage public health concerns.
- Patient portals: Cloud solutions enable the development of patient portals for engagement, allowing individuals to access their health information, participate in shared decision-making, and receive educational resources.
- Public health strategies: The cloud provides a robust platform for analyzing health trends and outcomes on a large scale, aiding governments and HCOs in developing effective public health strategies and policies to address widespread health issues.
Cloud-based analytics tools support population health management by processing and analyzing vast amounts of data from various sources, including EHRs, wearable devices, and social determinants of health.
Risks associated with cloud computing in healthcare
The major concerns with the adoption of cloud computing in healthcare revolve around the risk of compliance failure, data integration issues and data privacy concerns.
Let’s look at some of the major risks associated with cloud computing in healthcare:
Data security and regulatory compliance
One of the primary concerns associated with cloud healthcare services is the security and privacy of patient data. Healthcare data is highly sensitive and subject to strict regulations like HIPAA in the United States – between 2018 and 2021, fines and settlements for HIPAA violations totaled over $60 million. Cloud storage increases the risk of breaches and unauthorized access. Ensuring data encryption, secure access controls, and compliance with regulatory standards is crucial but challenging.
One of the primary concerns associated with cloud healthcare services is the security and privacy of patient data. Healthcare data is highly sensitive and subject to strict regulations like HIPAA in the United States – between 2018 and 2021, fines and settlements for HIPAA violations totaled over $60 million. Cloud storage increases the risk of breaches and unauthorized access. Ensuring data encryption, secure access controls, and compliance with regulatory standards is crucial but challenging.
Competition from hyperscalers
The nationwide expansion of Amazon Care, Amazon’s telehealth service, has triggered concerns among technology providers that they may lose market share to a cloud hyperscaler with advanced medical care models. Hyperscalers such as Amazon Web Services (AWS) have extensive resources, infrastructure, and investment capabilities, enabling them to rapidly scale and offer a wide range of services.
Both payers and payees are not comfortable with the prospect of entrusting sensitive patient data to large, multi-industry tech companies. While hyperscalers offer broad and powerful healthcare cloud services, healthcare providers often require specialized solutions tailored to their unique needs, including compliance with specific healthcare regulations and integration with existing healthcare systems. Partnering with large hyperscalers can also lead to vendor lock-in, where healthcare organizations become overly dependent on a single provider for infrastructure and services. This can limit their flexibility and bargaining power while transitioning to another provider can be costly and complex.
Navigating data standardization and interoperability
Integrating healthcare cloud solutions with existing on-premise systems and ensuring interoperability among different healthcare systems can be complex. With a majority of medical devices using their own proprietary language protocol, interoperability has been a recurring concern. Interoperability is essential for seamless data exchange and to provide effective patient care, but achieving this with various standards and formats is often a significant hurdle.
Both payers and payees are not comfortable with the prospect of entrusting sensitive patient data to large, multi-industry tech companies. While hyperscalers offer broad and powerful healthcare cloud services, healthcare providers often require specialized solutions tailored to their unique needs, including compliance with specific healthcare regulations and integration with existing healthcare systems. Partnering with large hyperscalers can also lead to vendor lock-in, where healthcare organizations become overly dependent on a single provider for infrastructure and services. This can limit their flexibility and bargaining power while transitioning to another provider can be costly and complex.
Healthcare cloud services: Why choose Torry Harris for cloud computing services
Torry Harris Integration Solutions (THIS) presents a comprehensive and strategic approach for healthcare organizations aspiring to modernize and digitize their operations. Our expertise in deploying advanced digital technologies, coupled with an in-depth understanding of pressing challenges in healthcare, positions us to facilitate a seamless digital transition for your organization.
Our suite of solutions is designed to not only enhance patient care through innovation but also to optimize operational efficiencies and fortify data security, all while ensuring strict adherence to healthcare regulatory standards. From integrating AI-powered analytics to navigating the complexities of interoperability and bolstering the security of sensitive patient data, our team at THIS is committed to delivering tailored solutions that address your unique needs.
Interested in learning more about how we can assist your organization in its healthcare digital transformation journey? Contact us to explore how we can collaboratively revolutionize your healthcare systems.
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Umesh BhoraleContent StrategistTorry Harris Integration Solutions |
