Learn how AWS technologies help healthcare providers, payers, and healthtech organizations enhance patient care, streamline operations, and secure data with advanced cloud solutions.
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Brian is an AWS Community Hero, Alexa Champion, runs the Boston AWS User Group, has ten US patents and a bunch of certifications. He's also part of the New Voices mentorship program where Heros teach traditionally underrepresented engineers how to give presentations. He is a private pilot, a rescue scuba diver and got his Masters in Cognitive Psychology working with bottlenosed dolphins.
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Kimberly Schaefer is a Principal Strategist at Caylent, focused on healthcare and life sciences. Offering a unique blend of hands-on nursing experience and extensive expertise in healthcare technology, Kimberly is skilled in turning complex healthcare challenges into actionable, technology-enabled solutions that drive measurable outcomes. With a deep understanding of both clinical workflows and business imperatives, she specializes in leveraging data and innovation to deliver competitive advantages for healthcare organizations. Kimberly is passionate about advancing the healthcare industry through strategic problem-solving, collaboration, and the application of cutting-edge technologies.
View Kimberly's articlesModern healthcare applications built on AWS are transforming data management and utilization in the healthcare sector. This article will examine how AWS technologies enable healthcare providers, payers, and healthtech organizations to improve patient care, streamline operations, and maintain data security through advanced cloud solutions.
We live in a world that is generating data at an exponential rate, with healthcare data accounting for 36% of all data. With no end to this growth in sight, data holds immense opportunity for healthcare and life science organizations to tap into to meet their goals of better health population outcomes, better patient experiences, and better cost realization.
Creating value from healthcare data requires rigorous processing, capturing, and storing capabilities to comply with its strict usability criteria. Understanding the importance of managing high-quality data is essential for creating a competitive advantage and positioning your organization to anticipate and react to changing market dynamics.
When dealing with healthcare data, the stakes are high. At an average investment of $2 billion to bring a drug to market, poor-quality data can jeopardize the successful development or launch of therapy, potentially denying patients access to essential treatments. Conversely, high-quality data can lead to personalized treatments, exemplified by the groundbreaking services offered by cancer genomics companies.
Next-gen solutions, like those powered by artificial intelligence (AI) and machine learning (ML), leverage models that can digest large amounts of historical data to find patterns that reveal meaningful insights. These models perform better with larger amounts of high-quality training data because they can be sensitive to outliers and anomalies.
These insights can revolutionize patient care experiences by contributing to:
With over 150 HIPAA-eligible services and purpose-built solutions, AWS offers a secure platform for HCLS companies to reinvent their digital systems to improve patient experiences. These services are HIPAA-eligible and integrated into the AWS ecosystem, creating a seamless interaction between data and services. Some key services built specifically to address the needs of HCLS use cases include:
Healthcare organizations face significant challenges when building and maintaining applications due to the vast scale of their data and strict regulatory requirements. Managing large volumes of healthcare data drives up storage and processing costs, while on-premises systems can increase expenses. Additionally, ensuring data security and compliance with regulations like HIPAA and GDPR is critical, due to the sensitive nature of the data. The fragmented nature of healthcare data across multiple platforms also makes it difficult to derive reliable insights, further complicating app development and maintenance.
Medical applications generate and utilize enormous volumes of data, including electronic health records, medical images, genomic data, and health behavior information. Managing and storing this vast amount of data can be a substantial challenge for companies - specifically around the complexity of transferring and managing large volumes of data.
Modern cloud architectural principles offer cost-saving benefits through pay-as-you-go pricing, where businesses only pay for the resources they use. This scalable model optimizes cost efficiency by aligning expenditures with actual usage, avoiding unnecessary expenses. Cloud providers handle infrastructure management, eliminating the need for dedicated IT data center teams, and ultimately reducing labor costs.
In order to support data lifecycle management, services like Amazon S3 provide a rich set of tiers for storing data effectively based on the expected usage pattern of that data. The best solution is often to use Intelligent Tiering (IT), where AWS automatically moves unused files from standard to lower-cost storage based on detected access patterns.
The limited scalability of on-premises data centers increases the risk of insufficient capacity to handle unexpected workload spikes, potentially resulting in application crashes or performance degradation. Service interruptions during the scaling process can impact customer experience and business performance, requiring careful consideration of the various implications.
Cloud elasticity allows businesses to scale resources according to demand, preventing overprovisioning and minimizing wasted resources. Amazon S3 provides a variety of tools for managing the vast amount of data it can store, including:
Due to the sensitive nature of healthcare data, it is often a prime target for ransomware due to its importance to an organization and the potential impact of its loss. Ransomware restricts access to data by either removing or encrypting it. Perpetrators exploit this to threaten organizations with public exposure or release of the data, pressuring them to comply with their threats.
AWS offers a broad range of services and tools to help prevent data security breaches. Firstly, AWS provides comprehensive data protection and privacy controls, allowing you to manage how your data is used, who has access to it, and how it is encrypted. AWS has purpose-built services, such as AWS Key Management Service, designed to generate and manage encryption keys securely and provide monitoring and logging features for compliance and threat detection.
Additionally, AWS offers continuous monitoring and threat detection services, such as Amazon GuardDuty, Amazon Macie, Amazon Inspector, and AWS Artifact, which use machine learning, anomaly detection, and integrated threat intelligence to identify and prioritize potential threats, helping to prevent malicious activity and unauthorized behavior.
It’s crucial for companies to prioritize compliance to avoid penalties and fines. As the regulatory landscape becomes more complex, you must continuously improve your compliance programs to address the growing number of laws and regulations. This involves documenting all compliance efforts, anticipating challenges, assessing risks, and presenting the business case for the compliance program.
By moving to a cloud-based data infrastructure, organizations can benefit from AWS services built for security, scalability, and reliability, essential for ensuring compliance with evolving regulations. Services such as data lakes, purpose-built data stores, and managed analytics services, enable companies to store and analyze data in a scalable, cost-effective, and compliant manner.
They help companies analyze data by providing scalable storage for diverse data types, specialized databases for specific needs, and on-demand analytics supporting diverse workloads. Additionally, AWS provides governance capabilities to manage access to data across various data stores, further supporting compliance efforts.
Data reigns supreme as a catalyst for strategic decision-making, but generating actionable insights can be complex without proper data governance, storage management, and data preparation. Data governance is vital for companies to derive reliable insights from their data. It encompasses well-defined policies and procedures for data access, usage, and interpretation, supporting business users in exploring and analyzing data while upholding data quality and security.
Without proper data governance, organizations may struggle to respond to market trends and make informed decisions, potentially leading to financial losses and decreased market share. In addition, given that medical decisions can have life-altering consequences, it’s crucial to uphold the highest possible standards for maintaining data quality.
AWS provides governance capabilities to manage access to data across data lakes and allows for centralized security, governance, and auditing policies, resulting in uniform access control for enterprise-wide data sharing. This paves the way for enhanced data management, unified governance, and scalable data analysis, ultimately generating actionable insights.
With a modern, cloud-native governed data platform, you can access a range of powerful benefits to enhance your data management and monetization use cases:
AWS Database Migration Service (DMS) simplifies database migrations, allowing businesses to smoothly transition their databases to AWS with minimal downtime and zero data loss.
Data ingestion patterns and tools enable organizations to ingest data from diverse sources. For batch ingestion, AWS provides tools like AWS Glue and AWS Lambda, which allow organizations to process and load large volumes of data at scheduled intervals.
Stream ingestion, on the other hand, is facilitated by services like Amazon Kinesis, enabling data streaming from applications and devices, allowing businesses to capture and process data in real-time for immediate insights and quicker decision-making. Additionally, API ingestion allows organizations to collect data from external sources using secure and well-documented APIs, further expanding the available data sources and enriching existing data for analysis.
Storing data efficiently and securely lies at the heart of a governed data platform. Using Amazon Simple Storage Service (S3) as a versatile and cost-effective data lake storage solution, and Amazon Redshift as a high-performance and fully managed data warehouse solution, organizations can build a comprehensive and agile data platform.
Amazon S3 provides scalable and secure storage for vast amounts of unstructured data, making it the foundation for advanced analytics, including Al. On the other hand, Amazon Redshift offers lightning-fast query performance and scalability for structured data, empowering data analysts and business users to derive valuable insights and empower data-driven decision-making.
AWS offers a range of governance tools, such as AWS Identity and Access Management (IAM) and AWS Key Management Service (KMS), to enforce strict access controls and encryption, safeguarding data from unauthorized access or breaches.
In addition to security services, AWS offers the Glue Data Catalog, which provides a centralized metadata repository, enabling organizations to maintain a consistent and comprehensive view of their data assets.
Storing data efficiently and securely lies at the heart of a governed data platform. Using Amazon S3, democratizing data within the platform enables a broader audience of users to access and explore data insights, empowering business teams across the organization to make informed decisions.
By implementing well-defined governance principles and democratizing data access, data transforms into a reliable and valuable asset.
AWS offers a wealth of AI/ML services, including Amazon SageMaker, which enables data scientists and developers to build, train, and deploy machine learning models at scale.
The introduction of AWS generative Al capabilities using SageMaker JumpStart or Amazon Bedrock makes it easier for developers to create generative Al applications, which opens up further possibilities for creativity and innovation.
In today's data-driven healthcare landscape, your organization's success depends on its ability to harness vast amounts of data, ensure ironclad security, and drive continuous innovation. Caylent empowers payers, healthcare systems, and healthtech organizations to revolutionize their digital infrastructure on AWS. Our approach encompasses strategic assessment, data-centric architecture, intelligent governance, advanced analytics integration, and continuous optimization that can transform your healthcare applications to meet modern demands.
With Caylent's HealthLake solution, you can efficiently manage extensive healthcare data, enable personalized treatments through AI and ML, ensure HIPAA compliance leveraging AWS's eligible services, optimize costs with flexible pricing models, and seamlessly scale to meet fluctuating demands. Our deep AWS expertise, coupled with comprehensive healthcare industry knowledge and a proven methodology, provides the end-to-end support you need to stay at the forefront of healthcare innovation. Caylent can partner with you to unlock the full potential of your data on AWS, driving improved patient outcomes and operational efficiency in an ever-evolving healthcare ecosystem.
Caylent Industries
Accelerate medical innovation and improve patient outcomes and experience with a secure and resilient global cloud infrastructure on AWS.
Caylent Catalysts™
Enhance patient care with AWS HealthLake, an advanced analytics & artificial intelligence solution.
Brian Tarbox
Kimberly Schaefer