Last Updated | July 25, 2024
The healthcare industry is quickly moving towards digitization and transforming its landscape following the COVID-19 pandemic. The healthcare industry acknowledges the significance of healthcare data, such as patients’ health information, sensitive data, medical knowledge, health records, and prescriptions. Dealing with these extensive physical documents is difficult, driving the demand for secure cloud storage in a private cloud.
AWS Healthcare is a tool that enables healthcare organizations to securely store their health records, organize data, and analyze information. Accessing their data in a structured format and analyzing it through the AWS HealthLake tool helps healthcare organizations obtain meaningful insights. Understanding how this advanced tool can benefit your organization is essential If you need AWS HealthLake to store, manage, and analyze your healthcare data.
This article will delve into all aspects of AWS HealthLake, including its features, advantages, applications, purpose, and how it can benefit your healthcare institution and also handling change with AWS Healthlake. Let’s get started!
AWS HealthLake: Overview
AWS HealthLake is software compliant with HIPAA regulations and enables healthcare groups to securely store, transform, categorize, and examine all their medical data in a single location. Healthlake AWS is a critical component in AWS’s suite of healthcare solutions, simplifying the management and analysis of healthcare data. It is a robust tool capable of examining electronic health records within minutes, providing valuable insights for organizations to make data-based decisions using Amazon comprehend medical.
According to one report, the digital health industry is projected to reach US$180.70bn by 2029, with an anticipated compound annual growth rate (CAGR) of 6.47%. The rapid digital transformation in healthcare is evident, and the primary driver is the shift towards storing health records on the AWS Health Lake cloud instead of traditional, unorganized paper files. Primarily, health data is often disorganized, yet it holds crucial information like patient records, prescriptions, medical images, and physician notes, which is indispensable.
Amazon Health Lake can convert raw data into FHIR APIs, simplifying comprehension and analysis. Based on Healthlake AWS FHIR, these APIs allow organizations to transfer large quantities of health records to cloud storage.
It contains NLP models that assist users in comprehending customer data and extracting valuable insights for data-driven decision-making, trend detection, and prediction. The AWS Healthlake’s capabilities ensure that data is seamlessly and consistently transformed into the FHIR standard, enhancing interoperability across healthcare systems.
Benefits of HealthLake AWS for Healthcare Data
There are various reasons why healthcare organizations should consider the AWS HealthLake tool for health data:
Rapid Health Data Collection
Healthcare organizations can efficiently transfer large data sets, such as clinical notes and lab reports, to AWS storage in FHIR R4 format using the AWS HealthLake tool for future use in downstream applications. Connected health devices are an excellent tool for real-time, real-world data collection.
Saving Time and Costs
It helps to save an organization’s precious time and money with AWS HealthLake because it will handle the cost of infrastructure to store healthcare data and analyze raw data in minutes. For organizations concerned about costs, AWS healthlake pricing offers a flexible model that scales with your usage, ensuring you only pay for what you need.
Secured Cloud Storage
One of the main factors prompting healthcare organizations to transition to healthcare solutions is the utilization of cloud storage. Raw data can be conveniently stored in AWS cloud storage securely and in compliance with HIPAA regulations.
Data Interoperability
Using the HealthLake APIs, healthcare organizations can easily copy health data in the Fast Healthcare Interoperability Resources (FHIR) industry standard format from on-premises systems to a secure healthcare data lake in the cloud, which can be used to transform raw data into FHIR-based data format for 360-view accessibility and analysis.
Data Analysis
AWS HealthLake includes different analysis tools like Amazon QuickSight and ML Models to analyze raw data and extract valuable information for organizations to make data-driven decisions, recognize trends, and predict outcomes.
AWS healthlake analytics play a crucial role in processing and visualizing the data. This enables healthcare organizations to gain actionable insights rapidly and helps with Predictive analytics in healthcare.
Security and Compliance
AWS HealthLake offers advanced cloud security and encryption support compliant with HIPAA regulations, enabling organizations to securely store their data in the cloud with authorized access control for privacy and safety.
Scalability
The AWS Cloud HealthLake tool can hold vast quantities of unprocessed health information. It enables organizations to expand without having to invest in data storage infrastructure. The AWS healthlake architecture is designed to provide scalability and robust data management, which are critical for handling the vast amounts of data generated in healthcare.
Features of AWS HealthLake
Following are some key features of the AWS HealthLake tool:
Fetch Data
By utilizing APIs, it is simple to bring healthcare data like clinical notes, medical history, lab reports, insurance claims, and other information into the AWS HealthLake data store. Initially, it will convert the data into FHIR R4 format for simplified importing.
Store
One crucial obstacle is the data’s disorganized form. When data is brought into AWS HealthLake, it is organized for simplicity and security, with encryption and HIPAA compliance.
Transform
AWS HealthLake has built-in Natural Language Processing (NLP) models, which can be used to transform unstructured raw data into organized data that can be stored in the FHIR resources.
Query
If you have any inquiries or need to modify healthcare data, you can perform read, update, and delete actions by locating the specific data and applying the changes.
Analyze
AWS for Healthcare provides integrated analytical tools like Amazon QuickSights and Amazon SageMaker to assist in developing, training, and applying personalized ML algorithms for efficient data analysis.
Imaging
AWS HealthLake imaging enables users to cut medical imaging storage costs by 40%, improve scalability, and decrease infrastructure expenses.
Challenges that Amazon HealthLake Faces During FHIR Data Conversion
When it comes to storing healthcare data in the AWS HealthLake tool, then some challenges come during FHIR Data conversion:
Healthcare Data Complexity
AWS HealthLake finds it challenging to identify, store, and organize healthcare data due to its unstructured nature and varying formats and standards.
Data Quality
Another obstacle is healthcare data quality due to inconsistent errors, missing information, and health data complications that can impact FHIR data’s accuracy. Dealing with change in aws healthlake includes managing the intricacies of transforming healthcare data while maintaining compliance and data integrity.
Data Mapping and Transformation
When you import health data into AWS HealthLake, first convert the raw data into FHIR format for mapping. This data format conversion is time-consuming and complex, especially for unstructured data.
Resource Modeling and Mapping
Once the data is transformed into FHIR resources, a resource-oriented model maps and understands different data types.
Technical Expertise and Resources
Also, technical expertise and various resources are required to convert raw data into FHIR format as per the AWS healthcare solutions and access the tools and resources to perform the conversion process.
Exploring How Amazon HealthLake Functions
AWS HealthLake adheres to a thorough procedure that organizations must follow to safely store, convert, and examine their health information. Below are the essential steps to adhere to:
First step
Initially, the health data must be brought into AWS HealthLake. This data comes in various formats and unstructured forms, such as medical records, patient information, lab results, and prescriptions. AWS HealthLake will convert the unstructured data into FHIR format upon importing it.
Second step
Amazon HealthLake will utilize machine learning models to detect patterns and forecast outcomes.
Third Step
It is equipped with an integrated NLP model to extract essential insights from the data.
The data has been organized and categorized in a way that makes locating it simple.
Fourth step
Different data analysis tools are available, including AmazonSageMaker, AmazonQuickSight, and third-party applications tailored to the organization’s needs.
This is the entire process of AWS HealthLake, which securely manages, converts, processes, and studies health data quickly while developing web applications. As a leading data lake healthcare solution, AWS HealthLake helps store vast amounts of healthcare data securely and efficiently.
Top Use Cases for AWS HealthLake
There are various areas where the AWS for Healthcare tool can be used across the healthcare domains:
Real-time Monitoring and Alerting
Using the AWS HealthLake tool, organizations can import and analyze health data from medical devices and sensors. This can help identify critical events for efficient patient management.
Clinical Research
AWS HealthLake can analyze large amounts of raw health data, which helps organizations explore and extract valuable information in the research part. This information helps organizations identify Healthcare technology trends and patterns, make predictions, and make data-driven decisions. A clinical quality management system can use this data during research and have access to a comprehensive collection of well-organized data.
Population Health Management
AWS HealthLake is also helpful in population health management, where it has analytical tools and ML models to forecast outcomes, analyze health patterns, and control costs for population health management.
Healthcare Analytics and Reporting
You can use AWS HealthLake to securely store data and analyze it for meaningful insights and detailed reports with cloud computing security.
Work with Folio3 Digital Health to develop your AWS Healthlake Solutions
With Folio3 Digital Health, you have a team of skilled designers, developers, testers, and marketers with all the experience needed to help you, from ideation to deployment and maintenance. Our team has years of experience delivering world-class solutions to healthcare clients.
Every Folio3 Digital Health product is HIPAA-compliant and uses FHIR and HL7 interoperability standards. These products meet all performance and regulatory requirements, ensuring it deliver the best results and remain legally compliant.
Conclusion
AWS HealthLake is essential in the healthcare sector. Organizations can utilize this tool to securely store, process, and analyze raw data quickly to obtain valuable insights for improved decision-making, trend identification, and predictive analysis. This manual will help you understand how AWS HealthLake can be utilized for health data and the advantages it offers to organizations.
If you are considering creating a healthcare app for your organization, hiring a custom healthcare software development company is the best option to have professionals create the software tailored to your needs. Folio3 is a reputable healthcare software development company with a team of skilled professionals who can comprehend your needs and provide the desired outcomes. Contact us today!
For further information on deployment and configuration, the aws healthlake documentation provides comprehensive guidelines and support material.
About the Author
Aisar Ali
Aisar Ali is a visionary software engineer at Folio3, specializing in digital health solutions. With expertise in Node.js, C++, GraphQL, REST APIs, and cloud platforms like Azure and AWS, Aisar excels in developing robust healthcare applications that enhance data integration and system architecture. Beyond technical prowess, he is committed to transforming healthcare access and efficiency, driving innovation that improves patient care and clinical decision-making. Aisar’s work not only advances technology but also enriches the lives of those it serves.
