Healthcare & Life Sciences (HCLS)

Innovative cloud-based solutions to enhance patient care, lower costs, and improve efficiency

Healthcare and life sciences organizations are looking for ways to lower costs and improve the quality of patient care. Intelligent, connected, and secure cloud-based solutions can help bring innovations to care delivery models, drug discovery, and genomics. These solutions can help enable healthcare and life sciences organizations to achieve their business and patient care goals as detailed below.

Deploy healthcare and life sciences discovery, development, manufacturing, and commercialization workloads. Learn more


Use AWS services and solutions in AWS Marketplace to store, protect, and optimize your data. Learn more


Predict outcomes, identify opportunities, and optimize solutions to meet real-world challenges. Learn more


Challenges

Healthcare organizations are looking for solutions that can address both immediate and long-term challenges, including:

Care coordination: When seeking care, patients may interact with a variety of healthcare providers and are expecting that their information is shared across this continuum of care. To do so requires integration and coordination between multiple IT systems throughout a provider network.

Patient engagement: Engaging patients to be active participants in managing their health is a key pillar of healthcare of the future. Addressing the various aspects of patient engagement is required to provide a comprehensive patient engagement experience.

Healthcare analytics: To perform clinical and population analytics, organizations need to leverage machine learning models and other advanced solutions that speed discovery, visualization, and sharing of new patterns and insights. The volume and variety of structured, unstructured, and streaming data in healthcare and life sciences requires highly-scalable platforms for storing and analyzing data as well as running predictive models that support real-time decision-making.

Compliance and security: Sensitive health data must be protected to ensure patient privacy. Compute, storage, and networking solutions need to provide the required level of security across cloud environments and ensure that IT infrastructure is maintained in compliance with changing policies and regulations.

Clinical data archival and storage: Short and long term storage solutions are needed to archive, and back up vast amounts of sensitive information, such as clinical, patient and operational data. Storage and archival solutions need to meet the demands of business in a secure, compliant, cost-effective and scalable manner.

Clinical information systems and operational excellence: Managing IT infrastructure on-premises can be difficult and time-consuming. The infrastructure needs to be customizable and secure, and provide fast, secure access to store and share patient information across electronic medical record and other mission-critical systems.

Healthcare solutions in AWS Marketplace

AWS Marketplace is a digital catalog that can help healthcare organizations modernize patient care, improve collaboration, comply with complex regulations, and lower costs by simplifying software procurement. With solutions that safeguard clinical data and help build secure, cloud-based solutions, healthcare payers, providers, and life sciences organizations can:

Have confidence in your infrastructure

Have confidence in your infrastructure

Strengthen security and compliance with comprehensive tools that monitor environments and safeguard protected health information throughout its lifecycle, from creation to storage and archiving.

Reinvest time and resources toward optimal care delivery

Reinvest time and resources toward optimal care delivery

Increase efficiency while reducing traditional staffing costs by utilizing a growing catalog of tools designed to automate clinical information systems and improve patient care, available through pay-as-you-go and other cost-effective models.

Accelerate insights to improve patient outcomes

Accelerate insights to improve patient outcomes

Turn data into actionable insights by leveraging a range of analytics services and machine learning models to quickly visualize clinical and population health data.

Engage and empower growing patient populations

Engage and empower growing patient populations

Optimize patient experiences across the care continuum by easily assimilating data from diverse sources to test, refine, and scale new approaches.

Healthcare & Life Sciences (HCLS) use cases

These are just a few examples of how HCLS organizations are accelerating research and development, improving patient care, and driving other key focus areas with AWS services and solutions in AWS Marketplace.

  • Innovate care delivery
  • Establish secure IT operations
  • Discover algorithms and ML models
  • Innovate care delivery
  • Innovate care delivery

    Create enhanced customer experiences through patient-managed services

    Change Healthcare manages millions of confidential transactions daily from its clients while maintaining full compliance with healthcare industry regulations, including HIPAA. Their products include Telehealth, Change Healthcare Clearinghouse, and a Medical Eligibility Benefits API. The Telehealth offering allows providers to access eligibility benefits, submit claims, and verify the status of claims, while Change Healthcare Clearinghouse provides real-time eligibility verifications, claims submissions, and claims status. The Medical Eligibility Benefits API allows providers to instantly verify patient coverage and provide access to co-insurance, copay, deductible, and other plan details. Change Healthcare helps accelerate the journey to a value-based healthcare system.


    Innovate care delivery

    Rapidly create and scale applications by extracting value from your data

    InterSystems IRIS for Health is the world’s first and only data platform specifically engineered to extract value from healthcare data. InterSystems advanced software empowers people at every step of the healthcare ecosystem to deliver what matters to patients, providers, payers, governments, and technology innovators to rapidly create and scale the industry’s next breakthrough applications.
     
    InterSystems’ interoperability technology has been at or near the top of KLAS rankings for over a decade. Today, more than half a billion health records are managed by solutions built on InterSystems technology.
     
    InterSystems IRIS for Health enables healthcare providers to:
     
    (1) Build health information systems that deliver intelligent workflows with real-time analytics
    (2) Move large, connected, healthcare data-intensive applications to the cloud
    (3) Deliver connected health solutions that draw data from multiple sources
    (4) Create new clinical research applications with big data from clinical trials, population health initiatives, and other diverse sources
    (5) Publish new apps for the Internet of Healthy Things
    (6) Serve up massive amounts of clean data for artificial intelligence and machine learning applications

    Innovate care delivery

    Clinical appliances for imaging

    Dicom Systems offers a proven and scalable de-identification toolset that unlocks valuable imaging studies for research, policy assessment, and comparative effectiveness studies. The Dicom Systems Unifier platform enables healthcare providers and researchers to acquire, exchange, modify, and archive medical images, diagnostic reports, and related patient data. Organizations can use the platform to quickly prepare their data, securely migrate their data to AWS, and then use the data lake in AWS to develop algorithms—all in less time and at a lower cost than competitive solutions.


    Innovate care delivery

    Healthcare analytics for providers, physicians, and patients

    Faster and more efficient analytics are critical to the future of healthcare and life sciences. Equipping providers, physicians, and other caregivers with data-driven insights can drive innovation and enhanced decision-making, which in turn means more efficient care and better patient outcomes. The challenge is to find the right analytics solution—one that is fast, secure, and designed specifically for the healthcare industry.

    TIBCO Spotfire for AWS provides customers best-in-class visual analytics with no data limits in a traditional subscription or pay-as-you go model with no up-front costs.


    Innovate care delivery

    Monitoring remote patient health application 

    Healthcare providers with patients outside of a healthcare facility, like a hospital, need a trusted way to receive data on the patients’ status from healthcare monitoring devices. The healthcare provider must also know the deployed monitoring devices are up and running as a technical problem could directly impact patients’ care.

    Dynatrace provides cloud-native monitoring for connected devices. Start monitoring your full IoT stack with no manual configuration in minutes. With its Real-User Monitoring, Dynatrace also delivers information for the user-facing side of an IoT environment. Dynatrace provides several API’s to import data from other sources so that its AI can consider everything that is important, and that all information can be found in one place. For a connected healthcare solution, the patient monitoring system collects and analyzes the data and provides it to the patient—as well as individuals with access privileges, such as doctors or select relatives—via the AWS cloud and an application interface.


    Innovate care delivery

    Deliver effective patient care with improved clinical outcomes

    The BLAST AMI (Basic Local Alignment Search Tool Amazon Machine Image) finds regions of similarity between biological sequences and then compares nucleotide or protein sequences to databases in order to calculate the statistical significance. It also allows users to perform sequence similarity searches without the limitations often experienced when using a public website or when setting up a stand-alone BLAST.

    The BLAST AMI includes a client that automatically downloads the most popular BLAST databases from the National Center for Biotechnology Information (NCBI) while also allowing users to upload their own custom databases. The AMI allows users to run stand-alone searches with BLAST applications and submit searches through a subset of the NCBI-BLAST URL API while performing searches with a simplified webpage. The BLAST AMI provides access to a popular sequence search similarity program in a convenient package.


    Innovate care delivery

    Electronic health record and practice management system

    Run your Electronic Health Record and Practice Management System on a scalable and secure cloud in order to efficiently deliver patient care and improve clinical outcomes. OpenEMR is an open source electronic health record and medical practice management solution that is ONC certified, multilingual, and supports a broad feature set including patient demographics, records, appointments, prescriptions, billing, reports, clinical decision support, and lab integration.

    OpenEMR on the cloud helps simplify OpenEMR management. OpenEMR on the cloud offers cost effective solutions which include scaling of computational resources, cutting-edge network security, zero hardware maintenance, easy software deployments, and robust backup and recovery solutions.

  • Establish secure IT operations
  • Establish secure IT operations

    Protect patient data, devices, and networks while addressing healthcare regulations

    Healthcare and life sciences (HCLS) organizations focus on protecting human lives, but they also need to defend the digital lives of patients and customers. Doing so depends on protecting data, devices, and networks while also complying with complex healthcare regulations. Trend Micro understands the unique challenges of the healthcare industry and provides layered solutions that integrate with existing infrastructure and have the flexibility to grow and change as the needs of HCLS organizations and their patients and customers evolve.

    Trend Micro security solutions include products targeted at user protection, hybrid cloud security, and network defense. Trend Micro Deep Security, powered by XGen, provides a comprehensive suite of cloud security capabilities from a single agent, so organizations can secure patient data in less time and at lower cost. The solution provides a consolidated view into all areas of security, automating repetitive tasks, immediately securing new AWS instances, and producing reports for auditors. The ease of deployment for Trend Micro Deep Security on AWS frees healthcare organizations to focus on growing the business and providing better patient and customer care.


    Establish secure IT operations

    Business continuity and disaster recovery with NetApp on AWS

    Service interruptions and physical disasters are two of the many risks involved in healthcare IT. Business continuity (BC) and disaster recovery (DR) ensures data resilience in the event of physical disasters, network outages, and malicious attacks. Healthcare organizations need to ensure that their cloud workloads are always available and include a reliable, easy-to-use backup solution that allows for instant recovery. Assurance that patient records are protected and not lost if the accessing hardware is destroyed, is key.

    NetApp® Cloud Volumes ONTAP® solves this by providing a scalable, affordable way to protect data and ensure it is recoverable and accessible in case of disaster. NetApp® Cloud Volumes ONTAP® can be easily integrated with your AWS infrastructure to backup data from your on-premises and/or cloud environments to AWS storage targets. With near-instant online recovery capabilities that do not require a secondary disaster recovery location, this solution provides flexibility and speed you cannot get from tape backup. NetApp Cloud Volumes ONTAP is a data storage management platform that enables stakeholders across the health IT spectrum to reliably and cost-effectively leverage the benefits of the cloud while streamlining data management and improving patient care.


    Establish secure IT operations

    Disaster recovery for business critical applications

    Both patients’ wellbeing and healthcare providers’ businesses depend on cost-efficient and compliant disaster recovery solutions that can keep systems up and running when disasters strike. This is an increasing challenge for healthcare and life sciences (HCLS) organizations with growing IT infrastructures, many different systems operating independently, and limited capital to add and manage new servers.

    Software-as-a-Service (SaaS) disaster recovery solutions, such as CloudEndure Disaster Recovery, deliver key advantages to HCLS organizations. CloudEndure Disaster Recovery is a one-touch disaster recovery solution that ensures a near-zero Recovery Point Objective (RPO) and Recovery Time Objective (RTO) for all applications, while reducing many traditional disaster recovery expenses. CloudEndure offers both Tier 1 and Tier 2 disaster recovery, with each tier providing a different level of functionality at a different price, so organizations can choose the most cost-effective solution based on workload criticality.


    Establish secure IT operations

    Improve patient care with a data lake for analysis

    Many healthcare and life sciences (HCLS) organizations struggle to store and quickly analyze data from new data sources like log files, data from click-streams, social media, and Internet-connected devices. Existing Extract-Transform-Load (ETL) and other storage solutions can get overwhelmed, slowing down innovation and projects that are critical to the bottom line, and can ultimately affect the quality of patient care. However, using a data lake along with complementary tools and architecture—such as Amazon Redshift, Amazon S3, and Matillion ETL—can alleviate these challenges to improve patient care.

    With data integration by Matillion, HCLS organizations can easily load their data to Amazon S3 using pre-built connectors. They can then use Matillion to trigger transformation jobs to make data relatable, analyze it in a clean state, and send it to visualization tools. This enables HCLS organizations to harness more data from new sources in less time, leading to faster, better decision-making to improve everything from clinical processes and care delivery to long-term patient outcomes.


    Establish secure IT operations

    Compliance and security monitoring across the healthcare enterprise

    Maintaining compliance in highly-regulated and rapidly-evolving industries such as healthcare and life sciences (HCLS) is difficult. Changing standards, new regulations, and escalating risks to an organization’s reputation and bottom line can lead to resources shifting to manage compliance rather than driving application development and patient-centered innovation. ClearDATA offers solutions to help HCLS organizations prioritize both security and compliance in the healthcare cloud and continued productivity and innovation.

    The ClearDATA Compliance (C2) Dashboard takes the guesswork out of translating regulatory statutes into auditable technical controls, giving HCLS organizations the insight needed to assess compliance posture relative to regulatory requirements. The C2 Compliance Dashboard is mapped directly to HIPAA, GDPR, GxP, NIST, and ISO controls and guidelines and can be enabled across AWS environments for consolidated visualization and easy monitoring thousands of components. This provides unique individual asset scorecards as well as a wide variety of additional reports to understand compliance posture over time and ensure it meets regulations.


    Establish secure IT operations

    Next-gen firewall protection for health care apps and data

    Healthcare providers depend on IT infrastructure to connect a vast network of offices and mobile users with private health data and key applications. For providers migrating on-premises applications and data to the cloud, this can introduce potential entry points for cyberattacks that compromise protected health information and put patients and providers at risk. Like in on-premises environments, an ideal approach for safeguarding applications and data in the cloud starts with selecting a next-generation firewall to allow only specific applications to access data and prevent threats within those application flows.

    Palo Alto Networks VM-Series extends the same effective protection capabilities of Palo Alto Networks Next-Generation Firewall to AWS environments. Healthcare organizations can launch VM-Series as the security gateway between their virtual private cloud’s Internet gateway and elastic load balancer to stop malicious traffic from entering their public cloud environment. Deploying a VM-Series firewall is a key step in establishing confidence internally and can offer evidence-based assurance to patients and customers.


    Establish secure IT operations

    Controlling security-costs while protecting patient records

    Securing sensitive patient and private internal data, complying with HIPAA and other regulations, and integrating security in complex cloud environments while minimizing costs are all priorities for healthcare and life sciences (HCLS) organizations. To effectively balance each of these priorities, HCLS organizations need proven and simple security solutions for fast provisioning and configuration of cloud environments with no downtime or risk to HIPAA compliance. Sophos security solutions on AWS help HCLS organizations consolidate their security without compromising effectiveness.

    By combining multiple security tools into one scalable solution, Sophos Unified Threat Management (UTM) makes security easier to deploy and manage, providing essential next-gen firewall protection for network, web, email, applications, and users. Sophos UTM also provides full visibility into AWS workloads through a centralized management control, so new updates can be deployed globally without having to manually apply them to every AWS account. This enables HCLS organizations to better protect patients’ privacy and protected health information against data loss, while also supporting compliance mandates and industry best practices.

    Establish secure IT operations

    Backup, recover and manage your data

    Healthcare organizations are under increasing pressure to not only protect a growing amount of data, but also create more value from that data to drive better care delivery. Commvault provides solutions to help the backup, recovery, and management of data, including files, applications, and databases, and hypervisors on-premises and in the cloud.

    Commvault’s modern data backup and recovery solution allows healthcare organizations to manage both clinical and business data with the simplicity of a single interface, no matter where that data resides. This solution eliminates the need for multiple point solutions, breaks down data silos, improves data management efficiency, and helps organizations understand and use their data most effectively.


    Establish secure IT operations

    Data protection and governance

    Companies in highly-regulated industries, such as healthcare and life sciences (HCLS), often struggle with protecting, finding and accessing the employees’ data spread across multiple systems. Mergers and acquisitions increase the challenge in preventing data loss and integrating data. Automating Legal Hold and eDiscovery can accelerate workflows, enabling companies to retain, cull, and review relevant data as needed. Implementing a robust backup solution also allows companies to quickly recover from ransomware attacks.

    Druva inSync provides cloud-native SaaS solutions to backup and recover data across endpoints and cloud applications (G Suite, Microsoft Office 365, Box and Salesforce) to address rising compliance and legal needs. HCLS companies can use Druva inSync to quickly view and manage their data on a single pane for Data Preservation (eDiscovery and Legal Hold) and Data Relevancy (Search and Culling Tools). This can enable these companies to dramatically increase the availability and visibility of business-critical data, while reducing the costs, risks, and complexity of safeguarding patient, customer, and business data.


  • Discover algorithms and ML models
  • Algorithms and ML models

    ML Models to Predict patient readmission

    Manufacturing pharmaceuticals at commercial scale involves an array of complex variables and dependencies, including many different processes, types of equipment, systems, raw materials, and human activities. All of this must be carefully orchestrated to develop and manufacture pharmaceutical products of high quality, adhere to stringent regulations for ‘good manufacturing practices’ (GMP) and FDA validation, and maintain sustainable production costs. By collecting and storing real-time data from sensors, equipment, and operational systems such as alarms, manufacturers gain trustworthy visibility into operations. It also provides the basis for creating predictive models to identify improvements and root causes before adverse events occur.

    Bigfinite Inc. is an advanced analytics and manufacturing intelligence platform that provides pharmaceutical and biotech manufacturers a way to gain the understanding and insights needed to improve efficiencies and ensure product quality. The Bigfinite platform collects and stores real-time data from production equipment, processes, and operational systems into a GMP-compliant big data environment using IIoT technologies. The data can then be used to build and train artificial intelligence/machine learning models to identify improvements that are then deployed with targeted solutions, helping to make manufacturers’ processes more robust and their operations more profitable.


    Algorithms and ML models

    Predict patient readmission

    Healthcare and life sciences organizations need to focus on existing challenges, but they also need to focus on the future. Being able to predict what’s coming next—disease development in individual patients or population-based trends, for instance—is essential to improving the quality of care and running more efficient, cost-effective businesses. To perform fast, accurate predictive analytics, organizations need proven machine learning (ML) solutions.

    TIBCO Data Science, a collaborative platform for operationalizing data science, is at the forefront of predictive healthcare. The solution applies ML to big data and automates analytical models, so organizations can identify trends and patterns and make informed predictions about future medical events.

    TIBCO offers ML models that use patient medical records to predict hospital readmissions, a costly issue that directly affects patient quality of life. The TIBCO platform streamlines collaboration and makes it easy to combine data, such as patient demographics and hospital treatment plans, to make accurate predictions that can transform healthcare treatments and follow-through.


    Algorithms and ML models

    Patient history provides predictive analysis for early detection

    By leveraging machine learning models to analyze a patient’s medical history, it is possible to calculate their risk of being diagnosed with multiple diseases within the next year. Organizations that can predict the onset of serious diseases can provide better care management for entire communities and save individual lives through early detection.

    Perception Health provides proprietary CARE algorithms powered by Amazon SageMaker, a fully-managed platform that is designed to enable developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale—without exposing HIPAA-protected information. Perception Health’s algorithm can be licensed by users on a per-patient basis and run on AWS. There are more than 14 billion medical claims and 6.5 million more added daily. With at-a-glance visuals, a spectrum of tools, and personalized expertise from data scientists, healthcare and life sciences organizations can validate strategies and optimize workflows that benefit providers, payers, and patients across the entire system.


    Algorithms and ML models

    Understanding patient trends improves no-show prediction

    Machine learning (ML) models can be used to address many problems and inefficiencies in the healthcare and life sciences industry. For instance, ML models can be used to provide early detection of diseases like dementia, but also to predict when patients are likely to fail to show up for appointments, a problem that accounts for billions of wasted dollars every year.

    Cloudwick’s robust ML capabilities can meet the analytics needs of organizations across healthcare. By automating the entire ML workflow, business users and developers can spend less time extracting and processing data and more time using forecast models to drive results. Cloudwick solutions on AWS include Medical No Show Prediction, which uses a machine learning model to predict the probability that a customer will not show up for an appointment.

    Cloudwick’s Medical No Show Prediction model uses a patient’s medical background and appointment-related information to make its prediction, while protecting patient privacy. The results are just one example of how machine learning models can help providers improve the quality of care and the care experience, while at the same time reducing costs.


    Algorithms and ML models

    Diagnose skin disease with improved accuracy for improved patient care

    Figure Eight is a human-in-the-loop machine learning (ML) platform. The Figure Eight technology platform uses ML solutions to create the high-quality training data needed to work in the real world. This model classifies skin images that could potentially contain diseases to help individuals gain insight into skin diseases they may have. This ability to predict skin diseases with a high degree of accuracy can improve diagnoses and treatment regimens, as well as patient care and outcomes.

    While this model is not currently intended as a diagnostic tool or second medical opinion, it can help doctors make more accurate diagnoses of issues including acne, rosacea, actinic keratosis, basal cell carcinoma, benign keratosis, eczema, melanoma, nevus, and other vascular issues.


    Algorithms and ML models

    AI extends medical diagnostics for disease identification

    Persistent Systems believes that machine learning will fundamentally transform the medical diagnostic space. Innovations in artificial intelligence (AI) are helping the healthcare industry tackle critical challenges regarding drug discovery, critical care, and disease identification. In the area of medical diagnostics, AI is poised to augment the capability of physicians and medical technicians by speeding diagnosis, in turn reducing costs.

    Persistent Systems has published four ML models in AWS Marketplace in the Healthcare domain, including three models specific to disease identification and classification. The Breast Cancer Classification model is trained on features computed from a digitized image of a Fine Needle Aspirate (FNA) biopsy of a breast mass and classifies it as Malignant/Benign. The Glaucoma Detection model is trained on basic features from the examination records for glaucoma and healthy controls such as ocular pressure, cornea thickness, retinal nerve fiber layer (RNFL) thickness, etc. to classify an ocular condition as glaucoma or not. Finally, the Lymphoma Subtype Classification model uses deep learning to classify Lymphoma Microscopic Images into 3 subtypes: Chronic Lymphocytic Leukemia, Follicular Lymphoma, or Mantle Cell Lymphoma.

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