Medical history is a highly personal subject. Its confidentiality is protected by the law in nearly every country and region around the world, and in the wrong hands it can wreak all kinds of unlawful havoc. In 2023, frequent security breaches were an unfortunate reality of the booming HealthTech industry, and to better understand this scourge, we need to inspect the many ways in which compromised medical data can hurt your patients.

Somebody’s personal, and therefore deeply confidential medical records may seem like too niche a target for cybercriminals, but nothing could be further from the truth. In a recent post, Thomas Lacher, a Certified Information Systems Security Professional, described the plethora of options open to criminals via compromised medical records, including “financial gain, medical identity theft, prescription drug abuse, ransom, espionage and insider threats”. Keeper cybersecurity platform also claims that hackers covet medical records due to their impressive lifespan that is longer than that of credit cards or login credentials. The motives tend split up into two categories:

• Direct abuse. This refers to the immediate malicious use of medical information itself, either as a tool of blackmail, method of obtaining prescription drugs by an impostor, or, on a high enough level, as a trump card in the hands of international terrorism.
• Indirect abuse. Here medical records make up the tip of the iceberg, and serve as an entryway into other sorts of criminal activity. For example, such a record can feature a patient’s name, date of birth, and personal identification number, all of which can later be used to hack into their bank account, leading to less healthcare-centered and more financially devastating results of identity theft.

The larger a healthcare system is, the more personal data it will contain, and the more complex, and therefore hard to defend, its cloud databases will be. HIPAA has also recently claimed that “the theft of medical records is harder to detect than other types of personal data”, which means that medical records are not only relatively easy to hack in large quantities but can be misused for longer periods before the crime gets addressed.

Aside from being the shield that protects the sensitive details from falling into the wrong hands, data security is just a fundamental part of HealthTech systems and services that ensures they function appropriately. Defense against data breeches is a huge priority of data security, but it is not the only one. Here are some of the others:

• Maintaining Trust and Reputation. Patients exhibit a level of trust by granting healthcare providers their information. Any security lapse can erode this trust and damage the reputation of the organization. By prioritizing data security, HealthTech companies demonstrate their commitment to protecting patient interests and maintaining high ethical standards.
• Compliance with Regulatory Requirements. All HealthTech companies are subject to strict standardized requirements governing patient data. Failure to comply with these regulations can result in significant fines, legal penalties, and reputational damage. Robust data security measures are the baseline for ensuring compliance with these standards.
• Facilitating Innovation. Secure access to high-quality data is essential for driving progress in healthcare. Well-protected companies empower researchers to leverage data-driven insights for improving patient outcomes and advancing medical science.
• Preventing Data Loss. In addition to external threats, data security also addresses risks associated with data loss due to system failures, human error, or natural disasters. Implementing data backup and recovery mechanisms alongside security protocols is a must.

Medical history is a highly personal subject. Its confidentiality is protected by the law in nearly every country and region around the world, and in the wrong hands it can wreak all kinds of unlawful havoc. In 2023, frequent security breaches were an unfortunate reality of the booming HealthTech industry, and to better understand this scourge, we need to inspect the many ways in which compromised medical data can hurt your patients.

This HIPAA-eligible service helps companies to organize and analyze healthcare data in the cloud. It uses machine learning to structure information from different sources, making it easier for healthcare organizations to derive insights. When it comes to data security, AWS claims that this solution is regularly tested to meet “rigorous security and access control standards”, with customer data being encrypted both in transit and at rest.

Amazon Comprehend Medical is a natural language processing (NLP) service that extracts medical information from unstructured text. It helps healthcare organizations get valuable insights from large volumes of medical data. The list of things Comprehend Medical reacts to is fairly long. It includes diagnoses, medications, dosages, medical procedures, and more. While the main type of data this particular service is meant to process comes from niche medical reports, the broader Amazon Comprehend solution can process all kind of sources, including social media posts, comments, and e-mails. In this way, healthcare organizations can use Comprehend to become more human-centric by analyzing patient feedback.

This recent addition to AWS family uses generative AI to automate the process of taking clinical notes. In the best traditions of automation, this service takes over a relatively boring task, boosting the productivity of medical workers as well as accelerating the notetaking speed. Worker burnout is one of the biggest challenges of post-covid healthcare. Within this context, a solution that aims to lift the burden of manual labor from the already overworked healthcare professionals is a small, but important step towards optimized and sustainable medicine.

Omics data exists in large datasets that are the end– product of analysis of biological molecules. AWS HealthOmics helps to analyze genomic, transcriptomic, and other omics data in DNA, RNA, and other molecules from live organisms. This, in turn, drives medical research and helps healthcare professionals to better understand patients’ genetic predispositions to diseases.

After a group of solutions tailored to meet the needs of healthcare organizations, we cannot forget that the more versatile, but unrelated to medicine AWS tools, can also be used to optimize healthcare.

• Amazon SageMaker is a service for building, training, and deploying machine learning models. Healthcare organizations can benefit from SageMaker when developing custom predictive models for disease diagnosis and treatment optimization.
• Amazon Polly is a text-to-speech service that supports multiple languages and voices. Healthcare professionals can use Polly to develop interactive voice response (IVR) systems and accessibility solutions.

• Amazon Translate is a neural machine translation service that enables healthcare organizations to break down language barriers when talking with patients, caregivers, and healthcare providers.
• Amazon Simple Storage Service (S3) is a scalable object storage that allows healthcare organizations to store and retrieve large amounts of data securely. It is commonly used to store medical images, electronic health records (EHRs), genomic data, and other healthcare-related data types.
• Amazon Virtual Private Cloud (VPC) is a virtual network service that can isolate the AWS resources different healthcare companies use, and create private networks within the AWS cloud. It helps ensure the confidentiality and integrity of sensitive healthcare data.

These are just a few examples of the healthcare services and solutions offered by AWS. With enough creativity, healthcare systems can make the most of the other tools in Amazon’s cloud toolbox. The newest developments like HealthOmics and HealthScribe prove that as the industry continues to evolve, AWS will likely introduce even more new services to address emerging HealthTech challenges.

Deployment of any application in the cloud starts from choosing a deployment strategy. The choice depends on many factors, including goals, the degree of security, and, for healthcare, compliance with regulations that secure the transfer of patient data. Here are the most well-known deployment strategies:

• Blue-green deployment is used in software development and cloud computing to minimize downtime and risk during the release of new versions of an application. It involves maintaining two identical production environments, known as “blue” and “green,” and routing traffic between them during the deployment process.
• Canary deployment is another deployment strategy used to validate new releases before rolling them out to the entire user base. The term “canary” refers to the old practice of using canary birds to check for toxic gas in coal mines. In tech, it means using a small subset of users or traffic to test the latest versions while the majority of users remain on a stable version.
• Rolling deployment gradually deploys new versions of the application to distant servers while the existing version continues to serve user traffic. This incremental approach reduces downtime by maintaining a blend of old and new versions during the deployment process. As each subset of servers is updated with the latest version, traffic is gradually shifted or redistributed. Enabling a smooth transition and should a problem arise, will be easier to manage.
• Serverless deployment or Function as a Service (FaaS), enables developers to build and deploy applications without using servers. In a serverless deployment model, the cloud provider dynamically allocates resources to run code in response to events or triggers, such as HTTP requests, database changes, or file uploads. When it comes to AWS, their tool CloudFormation will be of great help to companies willing to go serverless.
• Immutable deployment treats application artifacts, infrastructure configurations, and dependencies are treated as immutable; they are never modified after they are deployed. Updates or changes to the application are made by deploying new, updated versions rather than modifying existing components in place.
• Multi-region deployment is used to deploy applications across multiple geographic regions simultaneously. This approach helps improve availability and performance by distributing application components and data across different data centers.

Deployment strategy is the plan that you will follow and the bare-bones groundwork, but you also need to reinforce the development with useful tools that boost its speed and safety. In the vast constellation of more than 200 AWS services, some will be more helpful than others. Let’s divide them by the types of assistance that they provide.

Well-Architected Framework

 
It’s all in the name. AWS Well-Architected Framework is not a concept, but a separate tool, which addresses six subsets (or “pillars”) of app deployment: operational excellence, security, reliability, performance efficiency, cost optimization, and sustainability. This framework ensures that your architecture aligns with industry best practices and AWS guidelines.

Available, Scalable, And Resilient

 
Design your architecture for high availability and fault tolerance by leveraging Amazon EC2 Auto Scaling. Distribute your workload across multiple Availability Zones (AZs) to mitigate the risk of downtime due to infrastructure failures. Amazon RDS Read Replicas, Amazon DynamoDB auto-scaling, and AWS Lambda can also help you to automatically adjust capacity in response to changes in workload. These same tools can also be used to optimize the overall performance of your app.

Monitoring And Logging

 
Use AWS CloudWatch for monitoring AWS resources and collecting logs, AWS CloudTrail for logging API activity, and Amazon CloudWatch Logs for storing application logs. Set up notifications to detect and respond to performance issues and security threats proactively.

Backup And Disaster Recovery

 
Protect your data and ensure business continuity. Use AWS services like Amazon S3 for durable object storage, Amazon Glacier for long-term data archival, AWS Backup for centralized backup management, and AWS Disaster Recovery for replicating critical workloads across AWS regions.

Cost Optimization

 
Utilize cost management tools like AWS Cost Explorer and AWS Budgets to analyze and forecast spending. Leverage AWS Reserved Instances for predictable workloads, explore AWS Spot Instances for cost-effective compute capacity, and implement tagging and resource optimization practices to reduce waste.

Continuous Integration And Deployment (CI/CD)

 
Implement CI/CD pipelines using AWS CodePipeline, AWS CodeBuild, and AWS CodeDeploy to automate the build, test, and deployment processes. Integrate with version control systems like GitHub or AWS CodeCommit to enable automated code deployments and ensure consistency across environments.

Amazon Web Services offer a broad selection of tools that can help HealthTech developers to design and deploy apps in a secure environment, but the bulk of responsibility over protecting the patients’ data still resides on the healthcare system. The industry evolves day by day, but so do hackers. HealthTech providers need to fully empathize with the harmful effects of compromised medical records, and not only keep in mind the security risks of today, but plan for the new cyberattacks of tomorrow.

Our company can help you bravely face the HealthTech future. Innovecs is a global software development partner, offering a wide array of cloud services. We are proud of our AWS consulting partner status, and our experts would be happy to share their expertise and answer all of your questions. Reach out to us for a talk, and stay tuned for more insights from the world of health technology.