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AWS announces Minfy as Amazon Healthlake Partner. Better Together. Better World.

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Technology has revolutionized the Healthcare and Life Sciences industry. This has led to unprecedented ways in which the quality of human life has been enhanced: whether it be through early detection of diseases, steadfast treatments, rapid drug discoveries, or genome studies; many short-term and chronic diseases have found their magical potion aka cure.

Minfy has a history of expertise in the Healthcare and Life Sciences industries and continues to work with our customers to unlock various novel insights, find patterns from a plethora of human body parameters, and identify abnormalities from medical images. Drawing insights from such complex data can radically transform the preventive healthcare industry.  The need of the hour is a place where all this structured, semi-structured, and unstructured data can be organized, analyzed, managed, and used for feeding the machine learning models for predictions.

This is where Amazon HealthLake comes in, and Minfy is excited to announce that it has been selected as an Amazon HealthLake Launch Partner for the Amazon HealthLake Partner Program. This service allows healthcare providers, health insurance companies, and pharmaceutical companies to store, transform, query, analyze, and share health data in the cloud. Amazon HealthLake offers various features for storing, transforming, searching, and analyzing data, saving both time and energy while providing smooth efficiency and high accuracy.

Some of the vital features of Amazon HealthLake and its potential benefits for the Healthcare industry are mentioned below.

Secure and compliant data storage:

Amazon HealthLake supports data in the Fast Healthcare Interoperability Resources (FHIR R4) industry standard. With the use of HealthLake import API, importing files from S3 storage to the HealthLake datastore including lab reports, clinical notes, and insurance claims, is quick and easy. Amazon HealthLake’s data store creates a complete view of each patient’s medical history in chronological order and helps index all information to easily search without any hassle.

Amazon HealthLake is a HIPAA eligible service that allows for encryption with customer-managed keys. Customers can rest assured knowing that private health information (PHI) can be encrypted at the datastore level. You can control user access based on user needs with column level security to power AI/ML analytics.

Meaningful data transformation:

Integrated medical natural language processing (NLP) transforms all raw medical text data in the datastore to discern and extract meaningful information from unstructured healthcare data. Integrated medical NLP, which Amazon HealthLake leverages via Comprehend Medical, can automatically extract entities (e.g., medical procedures, medications), entity relationships (e.g., a medication and its dosage), entity traits (e.g., positive or negative test result, time of procedure), and Protected Health Information (PHI) data from medical text.

This transformed data is comparatively more mature and readier to be used to capture a patient’s medical history. What previously took hours or even days to capture and analyze can be done within minutes.

Better decision support by better search capabilities:

Amazon HealthLake supports FHIR Search and CRUD operations. In other words, the users can create, read, update, and delete pieces of information for more comprehensive and rich datasets. Even the electronic health/medical records (EHR or EMR) can be indexed into Amazon Kendra for an accurate representation of the medical history of the patient by ranking the content using Amazon Neptune knowledge graphs. With this semantic search, the query will fetch data that have context, unlike any other lexical search.

As the search results improve, the efficiency of comparisons between medical records and notes increases. When the medical records are well organized, then the shared clinical characteristics with the use of Neptune allow users to view metadata associated with patient notes in a simpler and standard view. This early intervention and efficiency of healthcare providers give more time to consult with patients better and allows a comprehensive check with a proper prescription to sustain a healthy life and hence move towards preventive care.

Detailed analysis and more promising predictions:

It is worth noting that Amazon HealthLake can seamlessly leverage Amazon SageMaker to build machine learning or deep learning models that can solve healthcare and life sciences challenges by interpreting the results via visualization techniques. Amazon HealthLake also connects to Amazon QuickSight to create dashboards by exporting and normalizing data to quickly explore patient trends. This can help find better insights, patterns, and anomalies in the health data. This will further enable regular interventions by healthcare providers to prevent a particular disease in its early stages itself.

Amazon HealthLake’s streamlining of data analytics and AI/ML model capability accelerate data insights for healthcare industry stakeholders. Several AWS cloud services can be used in conjunction with Amazon HealthLake, including Amazon Sagemaker to train the ML/DL models, Amazon QuickSight for visualization, Amazon Polly for telehealth, Amazon Kendra to search using natural language, and last but not least Amazon Rekognition to understand the medical images better, and these services can all be integrated to make the complete healthcare system exponentially efficient. Minfy is ready to leverage these services to deliver results to our customers and solve Healthcare and Life Sciences’ most challenging problems.

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