Value-based care requires data-driven decision-making but you don’t have the necessary resources to implement.
healthcare providers
are exploring new, technologically-driven ways to interact
and manage their patient populations. This includes home
health and monitoring, telehealth, and mobile applications.
However, these devices generate a large amount of data
which presents challenges around ingestion, processing,
and storage. There are also challenges in adapting
reimbursement systems for some of these technologies.
Your traditional IT model lacks the agility you need to keep pace with new technology that can improve outcomes
Insufficient security, compliance and availability can hamper your ability to compete and open the door to sophisticated, hard-to-identify attacks
Pill to Pill+ Model is where industry seeing the traction
Detour for an example of an AWS building block
And this approach of starting with the customer to enable innovation is rooted in a culture within our company which is about four things:
Innovation is in our DNA, and our structure and approach to product development and delivery is fundamentally different than other IT vendors.
Customer Obsession
Long Term Thinking
Inventive mind set that is okay with failure
And willingness to try new things, and therefore be misunderstood
While it’s difficult to precisely codify the rules and constructs for innovation, there are basic principles and mechanisms that are core to Amazon’s culture of innovation. And, not surprisingly, many of these are the same practices that govern success within the venture capital and startup world.
We’ll talk about each of these in greater detail but, as an overview, some of the key principles are
Customer Obsession; rigorous workback thinking
Long Term Thinking; stubbornness for a vision that has been developed through the workback process from the customer experience
Understanding that failures are inevitable in the pursuit of invention; mindset to fail fast and learn iteratively
Realization that innovators will, often, be seen as contrarian or outliers in the beginning and, potentially, for long periods of time
Really, enterprises and startups across every business segment are using AWS in a meaningful way.
Lyft pintrest slack Travel & hospitality :airbnbm expedia, Oyo in hc: Babylon,halodoc, Skinvision, Zocdoc,MayoClinic, Helix,
In BFSI: FINRA, Intuit, Coibase, In Social media & entertainment: Pintrest, slack, hungama, Netflix, education: BYJU, Courseera,
Companies around the world are moving to a cloud-based infrastructure to increase IT agility, gain unlimited scalability, improve reliability, and lower costs. They want the flexibility to expand their operations at a rapid pace without worrying about setting up new IT infrastructure. They want to enhance their end-user and customer experiences by minimizing latency, the time it takes for their data packets to travel, so they can avoid delays and interruptions.
AWS has millions of active customers every month. AWS is a large and rapidly growing business.
The AWS Cloud spans 69 Availability Zones within 22 geographic Regions around the world, with announced plans for 9 more Availability Zones and three more Regions in Cape Town, Jakarta, and Milan. Launched Bahrain recently for Middle East market
AWS has been continually expanding its services to support virtually any cloud workload, and it now has more than 140+ services that range from compute, storage, networking, database, analytics, application services, deployment, management, developer, mobile, Internet of Things (IoT), Artificial Intelligence (AI), augmented/virtual reality, security, hybrid and enterprise applications.
Amazon S3 holds trillions of objects and regularly peaks at millions of requests per second.
On average, every week, AWS customers are using more compute capacity on Amazon EC2 Spot instances than customers in 2012 were running across all of Amazon EC2.
Amazon Aurora continues to be the fastest growing service in the history of AWS, with tens of thousands of customers using Amazon Aurora for their relational databases, a number that has increased by approximately two-and-a-half times in the last year.
More than 100,000+ databases have been migrated using AWS Database Migration Service
Amazon Redshift is datawarehousing service and its usage is 10x faster than 2yr back.
More than a hundred thousand AWS customers use Amazon DynamoDB.
Amazon DynamoDB handles well over a trillion requests per day and trillions of requests per month.
Amazon Relational Database Service has hundreds of thousands of customers.
AWS announced that that tens of thousands of customers are using AWS machine learning services, with active users increasing more than 250 percent in the last year, spurred by the broad adoption of Amazon SageMaker since AWS re: Invent 2017.
NLP is just one of the technologies and capabilities reshaping healthcare. AWS is on the vanguard of democratizing these and putting them in the hands of every developer and data scientist. No longer the realm of science fiction.
Examples of each from various companies, Butterfly Network, Arterys, Change, etc.
Starting from Payers to Providers to Industry leaders and non-profit organisations using AWS services in imaginable meaningful way.
In providers space: Cleveland , Harvard Medical School to BCM …is bert Israel medical center Improving patient care with machine learning hosted on AWS has developed another machine learning model built on AWS that can detect where simple operating room schedule modifications would improve efficiency, save costs, and balance the load of the hospital during busier times. Patient readmission, higher volume of intensive care units using AWS cloud.
in Payer space; Aetna, CMS, in the industry Cerner, 3M, Philips, GE Healthcare, change Healthcare etc. Philips has created a Health Suite Digital platform to create next generation connected health and wellness innovation
Change healthcare is the largest health administrative network in the United States, processing claims, pharmacy requests, and performing other functions for more than 340,000 physicians and 60,000 pharmacies. Change Healthcare uses AWS services like Amazon EC2, Amazon S3, Amazon SQS, and Amazon SNS to handle millions of confidential transactions daily from its clients while maintaining with full compliance with healthcare industry regulations, including HIPAA.
In the Life Sciences space: Pfizer, Celgene, Novartis, Merck, Johnson & Johnson… etc.
Ambra Health, makers of the leading cloud-based, medical image management suite company which built their medical data and image management SaaS platform on AWS. it empowers some of the largest health systems such as Memorial Hermann and New England Baptist Hospital as well as radiology practices, subspecialty practices, and clinical research organizations to dramatically improve imaging and collaborative care workflows.
Xealth is a software platform that enables clinicians to easily integrate and prescribe digital health tools for patients from within their EHR workflows. These can include patient education, online third-party apps and programs, device monitoring, and non-clinical services such as food delivery and OTC product recommendations.
Attract and retain patients, increase efficiency, and improve workflow at your dental practice
The AWS Cloud spans 69 Availability Zones within 22 geographic Regions around the world, with announced plans for 9 more Availability Zones and three more Regions in Cape Town, Jakarta, and Milan. Launched Bahrain recently for Middle East market
William Ford Gibson is an American-Canadian fiction writer and essayist widely credited with pioneering the science fiction subgenre known as cyberpunk. Also known as noir prophet" of cyberpunk.
Our mission is to enable customers to transform their businesses by putting ML in the hand of every developer. [Note: adding a customer-focused angle to our mission will be most impactful with the analyst audience]
[Cover at high level + highlight our customer-focused approach – no need to address everything on this slide]
Our approach for ML is similar to how we approach other areas of the AWS business:
We focus on customers’ business needs and developer capabilities
Innovate rapidly on behalf of our customers
Offer a broad and deep set of services for our customers
We are also focused on providing customers with choices – which is why we support the most popular frameworks.
To summarize, the AWS AI and ML stack has three layers. Each layer addressing different audiences:
ML Frameworks & Infrastructure: For expert machine learning practitioners who work at the framework level and are comfortable building, training, tuning, and deploying machine learning models.
ML Services: For every day developers and data scientists we built and launched Amazon SageMaker, a managed ML service to build, train, and deploy machine learning models quickly.
AI Services: Developers with no prior machine learning experience can easily build sophisticated AI driven applications, like an AI driven contact center, live media subtitling, understanding voice of the customer, content moderation, or identity safety and verification, often
AI Services:
AI Services are intentionally easy to use. They can be accessed via a simple API call.
We’ve pulled the best and most targeted capabilities into ready-made services--for example image recognition or transcription.
The focus here is really on enabling any developer—no ML skills required—to be able to develop AI applications using one of our services.
These API services, used in conjunction, create compelling solutions that really target business problems and use cases.
Customers can build these capabilities into their new and existing applications to reduce costs, increase speed, improve customer satisfaction and insight, and build ‘modern’ intelligent applications
What is your use case? What are the capabilities you might need? There’s an AI Service, or a pairing of services that will address the need.
AI Services descriptions for color:
Amazon Rekognition:
Rekognition makes it easy to add image and video analysis to your applications. You just provide an image or video to the Rekognition API, and the service can identify the objects, people, text, scenes, and activities, as well as detect any inappropriate content.
Amazon Rekognition also provides highly accurate facial analysis and facial recognition on images and video that you provide. You can detect, analyze, and compare faces for a wide variety of user verification, people counting, and public safety use cases.Rekognition is a simple and easy to use API that can quickly analyze any image or video file stored in Amazon S3. Amazon Rekognition is always learning from new data, and we are continually adding new labels and facial recognition features to the service.
More info: https://aws.amazon.com/rekognition/
Amazon Polly:
Amazon Polly is a service that turns text into lifelike speech, allowing you to create applications that talk, and build entirely new categories of speech-enabled products.
Polly is a text to speech service that uses advanced deep learning technologies to synthesize speech that sounds like a human voice.
With dozens of lifelike voices across a variety of languages, you can select the ideal voice and build speech-enabled applications that work in many different countries.
More info: https://aws.amazon.com/polly/
Amazon Transcribe:
Amazon Transcribe is an automatic speech recognition (ASR) service that makes it easy for developers to add speech-to-text capability to their applications.
Using the Amazon Transcribe API, you can analyze audio files stored in Amazon S3 and have the service return a text file of the transcribed speech.
Amazon Transcribe can be used for lots of common applications, including the transcription of customer service calls and generating subtitles on audio and video content.
The service can transcribe audio files stored in common formats, like WAV and MP3, with time stamps for every word so that you can easily locate the audio in the original source by searching for the text. Amazon Transcribe is continually learning and improving to keep pace with the evolution of language.
More info: https://aws.amazon.com/transcribe/
Amazon Translate:
Amazon Translate is a neural machine translation service that delivers fast, high-quality, and affordable language translation.
Neural machine translation is a form of language translation automation that uses deep learning models to deliver more accurate and more natural sounding translation than traditional statistical and rule-based translation algorithms.
Amazon Translate allows you to localize content - such as websites and applications - for international users, and to easily translate large volumes of text efficiently.
More info: https://aws.amazon.com/translate/
Amazon Comprehend:
Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to find insights and relationships in text.
The service identifies the language of the text; extracts key phrases, places, people, brands, or events; understands how positive or negative the text is; analyzes text using tokenization and parts of speech; and automatically organizes a collection of text files by topic.
Using these APIs, you can analyze text and apply the results in a wide range of applications including voice of customer analysis, intelligent document search, and content personalization for web applications.
More info: https://aws.amazon.com/comprehend
Amazon Lex:
Amazon Lex is a service for building conversational interfaces into any application using voice and text.
Amazon Lex provides the advanced deep learning functionalities of automatic speech recognition (ASR) for converting speech to text, and natural language understanding (NLU) to recognize the intent of the text, to enable you to build applications with highly engaging user experiences and lifelike conversational interactions.
With Amazon Lex, the same deep learning technologies that power Amazon Alexa are now available to any developer, enabling you to quickly and easily build sophisticated, natural language, conversational bots
More info: https://aws.amazon.com/lex
Detour for an example of an AWS building block
Our mission is to enable customers to transform their businesses by putting ML in the hand of every developer. [Note: adding a customer-focused angle to our mission will be most impactful with the analyst audience]
Infrastructure security can be one of the most complex elements of your operation, because the high degree of interconnected systems across a wide range of hardware vendors makes it difficult to have good visibility into what’s going on and what new threats may have been recently identified in the wild.
But, with AWS, we operate together under a Shared Responsibility Model that makes us responsible from the hypervisor down, and you for the operating system up, which puts our respective attention on what we know best.
The AWS infrastructure is custom-built for the cloud, with all element designed to intercommunicate well and present the smallest attack surface possible. In addition, the physical security controls present in our data centers has been designed to be the most stringent in the world. This pursuit has led to AWS being trusted by governments, military organizations, global banks, healthcare institutions, and other high-sensitivity organizations.
Finally, our security team is monitoring the infrastructure all-day, every-day, and is well-connected with all major security watchdog groups and vendors to ensure that potential threats are identified immediately. And, they are doing this at massive scale, which is something that sets the AWS security organization apart. By looking across more than 1 million active accounts each month running virtually every conceivable type of workload, we can see issues that may only occur once in a billion operations multiple times a day. When we remediate the issue, we do so for the entire platform. That kind of visibility and response simply isn’t achievable for the vast majority of organizations.
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CAPITAL ONE: Capital One is using AWS to reduce its data centers from eight to three by 2018. Capital One is one of the nation’s largest banks and offers credit cards, checking and savings accounts, auto loans, rewards, and online banking services for consumers and businesses. The bank is using or experimenting with nearly every AWS service to develop, test, build, and run its most critical workloads, including its new flagship mobile-banking application. Rob Alexander, Capital One's chief information officer, says, "The financial service industry attracts some of the worst cyber criminals. We work closely with AWS to develop a security model, which we believe enables us to operate more securely in the public cloud than we can in our own data centers." Capital One selected AWS for its security model and for the ability to provision infrastructure on the fly, the elasticity to handle purchasing demands at peak times, its high availability, and its pace of innovation. [http://aws.amazon.com/solutions/case-studies/capital-one/]
AWS supports security standards and compliance certifications, including PCI-DSS, HIPAA/HITECH, FedRAMP, EU Data Protection Directive, and FISMA, which can help customers satisfy compliance requirements for virtually every regulatory agency around the globe.