According to a National Academy of Medicine discussion paper, social determinants of health (SDoH) account for upwards of 80% of a population’s health outcomes. Breaking this down further, 50% come just from socioeconomic and physical environment factors such as education, employment, income, family and social support, community safety, air and water quality, and access to housing and transit. SDoH determine access to and quality of healthcare, and are contributors to a system of disparate access to care.

We believe that to more efficiently provide comprehensive healthcare access to more people, providers will leverage technology to blend in-person and virtual modes of care delivery.

In this article, Amwell and Google Cloud examine five ways telehealth – as part of a provider’s overall care model – can help democratize access to healthcare. (graphic url) 

Remove distance as a barrier to care

8.6 million Americans live more than 30 minutes from their nearest hospital. Long drives can deter patients from seeking care or maintaining routine visits. On the flip side, 92% of Americans nationwide have access to wired broadband in the home or through mobile broadband. Therefore, having a virtual visit just a click away can help remove barriers to care, like distance.

Eliminate the risk of unnecessary exposure

Virtual care means that patients don’t have to worry about potential exposure in transit, while sitting in waiting rooms, or from direct interactions during in-person health visits. This is particularly relevant when it comes to those with chronic diseases or underlying conditions. Telehealth provides patients who may be more susceptible to diseases with access to continuous healthcare without putting them at higher risk for developing more severe symptoms. Virtual visits can occur in the comfort –and safety– of patients’ homes.

Extend access to specialized care

55% of preventable hospitalization or mortality in rural settings is due to lack of access to specialty care. With telehealth, physical proximity to specialized services–typically in urban areas–can be reduced as a limiting factor. Virtual solutions grant everyone access to top specialists, regardless of location.

Save time and money

By augmenting in-person visits with telehealth applications, providers can benefit from greater efficiencies in scheduling, helping to improve their bottom line, and add more flexibility to their workday. Meanwhile, patients can spend less on travel and childcare, limit time taken off work, and save on other costs associated with in-person visits — for a savings of $35 to $690 per visit. In a survey by the COVID-19 Healthcare Coalition, 76% of the 2,000+ patients surveyed across the US responded that transportation was removed as a barrier, 65% reported they no longer had to take time off from work for an appointment, and 67 percent reporting lower costs than an in-person visit.

Combat physician shortage and fatigue

Research shows there will be a shortage of more than 100,000 doctors by 2030. In the midst of a physician shortage, telehealth can help improve care delivery and make it more efficient, ensuring more people can still have their healthcare needs addressed. Additionally, by integrating intelligence such as case triaging along with telehealth into a virtual care model, providers can help reduce clinician burnout.

Amwell and Google Cloud are partnering to deliver transformative telehealth solutions that will make it easier for more patients to receive care and improve patient and clinician experiences across the continuum of care. One example includes embedding real-time captioning and translation services powered by Google Cloud’s AI and NLP technologies within the Amwell platform to increase health access and understanding for more people.

As physicians, we are excited that the future of healthcare will continue to blend cloud technologies like EHR-integrated telehealth platforms, AI, healthcare-trained virtual agents along with in-person care to create an integrated hybrid care model that will improve patient outcomes and unburden providers, all while expanding access to broader patient populations.

To learn more, download the whitepaper “Healthcare’s Virtual Transformation,” written in conjunction with Becker’s Hospital Review.

^{1: “Social Determinants of Health 101 for Health Care: Five Plus Five,” National Academy of Medicine, October 2017}

Last week we announced the private preview of Duet AI for Google Cloud, an always-on AI collaborator that uses generative AI to provide help to developers and cloud users. This article gives you a detailed look at Duet AI for developers, showing how Duet AI can help provide developers with real-time code suggestions, chat assistance, and enterprise-focused customization. You can sign-up here to join our waitlist for Google Cloud’s AI trusted tester program.  

We believe that addressing these use case​​s with large language models (LLMs) will usher in a major leap in productivity in enterprise development. Duet AI uses Codey, a family of code models built on PaLM 2. 

Developers continuously seek ways to improve their productivity and, over the past few decades, these efforts have resulted in massive productivity leaps due to technological changes. From advanced debuggers and online developer communities, to modern IDEs/notebooks and cloud computing, each advance brought massive changes in productivity. Despite these improvements, developers still face numerous challenges, some of which are unique to cloud development:

• Disruptive context switching and friction when integrating a new tool or service
• Excessive time spent on repetitive tasks
• Time required to understand a new code base or project
• Large cognitive workload when working on large code bases or complex APIs

Duet AI for developers focuses on challenges and tasks across the development lifecycle:

Code/Boilerplate Generation — Developers can describe the tasks they have in mind as a comment or function name, such as creating a Cloud Pub/Sub topic. Duet AI will generate a reference implementation that can be reviewed and modified, so developers don’t need to spend time reading through multiple documentation pages.

Inline Code Completion — To reduce the time spent on repetitive tasks and minimize the cognitive workload of tasks such as writing repetitive code or retrieving variable names, Duet AI provides intelligent, context-aware code completion, helping reduce the time spent on coding and enhancing the quality of the written code.

Enterprise Customization — Organizations frequently have massive code bases and specific recommended frameworks and best practices, which generic code assistance solutions may not be best positioned to support. With Vertex AI, developers will be able to tune and customize the underlying models and connect them to the Duet AI experience, allowing for assistance optimized to the needs of the organization.

Code Explanation — Developers spend significant time and effort reading and understanding code written by their peers or external contributors. To help assist in this process, Duet AI for code assistance provides an “Explain this code” option available whenever a developer selects their code, allowing them to more quickly understand, map, and navigate unfamiliar code bases.

Code security guardrails — Code generated by Duet AI can also be scanned for vulnerable dependencies via Source Protect, helping surface known public vulnerabilities impacting code, along with suggested fixes when available, bringing additional security.

By harnessing the power of AI-driven developer assistance such as the one provided by Duet AI for developers, businesses can unlock unprecedented levels of productivity and efficiency in software development, paving the way for a new era of innovation and growth.

These early features of Duet AI for Google Cloud will be available for limited users and we will be expanding access very soon. Sign up here to join Google Cloud’s AI Trusted Tester Program.

Hackensack Meridian Health (HMH) executive Mark Eimer explains how an ambitiously-timed rollout of a comprehensive suite of Google products helped the entire organization—from doctors to IT staff—achieve better security, cultivate a more equitable work environment, and ultimately, improve patient outcomes.

How does a recently merged, 17-hospital healthcare system fast-track a platform migration and hardware rollout securely and in a way that improves work for everyone, regardless of location or role? These are the questions that kept me up at night in early 2020, when the pandemic demanded a “big bang”—something our legacy laptops and operating systems couldn’t handle.

We began our work with Google in 2020 with the adoption of Chrome as our default browser. As we migrated platforms, keeping patient data safe was of the utmost importance to us, along with providing every staff member with the tools they needed to work virtually. Our staff often experienced issues accessing our web-based applications using Internet Explorer or Edge Browser, a problem that went away when we switched to Chrome. Chrome’s versatile compatibility also made it easier for my team to migrate all of our web-based operations, and Chrome’s security and manageability were key components to making this switch a huge win for the organization.

The success of this migration led us to extend our Google partnership to patient care applications—where Google’s expertise in AI and ML helps scale the use of diagnostics tools and improve other aspects of the patient journey.

Achieving security at every step 

Like so many other healthcare organizations, we’ve been concerned about ransomware attacks. This is part of why we moved to Google Workspace and distributed over 3,000 Chrome OS devices in kiosk mode in March of 2020, when many of us went remote due to the pandemic. We were very concerned about team members accessing corporate applications through home devices that were running EOL operating systems (WIN7), as well as a general lack of antivirus and encryption measures.

We were protected by the fact that Google’s software and hardware both had built-in security features that we needed to stave off sophisticated attackers. For example, Chrome OS automatically updates to the latest security update and encrypts data living outside the cloud on the hardware. These features protected us from security-related disruptions, letting us securely move a huge library of file shares and emails across thousands of accounts to Google Chrome OS in just four months.

A year later, in March 2021, we migrated the enterprise over to Google Workspace and saw an immediate reduction in spam by 30% from the inherent built-in AI/ML. This meant staff were less likely to receive (and click through) phishing attempts. My team could connect, create, and collaborate easily and securely—even as more of us were working from home and needed to access sensitive data remotely. 

Leveling the playing field

As an organization, we were surprised by how many team members didn’t have personal computers at home. We quickly decided that if we needed team members to work from home, the health network would have to supply hardware. Chromebooks’ lower price tag compared to PCs—on top of their built-in security controls—allowed us to purchase, deploy, and support that initial distribution of 3,000 Chromebooks to team members in less than three weeks, providing devices to every eligible remote employee instead of just a select few. This was vital to reaching our equitable technology goal as part of our diversity and inclusion initiative: everybody has the same tools to do good work.

When all employees have what they need to do their jobs well, we get better patient outcomes. Before we began this cloud adoption journey, patient and staff experiences were different within the hospitals and outside of them. 

Now it’s the same wherever our staff is, and we’ve seen efficiency and accessibility benefits extend to the patient side. For example, we built a web-based contact center that supports 80 locations that use Workspace and Chrome OS devices. Since customer service, admin, and providers are all on the same system, it has become a one-stop shop for patients.

Furthermore, through the Grow with Google program, we were able to provide another benefit to employees that drove our equity goals. Google trained 50 non-IT staff members—from environmental services, food and nutrition, and other non-tech areas who were interested in making a career change to IT—on the Google products we were using. They may not have thought about switching to a career in IT before the Grow with Google program came to our organization, but through this partnership, they now have that opportunity.

A strategic, long-term partner

With any large-scale rollout, the work doesn’t end once laptops are in employee hands. Google has shown their commitment to long-term collaboration as they continuously optimize their products for the unique needs of healthcare providers and go the extra mile in tailoring tools to our staff’s workflows. 

For example, on the Chrome OS side, the Google team has helped our registration desks and document centers with device integration for hardware like credit card readers and e-signature pads. They’ve also helped us meet security and privacy requirements mandated by state and federal governments around HIPAA, Medicaid, and Medicare reimbursements. Over this next year, we’ll look at a feature roadmap with Google Cloud to deliver further enhancements, iterating on the product itself to meet our needs for the present and the future.

Delivering the future of healthcare

The benefits we’ve seen around security and usability—and the ability to provide all staff with equal access to Google’s technology—are why we’re expanding our partnership with Google to both the administrative and clinical sides of HMH. In addition to further Google rollouts with corporate, next year we’re distributing Chromebooks to all 350 of our ambulatory clinics.

We’re also working with the Google professional services team to create a custom AI model that analyzes 3D mammogram images. This AI model will enable two providers to read mammograms—which adheres to international best practices but is currently rare in the US—without requiring additional time. Conducting double readings of mammograms will yield better health outcomes for our patients, such as a lower patient recall rate and an increased accuracy in detecting breast cancer.

We’re currently building the model using a variety of Google Cloud products, including Cloud Healthcare API. Once complete, this model is expected to be trained, deployed, and maintained in Google’s Vertex AI, allowing our providers to be more productive as they make clinical decisions with AI support. As the model is proven over time, we plan to make the predictive services accessible to other healthcare organizations.

With Google, we’re able to achieve a unified architecture for storing data as well as training and deploying AI models, which enable our staff to work more efficiently and securely from anywhere. While I may not be able to predict the future as accurately as AI can, I foresee our continued partnership with Google as a key part of HMH’s improved provider and patient outcomes.

At Google Cloud, we continue to invest in key technologies to progress towards our true north star on invisible security: making strong security pervasive and simple for everyone. Our investments are based on insights from our world-class threat intelligence teams and experience helping customers respond to the most sophisticated cyberattacks. Customers can tap into these capabilities to gain perspective and visibility on the most dangerous threat actors that no one else has. 

Recent advances in artificial intelligence (AI), particularly large language models (LLMs), accelerate our ability to help the people who are responsible for keeping their organizations safe. These new models not only give people a more natural and creative way to understand and manage security, they give people access to AI-powered expertise to go beyond what they could do alone. 

At the RSA Conference 2023, we are excited to announce Google Cloud Security AI Workbench, an industry-first extensible platform powered by a specialized, security LLM, Sec-PaLM. This new security model is fine-tuned for security use cases, incorporating our unsurpassed security intelligence such as Google’s visibility into the threat landscape and Mandiant’s frontline intelligence on vulnerabilities, malware, threat indicators, and behavioral threat actor profiles. 

Google Cloud Security AI Workbench powers new offerings that can now uniquely address three top security challenges: threat overload, toilsome tools, and the talent gap. It will also feature partner plug-in integrations to bring threat intelligence, workflow, and other critical security functionality to customers, with Accenture being the first partner to utilize Security AI Workbench. 

The platform will also let customers make their private data available to the platform at inference time; ensuring we honor all our data privacy commitments to customers. Because Security AI Workbench is built on Google Cloud’s Vertex AI infrastructure, customers control their data with enterprise-grade capabilities such as data isolation, data protection, sovereignty, and compliance support. 

Preventing threats from spreading beyond the first infection

We already provide best-in-class capabilities to help organizations immediately respond to threats. But what if we could not just identify and contain initial infections, but also help prevent them from happening anywhere else? With our AI advances, we can now combine world class threat intelligence with point-in-time incident analysis and novel AI-based detections and analytics to help prevent new infections. These advances are critical to help counter a potential surge in adversarial attacks that use machine learning and generative AI systems. That’s why we’re excited to introduce:  

• VirusTotal Code Insight uses Sec-PaLM to help analyze and explain the behavior of potentially malicious scripts, and will be able to better detect which scripts are actually threats. 
• Mandiant Breach Analytics for Chronicle leverages Google Cloud and Mandiant Threat Intelligence to automatically alert you to active breaches in your environment. It will use Sec-PaLM to help contextualize and respond instantly to these critical findings.

These new updates build on the existing AI in Google’s industry-leading solutions. For example, Chronicle Security Operations already uses frontline intelligence, integrated reasoning, and machine learning to identify initial infections, prioritize impact, and contain threats. Another example is reCAPTCHA Enterprise, which uses image noising capabilities to help protect your site from adversaries that leverage novel AI advances, greatly enhancing our defenses against bots. 

Adding intelligence to reduce toil

At Google Cloud, we help organizations modernize security wherever they are, in part by simplifying their security tools and controls whenever possible. Advances in generative AI can help reduce the number of tools organizations need to secure their vast attack surface areas and ultimately, empower systems to secure themselves. This will minimize the toil it takes to manage multiple environments, to generate security design and capabilities, and to generate security controls. Today, we’re announcing: 

• Assured OSS will use LLMs to help us add even more open-source software (OSS) packages to our OSS vulnerability management solution, which offers the same curated and vulnerability-tested packages that we use at Google.
• Mandiant Threat Intelligence AI, built on top of Mandiant’s massive threat graph, will leverage Sec-PaLM to quickly find, summarize, and act on threats relevant to your organization. 

These announcements build on existing capabilities that help customers centralize visibility and control, detect targets, and improve security across their platform. For example, Security Command Center (SCC) uses always-on machine learning to detect malicious scripts executing in the customer container environment and immediately alert the customer. In addition, Cloud Data Loss Prevention leverages machine learning to find and classify data, and with Confidential Computing you can collaborate on, train, and deploy sensitive and regulated AI models in the cloud, all while preserving confidentiality. 

Evolving how practitioners do security to close the talent gap 

At Google, we believe that to truly democratize security, we need to first acknowledge that AI will soon usher in a new era for security expertise that will profoundly impact how practitioners “do” security. Most people who are responsible for security — developers, system administrators, SRE, even junior analysts — are not security specialists by training. 

Imagine a world where novices and security experts are paired with AI expertise to free themselves from repetition and burnout, and accomplish tasks that seem impossible to us today. To help power this evolution, we’re embedding Sec-PaLM-based features that can make security more understandable while helping to improve effectiveness with exciting new capabilities in two of our solutions: 

• Chronicle AI: Chronicle customers will be able to search billions of security events and interact conversationally with the results, ask follow-up questions, and quickly generate detections, all without learning a new syntax or schema.
• Security Command Center AI: Security Command Center will translate complex attack graphs to human-readable explanations of attack exposure, including impacted assets and recommended mitigations. It will also provide AI-powered risk summaries for security, compliance, and privacy findings for Google Cloud.

These new releases bolster our existing efforts to tackle these issues through capabilities like IAM Recommender, which suggests permissions better suited to actual usage patterns. We will soon be augmenting this capability to cover organizational policies, further enabling the administrator to help improve the security posture of their organization. In addition, Mandiant Automated Defense applies machine learning to help reduce the repetitive Tier 1 alert triage problem and address alert fatigue. 

Offering availability 

VirusTotal Code Insight, available now in Preview, is our first example of putting Security AI Workbench to work for our customers. We will be rolling out other offerings to trusted testers in coming months, and they will be available in Preview more broadly this summer. Click here for the demo. 

Security AI Workbench, including Sec-PaLM and partner integrations, in addition to the product innovations described in our demo, are all building blocks for a larger effort to elevate security across the ecosystem. So far, that effort: 

• Provides assistive functions to rapidly develop IT generalist talent to Tier 1 security operator status in a way that wasn’t previously feasible. Security Command Center now can summarize threat intelligence insights and findings for Google Cloud, and Chronicle can quickly generate YARA-L rules or other detections. 
• Provides advanced functions such as iterative query and multivariate detection generation, conversational filtering and interaction with results, and smart case awareness to empower advanced Tier 2 and 3 security operators to focus on threat analysis instead of struggling with process and toil. Mandiant Threat Intelligence users now can elevate their core competencies to hunt, investigate, and remediate threats — using the same tools our own Mandiant experts use. 
• Fuses threat intelligence and AI-based analytic capabilities, which are unsurpassed in the market. VirusTotal Code Insight enables security teams to help gain insights and identify threats in suspicious code. This can significantly enhance their ability to detect and mitigate potential attacks.

However, this is just an initial step. We’ll continue to iterate and innovate, and we encourage customers and partners to leverage Security AI Workbench in new and exciting ways. Moving forward, we anticipate many new use cases to emerge over time. 

Building a safer future

While generative AI has recently captured the imagination, Sec-PaLM is based on years of foundational AI research by Google and DeepMind, and the deep expertise of our security teams. This work includes new efforts to expand our partner ecosystem to provide businesses with security capabilities at every layer of the cybersecurity stack. We have only just begun to realize the power of applying generative AI to security, and we look forward to continuing to leverage this expertise for our customers and drive advancements across the security community.