How Google Cloud and Fitbit are building a better view of health for hospitals, with analytics and insights in the cloud

Great technology gives us new ways of seeing and working with the world. The microscope enabled new scientific understanding. Trains and telegraphs, in different ways, changed the way we think about distance. Today, cloud computing is changing how we can assist in improving human health.When you think of the healthcare system, it historically includes a visit to the doctor,  sometimes coupled with a hospital stay. These are deeply important events, where tests are done, information on the patient is gathered, and a consultation is set up. But as you think about this structure, there are also limits. Multiple visits are inconvenient and potentially distressing for patients, expensive for the healthcare system and, at best, provide a view of patient health at a specific point in time.But what if that snapshot of health could be supplemented with a stream of patient information that the doctor could observe and use to help predict and prevent diseases? By harnessing advancements in wearables—devices that sense temperature, heart rate, and oxygen levels—combined with  the power of cloud and artificial intelligence (AI) technologies, it is possible to develop a more accurate understanding of patient health.This broader perspective is the goal of a collaboration between cardiologists at The Hague’s Haga Teaching Hospital, Fitbit—one of the world’s leading wearables that tracks activity, sleep, stress, heart rate, and more—and Google Cloud.Initially focusing on 100 individuals who have been identified as at-risk of developing heart disease, during a pilot study (ME-TIME), cardiologists at the hospital will give patients a Fitbit Charge 5—Fitbit’s latest activity and health tracker with ECG monitoring1—to wear at home after an initial consultation.With user consent, the devices will send information about certain patient behavioural metrics to the hospital via the cloud, in an encrypted state. This data is only accessed by (Haga Teaching Hospital approved) physicians and data scientists at the hospital and is not used by Haga for any other purposes than medical research during the study.2 With user consent, the data, which includes the amount of physical activity a patient is undertaking, will be monitored by Haga ’s physicians against other clinical information already gathered about the individual by the hospital during prior consultations. With user consent, Haga Teaching Hospital will also compare the data against its other relevant pseudonymized experience data, so the hospital can learn more about potential patterns and abnormalities associated with certain heart conditions. This is made possible by Google Cloud’s infrastructure, which will be used to store the encrypted data at scale, while artificial intelligence (AI) and data analytics tools will power near real-time analysis. For example, predictive analytics on this data could help identify early signs of a life-threatening disease such as a heart attack or stroke, so doctors can investigate further and provide preventative treatment—even before symptoms arise. Haga is using Device Connect for Fitbit, a new solution from Google Cloud, as part of the trial. Now available for healthcare and life sciences enterprises, the solution empowers business leaders and clinicians with accelerated analytics and insights from consenting users’ Fitbit data, powered by Google Cloud.3The project is in collaboration with partner Omnigen who has supported Haga with deployment, in addition to processing and analysis of data. Other hospitals in the Netherlands are already expressing interest in participating in similar projects. Longer term, we see applications to help with deeper understanding of overall population health for healthcare professionals, reducing unnecessary visits to the hospital – and better operation of the wider healthcare system. Preliminary results of the project may be available as early as the end of this year.“Health is a precious commodity. You realise that all the more if you are struck down by an illness. If you can prevent it or catch it in time so that it can be treated, you have gained a great deal,” said cardiologist, Dr. Ivo van der Bilt of Haga Teaching Hospital, who has been leading on this collaboration. “Digital tools and technologies like those provided by Google Cloud and Fitbit open up a world of possibilities for healthcare and a new era of even more accessible medicine is possible.”“This collaboration shows how Fitbit can help support innovation in population health, helping healthcare systems & care programmes create more efficient and effective care pathways that aren’t always tied to primary or secondary care settings. Plus it provides patients with tools to help them with their health and wellbeing each day, with metrics which can be overseen by clinical care teams.” said Nicola Maxwell, Head of Fitbit Health Solutions Europe, Middle East & Africa.This collaboration is an important step towards a goal of creating a more dynamic, rich, and holistic understanding of human health for hospitals, carried out with a strong emphasis on transparency. We are proud to be part of a project that we expect can help patients and healthcare workers alike. We believe this is only the start of what’s possible in healthcare with digital tools like Fitbit and cloud computing. 1. The Fitbit ECG app is only available in select countries. Not intended for use by people under 22 years old. See fitbit.com/ecg for additional details.2. Haga Teaching Hospital is responsible for any consents, notices or other specific conditions as may be required to permit any accessing, storing, and other processing of this data. Google Cloud does not have control over the data used in this study, which belongs to Haga Teaching Hospital. More generally, Google’s interactions with Fitbit are subject to strict legal requirements, including with respect to how Google accesses and handles relevant Fitbit health and wellness data. Details on these obligations can be found here. 3. This is the same data as that made available through the Fitbit Web API, which the Device Connect integration is built on.Related ArticleIntroducing Device Connect for Fitbit: How Google Cloud and Fitbit are working together to help people live healthier livesHow Google Cloud and Fitbit are working together to help people live healthier lives with Device Connect for Fitbit.Read Article
Quelle: Google Cloud Platform

Introducing Device Connect for Fitbit: How Google Cloud and Fitbit are working together to help people live healthier lives

Healthcare is at the beginning of a fundamental transformation to become more patient-centered and data-driven than ever before. We now have better access to healthcare, thanks to improved virtual care, while wearables and other tools have dramatically increased our ability to take control of our own health and wellness. Healthcare alone generates as much as 30% of the world’s data and much of this will come from the Internet of Medical Things (IoMT) and consumer wearable devices. Gaining insights from wearable data can be challenging, however, due to the lack of a common data standard for health devices resulting in different data types and formats. So what do we do with all this data, and how do we make it most useful?  Today, Fitbit Health Solutions and Google Cloud are introducing Device Connect for Fitbit, which empowers healthcare and life sciences enterprises with accelerated analytics and insights to help people live healthier lives. Fitbit data from their consenting users is made available through the Fitbit Web API, providing users with control over what data they choose to share and ensuring secure data storage and protection. Unlocking actionable insights about patients can help support management of chronic conditions, help drive population health impact, and advance clinical research to help transform lives. With this solution, healthcare organizations will be increasingly able to gain a more holistic view of their patients outside of clinical care settings. These insights can enhance understanding of patient behaviors and trends while at home, enabling healthcare and life science organizations to better support care teams, researchers, and patients themselves. Based on a recent Harris poll, more than 9 in 10 physicians (92%) believe technology can have a positive impact on improving patient experiences, and 96% agree that easier access to critical information may help save someone’s life.Help people live healthier livesThis new solution can support care teams and empower patients to live healthier lives in several critical ways:Pre- and post-surgery: Supporting the patient journey before and after surgery can lead to higher patient engagement and more successful outcomes.1 However, many organizations lack a holistic view of patients. Fitbit tracks multiple behavioral metrics of interest, including activity level, sleep, weight and stress, and can provide visibility and new insights for care teams to what’s happening with patients outside of the hospital.  Chronic condition management: For people living with diabetes, maintaining their blood glucose levels within an acceptable range is a constant concern. It’s just one of countless examples, from heart diseases to high blood pressure, where care teams want to promote healthy behaviors and habits to improve outcomes. Better understanding how lifestyle factors may impact disease indicators such as blood glucose levels can enable organizations to deliver more personalized care and tools to support healthy lifestyle changes. Population health: Supporting better management of community health outcomes with a focus on preventive care can help reduce the likelihood of getting a chronic disease and improve quality of life.2 Fitbit users can choose to share their data with organizations that deliver lifestyle behavior change programs aimed at both prevention and management of chronic or acute conditions.Clinical research: Clinical trials depend on rich patient data. Collection in a physician’s office captures a snapshot of the participant’s data at one point in time and doesn’t necessarily account for daily lifestyle variables. Fitbit, used in more than 1,500 published studies–more than any other wearable device–can enrich clinical trial endpoints with new insights from longitudinal lifestyle data, which can help improve patient retention and compliance with study protocols.Health equity: Addressing healthcare disparities is a priority across the healthcare ecosystem. Analyzing a variety of datasets, such as demographic and social determinants of health (SDOH) alongside Fitbit data has the potential to provide organizations and researchers with new insights regarding disparities that may exist across populations—such as obesity disparities that exist among children in low-income families, or increased risk of complications among Black women related to pregnancy and childbirth. Learn more about Fitbit’s commitment to health equity research here.Accelerate time to insightGaining a more holistic view of the patient can better support people on their health and wellness journeys, identify potential health issues earlier, and provide clinicians with actionable insights to help increase care team efficiency. Device Connect for Fitbit addresses data interoperability to “make the invisible visible” for organizations, providing users with consent management and control over their data. Leveraging world-class Google Cloud technologies, Device Connect for Fitbit offers several pre-built components that help make Fitbit data accessible, interoperable and useful—with security and privacy as foundational features.Enrollment & consent app for web and mobile: The pre-built patient enrollment and consent app enables organizations to provide their users with the permissions, transparency, and frictionless experience they expect. For example, users have control over what data they share and how that data is used.Data connector: Device Connect for Fitbit offers an open-source data connector3, with automated data normalization and integration with Google Cloud BigQuery for advanced analytics. Our data connector can support emerging standards like Open mHealth and enables interoperability with clinical data when used with Cloud Healthcare API for cohort building and AI training pipelines.Pre-built analytics dashboard: The pre-built Looker interactive visualization dashboard can be easily customized for different clinical settings and use cases to provide faster time to insights.AI and machine learning tools: Use AutoML Tables to build advanced models directly from BigQuery or build custom models with 80% fewer lines of code required using Vertex AI—the groundbreaking ML tools that power Google, developed by Google Research. Google Cloud’s ecosystem of delivery partners will provide expert implementation of services for Device Connect for Fitbit to help customers deploy at scale, and includes BlueVector AI, CitiusTech, Deloitte, and Omnigen.Potential to help predict and prevent diseaseThe Hague’s Haga Teaching Hospital in the Netherlands is one of the first organizations to use Device Connect for Fitbit. The solution is helping the organization support a new study on early identification and prevention of vascular disease. “Collaborating with Google Cloud allows us to do our research, with the help of data analytics and AI, on a much greater scale,” cardiologist Dr. Ivo van der Bilt said. “Being able to leverage the new solution makes it easier than ever to gain the insights that will make this trial a success. Health is a precious commodity. You realize that all the more if you are struck down by an illness. If you can prevent it or catch it in time so that it can be treated, you have gained a great deal.” Fitbit innovation continuesSince becoming part of the Google family in January 2021, Fitbit has continued to help people around the world live healthier, more active lives and to introduce innovative devices and features, including FDA clearance for the new PPG AFib algorithm for irregular heart rhythm detection, released in April of this year. Fitbit metrics including activity, sleep, breathing rate, cardio fitness score (Vo2 Max), heart rate variability, weight, nutrition, SP02 and more will be accessible through Device Connect Fitbit.  Google’s interactions with Fitbit are subject to strict legal requirements, including with respect to how Google accesses and handles relevant Fitbit health and wellness data. You can find details on these obligations here.We look forward to empowering our customers to create more patient-centered, data-driven healthcare. Read more about Haga Teaching Hospital’s work to predict heart disease on the Google Cloud blog, and visit cloud.google.com/device-connect to learn more about Device Connect for Fitbit.1. Harris Poll2. CDC3. Device Connect for Fitbit is built on the Fitbit Web API and data available from consenting users is the same as that made available for third parties through the Fitbit Web API, and enables the enterprise customer services through Google Cloud.Related ArticleRead Article
Quelle: Google Cloud Platform

Amazon RDS für Oracle unterstützt jetzt den Instance-Speicher für temporäre Tablespaces und den Database Smart Flash Cache für M5d- und R5d-Instances

Der Amazon Relational Database Service (Amazon RDS) für Oracle unterstützt jetzt den Instance-Speicher für temporäre Tablespaces und den Database Smart Flash Cache (Flash-Cache) für M5d- und R5d-Instances. M5d- und R5d-Instances sind ideal für Anwendungen, die Zugriff auf schnellen, lokalen Speicher mit niedriger Latenz benötigen, einschließlich solcher, die temporäre Datenspeicherung für Hilfsarbeitsspeicher, temporäre Dateien und Caches benötigen.
Quelle: aws.amazon.com

Registrierung für Erweiterten FreeRTOS-Wartungsplan jetzt offen

Wir freuen uns, bekannt zu geben, dass die Registrierung für den Erweiterten Wartungsplan (EMP) für FreeRTOS jetzt offen ist. FreeRTOS ist ein Echtzeitbetriebssystem für Mikrocontroller. EMP-Abonnements für FreeRTOS ermöglichen es Entwicklern von Embedded-Systemen, kritische Fehlerbehebungen und Sicherheitspatches für die von ihnen gewählte FreeRTOS-LTS (Long Term Support)-Version bis zu zehn Jahre nach Ende des ursprünglichen Support-Zeitraums zu erhalten. Während des Abonnementzeitraums erhalten Entwickler Benachrichtigungen über anstehende Patches in FreeRTOS-Bibliotheken, damit sie ihre Produktwartungsaktivitäten systematisch planen können. Dadurch können Entwickler ihre mikrocontrollerbasierten Geräte über Jahre hinweg schützen, Kosten für Betriebssystem-Upgrades sparen und das Risiko im Zusammenhang mit dem Patchen ihrer Geräte reduzieren.
Quelle: aws.amazon.com

AWS Batch verlängert den Job-Berichtsaufbewahrungszeitraum von 24 Stunden auf 7 Tage

AWS Batch hat den Job-Berichtsaufbewahrungszeitraum von 24 Stunden auf 7 Tage verlängert. Das bedeutet, dass Sie jetzt die Details zu AWS Batch-Jobs abfragen können, die vor bis zu 7 Tagen abgeschlossen wurden. Mit diesem längeren Aufbewahrungszeitraum müssen Sie sich keine Gedanken mehr um Jobs machen, die nach einem Tag verschwinden. Sie können Jobs einige Tage nach dem Absenden abfragen und haben einen besseren Einblick in die Jobs, die Sie im Laufe der Woche abgesendet haben.
Quelle: aws.amazon.com

AWS IoT TwinMaker veröffentlicht v1.2.0 des TwinMaker Grafana-Plugins

AWS IoT TwinMaker führt neue Funktionen ein, um die Leistung von Datenpanels zu verbessern, die mit dem TwinMaker Grafana-Plugin betrieben werden. Eine vollständige Liste an Funktionen finden Sie im Änderungsprotokoll zur AWS IoT TwinMaker App in Grafana. Zu den wichtigsten Funktionen in dieser neuen Version gehören:

Kunden können jetzt die maximale Anzahl an Alarmen definieren, die von der Abfrage Get Alarms abgerufen werden, wodurch sich die Payload-Größe konfigurieren lässt.
Die Abfragen Get Property Value History by Entity und Get Property Value History by Component Type unterstützen jetzt Vorlagevariablen wie propertyName. Somit können Entwickler dynamische Zeitreihen-Datenpanels erstellen, die basierend auf den ausgewählten Entitäten unterschiedliche Eigenschaften/Metriken anzeigen.

Quelle: aws.amazon.com

AWS Fargate erhöht die Konfiguration von Rechen- und Speicherressourcen um das Vierfache

Kunden von AWS Fargate können jetzt Amazon Elastic Container Service (ECS)-Tasks und Amazon Elastic Kubernetes Service (EKS)-Pods für die Verwendung von bis zu 16 vCPUs konfigurieren, was einer etwa vierfachen Steigerung gegenüber früher entspricht. vCPUs sind die primäre Rechenressource in ECS-Tasks und EKS-Pods. Eine höhere Anzahl an vCPUs ermöglicht es rechenintensiven Anwendungen wie Machine-Learning-Inferenz, wissenschaftlicher Modellierung und verteilter Analytik, leichter auf Fargate ausgeführt zu werden. Darüber hinaus können Kunden nun bis zu 120 GiB Speicher auf Fargate bereitstellen, was ebenfalls einer vierfachen Steigerung gegenüber früher entspricht. Dies hilft Batch-Workloads, Extraktions-, Transformations- und Lade-Tasks (ETL) sowie Genomik- und Medienverarbeitungsanwendungen, schneller speicherintensive Operationen auf Fargate auszuführen. Größere vCPU- und Speicheroptionen können auch die Migration zu Serverless-Container-Computing für Anwendungen vereinfachen, die mehr Rechenressourcen benötigen und nicht einfach in kleinere Microservices umgestaltet werden können.
Quelle: aws.amazon.com