Heart Healthy Foods You Should Try

As you age, taking care of your heart becomes increasingly important. By staying away from tobacco products, managing your stress and staying physically active, you help to keep one of your body's vital organs strong and healthy. But those aren't the only contributing factors – a well-balanced, nutritious diet is also key for maintaining your heart health and reducing your risk for developing chronic diseases such as heart disease, according to Eating Well magazine.

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Oracle

We’re a cloud technology company that provides organizations around the world with computing infrastructure and software to help them innovate, unlock efficiencies and become more effective. We also created the world’s first – and only – autonomous database to help organize and secure our customers’ data.

OTHER ARTICLES
Health Technology, Digital Healthcare

Can New Technology Drive Health Care’s Future?

Article | September 7, 2023

Over the past twenty-five years most businesses have been revolutionized by the easy availability of cloud and mobile-based computing systems. These technologies have placed power and access into the hands of employees and customers, which in turn has created huge shifts in how transactions get done. Now the companies with the highest market value are both the drivers of and beneficiaries of this transition, notably Apple, Facebook, Amazon and Alphabet (Google), as well as their international rivals like Samsung, Baidu, Tencent and Alibaba. Everyone uses their products every day, and the impact on our lives have been remarkable. Of course, this also impacts how businesses of all types are organized. Underpinning this transformation has been a change from enterprise-specific software to generic cloud-based services—sometimes called SMAC (Social/Sensors/Mobile/Analytics/Cloud). Applications such as data storage, sales management, email and the hardware they ran on were put into enterprises during the 80s and 90s in the client-server era (dominated by Intel and Microsoft). These have now migrated to cloud-based, on-demand services.

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Digital Healthcare

Role of AI and ML in the Healthcare Industry

Article | November 29, 2023

Contents 1. Alexa, Are You There? 2. Digital Assistants-Cum-Doctor-Assistants 3. Toward An AI-Friendly Life! 1. Alexa, Are You There? If Siri, Alexa, Google Now, or Cortana are your friends, you do not need any special introduction for today’s topic! This is because these digital assistants have become part and parcel of our lives; from completing our minimal tasks to helping us solve our problems, they make our day-to-day life simpler and more manageable. Popularly called AI, Artificial Intelligence is the simulation of human intelligence processes by machines. Similarly, Machine Learning, also called ML, is the capability of a machine to imitate intelligent human behavior. 2. Digital Assistants-cum-Doctor Assistants The unpredictable pandemic years, which took thousands of lives, depict the rise of complexities in the healthcare industry. To deal with such cases in the future tactfully, the healthcare segment needs to be proactive and implement advanced technologies to detect, resolve, and prevent untimely death. Modern technologies such as Artificial Intelligence and Machine Learning help the medical fraternity perform tasks usually done by humans quickly and accurately, saving much time that can be utilized elsewhere. Let’s take a quick tour of how AI and ML can boost the healthcare industry: Artificial Intelligence can broadly scan patient databases or consult patients via a chatbot or online support system to understand their symptoms, send data to doctors, and get real-time diagnoses and prescribed medicines. Machine Learning, a subset of AI, can replace traditional processes with a supervised one, as in, a patient can be treated based on similar symptoms and treatment of other patients. The process requires a quick scanning of the database, which can be time-consuming if done by human effort. Taking technology by storm, patients suffering from neurological disorders can be treated via Brain-Computer Interfaces (BCI) backed by AI. With the help of this technology, normal bodily functions, such as the ability to move, speak or react, can be restored. It can also assist doctors in treating patients with strokes, locked-in syndrome, etc.The healthcare segment is revolutionizing, as sensitive operations such as heart surgery are being performed with robotic precision and control with AI-based algorithms. For this purpose, precision machine learning processes are being used to train robots and improve accuracy. AI can also help in digital pathology. Instead of placing separate slides or tissue blocks and observing them manually, pathologists can do it via AI, which can help analyze digital slides using image analysis and machine learning. 3. Toward an AI-friendly Life! If you never forget to wear a smartwatch, track daily steps, get water intake notifications, eat mindfully, and consistently monitor pulse rates, then you are already AI-friendly! You have successfully incorporated AI into your life and taken the first step towarda healthy life!

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Health Technology

Innovation Insight for Healthcare Provider Digital Twins

Article | September 12, 2023

A digital twin is a digital representation of a real-world entity or system. The implementation of a digital twin is a model that mirrors a unique physical object, process, organization, person or other abstraction. For healthcare providers, digital twins provide an abstraction of the healthcare ecosystem’s component characteristics and behaviors. These are used in combination with other real-time health system (RTHS) capabilities to provide real-time monitoring, process simulation for efficiency improvements, population health and long-term, cross-functional statistical analyses. Digital twins have the potential to transform and accelerate decision making, reduce clinical risk, improve operational efficiencies and lower cost of care, resulting in better competitive advantage for HDOs. However, digital twins will only be as valuable as the quality of the data utilized to create them. The digital twin of a real-world entity is a method to create relevance for descriptive data about its modeled entity. How that digital twin is built and used can lead to better-informed care pathways and organizational decisions, but it can also lead clinicians and executives down a path of frustration if they get the source data wrong. The underlying systems that gather and process data are key to the success for digital twin creation. Get those systems right and digital twins can accelerate care delivery and operational efficiencies. Twins in Healthcare Delivery The fact is that HDOs have been using digital twins for years. Although rudimentary in function, digital representations of patients, workflow processes and hospital operations have already been applied by caregivers and administrators across the HDO. For example, a physician uses a digital medical record to develop a treatment plan for a patient. The information in the medical record (a rudimentary digital twin) along with the physician’s experience, training and education combine to provide a diagnostic or treatment plan. Any gaps in information must be compensated through additional data gathering, trial-and-error treatments, intuitive leaps informed through experience or simply guessing. The CIO’s task now is to remove as many of those gaps as possible using available technology to give the physician the greatest opportunity to return their patients to wellness in the most efficient possible manner. Today, one way to close those gaps is to create the technology-based mechanisms to collect accurate data for the various decision contexts within the HDO. These contexts are numerous and include decisioning perspectives for every functional unit within the enterprise. The more accurate the data collected on a specific topic, the higher the value of the downstream digital twin to each decision maker (see Figure 1). Figure 1: Digital Twins Are Only as Good as Their Data Source HDO CIOs and other leaders that base decisions on poor-quality digital twins increase organizational risk and potential patient care risk. Alternatively, high-quality digital twins will accelerate digital business and patient care effectiveness by providing decision makers the best information in the correct context, in the right moment and at the right place — hallmarks of the RTHS. Benefits and Uses Digital Twin Types in Healthcare Delivery Current practices for digital twins take two basic forms: discrete digital twins and composite digital twins. Discrete digital twins are the type that most people think about when approaching the topic. These digital twins are one-dimensional, created from a single set or source of data. An MRI study of a lung, for example, is used to create a digital representation of a patient that can be used by trained analytics processes to detect the subtle image variations that indicate a cancerous tumor. The model of the patient’s lung is a discrete digital twin. There are numerous other examples of discrete digital twins across healthcare delivery, each example tied to data collection technologies for specific clinical diagnostic purposes. Some of these data sources include vitals monitors, imaging technologies for specific conditions, sensors for electroencephalography (EEG) and electrocardiogram (ECG). All these technologies deliver discrete data describing one (or very few) aspects of a patient’s condition. Situational awareness is at the heart of HDO digital twins. They are the culmination of information gathered from IoT and other sources to create an informed, accurate digital model of the real-world healthcare organization. Situational awareness is the engine behind various “hospital of the future,” “digital hospital” and “smart patient room” initiatives. It is at the core of the RTHS. Digital twins, when applied through the RTHS, positively impact these organizational areas (with associated technology examples — the technologies all use one or more types of digital twins to fulfill their capability): Care delivery: Clinical communication and collaboration Next-generation nurse call Alarms and notifications Crisis/emergency management Patient engagement: Experiential wayfinding Integrated patient room Risks Digital Twin Usability Digital twin risk is tied directly to usability. Digital twin usability is another way of looking at the issue created by poor data quality or low data point counts used to create the twins. Decision making is a process that is reliant on inputs from relevant information sources combined with education, experience, risk assessment, defined requirements, criteria and opportunities to reach a plausible conclusion. There is a boundary or threshold that must be reached for each of these inputs before a person or system can derive a decision. When digital twins are used for one or many of these sources, the ability to cross these decision thresholds to create reasonable and actionable conclusions is tied to the accuracy of the twins (see Figure 2). Figure 2: Digital Twin Usability Thresholds For example, the amount of information about a patient room required to decide if the space is too hot or cold is low (due to a single temperature reading from a wall-mounted thermostat). In addition, the accuracy or quality of that data can be low (that is, a few degrees off) and still be effective for deciding to raise or lower the room temperature. To decide if the chiller on the roof of that patient wing needs to be replaced, the decision maker needs much more information. That data may represent all thermostat readings in the wing over a long period of time with some level of verification on temperature accuracy. The data may also include energy load information over the same period consumed by the associated chiller. If viewed in terms of a digital twin, the complexity level and accuracy level of the source data must pass an accuracy threshold that allows users to form accurate decisions. There are multiple thresholds for each digital twin — based on twin quality — whether that twin is a patient, a revenue cycle workflow or hospital wing. These thresholds create a limit of decision impact; the lower the twin quality the less important the available decision for the real-world entity the twin represents. Trusting Digital Twins for HDOs The concept of a limit of detail required to make certain decisions raises certain questions. First, “how does a decision maker know they have enough detail in their digital twin to take action based on what the model is describing about its real-world counterpart?” The answer lies in measurement and monitoring of specific aspects of a digital twin, whether it be a discrete twin, composite twin or organization twin. Users must understand the inputs required for decisions and where twins will provide one or more of the components of that input. They need to examine the required decision criteria in order to reach the appropriate level of expected outcome from the decision itself. These feed into the measurements that users will have to monitor for each twin. These criteria will be unique to each twin. Composite twins will have unique measurements that may be independent from the underlying discrete twin measurement. The monitoring of these key twin characteristics must be as current as the target twin’s data flow or update process. Digital twins that are updated once can have a single measurement to gauge its appropriateness for decisioning. A twin that is updated every second based on event stream data must be measured continuously. This trap is the same for all digital twins regardless of context. The difference is in the potential impact. A facilities decision that leads to cooler-than-desired temperatures in the hallways pales in comparison to a faulty clinical diagnosis that leads to unnecessary testing or negative patient outcomes. All it takes is a single instance of a digital twin used beyond its means with negative results for trust to disappear — erasing the significant investments in time and effort it took to create the twin. That is why it is imperative that twins be considered a technology product that requires constant process improvement. From the IoT edge where data is collected to the data ingestion and analytics processes that consume and mold the data to the digital twin creation routines, all must be under continuous pressure for improvement. Recommendations Include a Concise Digital Twin Vision Within the HDO Digital Transformation Strategy Digital twins are one of the foundational constructs supporting digital transformation efforts by HDO CIOs. They are digital representations of the real-world entities targeted by organizations that benefit from the advances and efficiencies technologies bring to healthcare delivery. Those technology advances and efficiencies will only be delivered successfully if the underlying data and associated digital twins have the appropriate level of precision to sustain the transformation initiatives. To ensure this attention to digital twin worthiness, it is imperative that HDO CIOs include a digital twin vision as part of their organization’s digital transformation strategy. Binding the two within the strategy will reinforce the important role digital twins play in achieving the desired outcomes with all participating stakeholders. Building new capabilities — APIs, artificial intelligence (AI) and other new technologies enable the connections and automation that the platform provides. Leveraging existing systems — Legacy systems that an HDO already owns can be adapted and connected to form part of its digital platform. Applying the platform to the industry — Digital platforms must support specific use cases, and those use cases will reflect the needs of patients, employees and other consumers. Create a Digital Twin Pilot Program Like other advanced technology ideas, a digital twin program is best started as a simple project that can act as a starting point for maturity over time. Begin this by selecting a simple model of a patient, a department or other entity tied to a specific desired business or clinical outcome. The goal is to understand the challenges your organization will face when implementing digital twins. The target for the digital twin should be discrete and easily managed. For example, a digital twin of a blood bank storage facility is a contained entity with a limited number of measurement points, such as temperature, humidity and door activity. The digital twin could be used to simulate the impact of door open time on temperature and humidity within the storage facility. The idea is to pick a project that allows your team to concentrate on data collection and twin creation processes rather than get tied up in specific details of the modeled object. Begin by analyzing the underlying source data required to compose the digital twin, with the understanding that the usability of the twins is directly correlated to its data’s quality. Understand the full data pathway from the IoT devices through to where that data is stored. Think through the data collection type needed for the twin, is discrete data or real-time data required? How much data is needed to form the twin accurately? How accurate is the data generated by the IoT devices? Create a simulation environment to exercise the digital twin through its paces against known operational variables. The twin’s value is tied to how the underlying data represents the response of the modeled entity against external input. Keep this simple to start with — concentrate on the IT mechanisms that create and execute the twin and the simulation environment. Monitor and measure the performance of the digital twin. Use the virtuous cycle to create a constant improvement process for the sample twin. Experience gained through this simple project will create many lessons learned and best practices to follow for complex digital twins that will follow.

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Digital Healthcare

Accelerate Growth with Top 7 EHR Analytics Courses

Article | July 7, 2023

Stay at the forefront of the digital healthcare revolution by mastering EHR analytics. Discover the top EHR certifications that provide comprehensive training and industry-recognized credentials. As healthcare organizations increasingly embrace digital solutions, the demand for skilled professionals well-versed in EHR analytics continues to soar. Numerous certifications and courses have emerged to meet this demand, offering comprehensive training and industry-recognized credentials. This article delves into the top EHR certifications and courses, exploring their unique features, advantages, and opportunities for professional growth and advancement. 1. Certified Electronic Health Records Specialist By pursuing this course, participants will gain knowledge and practical skills in EHR, medical billing & coding, anatomy & physiology, medical terminology, medical law and ethics, and health insurance in the United States. This electronic health record specialist certification includes hands-on exercises using specialized software to create patient records, generate lab reports, and take notes & codes. Furthermore, it emphasizes the legal aspects of patient confidentiality and the responsible disclosure of medical records, ensuring a solid understanding of privacy regulations and ethical obligations within the healthcare industry. 2. Deep learning in Electronic Health Records - CDSS 2 The course provides a comprehensive overview of the fundamental principles of electronic health records (EHR) while also addressing the challenges of applying time-series classification methods to EHR data, such as missing values and variable heterogeneity. Professionals will learn various imputation techniques and encoding strategies to handle these challenges effectively. Upon completion of the course, University of Glasgow awards a certificate. Additionally, this electronic health records certification explores the role of clinical decision support systems (CDSS) in analyzing data to aid healthcare providers in making informed decisions and improving patient care. 3. Introduction to Electronic Health Records The course aims to provide an introduction to the field of digital health, covering essential concepts and definitions in this emerging area. It encompasses various vital topics, including Learning Health Systems, EHR, and a wide range of digital health technologies such as mobile applications, wearable devices, health information systems, telehealth, telemedicine, ML, AI, and big data. The EHR analytics course evaluates these technologies by examining the opportunities and challenges they present and the evidence of their effectiveness in the context of digital health, both globally and within public health and healthcare domains. This electronic health record certification includes a case study on using digital health technologies to address various aspects of the global response to COVID-19. 4. Interprofessional Healthcare Informatics This course is offered jointly by the University of Minnesota and its National Center for Interprofessional Practice and Education. It provides a hands-on and interactive exploration of fundamental informatics tools and techniques, incorporating technology-enabled educational innovations to enhance the learning experience. The ten modules in the course will help participants create an online learning community and a functioning healthcare informatics network. The EHR analytics course covers multiple topics, such as emerging technologies, telehealth, gaming, simulations, and eScience. It aims to collectively imagine and shape the future of healthcare informatics within the rapidly evolving landscape. The course welcomes healthcare professionals and IT enthusiasts, encouraging a diverse and interdisciplinary approach to learning. 5. Certified Electronic Health Records Specialist The Certified Electronic Health Records Specialist (CEHRS) course is a fully-online program designed to train individuals to become certified specialists in electronic health records. It equips participants with the necessary skills to navigate EHR systems and pass the CEHR certification exam. In this EHR certification program, professionals will learn essential tasks such as auditing patient records for compliance, extracting clinical information, coding for reimbursement claims, processing medical record requests, reviewing documents for accuracy, collecting patient data, and facilitating communication with healthcare professionals and insurance providers. The course focuses on hands-on experience with actual EHR software, provides an overview of EHR systems, emphasizes compliance with HIPAA regulations, explores various medical record components, and trains students to track vital patient information and report public health data effectively. 6. Electronic Healthcare Records Basics, Plain & Simple This EHR analytics course emphasizes the critical role EHRs play in improving healthcare services. The course holds immense importance as it delves into topics such as the comparison between digital and paper patient records, definitions of EMR, EHR, and PHR, the necessity for a unified view of records, the critical components of EHR systems, perspectives from both patients and clinicians, technology-related challenges, the concept of meaningful use, and the impact of the 21st Century Cures Act in facilitating advancements in healthcare. By undertaking this course, participants will acquire comprehensive knowledge as well as an understanding of EHR systems and their potential for revolutionizing healthcare delivery. 7. Records and Health Information Management This comprehensive EHR training certification program has been designed for professionals looking to advance their careers or seeking to stay up-to-date in the medical field and prepare for industry-standard certification exams. The course covers essential skills such as processing patient admission and discharge documents, accurately recording and maintaining information in the electronic medical record (EMR), understanding third-party reimbursement terminology and concepts, and utilizing computer hardware as well as software to enter and process data using medical record software. Learners can get an excellent opportunity to gain comprehensive insights into electronic health records and enhance career prospects in the healthcare industry. Closing Lines The EHR analytics certifications discussed in this article offer healthcare professionals invaluable opportunities for long-term success and growth in the evolving realm of healthcare informatics. By acquiring the necessary skills and knowledge through these programs, professionals can enhance their proficiency in managing and utilizing EHR systems, positioning themselves as highly sought-after assets within the healthcare industry. The comprehensive EHR certification training provided by these certifications and courses not only equips individuals with the technical know-how but also grants them industry-recognized credentials that validate their expertise. This recognition opens doors to diverse career pathways, including positions in healthcare organizations, consulting firms, research institutions, and governmental agencies. Moreover, staying abreast of the latest developments in EHR systems through continuous education ensures professionals remain at the forefront of technological advancements, enabling them to adapt and thrive in a fast-paced digital healthcare landscape.

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Spotlight

Oracle

We’re a cloud technology company that provides organizations around the world with computing infrastructure and software to help them innovate, unlock efficiencies and become more effective. We also created the world’s first – and only – autonomous database to help organize and secure our customers’ data.

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Sunrise Senior Living Donates $75,000 to the Alzheimer’s Association

Sunrise Senior Living | May 02, 2016

Sunrise Senior Living announced today that it will be making a $75,000 donation to the Alzheimer’s Association’s® Brain Ball. To date, with sponsorship and fundraising activities combined, Sunrise has contributed nearly $3M to support the Alzheimer’s Association®.

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Sunrise Senior Living to Bring its World-Class Senior Care to Welltower’s New York City Development Project

Sunrise Senior Living | August 09, 2016

Sunrise Senior Living has been named operator of Welltower’s senior living community being developed in Midtown Manhattan. The project, in collaboration with international real estate firm Hines, is planned for the northeast corner of 56th Street and Lexington Avenue. Slated for a late 2019 opening, the residential community will promote wellness for its senior residents in need of high-quality assisted living and memory care services.

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Sunrise Senior Living Team Members Earn Industry “Hero Awards” for Excellence in Personalized Care

Sunrise Senior Living | October 19, 2016

Two Sunrise Senior Living team members in Pennsylvania and North Carolina, respectively, were recently recognized by health care associations for their individual contributions to providing seniors with compassionate, high-quality care.

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Sunrise Senior Living Donates $75,000 to the Alzheimer’s Association

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Sunrise Senior Living announced today that it will be making a $75,000 donation to the Alzheimer’s Association’s® Brain Ball. To date, with sponsorship and fundraising activities combined, Sunrise has contributed nearly $3M to support the Alzheimer’s Association®.

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Sunrise Senior Living | October 19, 2016

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