SMART HEALTHCARE

New technologies have influenced many parts of our daily life. Today’s healthcare system has also recognized the advantages of using Information and Communication Technology (ICT) to improve the quality of healthcare, turning traditional into smart healthcare. According to Blue Stream Consultancy, “smart healthcare is defined by the technology that leads to better diagnostic tools, better treatment for patients, and devices that improve the quality of life for anyone and everyone.” The key concept of smart health includes eHealth and mHealth services, electronic record management, smart home services and intelligent and connected medical devices. As mentioned above, one of the key concepts for improving today’s healthcare is eHealth, i.e. the usage of ICT in care. This is also how the World Health Organization defines the term: “eHealth is the use of information and communication technology (ICT) for health. Examples include treating patients, conducting research, educating the health workforce, tracking diseases and monitoring public health.” The European Union extends this definition by adding that eHealth “can benefit the entire community by improving access to care and quality of care and by making the health sector more efficient. This includes information and data sharing between patients and health service providers, hospitals, health professionals and health information network; electronic health records; telemedicine services; portable patient-monitoring devices, operating room scheduling software, robotized surgery and blue-sky research on the virtual physiological human.” The goal of the EU concerning eHealth is an improvement of EU residents’ health by using eHealth tools that provide instrumental information between countries when needed. To guarantee this improvement, the EU wants to enhance these eHealth tools and make them more effective, user-friendly and widely accepted by patients and professionals. Moreover, the EU aims at increasing the quality of healthcare and enabling better access to health care by making eHealth part of health policy.
  • Genomics

    Genomics

    Genomics is the study of whole genomes of organisms, and incorporates elements from genetics. Genomics uses a combination of recombinant DNA, DNA sequencing methods, and bioinformatics to sequence, assemble, and analyze the structure and function of genomes. It differs from 'classical genetics' in that it considers an organism’s full complement of hereditary material, rather than one gene or one gene product at a time. Moreover, genomics focuses on interactions between loci and alleles within the genome and other interactions such as epistasis, pleiotropy and heterotic. Genomics harnesses the availability of complete DNA sequences for entire organisms and was made possible by both the pioneering work of Fred Sanger and the more recent next-generation sequencing technology.

  • Connected Imaging & Algorithmic Diagnosis

    Connected Imaging & Algorithmic Diagnosis

    A medical algorithm is any computation, formula, statistical survey, nomogram, or look-up table, useful in healthcare. Medical algorithms include decision tree approaches to healthcare treatment (e.g., if symptoms A, B, and C are evident, then use treatment X) and also less clear-cut tools aimed at reducing or defining uncertainty.

    Medical algorithms are part of a broader field which is usually fit under the aims of medical informatics and medical decision-making. Medical decisions occur in several areas of medical activity including medical test selection, diagnosis, therapy and prognosis, and automatic control of medical equipment.

    In relation to logic-based and artificial neural network-based clinical decision support system, which are also computer applications to the medical decision-making field, algorithms are less complex in architecture, data structure and user interface. Medical algorithms are not necessarily implemented using digital computers. In fact, many of them can be represented on paper, in the form of diagrams, nomographs, etc.

    The intended purpose of medical algorithms is to improve and standardize decisions made in the delivery of medical care. Medical algorithms assist in standardizing selection and application of treatment regimens, with algorithm automation intended to reduce potential introduction of errors. Some attempt to predict the outcome, for example critical care scoring systems.

    Computerized health diagnostics algorithms can provide timely clinical decision support, improve adherence to evidence-based guidelines, and be a resource for education and research.

    Medical algorithms based on best practice can assist everyone involved in delivery of standardized treatment via a wide range of clinical care providers. Many are presented as protocols and it is a key task in training to ensure people step outside the protocol when necessary. In our present state of knowledge, generating hints and producing guidelines may be less satisfying to the authors, but more appropriate.

  • Citizen Health Records

    Citizen Health Records

    Citizen Health is building a decentralized universal health collective owned & governed by the people, not corporations or governments.

    By applying first principles thinking, we’ve fundamentally redesigned how healthcare is managed, how it’s paid for, and how decisions are made.

  • Healthcare Research Platform

    Healthcare Research Platform

    The Internet of Things (IoT) makes smart objects the ultimate building blocks in the development of cyber-physical smart pervasive frameworks. The IoT has a variety of application domains, including health care. The IoT revolution is redesigning modern healthcare with promising technological, economic, and social prospects. This paper surveys advances in IoT-based healthcare technologies and reviews the state-of-the-art network architectures/platforms, applications, and industrial trends in IoT-based health care solutions. In addition, this paper analyzes distinct IoT security and privacy features, including security requirements, threat models, and attack taxonomies from the healthcare perspective. Further, this paper proposes an intelligent collaborative security model to minimize security risk; discusses how different innovations such as big data, ambient intelligence, and wearables can be leveraged in a healthcare context; addresses various IoT and eHealth policies and regulations across the world to determine how they can facilitate economies and societies in terms of sustainable development; and provides some avenues for future research on IoT-based health care based on a set of open issues and challenges.

  • Medical Device Integration

    Medical Device Integration

    The Medical Devices Integration (MDI) solution is a software-based vendor-neutral solution that automatically collects and integrates patients' vital signs data generated from various medical devices to the Electronic Medical Records (EMR) system wirelessly.

    By seamlessly transferring data from monitoring devices to the EMR system, the MDI helps to eliminate healthcare staff's time taken to manually record and input readings into the EMR. This improves users' workflows and productivity, as well as bett er accuracy and timeliness of patient information in the EMR.

    How It Works

    Nurses scan the patient's bar-coded wristband, to identify and verify the correct patient before taking his/her vital signs.  The nurses then verify both the patient's name and identification number (NRIC) and the corresponding readings before confirming the entry in the MDI.  This barcode scanning and validation checks are built into the MDI solution to ensure completeness and accuracy of patient vital signs readings before they are interfaced directly to the right patient records in the EMR. This data collected is integrated from various medical devices to the EMR system.

    The solution deploys a middleware to communicate with the EMR using HL7 messages centrally while using many protocols to talk to the hospital devices. It runs on standard computing platforms and supports existing computers and workstations.

  • Telepresence

    Telepresence

    A typical video conference system includes a codec, monitor and sound system. In conference rooms for many people, additional monitors, microphones, and speakers are often added to create a fuller sense of the moving video and audio between video conference locations. Telepresence changes all of this.

    Telepresence systems are highly integrated multi-codec, multi-monitor, multi-microphone and multi-channel speaker systems. The objective of a Telepresence system is to present interactive video and audio between locations with near lifelike audio quality and with near life-size video images.

    The Telepresence Effect

    The Telepresence Effect is distraction free interactive video communication and collaboration. Meeting participants in a Telepresence meeting appear life-size and their voices sound as they would if all meeting participants were in the same meeting room. Additionally, smooth, easy and reliable presentation of computer content between meeting participants is generally considered a significant feature in the overall Telepresence Effect.

    In order to create this "Telepresence" effect, video conferencing companies such as Polycom, Tandberg/Cisco, and Life-size bind together and conceal multiple codecs, cameras, speakers, microphones and monitors into a video wall or a large monitor panorama. This wall or panorama is supplemented by high-quality audio so that speech clarity and tone from meeting participants are nearly perfect and spatially accurate. Spatial accuracy means that a person's voice sounds like it comes from them because it emanates from or near a monitor on which they appear.

    The result is an interactive video conference with a level of visual and audio clarity that is stunningly real and lifelike. The Telepresence Effect is a significant step beyond everyday video conferencing with set-top systems.

  • Telemedicine

    Telemedicine

    Telemedicine (also called telehealth) is transforming healthcare. Originally envisioned as a way to remotely diagnose and treat rural populations that lack specialized medical professionals, telemedicine is connecting patients everywhere with providers and caregivers. Patients are getting more control over when and how they get healthcare and more peace of mind because they are being monitored reliably.

    What’s changed? The Internet of Things (IoT) has become a reality, often running on Narrowband, the network optimized for it. IoT is connecting patients, smart medical devices, laptops, tablets, phones and wireless sensors with medical professionals.

    Example: a vital sign monitor and other bedside devices communicate via IoT with a home medical station, allowing a doctor or nurse to check the patient’s condition including compliance with their medication program.

    IoT represents a new model for healthcare, involving tablet-based gateways that can access apps to transmit patient data securely to a provider doing remote diagnosis as well as to the medical device manufacturer or other entity supporting the patient’s treatment. IoT-based connectivity supports a wide variety of functions such as user authentication, software updates, security, payments and information about medical and treatment history, care plans and prescriptions.

    Telemedicine via IoT has potential to improve the health of patients with chronic illnesses, a major cause of rising healthcare costs.

    IoT promises to facilitate medical device interoperability, better treatment decision making via analytics, and faster scalability. Meanwhile, on the horizon: 5G, a unified framework for connectivity that will accelerate development of IoT-based telemedicine—and high definition video for better communication between patient and doctor.

    IoT, optimally running on Narrowband, is providing the natural next step for telemedicine to move into the healthcare mainstream. Medical devices that have Internet addresses and can generate data for tracking, analysis, and action promise a future of better care at lower cost.

  • Value Based Care

    Value Based Care

    Value-based care is a form of reimbursement that ties payments for care delivery to the quality of care provided and rewards providers for both efficiency and effectiveness. This form of reimbursement has emerged as an alternative and potential replacement for fee-for-service reimbursement which pays providers retrospectively for services delivered based on bill charges or annual fee schedules.

    In order to transform how healthcare providers are reimbursed for services rendered, the Centers for Medicare & Medicaid Services (CMS) has itself introduced an array of value-based care models, such as the Medicare Shared Savings Program and Pioneer Accountable Care Organization (ACO) Model. Private payers have in turn adopted similar models of accountable, value-based care.

    While the traditional fee-for-service reimbursement model promoted quantity of services, federal officials have proposed several reimbursement programs that reward healthcare providers for the quality of care that they give to patients. Value-based care aims to advance the triple aim of providing better care for individuals, improving population health management strategies, and reducing healthcare costs.

    In more basic terms, value-based care models center on patient outcomes and how well healthcare providers can improve quality of care based on specific measures, such as reducing hospital readmissions, using certified health IT, and improving preventative care.

    The Department of Health & Human Services (HHS) has set a goal of converting 30 percent of fee-for-service Medicare payments to value-based payment models by the end of 2016. The agency expects 50 percent of traditional payments to make the transition by 2018.

    As the healthcare industry transitions to this new way of delivering care, many healthcare providers are left wondering how value-based care is different than the traditional model, what programs are available, and how successful has it been?

  • Population Health

    Population Health

     

    One area where IoT is making an impact is in advancing population health management and, more specifically, transforming costly senior care. With a rapidly growing senior population and approximately 80 percent of older adults having at least one chronic disease, IoT helps clinicians address key challenges seniors face such as the prevention and management of falls and medication adherence. With IoT, health systems are able to tap into an ecosystem of integrated solutions, from telehealth, to home monitoring, connected devices and more, to help provide ongoing, cost effective interventions to patients as they transition through different settings and levels of risk. IoT supports efforts to provide seamless patient care in the following three ways:

     

    1. Increased patient engagement
    2. Reduced costs of care
    3. Enhanced interoperability

     

  • Inventory Management- Pharmacy and Warehouse

    Inventory Management- Pharmacy and Warehouse

    “Inventory is usually a pharmacy’s largest asset. Once inventory levels are established, they become an important input to the financial aspect of any business, as they are key to driving cash flow and profitability, “said Don Raby, CPA, CGMA, Chief Financial Officer at PBA Health, an independently owned pharmacy services organization dedicated to helping independent pharmacies succeed in today’s marketplace.

    PBA Health provides group purchasing services, expert contract negotiations, and distribution services. The company also operates a VAWD-accredited warehouse and is a member of the Healthcare Distribution Alliance (HDA).

    Too much inventory translates to too little cash. Also, to less profitability. However, too little inventory can mean lost sales. If you don’t have the products patients need, they’ll go to another pharmacy to fill their prescriptions.

    “As a pharmacy owner, you have many facets to consider when managing your inventory. And certain best practices can drastically improve your bottom line,” Raby said.

  • Workflow Management & Optimization

    Workflow Management & Optimization

    Workflow management, or workflow optimization, means improving your current workflow. It can take a number of different forms. You might reduce your operating costs, find ways to get work done more efficiently or add new functions to your current workflow.

    Workflow optimization can also help get work done in less time or make things more efficient in other ways. This optimizes your business processes so you can get more things done with less time and money, and gain an advantage over the competition.

  • Precision Medicine (BigData/HPC)

    Precision Medicine (BigData/HPC)

    Precision medicine is an approach to patient care that allows doctors to select treatments that are most likely to help patients based on a genetic understanding of their disease. This may also be called personalized medicine. The idea of precision medicine is not new, but recent advances in science and technology have helped speed up the pace of this area of research.

    Today, when you are diagnosed with cancer, you usually receive the same treatment as others who have the same type and stage of cancer. Even so, different people may respond differently, and, until recently, doctors didn’t know why. After decades of research, scientists now understand that patients’ tumors have genetic changes that cause cancer to grow and spread. They have also learned that the changes that occur in one person’s cancer may not occur in others who have the same type of cancer. And, the same cancer-causing changes may be found in different types of cancer.

  • IoT Data Science & Analytics

    IoT Data Science & Analytics

    The word Data and Data Science have taken the business world by storm. Nowadays, improving business productivity and performance greatly depends on the collection and analyzing data. Businesses have been processing data for ages but the introduction of the Internet of Things (IoT) has been a game changer. Data collected through IoT is analyzed using different techniques as compared to that collected traditionally. Furthermore, Data Scientists require more sophisticated skills for analyzing IoT data.

    Difference between Traditional and IoT Data Science

    Traditional Data Science has been supporting businesses on static data and it will be wrong to undermine its importance. However, the business world has become highly competitive and it is only going to intensify in those terms. For this purpose, newer and smarter technologies are needed. Therefore, businesses are now finding it necessary to invest in IoT Data Science.

    In traditional Data Science, the analytics are static and restricted in use. The information that is received may not be updated so the results achieved after processing may not be smart or usable. On the other hand, since IoT data is being received in real-time, the analytics complement the latest market patterns. This allows making this analytics more actionable and intelligent as compared to traditional ones.

    However, it is not so easy to process such complex information. There are many sensor sources within an IoT network. It becomes important to differentiate between the multiple sensor points and external components that may be responsible for adding to the data points. Also, as more technology layers are added or integrated with IoT, it becomes more difficult to structure and process the multitudes of incoming data. So yes, Data Scientists do need to up their skill in order to comprehend IoT-generated data.

  • Telecare

    Telecare

    Telecare helps to manage risk and support independence by means of unobtrusive wireless sensors placed around the home which detect possible problems such as smoke, gas, flood or a person falling.

    Sensors automatically raise a local, audible alarm, as well as alerting a care, key holder or the monitoring center as appropriate.

     

  • Remote Patient Monitoring

    Remote Patient Monitoring

    Remote patient monitoring (RPM) uses digital technologies to collect medical and other forms of health data from individuals in one location and electronically transmit that information securely to health care providers in a different location for assessment and recommendations.

    Monitoring programs can collect a wide range of health data from the point of care, such as vital signs, weight, blood pressure, blood sugar, blood oxygen levels, heart rate, and electrocardiograms.

    This data is then transmitted to health professionals in facilities such as monitoring centers in primary care settings, hospitals and intensive care units, skilled nursing facilities, and centralized off-site case management programs.  Health professionals monitor these patients remotely and act on the information received as part of the treatment plan.

    Monitoring programs can also help keep people healthy, allow older and disabled individuals to live at home longer and avoid having to move into skilled nursing facilities. RPM can also serve to reduce the number of hospitalizations, readmissions, and lengths of stay in hospitals—all of which help improve quality of life and contain costs.

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