Cloud computing over the intelligent healthcare system

According to the American Association of Retired Persons (AARP)[245], 85% of senior citizens want to stay at home for treatment as long as the facilities are available. One of the concerns is that a large population around the world is aged 60 years or above. In the report of the United Nations on world population aging, which was published in 2015, it was mentioned that around 900 million people around the world are 60 years of age or above. This population will rise to 1402 million by 2030. Such a large population will occupy a significant portion of the health facilities in the hospitals. This situation can be avoided by building smart homes and cities, where automatic diagnosis systems will be a critical component. The automatic healthcare systems receive the data through the loT and transmit it to central cloud for the evaluation. The cloud furthermore stores/mines the data and intelligently predicts patient's health status. It also provides feedback to patient through the computing device. The physician then can attend to the patient directly or send necessary precautions to patient via communicating device. Moreover, so far there is no automated medical server used in the field of healthcare as it requires large number of specialists to monitor the patient's health status data.

The cloud is equipped with complex and high speed computation modules. At the same time, the computation module accepts the new data from patient and processes it, then compares the obtained result with the previous results. If found suitable, the patient will receive feedback. In case the suitable record is not found, the appropriate physician will be informed through via phone call or SMS. The physician can get the information about patient from the cloud. Cloud storage capable of storing high volumes of varying data was also shown to be essential to a big data healthcare system by several previous works. If even a thousand people wore a single pulse sensor that communicated hourly with a cloud storage database via a low-power wide-area network (LPWAN), there would be 168,000 new data points per week. This number increases drastically as more people wear sensors connected to the cloud storage framework, and as more kinds of sensors are introduced. Using the big data that will rapidly form and continue to grow in cloud storage, machine learning algorithms can be implemented in the high-computing environment of the cloud.

These algorithms could be designed to mine through the large amount of data, identify previously unknown disease trends, and provide diagnostics, treatment plans, and much more. As we know the cloud storage is the most viable method for storing data. However, providing accessibility for healthcare professionals without compromising security is a key concern that should be addressed by researchers developing healthcare loT systems. Machine learning offers the potential to identify trends in medical data that were previously unknown, provide treatment plans and diagnostics, and give recommendations to healthcare professionals that are specific to individual patients. Therefore, cloud storage architectures should be designed in a way to support the implementation of machine learning on big data sets.

IoT and smart health system paradigms

The following topics covers the broad area of loT and smart health system paradigms.

History of IoT in healthcare

In the past decade, internet-connected devices have been introduced to patients in various forms. Whether data comes from fetal monitors, electrocardiograms, temperature monitors or blood glucose levels, tracking health information is vital for some patients, though many of these measures required follow-up interaction with a healthcare professional. Yet, the use of loT devices has been instrumental in delivering more valuable, real-time data to doctors and reduces the need for direct patient-physician interaction. Early applications of loT in healthcare are "smart beds," which detect when they are occupied and when a patient is attempting to get up. A smart bed can also adjust itself to ensure appropriate pressure and support are applied to the patient without the manual interaction of nurses. Another area where smart technology quickly became an asset in healthcare is when coupled with home medication dispensers. These dispensers automatically upload data to the cloud when medication isn't taken, or any other indicators for which the care team should be alerted.

Role of IoT in Healthcare

Turn Data Into Actions: Quantified health is going to be the future of healthcare because health that is measurable can be better improved. Therefore, it is wise to take advantage of quantified health technology. We also know that data affects system performance, and for that we depend on loT devices.

  • Improve Patient Health: What if the wearable device connected to a patient tells you when his heart-rate is going out of control. Moreover, updating personal health data of patients on the cloud and eliminating the need to feed it into the electronic medical records (EMRs), loT ensures that every tiny detail is taken into consideration to make the most advantageous decisions for patients. Moreover, it can be used as a medical adherence and home monitoring tool.
  • Promote Preventive Care: Prevention has become a primary area of focus as healthcare expenses are projected to grow unmanageable in the future.

The widespread access to real-time, high fidelity data on each individual's health will reform healthcare by helping people live healthier lives and prevent disease.

  • Enhance Patient Satisfaction & Engagement: loT can increase patient satisfaction by optimizing surgical workflow, e.g., informing about patient's discharge from surgery to their families. It can increase patient engagement by allowing patients to spend more time interacting with their physicians as it reduces the need for direct patient-physician interaction as devices connected to the internet are delivering valuable data.
  • Advance Care Management: It can enable care teams to collect and connect millions of data points on personal fitness from wearables like heart- rate, sleep, perspiration, temperature, and activity. Consequently, sensor- fed information can send out alerts to patients and caregivers in real-time so they get event-triggered messaging like alerts and triggers for elevated heartrate, etc. This will not just massively improve workflow optimization but, also, ensure that all care is managed from the comfort of home.
  • Advance Population Health Management: loT enables providers to integrate devices to observe the growth of wearables as data captured by the device will fill in the data that is otherwise missed out in electronic health record (EHR). Care teams can receive insight driven prioritization and use loT for home monitoring of chronic diseases. This is another way that caregivers can make their presence felt in daily lives of the patients.

Challenges of IoT in healthcare

Internet of Things (loT) technology implementations have raised numerous concerns around personal data privacy and security. While many of today's devices use secure methods to communicate information to the cloud, they could still be vulnerable to hackers. Beyond personal data being stolen and misused, loT devices can be used for harm. For example, loT in healthcare can be life-threatening if not properly secured.

Example 1: A 2012 episode of "Homeland" demonstrated a hack of a pacemaker inducing a heart attack. Later the vice president of company, Dick Cheney, subsequently asked the wireless capabilities of that pacemaker be disabled. Example 2: In 2016, Johnson & Johnson warned one of its connected insulin pumps was susceptible to attack, potentially allowing patients to deliver unauthorized insulin injections.

Example 3: Then, in 2017, St. Jude released patches for its vulnerable remote monitoring system of implantable pacemakers and defibrillator devices. These are just a few of the medical loT attacks that have made headlines.

To counter these risks, the U.S. Food and Drug Administration (FDA) has published numerous guidelines for establishing end-to-end security for connected medical devices, and regulators will likely continue to regulate connected devices used by patients. In late 2018, the FDA signed a memorandum of agreement with the Department of Homeland Security to implement a new medical device cybersecurity framework to be established by both agencies. It also issued a draft update to its pre-market guidance for connected healthcare device manufacturers in 2018 to ensure end-to-end security is built in during device design and development stages. The possible solutions are (1) end-to-end communication encryption, (2) embedded secure code implementation, (3) regular software updates, (4) mutual authentication, and (5) device identification.

Future of IoT in healthcare

In present day the loT medical applications are available with multiple user- friendly configuration options along with simplified user interface, so, hospitals and healthcare sectors are no longer need to wait for training to deploy. Next generation devices are in the implementation or post-implementation stages. The future of loT in healthcare is now. In fact, Aruba Networks predicted that 87% of healthcare organizations will be using loT technology in their facilities by the end of 2019. Furthermore, it stated that 73% of applications of loT in healthcare will be used for remote patient monitoring and maintenance, 50% for remote operation and control, and 47% for location-based services.

Patient centered care

Healthcare is shifting its priorities from hospital centered services to patient centered services. The Institute of Medicine suggested an approach for improvement and "crossing the quality chasm" by outlining six aims for healthcare to be safe, effective, patient-centered, timely, efficient and equitable. Among the principles that had been proposed, the one that garnered most attention was the aim for healthcare to be "patient-centered by providing care that is respectful of and responsive to individual patient preferences, needs and values and ensuring that patient values guide all clinical decisions." Eight dimensions of patient-centered care as outlined by the Picker Institute include:

  • 1. Respect for patient's values, preferences and expressed need;
  • 2. Coordination and integration of care;
  • 3. Information, communication and education;
  • 4. Physical comfort;
  • 5. Emotional support and alleviation of fear and anxiety;
  • 6. Involvement of family and friends;
  • 7. Transition and continuity;
  • 8. Healthcare technology accessibility to every one.

The other beam of comfort lies in the information technology arena, whose epoch-making invention and development have been at the vanguard of human progress, in recent history. Today, technological advancements have made digital tools widely accessible and handy to the masses with approximately 46% of the world's population having access to the internet in 2016 and nearly 7.683 billion people having mobile cellular subscriptions in 2017[72]. Owing to this accessibility to the digital world, people have now become introduced to a boundless sphere of information, effortless communication, and endless opportunities by literally a click of the finger. Harnessing upon this massive penetration, technology has been deployed in healthcare which was advocated by the Institute of Medicine (loM) as a vital means to accomplish the aforementioned six aims. Additionally, the World Health Organization (WHO) also resonated with the essential role of technology in realizing the 2030 sustainable development goals related to health. [82]. In the 1960s, advancements in communication technology and information and communication technology (ICT) opened doors to Telemedicine, which is literally means of "healing at a distance" and, according to the Institute of Medicine, it is defined as "the use of electronic information and communications technologies to provide and support healthcare when distance separates the participants."

Soon, it was recognized that the approach towards the remote provision of healthcare needed to encompass a more comprehensive outlook by incorporating non-physician related care, such as nursing, pharmacy and elements of public health education along with promotion of self-care. This broader scope of telemedicine was coined as Telehealth. The turn of the century witnessed a colossal upsurge of the internet and ever)' sector including healthcare went on board to benefit from the fresh opportunities that now lay before them. This led to the rise of Electronic Health (eHealth) which is defined as "an emerging field in the intersection of medical informatics, public health, and business, referring to health services and information delivered or enhanced through the Internet and related technologies. In a broader sense, the term characterizes not only a technical development, but also a state-of-mind, a way of thinking, an attitude, and a commitment for networked, global thinking, to improve healthcare locally, regionally, and worldwide by using information and communication technology."

But what may be considered a game changer was the proliferation of mobile phones into the hands of a common man. Capitalizing upon this accessibility to technology, the healthcare sector found new ways to address the healthcare challenges facing them, heralding the rise of mobile health (mHealth). The mHealth is a subset of eHealth and provides medical and public health services and information via mobile technologies such as mobile phones and personal digital assistants (PDAs). The mHealth offers a means for healthcare professionals to keep their patients updated via reminders, alerts and health-related information. Multiple studies have focused on the role of mobile SMS as a means for impelling behavior change, self-efficacy and improving knowledge in areas such as sexual and reproductive health.

With the coming of the Internet of Things (loT) into the picture, it became possible to create a network between different devices through software, sensors and network connectivity thereby enabling an exchange of data between them. This propelled the rise of Digital Health which is defined as "an improvement in the way healthcare provision is conceived and delivered by healthcare providers through the use of information and communication technologies to monitor and improve the wellbeing and health of patients and to empower patients in the management of their health and that of their families" and includes categories such as mHealth, health information technology (IT), wearable devices, telehealth and tele-medicine and personalized medicine.

In recent times, with the realization of bringing patient-centric values of patient engagement and empowerment to the forefront, adoption of the latest technology in healthcare is become more common. With this scenario a new socio-technical concept of "Connected Health" came into reality. Its aim is to make health and wellness services safe, effective, efficient and as a result enhance the quality of life and lower costs. Connected Health is an overarching model that includes all aspects of technology use in healthcare such as telemedicine, telehealth, mHealth, and eHealth. Furthermore it mirrors gaps between technologies for information sharing and connectedness together for proactive care and integrated healthcare services. Moreover, it has opened up a new vista in healthcare by digitally connecting clinicians to clinicians, patients to clinicians and patients to other patients. Hospital facilities too are progressing in parallel by utilizing technological innovations to enhance the care and safety of the patients during their stay at the hospital, for instance, by installing automation systems in the building to regulate temperature, ventilation, and fixing smart locks. Interconnected clinical information systems such as Laboratory Information Systems ensure smart patient care processes. Moreover, identification systems enable authentication and tracking of patients, staff, and hospital equipment.

Teleconsultation and Remote Patient monitoring

The ample opportunities for effective communication resulting from technological advancements have laid the groundwork to enable real-time consultations between health providers and patients separated by geographical distance, a process known as teleconsultation and thus bridging the communication gap between them. A more robust form of teleconsultation is remote patient monitoring (RPM) which deploys the latest IT tools to provide diagnostic and treatment services to the patients located in remote and rural areas. For instance, Alentejo, an underserved region in Portugal with regard to adequate and accessible healthcare, successfully initiated telemedicine and teleconsultation in 1998 as a means to improve healthcare and is now an essential part of service delivery there. Moreover, a systematic review highlighted the feasibility of telemedicine in the field of dentistry for remote screening, diagnosis, and consultation. Additionally, teleconsultations with the health provider have been found to enrich patient sat?isfaction due to improved outcomes, ease of use, low cost, better communication and reduced travel time. Furthermore, studies have underlined strong support in favor of telemedicine in the aspect of patient safety since it has been revealed that use of telemedicine for consultation brought down the number of medical errors in between clinical visits, besides playing a part in lowering medication errors. As excessive waiting time at the hospital continues to be a pressing problem faced by patients, the efficiency of e-consultations to provide convenient access to healthcare professionals may be considered.

Wearable sensors

Miniaturized, sensor-enabled wearable devices have made it plausible for patients with chronic diseases such as cardiovascular disease and diabetes to monitor their vital signs such as blood pressure and blood glucose level and thus indulge in self-care. It further allows the patient to transfer the data obtained to a healthcare professional using wireless technology. A review highlighted the feasibility of wearable devices in the promotion of physical activity and weight loss. Moreover, the data obtained from the wearable sensors alert the patient and the healthcare team regarding adverse events and prompts timely remedial action. The Fig.11.2 represents the wearable sensors in healthcare.

Source: Wuefab

Figure 11.2: Wearable sensors in Healthcare

Insideable devices

Unlike wearable sensors which usually remain in contact with the skin, ingestible sensors gauge the internal changes in homeostatic imbalance and offer novel means to diagnose and monitor the human body. An ingestible sensor has been approved to monitor medication compliance among patients with hypertension and heart failure. Another novel technique of monitoring is by way of implantable sensors which can be positioned below the skin and permits the measurement of vital signs, for example, Cardio MEMS is an implantable device which helps in continuously monitoring pulmonary artery pressure. A randomized clinical trial revealed a reduction in hospitalization of patients with chronic heart failure by 50% when their daily pressures were monitored [156].

Mobile apps

Smartphones with inbuilt health apps provide a unique opportunity for patient engagement by promoting, adopting and maintaining healthy behaviors. As of 2015, approximately 165,000 health-related apps are available and are broadly classified as "wellness management apps" [253] which assist in modifying behaviors related to lifestyle, diet, fitness, etc., and "health condition management" apps which facilitate dealing with disease conditions by providing information about the disease, access to care and medication reminders. Chronic conditions including mental health conditions, diabetes, cardiovascular diseases, nervous system disorders and musculoskeletal conditions are amongst the most common conditions focused on health condition management apps.

Electronic Medical Records (EMR)

EMRs that can store health and medical information of a patient in digital form have widely attracted physicians; for instance, in Canada, approximately 75% [250]of physicians have shifted to EMR use. Besides improving the communication between the healthcare team, it delivers them readable and organized information which reduces the risk of medical errors. The Fig.11.3 represents samples of EMR in healthcare.

Health portals

Aimed at bridging the communication gap between the patient and providers, portals are personal healthcare-related websites that allow the patients to communicate with their healthcare team through teleconsultations. Moreover, they permit access to lab test results, schedule appointments with the doctors and refill prescriptions. A systematic review of the effect of patient portals concluded that ten out of twenty-seven studies reported positive effects in terms of medication adherence, self-care practices, improved patient satisfaction and functional status.

Big data

As a result of the digitalization of medical and health records (EMRs) and data generated from wearable devices, a large and complex volume of data is being produced known as Big Data. This massive reservoir of information is now being put to use by assisting clinicians in providing an observational evidence base.

Source: en.wikipedia.org-electronic health record Figure 11.3: Electronic Medical Records (EMR)

Big Data has also facilitated the opportunity to deliver personalized treatment by using analytics in assimilating genomics with EMR.

The human genome project

By far the most monumental scientific discovery in recent times was the unraveling of information regarding the structure, organization and function of the human genome undertaken by an international research collaboration known as the Human Genome Project. This project was an epitome of a partnership between biologists and technologists since the investigation into the genome applied computing technology extensively and these days, owing to further advances in biomedical technology, a sea change in the diagnosis and treatment of diseases is anticipated.

Personalized and precision medicine

As a result of advancements made through the Human Genome Project[111 ] in understanding a person's genetic makeup which determines their susceptibility to certain diseases, it is now possible to provide tailored therapies suitable for each patient, thereby making them safer and effective. Personalized medicine takes into account not just the genetic makeup of individuals but also their preferences, beliefs, attitudes, knowledge and social context. On the other hand, precision medicine utilizes patient centrism, engagement, digital health application, genomics, molecular technologies and data sharing in healthcare deliver)'.

D Printing

3D printing refers to the "deposition of materials such as plastic, metal, ceramics, powders, liquids or living cells in layers to produce a 3D object." It is redesigning healthcare since it is now possible to recreate body parts such as personalized prosthetics. Remarkably, Spanish scientists have successfully launched a prototype for a 3D bioprinter that can create a fully functional human skin and can be transplanted to burn victims[270].

Artificial intelligence in healthcare

An exciting dimension to the digitalization of healthcare is the development of intelligent machines which exhibit cognitive actions analogous to human beings and are capable of conducting real-time analytics using algorithms. For instance, IBM Watson helps clinicians make decisions by using natural language capabilities, hypothesis generation, and evidence-based learning. This mechanism is particularly useful given the surge in Big Data and will assist in excavating information and aid the doctors in making a quick and precise diagnosis. The potential role of an artificial conversation agent or Chatbot, which uses speech or textual methods to conduct a conversation is being explored in healthcare to assist with behaviour change in diabetes and obesity management. Additionally, Babylon Health is a conversational health service provider which uses artificial intelligence to have consultations with doctors.

CASE STUDY 1

A real-time system for the monitoring of blood glucose levels in diabetic patients. This system requires patients to take blood-glucose readings at set intervals manually. It after that considers two kinds of blood glucose abnormalities. The first is abnormal blood glucose levels, and the second is a missed blood-glucose reading. The system then analyses the severity of the abnormality, and decides whom to notify, the patient themselves, caregivers and family members, or emergency healthcare providers such as doctors. This system is practical, and it is realizable.

CASE STUDY 2

A system aimed at detecting heart attacks was built using ready-made components and a custom antenna. An electrocardiogram (ECG) sensor is used to measure heart activity, which is processed by a microcontroller. This information is shared via Bluetooth to the user's smartphone, where the ECG data is further processed and is presented in a user application. The authors identify that developing heart attack prediction software would improve the system. Further improvements could be made by measuring the respiratory rate, which is known to aid in the prediction of a heart attack.

 
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