Value-based healthcare, personalized medicine and patient centricity will quickly reshape how medical care is delivered and paid for. An important force behind this trend is the connectivity enabled by the Internet of Things (IoT), which wirelessly links people, IT systems and things, and enables two-way transfers of data through a network. All this can happen effortlessly, without human-to-human or human-to-computer interaction.
Is IoT in healthcare the missing link in value-based care?
IoT in healthcare enables us to connect a multitude of people, things with smart sensors (such as wearables and medical devices), and environments. Sensors in IoT devices and connected “smart” assets can capture patient vitals and other data in real time – then data analytics technologies, including machine learning and artificial intelligence (AI), can be used to realize the promise of value-based care. For example, significant value can be gained through:
- Operational improvements, which boost operational efficiencies in ways that enhance quality of care while reducing costs.
- Clinical improvements, which enable faster and more accurate diagnoses and a more patient-centric, scientific determination of the best therapeutic approach to support better health outcomes.
Let’s take a closer look at the potential for IoT in healthcare – also referred to as the Internet of Medical Things (IoMT) – to achieve true, value-based care.
A Connected Future: IoT for Healthcare Providers
IoT is paving the way for huge leaps forward in value-based care. What does IoT in healthcare look like today – and in the future? Learn from real-world examples of how data and IoT analytics are shaping future healthcare options.
IoT in healthcare can dramatically optimize workflow and staffing. Even a basic IoT solution can collect and bring together such data as staff location and expertise, patient acuity and location, and availability and location of critical diagnostic and therapeutic equipment. Once modeled, this data can help staffing managers improve workflows and make better staffing and scheduling decisions. The data can also be used to understand the movement of people and assets, and to predict where staffing and equipment will be needed most the next day or in the weeks ahead. Ideally, healthcare facilities will be able to move to appropriate dynamic, on-demand scheduling and resource allocation schemes. This would ensure that the right people are assigned to the right places to efficiently deliver quality care while improving staff morale and patient satisfaction.
Using IoT in healthcare, we can finally begin to tackle the critical problem of alert fatigue in clinical care delivery. This occurs when care providers receive too many clinical alerts – with up to 99 percent of them being false alarms. Alert fatigue is directly responsible for growing numbers of patient injuries and deaths.1
With IoT in healthcare, there are many ways to improve patient care and safety. For example, hospitals can use smart, connected monitoring devices that are linked to patient records, pharmacy systems, room location, nursing staff schedules and more. The sensors in these smart devices collect data, which is integrated with other medical device and system data and then analyzed to determine whether to trigger a silent alarm for a noncritical event or an audible alarm for a life-critical event. In this way, IoT will increase confidence in alarms, reduce work load and drive timely action – keeping patients safer.
Perhaps the greatest opportunities for IoT in healthcare lie in helping clinicians make faster, more accurate diagnoses and more precise, personalized treatment plans. These capabilities can improve outcomes, reduce costs and ultimately provide greater access to high-quality care for more people across the globe. IoT in healthcare technologies can integrate and analyze diverse types of diagnostically relevant data and move it to clinical decision-support systems. Healthcare providers using these systems will have a more complete picture of each patient’s health, as well as the tools to make faster and more precise treatment recommendations. Such opportunities are already being realized in the diagnosis and treatment of sepsis, where speed and accuracy are critical to saving patients’ lives.
IoT in healthcare: Better patient outcomes, lower cost
These are all examples of how IoT in healthcare allows us to collect granular patient data at frequencies previously unimaginable – not just when people are sick or in a hospital, but where people live and work. This data can be combined with behavioral, physiological, biochemical, genetic, genomic and epigenetic data and more. The volume and scope of the data will make it possible to develop powerful learning and adaptive diagnostic and therapeutic models. Over time, these algorithms will be able to detect new, previously hidden or unknown patterns and relationships between data, diagnoses, treatments and patient outcomes. The result will be next-generation expert systems that will eventually develop a level of autonomy in diagnosis and treatment. Soon, we’ll see them routinely assisting physicians and nurse practitioners, helping them provide high-quality care and achieve better patient outcomes at a lower cost.
Perhaps the greatest opportunities for IoT in healthcare lie in helping clinicians make faster, more accurate diagnoses and more precise, personalized treatment plans. This can improve outcomes, reduce costs and ultimately provide greater access to high-quality care for more people across the globe. Mark Wolff Chief Health Analytics Strategist, Global IoT Division SAS
About the Author
Mark Wolff, PhD, has more than 25 years of experience in the health and life science industries as a scientist and analyst. His areas of expertise include the development and application of advanced and predictive analytics in health care and life sciences, with an interest in outcomes and safety. His current work focuses on methods and application of machine learning to real-time sensor/IoT data, supporting safety research, visualization and development of intelligent decision-support systems.
“Alarm Fatigue: A Patient Safety Concern.” The American Association of Critical-Care Nurses.
- Хакатон открыл для меня новые сценарии применения аналитикиВ 2021 году компания SAS организовала международный хакатон #HackinSAS. В ходе хакатона участники из разных стран, с разным опытом и навыками создавали готовые для внедрения в эксплуатацию приложения и продукты с использованием аналитики SAS, искусственного интеллекта, облачных вычислений и технологий с открытым исходным кодом.
- 5 способов измерить здоровье улья с помощью аналитики и потоковых данныхТакой аналитический подход к пониманию здоровья пчелиных ульев может автоматически предупреждать пчеловодов об изменениях в весе улья, температуре, летной активности и многом другом.
- ModelOps: непрерывное управление жизненным циклом моделиModelOps – методика бесперебойной интеграции аналитических моделей в бизнес, когда модели, созданные командой аналитиков, реализуются в ИТ окружении компании в условиях внесения регулярных изменений и обновлений.