Technology and the Internet of Things (IoT) are having a big impact on health care and health insurance, with research by Bain predicting that the revenue obtained from IoT and analytics alone will reach 22 billion by 2025.
In the health insurance sector, technologies such as artificial intelligence are enabling companies to sift through millions of pieces of data to find ways to reduce premiums, match products with their ideal target market, and generate new business leads. How can technology empower health insurance brands to deliver better service and build a larger client base?
Current leaders in the health insurance industry often ask beneficiaries to use wearable devices that track activity and calorie intake. Doing so enables them to collect vital information that can be used to offer reward programs. Various insurance providers are offering discounted rates on health insurance, and life insurance for diabetics. Discounts may seem small at first, but over the lifetime of a policy, consumers can save thousands of dollars.
It also encourages wearers to take vital steps to prevent obesity, Type 2 diabetes, stress, and other diseases and conditions linked to an inactive lifestyle or to a poor diet comprising high percentages of sugar and refined ingredients.
Like so many industries in today’s Third Industrial Revolution, the pace of innovation in healthcare today is fast and ever-changing. New technologies – like artificial intelligence (AI), machine learning, big data, the Internet of Things (IoT) and voice recognition – are at the heart of applications and tools that are becoming demanded by patients and more ingrained in clinicians’ daily workflows.
For vendors developing new solutions based on these technologies, it appears they find themselves in a ‘race,’ striving to be first-to-market in order to establish their competitive edge. But being on the bleeding edge of innovation isn’t always easy. The healthcare industry has not been immune to this rapid quest for first-mover advantage. Often when this occurs, these new solutions sacrifice the quality and functionality required to deliver on promised improvements.
Think about the initial introduction of the electronic health record (EHR). Billed as a way to make practices and physicians more efficient, many early EHR solutions had the opposite effect – creating a significant learning curve and adding to physicians’ workloads overall. While EHRs may have made great strides toward digitizing medical records, taking paper and manual processes out of the equation, they often created new problems that placed different burdens on practices, providers and patients. In fact, in the early days, physicians reported spending more than half of their workday – an average of six hours – using the EHR, plus another 86 minutes after hours.
But EHRs are not the only healthcare technology solution attributing to this challenge – it transcends innovation across the entire health IT sector. As an industry, we must take a step back and slowdown to ensure all new technology can deliver meaningful change to practices, providers and patients.
How to Design New Healthcare Technology with the End-User in Mind
A key to ensuring healthcare technology delivers true benefits is considering how it will fit into day-to-day operations of the end-user – whether that be a patient, a nurse, a surgeon or a billing manager. Before introducing any new technology to the market, make sure your first intention is to get it right.
To do that, engineering teams must employ “user-centered design,” a concept that emerged in the mid-1980s. This approach, defined by the International Standards Organization, “aims to make systems usable and useful by focusing on the users, their needs and requirements, and by applying human factors/ergonomics, usability knowledge and techniques.” The goal ultimately is to enhance effectiveness and efficiency, improve human well-being, user satisfaction, accessibility and sustainability, and to counteract possible adverse effects of use on human health, safety and performance.
User-centered design in healthcare could entail shadowing a nurse to observe his workflow when triaging patients, following a surgeon to see how she develops post-op papers, or interviewing patients to understand how they obtain healthcare information in their daily lives.
With that experience, you can then ascertain what capabilities would make users’ lives easier or more effective. From there, determine if there’s a way to improve an existing product on the market to fulfill needs, or whether a completely new platform is required.
Key Questions to Answer When Implementing a User-Centered Design Approach
There are several questions you must consider when following this method:
By George Mathew, MD, chief medical officer, North America, DXC Technology.
Patients, like all consumers, are more digitally aware and connected than ever before, as they continue to embrace the latest mobile devices and wearables. These devices, as well as the increasing availability of information on health management, have made patients more engaged participants in managing their own health and wellness.
As a result, they demand timely access to their own health information and expect care services that are personalized and convenient. They also want to use consumer-friendly digital tools to engage with their clinical records, lab results, medications and treatment plans.
However, many health organizations are still evolving their approach to meet this challenge. Existing systems of record in healthcare are often siloed, making it difficult to share actionable patient information across the continuum to accelerate service delivery and improve outcomes. The solution lies in implementing next-generation digital health platforms to integrate sources of historical clinical and wellness data to derive insights that drive more engaging patient experiences, better outcomes and lower costs.
Bridging the Information Gap
Integrating data sources across healthcare segments and aggregating them into a single digital-patient record, empowers patients and providers to make better healthcare choices and improve quality of care.
Rather than searching and clicking across multiple systems, an integrated digital patient-care platform creates a “single source of truth” to give patients and their providers quick and easy access to real-time, context-specific information for timely decisions. Benefits include the following:
Providers can optimize clinical operations, with results that include streamlined processes, reduced patient admissions, shorter hospital stays and, ultimately, improved quality of care for patients.
Patients may obtain a full view of their complete health journey and access relevant education and medication information — instead of having to wait for follow-up visits to see and discuss their results.
Patient engagement can also be improved through secure patient messaging capability, the ability for providers to receive patient experience feedback, and deployment of intelligent virtual assistants across a range of mobile devices to create a connected healthcare experience.
Additionally, when healthcare staff have access to the most up-to-date data, they can ensure the right materials are in the right place, reducing material waste and minimizing patient wait times. Furthermore, integrating clinical and wellness systems can help providers efficiently collect population health data to maximize health outcomes through early interventions.
The approval of electrocardiogram’s (EKG) through the FDA that enables atrial fibrillation detection right from a patient’s watch band is just one example of how the digitization of medical devices, a part of the Internet of Things movement, is leading product development and innovation in medicine. However, while medical devices built on a connected services platform include components for data storage, security, accessibility, and mobile applications, along with advanced analytics, successfully implementing artificial intelligence to drive actionable intelligence remains a challenge from an execution perspective. According to Gartner, 85 percent of data science projects fail. Successful integration of data science into medical device development requires a rethinking around the role of data science in product design and life-cycle management.
Viewing data science as a product
While data science is rightly defined as the process of using mathematical algorithms to automate, predict, control or describe an interaction in the physical world, it must be viewed as a product. This distinction is necessary because, like any medical product, data science begins with a need and ends with something that provides clear medical utility for healthcare providers and patients.
It is erroneous to restrict the realm of data science to just the designing of algorithms. While data scientists are good at fitting models, their true value comes from solving real-world problems with fitted data models. A successful algorithm development process in data science includes business leaders, product engineers, medical practitioners, and data scientists collaborating to discover, design and deliver. For instance, a typical data science integration with a medical device product would include many of the following activities:
Identifying the medical need
Identifying proper data variables
Developing the right analytic models
Designing analytic algorithm integrations
Performing testing and verification
Deploying beta versions
Monitoring real-time results
Maintaining and updating algorithms
Considering data science as a product or feature of a product provides organizations with a different paradigm for execution focused on a tangible outcome. Data scientists are trained to develop accurate models that solve a problem, but the challenge many companies face is operationalizing those models and monetizing their outputs. Furthermore, conceptualizing data science as a product will ensure companies focus on its implementation, rather than just its development.
Advanced analytics: Part of the process, not an afterthought
Designing intelligence (even AI) into a connected medical device first depends on whether the data is being used to make a real-time decision or report on the outcome of a series of events. Most companies don’t realize the layers of advanced analytics that create actionable intelligence. By understanding these layers, which range from simple rule- and complex rule-based analytics to asynchronous event rules, complex event processing, and unsupervised learning models, companies can move quickly into developing mature analytics that have an impact from day one. As a company matures its analytics system from descriptive and diagnostic to predictive and prescriptive, it should also evolve to include strategic opportunities to provide business value, including automating decisions that can be delegated to a smart decision-support system.
Successful integration involves viewing advanced analytics as an architecture and not as a single solution to be implemented. The best way to make sure that you are successful in analytic development is to follow a continual process of discovery, design and delivery. For instance, data science architecture may begin with a business question, requiring you to determine if you have the right data and can actually leverage that data in the existing IT system. If you don’t answer this basic question, you will have challenges fully vetting the analytic opportunities available to you.
Recognizing common challenges in data science execution
Data science execution is often impaired by common missteps, like incongruence between customer and business needs and solving technical problems when it’s too late to have a positive impact. Another significant mistake from the business side is treating data science like a one-time accomplishment and not realizing it is a continuous process, or like a software development process with an unwarranted fixation on tools rather than skills and capabilities.
To use a common metaphor, data science is not a single moon shot, but laps around a track. Ultimately your goal is to run progressively faster around the track. An equally major drawback hindering execution is artisan thinking where design is seen as the ultimate end to the data science process. In fact, the most desirable approach is a modular system with emphasis on consistently maintaining and improving what has already been designed. This is particularly true for medical devices where innovation and changes in technology are continuing to better support and enable patients and practitioners.
Remote monitoring. Smart sensors. Better communication and overall patient care. The internet of things has some incredible applications for the health industry — assuming we can overcome the security challenges it brings with it. But where do we start?
The potential of the Internet of Things to revolutionize the world has already been well-documented – as has its potential security shortcomings. I don’t believe it’s hyperbole to call IoT one of the most disruptive digital technologies ever developed, if not the most. But that disruption can easily be a double-edged sword.
Consider the healthcare industry, for example. Hospitals, care providers, and covered entities regularly work with some of the most sensitive data in the world, subject to some of the most stringent protections. They have an inarguable duty of care to keep protected health information (PHI) out of the wrong hands.
Incautious application of IoT technology runs directly counter to that duty of care.
Unless you want your organization to be included in that statistic, you’re going to need to take a step back and re-examine your security practices. The Internet of Things is by its very nature unlike any technology you’ve used in the past. What that means is that it requires a completely different approach.
You must have some way of monitoring, managing, and locking down any endpoints that might have even a passing connection to patient data. You need to implement new processes and procedures regarding how devices are used and interconnected within your organization. Finally, you need to be aware of PHI no matter where it is and who’s using it — and if someone is accessing it who shouldn’t be, you need the capacity to lock down their access and protect that data.
For an industry where even standard IT can prove challenging, that’s a pretty intensive list. It’s a small wonder, then, that many healthcare organizations choose to work with managed services providers rather than deal with things internally. And if, after a security assessment, you find that your own IT staff lack the expertise, that might be the best bet for you as well (at least until your staff can receive proper training).
Of course, selecting an IoT services provider comes with its own laundry list of challenges. You’ll need to school yourself in the tactics and language the bad eggs use to try to lure in new clients, and you’ll need to ensure that any providers you work with are fully HIPAA-compliant. There are a few signs you should look out for in that regard:
One of the most recognized annual awards programs in the world today—the MedTech Breakthrough—has recently announced the results of its 2018 awardees. Evaluated by an independent expert panel, the nominees were carefully examined, and winners were selected based on various considerations. Awards were given according to the following categories: medtech leadership, clinical and health administration, patient engagement, electronic health records, genomics, internet-of-things (IoT) healthcare, medical data, mobile communication and telehealth, healthcare cybersecurity and medical devices.
This award program is a testament to the continuous innovations in the field of medicine brought about by the incorporation of various technological advancements in other fields of science.
The Progress of Medicine
The progress of medical science at present is obviously at its zenith as compared to its level of progress in the past. Medicine, for example has existed for several millennia, and most of it was largely non-scientific, for in earlier times medicine was closely associated with religious and superstitious beliefs.
In our contemporary time, however, every aspect of medicine seems to be innovating at an unprecedented pace, and other technological advancements in fields like physics, genetics, computer programming and engineering, and chemistry seem to be all contributing to the progress of medical science and medical institutions.
By simply looking at the above mentioned awards distributed by MedTech Breakthrough, for example, you would immediately see the inclusions of the internet-of-things, genomics, medical data, mobile communications and electronic records, all of which seem to have a somewhat detached relationship to medical science. Yet, it is obvious that the progress of medical science can no longer be isolated from other technological advancements.
Medical Science and Alternative Medicines
Medical science has slowly detached itself from alternative medicines by strictly subscribing to the scientific method in the diagnostic and treatment of diseases. If a medical practice, therefore, is based only on alternative medicines without the backings of scientific studies, it is presumed to be based on unwarranted assumptions without scientific merit. Scientific medicine, however, does not peremptorily debunk the efficiencies of alternative medicines, for that would be unwise. What it is debunking is the method by which alternative medicines assume the efficacious of their alternative methods of treatments.
A good point of reference would be the practice of chiropractic. Chiropractors for example, start with the premise that diseases are simply indicative of the effects of subluxations. They focus then on the detection and eventual correction of vertebral subluxation to heal maladies. Although there are mixer chiropractors who combine diagnostic and treatment approaches from different osteopathic viewpoints, most of them still solely attribute diseases to subluxation. Yet, subluxation and its relationship to a disease is really hard to prove scientifically.
Mobile technology is impacting every element of American healthcare–from insurance and billing to documentation and caregiving, the impacts are being felt. The truly transformative element of the mobile revolution is not the technology itself, or the way it changes the look and feel of the tasks it affects. Despite complaints of the depersonalizing effect of technology, the ultimate value of mobile in the sector will be how it enhances and encourages communication.
Providers are Going Mobile
Already, flexibility and functionality have already drawn providers to mobile devices and solutions. Voice-to-text technology and similar automated solutions are in the offing to relieve the documentation burden that has dampered some amount of enthusiasm toward digitization. Bolstered by these advancements, caregivers will go from subjects of their EHRs to masters of patient encounters.
One of the huge benefits of mobility — as opposed to simply being networked on desktop computers or having a digital health records solution — is the capacity for greater native customization and app development. Native apps are like the currency of the mobile, smart device world providers are entering. Developers can deliver personal, branded interfaces that allow doctors to choose precisely how they want their dashboards to look, giving their EHRs a custom touch that has been sorely lacking throughout their implementation.
App-centric development will further reduce the friction of adoption and utilization, giving doctors a sense of empowerment and investment, rather than the bland inertia that has carried digitization thus far.
The personalization of the technology through app development will help boost adoption, and return the focus to what the technology enables, rather than how it looks or what it has replaced. Mobile technology’s strength will be in reconnecting doctors and patients, and creating bridges of data and communication across the continuum of care.
Patients are Going Mobile
Patient-facing health apps and mobile point of access to care combine convenience and cost-saving with a learning curve. Increasing the visibility of EHRs through mobile portals gives patients greater reason to develop some basic health literacy, and levels the playing field during doctor encounters. The more providers use mobile solutions, the more incentive patients will have to do the same.
When apps are connected to prescription management and can monitor adherence to treatment plans, mobile devices provide a two-way mirror enabling doctor and patient to remain connected long after the encounter is over. This can allow providers to better anticipate and intervene where drug abuse is at risk, as well as to prevent ED admissions and re-admissions beyond what telehealth has been able to achieve.
Even without connecting providers, mobile health apps will also support personal health management, with an eye to prevention as well as education. From diet-planning to workout tracking and even disease management, patients have more ways than ever to study their bodies and better understand their unique wellness needs. As providers and their EHRs evolve to integrate mobile patient-generated data, the potential for customization will make each encounter more conversation-driven, using data as a platform to educate, engage, and advance communication.
All these personal, data-rich conversations will help push prevention and population health into front of mind for a generation.
The Internet of Things (IoT) is taking hold in nearly every aspect of our lives. No longer are we content with simply connecting via a computer or mobile device. These days, our homes are filled with connected devices, all purporting to make our lives easier, more efficient, and in many cases, more entertaining.
However, the IoT’s creep isn’t limited only to our homes. One area where IoT is already taking hold and is expected to grow even more is in the health care industry. Often referred to as Medical IoT (or just connected medical devices), the adoption of connected devices is already at impressive levels and the trend is for even more devices to be accessible via the internet in the future.
For example, it’s not uncommon to find patients using wearable devices to collect and transmit data about their blood sugar, blood pressure, heart rate, and oxygen rate to their physicians, or to find wireless devices within hospitals that automatically transmit patient vital signs and other monitoring data straight from the hospital room to hospital staff, no matter their location. The assumption is that thanks to such continuous monitoring and real-time data, physicians can provide better quality care and improve patient outcomes.
Undoubtedly, the IoT certainly creates a great deal of opportunity within health care to deliver better outcomes. At the same time, though, there is also the question of the true value of connected devices in every circumstance. The fact is, while there is a certain “cool” factor associated with IoT technology, and a sense of wonder at the fact that a device can transmit data wirelessly, there is also a concern that developers will attempt to include connectivity just because they can. Unless the technology aligns with user expectations and behaviors, is reliable, and delivers actual meaningful outcomes — and doesn’t just add an unnecessary feature to the device — it is unlikely to be successful.
Therefore, when developing connected medical technology, it is just as important to consider why you are connecting it as it is to consider how you will connect it. Often, the how isn’t nearly as complicated as one might think, thanks to relatively inexpensive and widely available microcontrollers and applications. The why, on the other hand, is more complex, and requires developers to consider not only the potential benefits of connecting a medical device, but several other key points as well, among them the potential for data overload, the security of the devices, and addressing potential malfunction, to determine whether a device can benefit from connectivity.
Chief Concerns for Connected Medical Devices
While there are plenty of points to consider when developing any type of medical device, when the device is designed to be connected to the internet, there are additional things to think about.