Few things hold more potential to drastically change (and save) lives than digital health transformation and healthcare IoT. As the Internet of Things (IoT) continues to develop and expand, innovation possibilities with the Internet of Medical Things (IoMT) are infinite. As I discussed in part 1 of this series "Digital Health Transformation: Realizing the Promise, Reducing the Risk", the connected infrastructure of medical devices, software applications, health systems, and services is already being used by individuals to track their health through wearables, such as FitBit and Apple Watch. Hospital and clinical staff are using IoMT to communicate with patients about appointments, medication management, lab results, care plans, remote monitoring, and more.
This is just the tip of the iceberg for digital healthcare transformation. To realize this promise of the future, we have to first understand the unique challenges and risks associated with IoMT technology development and implementation. Once we understand these challenges, we are better equipped to mitigate the risks. Luckily, here in the Triangle, we are surrounded by the resources and expertise in healthcare and IoT that are required for disruptive innovation.
7 Obstacles to Rapid Innovation on the Internet of Medical Things (IoMT)
1. Moving Pieces
IoT device development takes a village of experts with vastly differentiated skill sets. Building a connected device, especially in healthcare, involves a different process than the average software project. The path from concept to a testable product isn't linear; it is much more complex than the lean startup, minimum viable product (MVP) approach. When dealing with a healthcare device, you'll likely have to manufacture something in order to do a beta test. Manufacturing introduces significant barriers - taking orders, managing inventory, up-front costs prior to market validation, and many other risks associated with IoMT.
Fundraising for any company is a challenge. You can have an experienced leadership team, operate in a high-growth space with a proven model, have a well-documented cost structure, and have revenue and still not be able to secure funding. Now, imagine that you're innovating in the healthcare and IoT space with unknown risks, unknown costs, unknown time to market, and significant upfront investment required for market validation. Getting an investment is going to be tough. Not only are you faced with many unknowns but it's extremely difficult to find investors and venture capitalists (VCs) that have experience in the IoMT space and are willing to take such a large financial risk. Even with a great team of engineers (electrical, mechanical, industrial, and software) that have experience innovating in the healthcare space, tried-and-true funding models in IoT are scarce. If you're able to manufacture and beta test without investment, going to market will prove to be a challenge due to the large moving ship syndrome.
3. Large Moving Ship Syndrome
In IoMT projects, startups cannot follow the canonical “ask forgiveness and not permission” approach to go-to-market. Nor can they “move fast and break things” due to governmental compliance regulations and large organization bureaucracy. Ignoring this required protocol can be a costly mistake. Many health-related IoT developers may hope to integrate quickly, but government and medicine are traditionally slow-moving. So, not only are you trying to build a scalable business model and secure funding from skeptical investors but you also have to negotiate contracts with slow-moving healthcare facilities while ensuring you are compliant in the eyes of the government (HIPAA, FDA). And while you may be compliant today, the compliance laws could change by the time you get a contract inked with a hospital or when you're ready to go to market. These are large barriers to entry and significantly increase upfront legal costs, time to market, and overall risk.
4. IoMT Integration in Healthcare Facilities
In addition to overcoming the large moving ship syndrome, integration in healthcare facilities is multi-faceted. First, it requires licensing approval from every medical facility in which you want to integrate. Once you secure licensing, the integration isn't one-and-done and then scale. Every hospital, physician’s office, and the health-related center has a unique electronic medical record (EMR) system. This often means a unique integration is required at each healthcare facility location and into the corresponding EMR system. This lack of ability to integrate affects an organization’s potential for scale, making this a fundamental barrier for IoMT products, despite their potential.
5. Cybersecurity Risks
Healthcare IoT devices hold highly sensitive medical and financial information that must be handled carefully. This personal data is very valuable to hackers. According to Becker's Hospital Review, "Patient records can sell for up to $1,000 due to the amount of information found in the documents, including date of birth, credit card information, Social Security number, address, and email." To put that in perspective, Social Security numbers are sold as low as $1, and credit card information sells for up to $110. Hackers have a financial motivation to steal health-related data and IoT devices are the perfect place to start. Why is that? Generally speaking, healthcare IoT devices aren't designed with a cybersecurity-first mindset. Most devices on the market are ridden with easy-to-exploit vulnerabilities. IoMT devices are built to perform the task at hand, like monitor vital stats or alert a patient of an upcoming appointment. A health tracking app isn't designed to keep hackers out; it's designed to track your vital statistics. The critical need to protect data makes these cybersecurity risks vital to consider in the IoT healthcare development process.
6. Data Collection Monitoring
One of the biggest promises of IoMT products and services is the actionable insights that can be extracted from massive datasets. These datasets can save lives. When a medical IoT device first collects data, it is in an unstructured (or “unreadable”) format. In order to convert that data into something useful, it first has to be stored (and storage isn't cheap) and then it has to be analyzed using “elastic computing resources that are independent of storage.” The more data that is generated, the more storage and analysis that is required, both of which increase costs. Effective data collection, processing, and monitoring are massive opportunities for IoMT.
7. Interoperability, Or Lack Thereof
Successful interoperability in medical tech means that information systems “within and across organizational boundaries” must be able to communicate with one another “with the goal of optimizing the health of individuals and populations.” Computerized health took off in the 1990s as EMRs were first introduced but, almost 30 years later, healthcare is still extremely decentralized. The rise of Fast Healthcare Interoperability Resources (FHIR) has helped with centralization but there is a massive opportunity for improvement. Barriers to widespread medical interoperability exist even without factoring in the complexity of integrating new IoT systems.
Successful IoMT Projects
Do not fear! Identifying challenges is a key part to mitigate the risks in healthcare IoT. Knowing the hurdles you may face before you embark on your journey prepares you for success. With these challenges in mind, we have the opportunity to think globally and act locally. Here in the Triangle, we are in a unique position to innovate the healthcare space. By working with a diverse set of community partners, we help Smashing Boxes clients understand these challenges from various perspectives and overcome them.
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The rise of the Internet of Medical Things (IoMT) is enabling a new value-based care model to break barriers to better, faster, and more cost-effective health outcomes.
In this ebook, you will learn about:
What’s driving the need for change
The emergence of value-based care
Technology-enabled healthcare innovation
Challenges and risks of connected devices
Decision-making across the IoMT framework
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