Top Challenges Facing IoT/ IoH

How we can overcome them?

Kiersey Simon, Cofounder and COO, Bluedrop Medical

The field of the Internet of Things (IoT), Internet of Health (IoH), or Connected Health, offer great promise for addressing issues faced by healthcare systems. Without a well-developed process at each point in the system there will be barriers to the roll out and widespread adoption of any new solution.

There are significant issues faced by healthcare systems around the world, including ageing populations, chronic disease, spiralling costs, and a desire to shift care from tertiary to primary settings. The field of the Internet of Things (IoT), Internet of Health (IoH), or Connected Health, offer great promise for addressing these issues. The basic principle of connected health is quite straightforward. Sensors gather vital data from the patient in the comfort of their home, which can be reviewed remotely. This allows problems to be identified earlier and reduces the number of unnecessary trips for check-ups, which in turn leads to improved outcomes, increased efficiency, and reduced costs. However, the reality has not been as straightforward. The promise of connected health has been apparent since the early days of widespread access to internet, and yet the rates of adoption have thus far failed to match the expectations. There are also fewer examples of IoH that can be hailed as major successes at this point than would have been predicted by market analysts 10-15 years ago.

There are many challenges faced by connected health which include unrealistic expectations, reimbursement, integration challenges, and data security to name a few. This article seeks to explore some of these issues and identify routes to overcoming them.

Matching Expectations

Unrealistic expectations are one of the big issues faced by connected health.The Gartner Hype Cycle is a curve which is used to graphically display how the level of expectation associated with an emerging technology evolves over time. There are 5 stages to the curve; technology trigger, peak of expectations, trough of disillusionment, slope of enlightenment, and the plateau of productivity.

It describes how expectations ramp up as we initially overestimate the potential of a new technology, which is followed by a period of disillusionment when the realisation occurs that solutions are more difficult to develop and deploy than initially expected. Some technologies never make it past this point. Others slowly start to make headway as useful applications of the technology identified and exploited. With sufficient time the market matures, and continued growth comes more in the form of increased efficiency rather than innovation.

Connected health has been in the trough of disillusionment on the Gartner Hype Cycle for the past 8 years. The level of expectation with the field was very high, which is not particularly surprising given that connected health appears to be a panacea for many of the problems faced by healthcare systems. What is unexpected is the length of time it is taking for connected health solutions to demonstrate success and gain widespread adoption.


One of the issues encountered by connected health has been the muted success to date of solutions which are quite broad, but not very deep. The broad solution seeks to address multiple morbidities and be suitable for a large cohort of patients. Often the broad solution consists of a suite of off-the-shelf products that can gather data from the patient, and a subset of these products are given to the patient based on their needs.

A deep solution is one that is purpose built to address a distinct issue for a defined patient population. The monitoring and intervention protocols are developed specifically for the target cohort.

When these approaches are compared by ‘market size’ or ‘target population’, the broad solution has the advantage. It can be used to address more patients therefore should be more successful for the company producing it, and should be of more use to the healthcare system using it.

However, the needs of different cohorts within a disease state can vary significantly based on patient demographics or the disease stage. Solutions which target a broad base may not be tailored to maximise the benefit to specific issues. It is difficult to accurately assess the ‘efficacy’ or ‘cost benefit’ of a broad solution, as it is very challenging to isolate its impact on a specific issue and patient cohort. In such a case the evidence for a deep solution can be gathered in a shorter timeframe, at a lower cost, and because the study is more focused the evidence may be substantially stronger.

Implementing change is always  difficult, and without clear evidence of there being a significant benefit associated with the change, it becomes even more difficult. Instead of focusing on broad solutions which may give an incremental benefit over the current standard of care, the emphasis should be on identifying the connected health solution that delivers outstanding benefits.  With strong data  demonstrating the efficacy and cost benefit, the support to make the transition to the new standard of care will follow.

Drowning in Data

Drowning in data is another issue which has impeded the growth of connected health. The amount of data being collected has increased exponentially, but value of this data has yet to match its volume. The ability to collect and send data does not by itself lead to improved outcomes. Digital snake-oil is term which has been used to concisely label this issue.

Every healthcare professional has a busy schedule, and imposing a requirement to carve out time to spend reviewing data, which may not be of value to the patient or clinician, is not the best use of anyone’s time. The real value in the data is to provide the healthcare professional with actionable insights.

Ideally the connected health system identifies the occurrence of a problem, and provides both the alert and the recommendation as to what course of action should be taken for that issue. The physician can then focus on administering the appropriate intervention, rather than spending time determining what the appropriate care pathway is. For this to occur, solutions, data review protocols, triage, and interventions all need to be developed in collaboration with clinical stakeholders.

By focusing on specific issues that have clear definitions, the connected health monitoring protocols can be developed sufficiently to provide a discrete response and remove the need for clinical interpretation. In such cases the review may be performed by a trainer inspector, or AI, rather than a medical professional.


The traditional fee-for-service payment model is a significant challenge which must be overcome to enable widespread adoption of connected health solutions. As most connected health solutions are preventative, and most payment models are fee-for-service, there is a gap that must be bridged. Typically, a connected health solution is not an iterative improvement on the current standard of care, it’s something entirely new that hasn’t been paid for before.

As a result, the ability to clearly demonstrate the efficacy and economic benefit become increasingly important to make a strong case for reimbursement. Pilot studies with partner organisations, with a focus on a specific cohort are required to demonstrate the real-world effectiveness of a connected health solution. Traditional clinical trials are potentially of less value than for a therapeutic product. This is because one of the main concerns about connected health solutions is adherence in the real world, which is a challenge to answer with an RCT.

Therefore, the solution should have a defined target population and specific measurable clinical and economic outcomes which can be monitored during a study. Data which has been developed in collaboration with an organisation may be more powerful in driving adoption compared to the results of a study carried out elsewhere.

Data Security

This is an area of increasing concern for all organisations, which has also slowed the deployment of connected health solution as organisation find it difficult to accurately assess the cyber security risk associated with the new connected health solution. There have been multiple cases of data breeches and ransomware in 2017. It is a requirement not only for getting approval for selling a device, but will also be heavily scrutinised by potential partner organisation such as a hospital group, public health service, or private health insurance company. In each instance all parties need to be comfortable all necessary steps have been taken to minimise the cyber security risks.

The General Data Protection Regulation was recently enacted in the EU. It is currently in a grace period but will come into full effect in May 2018. This will drive multiple requirement for organisations such as increased contractual agreements between partner organisation, and the appointment of a Data Protection Office.  Data Protection Commissioners have also been empowered to hand down fines of up to €20m or 4 per cent turnover of a particular undertaking following a significant data breech.

User Design

The FDA have recently updated their guidance in relation to human factors and usability engineering for medical devices. The primary focus of this guidance is to minimise risk to the patient. However, the methodologies recommended can be applied to other aspects of the product lifecycle to improve its design for all stakeholders.

Most user design has been focused on how the patient uses the device, but good design is required at each step where there is interaction with the product; the prescription and payment process, training and set up, the actual use of the device by the patient, the review process, and the intervention process.

Without a well-developed process at each point in the system there will be barriers to the roll out and widespread adoption of any new solution.

Closing Thoughts

Connected health offers huge potential for improving outcomes and reducing costs. However, the transition to a new model of care is a challenge that will require support of all stakeholders. For this reason, the midterm focus should be on identifying and implementing solutions which consider all elements of the lifecycle, and which have outstanding data supporting their efficacy and cost benefit. Successfully addressing specific issues will pave the road to more widespread adoption of connected health.

--Issue 38--

Author Bio

Kiersey Simon

Kiersey Simon is the co-founder and COO of Bluedrop Medical - a connected health startup developing an  IoT foot-scanner which utilises computer vision and AI to remotely monitor and prevent diabetic foot ulcers.  Simon previously worked at Medtronic in R&D, where he developed implantable devices and was a member of the TAVI BioInnovate Team. Simon holds a Masters in Biomedical Engineering and a Bachelors in Mechanical Engineering, both from University College Dublin.

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