In the last few years, we have experienced incredible digital transformations in many areas of our lives. At a business level, the big tech players have become the most valuable companies in the world, displacing more traditional industries. Conversely, the medical device industry has been characterised by consolidation rather than disruption, and the largest companies today are in most part the same as they were a decade ago. But radical change is underway.

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The pandemic has forced innovation and has accelerated digital adoption by several years. Its penetration into the world of healthcare will have profound effects. In this article, I’m going to explore what this means for device companies in the acute and critical care spaces. Let’s begin by scanning the emerging landscape.

Enablers and blocks

Digital transformation has been enabled by breakthroughs in multiple technology areas. At its heart are advances in artificial intelligence (AI), with the ready availability of machine learning tools for data analytics, and the development of algorithms. In particular, it is becoming easier to get insights out of unstructured data – the clinician notes, signals and images that comprise around 80% of medical data.

Deployment of powerful algorithms requires processing power that has until now only been economically viable in the cloud, giving potential issues of security, availability, and latency. However, the development of powerful edge compute technologies is now allowing AI to be implemented directly in devices.

Healthcare is a risk averse industry, generally waiting until technologies have been proven out in other, less critical application areas. But the signs are there that the sector is ready to embrace change. Medical devices incorporating fixed AI have already been approved and regulatory frameworks are being put in place for adaptive algorithms. 

Recent critical care conferences have been peppered by presentations on data analytics – clinician led activities to get better insights into how to improve care. And we are seeing developments in interpretable AI and validation strategies, providing important answers to concerns about the validity of ‘black box’ algorithms.

Last but not least, the coronavirus pandemic has forced everyone to reconsider what is possible and desirable in many areas, compressing a decade of incremental change into a few months. 

What can we learn from other sectors?

There is a lot of buzz around the technology breakthroughs in AI, internet of things, cloud computing and edge processing. Yet digital transformation is about much more than technology enablers. The use of digital technologies has allowed profound changes to business models and the value propositions offered. This is what has allowed the tech companies to disrupt entire industries, using approaches that have been adapted and refined by thousands of start-ups.

Looking through these approaches, several key themes emerge. While they may require careful consideration and tailoring, there is scope to apply these to medical devices and the critical care sector.

The power of platforms and ecosystems 

Many highly successful digital companies are based on platforms – systems that create value by facilitating direct interaction between two or more distinct user groups. These platforms are very familiar in our private lives in areas such as social media with ads (Facebook), trading (Amazon) and transactions (PayPal). 

Many of them benefit from network effects – the more they are used, the more useful they become to their user groups. This positive feedback can result in a single player dominating a segment of the market. Platforms become very powerful when they are at least partly open, using software development kits and application programming interfaces to allow third parties to contribute apps as well as content. 

This draws on network effects to strengthen the overall offer and build a powerful ecosystem. It is a striking characteristic that such open interconnected platforms lead to an environment where companies are competitors in some areas and collaborators in others.

We are already familiar with platforms in critical care, such as multiparametric monitors and clinical information systems. While these often offer a high level of customisation for the user, they tend not to be very open. Interfacing a new device can be painful and there is no scope to implement third party applications. 

Another key platform play by digital companies is to disrupt the value chain by cutting out middlemen (disintermediation) or inserting themselves between a supplier and the end customer (intermediation) by providing a superior offer. Think of Uber Eats or Deliveroo inserting themselves between takeout companies and their customers.

A great example of intermediation in the medical world is Arterys, a medical imaging company. It started as a cloud provider that reduces the infrastructure cost of processing MRI images. But by opening its platform to developers and clinicians, it has enabled the development of hundreds of imaging applications pertinent to niche specialities that could not have been developed by a monolithic R&D programme.

Rapid iteration and innovation

Digital technologies can make the testing of ideas cheap, fast and easy. What’s more, lessons from failures can be learned early. As a result, in the tech industry decision making has moved away from intuition and market wisdom to being data based. We have seen the rise of the minimum viable product – a bare bones initial offering that is rapidly iterated after launch with growing customer experience. This is particularly powerful for new-to-the-world offerings, where both the value proposition and the product can take time to work out.

Rapid iteration does not sit very well with released regulated products. But it can work well in early development, as an organisation works closely with customer partners to iterate prototypes in a research environment before moving to a commercial one. We are seeing this as an increasing trend, with medical device companies collaborating with hospitals as strategic partners. Applications that are not classified as medical devices, such as workflow management systems, are easier to roll out in this way. They can be an important part of developing a digital offering that becomes increasingly clinical over time.

Leveraging data and learning from customers

Data has historically been expensive to acquire, store and manage. Today there is an abundance of data; the challenge is to connect across silos and turn it into valuable information and insights. Tech companies avidly analyse their customers’ activities to gain relevant insights. This could be to iterate their offering or identify new areas of value. They may offer free applications to collect specific data or set users tasks that help train AI algorithms. 

There are numerous opportunities for applying these approaches in the medical device space. 
System usage and performance data can feed into smart service scheduling and is used in many industries to identify deterioration before failure of complex systems. Likewise use patterns are used to get better control over the supply chain and identify use of competitive third-party disposables. 

Medical device companies need to undertake vigilance activities on marketed devices. Collecting and analysing data directly from devices in the field is a powerful way to help drive system improvement. Patterns of errors show up much more quickly than feedback from customer complaints. Similarly, detailed feedback on design can help inform product management – which modes or functions are used and which not, is better messaging or training required, do they justify the UI and software real estate that they take?

Taking this further, getting a better understanding of the details of how your devices perform across a wide range of users and sites can build a much richer picture than could ever be realistically gathered using ethnographic research. Understanding how systems are used depending on the circumstances is an important building block for decision support systems and automated operation. 

Where are the opportunities?

Critical care is a hugely complex environment, with a lot of connected devices generating far more data than staff can assimilate without computational support. As monitoring devices and modes of therapy become mature, value will become increasingly about working out what to do with the data rather than generating it. There are numerous opportunities for intelligent systems to enhance the capabilities of care staff, improve situational awareness, get rid of distractions such as nuisance alarms and help improve workflows. 

Some of these opportunities will be readily deployable within devices, making use of data generated by that device. However, others will require data drawn from multiple sources, something that is particularly difficult in the existing data architecture due to poor interoperability. 

In reality, the transformation promised by digital technologies is already happening in the critical care space. Intelligent ventilation has already been around for a few years. We are seeing the emergence of systems that are looking to have platform potential – from the large players in the monitoring and IT system space, connectivity and communications companies, and start-ups – such as the Mona digital assistant technology under development by Clinomic.

It will be fascinating to see how much players in the space embrace true interoperability. Wearable monitoring technologies are getting better and moving out of the consumer domain and into the general ward. It is foreseeable that they will eventually be accurate and reliable enough for critical care. 

What is your digital transformation play?

If you are not already doing so, now is the time to think about your own path towards the digital future, to secure your place in the ICU ecosystem. As food for thought, I will leave you with a few questions:

  • How do you see the emerging digital landscape and what position are you aiming for in the ecosystem?
  • How will you use digital technologies to capture valuable insights from customers?
  • How will you ensure you maximise value from the data you generate and ensure that no-one gets between your device and the customer?
  • How will you leverage the network and platform effects into your next product? 
  • What are the disruptive technologies that could threaten your business in the future and when is the right time to respond to them?

Plenty to contemplate there, I think you’ll agree. Meanwhile, it you’d like to discuss these or any other subjects, please don’t hesitate to email. It would be great to continue the conversation.

Gavin Troughton
Head of Acute & Critical Care