Life Science and Pharmaceutical Industry

How digital innovation can help pharma companies shift from treating diseases to becoming providers of health

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  • There are numerous challenges to overcome before a functioning model of preventative healthcare can be achieved.  

  • These challenges affect everything from reimbursement models, to technology capabilities, to cultural and mindset shifts.   

  • Whilst the overall goal is difficult to achieve, the seeds of preventative healthcare are already being sown, and many pharma companies are forging digital technology partnerships to help secure their place in this emerging market.   

  • In this blog post, we explore the challenges in detail and outline approaches to help you build towards preventative healthcare.  

The entire pharma industry is built on caring for the sick and – ideally – curing diseases. At first glance, pharma organisations have very little financial incentive to look beyond that business model. Their competencies are strong, their development pipelines are full and their markets are both plentiful and profitable.

However, that could change – and the impetus for such a transformation could be digital. What if digital technologies allowed pharma companies to help prevent diseases before they happen – to supplement curing illness with maintaining wellness? Crucially, is there a way for pharma companies to make money from prevention – and, if so, could prevention become the new competitive arena for the industry?  

In this piece, we explore these key questions and develop potential answers which can serve as food for thought for further development of the field.  

Who pays for prevention?

Of the four concepts that make up “P4 medicine” (predictive, preventive, personalised, and participatory) prevention stands out as the biggest potential disruptor of pharma’s status quo – at least in principle. But how real is the potential of this disruption?  

We are still a long way from disease prevention and are also undergoing a significant demographic change with an increasingly ageing population. So in the mid-term, there will be plenty of sick people that hope to be treated or even healed.  

Pharma organisations have built their fortunes on understanding and grappling with the complexity of human disease mechanisms. It’s only natural for them to focus on curing illness, or merely treating symptoms, rather than trying to get into preventive care. Regardless of how big the potential upside may be from preventing (say) cancer, it’s still a world away from what pharma companies are used to.  

But more to the point, even if pharma companies wanted to pursue prevention, there’s currently no viable business model through which they could do so. To put it bluntly: who will pay the costs? 

More specifically, how will we get from a system where healthcare providers pay for treatments as and when they are needed, to a new regime where individuals pay not only for outcomes (which we’re already seeing), but for outcomes in advance? (which we refer hereafter to as “pre-imbursement”.)  

If the goal is preventing diseases rather than treating them, how do we define success in a way that stakeholders (whoever they end up being) are willing to pay for – and makes business sense for pharma organisations? 

The future is digital

Understandably, there’s no simple answer to the pre-imbursement question. But whatever the future of healthcare turns out to be, it will almost certainly be built upon the use of digital technology.  

A survey from McKinsey & Company found that 75% of all patients expect to use digital services in the future. And tech players are listening: dozens of new tech-first entrants (from startups to hyperscalers like Amazon, Microsoft and Apple) are racing to stake out their territory in the emerging digital health landscape with both software (apps) and hardware (e.g. wearable tech).  

With the emergence of digital therapeutics (DTx) – today led by relatively small players – some medical-grade tech companies are making inroads into areas where pharma organisations traditionally reigned supreme. And with lifestyle apps for health, they’re staking a claim to consumers’ attention and brand loyalty in the wellness market, too.  

What’s more, in the wellness area, tech firms face less strict regulations compared to the constraints pharma organisations are typically used to.  

This allows them to operate on the border of what is considered a ‘medical-grade’ solution (i.e. they avoid medical claims, which need to be substantiated by clinical trials, and use their products in ways that do not present health safety risks according to their intended use). If and when digitally enabled prevention develops as a field, pharma businesses may find that tech players are already sitting on the territory they’d like to claim.  

Tech firms know all about digital technologies, but still can’t match pharma’s enormous health expertise – as things currently stand. Pharma organisations have a deep clinical background, access to high-quality medical data, and ready-made relationships and interfaces with key stakeholders across the whole health ecosystem – from healthcare providers to insurers, payers, and more. 

However, just because newcomers are over-confident, or even naïve (even Google had a setback with the FDA recently, albeit not related to prevention), that doesn’t mean Pharma can just ignore them. Whoever ultimately shapes the preventive healthcare future, and however long it takes to arrive – it’s a highly active field. That’s why pharma companies need a strategy to adapt to (and even benefit from) the emergent opportunities in preventive care. 

In the following sections, we look at three crucial aspects of digitally enabled preventive healthcare: the rise of healthcare data, new business models, and the configuration of the new healthcare ecosystem

1. The rise of data 

Digitally enabled preventive healthcare isn’t just about anticipating environmental or genetic susceptibility to certain conditions. It’s about empowering patients to monitor, manage, and mitigate the risks and negative impacts of chronic disease – the key to that will be data.  

Some new and comprehensive data sources have already emerged. Consumers are also demonstrating a huge appetite for fitness trackers and wearable devices that collect data on their physical movement, heart rate, blood oxygen level, sleep quality, and so on. The quantified self movement feels as strong as never.  

The trend for wearables shows that patients are increasingly prepared to take a proactive role in their own health. However, consumer wearables tend not to drive preventive decision-making or behavior change by themselves: about half of all FitBit users don’t find their device useful enough to use long-term.  

That could be because the guidance they receive still lacks medical meaningfulness. This is due to the fact that data generated by consumer-grade devices isn’t up to medical quality or standards. Consequently, even the most committed ‘power user’ of these devices must still turn to a trained physician for reliable medical guidance – but maybe that could change.

Markers of success

In 2019, the EMA gave the go-ahead for a completely new digital clinical endpoint, co-developed by Roche, to generate biomarkers for Duchenne Muscular Dystrophy (DMD). The biomarkers are extracted from walking behavior as measured by a specially developed wearable device known as ActiMyo.  

Turning to respiratory health, Propeller Health’s asthma platform provides patients with a digital sensor on their inhaler and a smartphone application to track their usage (against factors like weather conditions and activity) and provide structured treatment advice. Users experienced a 78% reduction in rescue inhaler use over 12 months. Data collected just before a negative event will generate additional digital biomarkers with the power to predict and prevent similar events in the future.  

Another example from our clients, Healios, develops digital biomarkers to both improve the journey for patients suffering from multiple sclerosis and to accelerate research in this space. Healios’ solution aims to allow doctors to determine the progress of the disease earlier and more precisely, so they can slow progression and accumulation of impediments.  

Despite these encouraging signs, digital biomarkers are still in their infancy. Even a “simple” biomarker like blood pressure is difficult to measure continuously (and accurately) with a wearable device. And that’s before we consider complex ones – such as the compound concentration for PK/PD studies. 

However, the direction of travel is clear. As technology matures, more reliable, “medical grade” data will be collected, making it possible to identify more biomarkers. For pharma organisations, the opportunity lies in tapping into new high-quality data sources across the ever-expanding healthcare value chain, such as data generated by mobile apps and medical IoT sensors.  

The next challenge is to use that data to enhance existing treatments or even create standalone digital therapies – also moving away from reactive healthcare to proactive healthcare, where an early detection of an unusual pattern of biomarkers might indicated an upcoming disease or change in the course of a disease. In the latter case, a validated AI system is often necessary to make sense of large amount of data and predict outcomes, but sometimes just monitoring a few ‘basic’ vitals could be enough to detect for example relapses in some long-term treatments such as cancer therapies. 

2. New business models 

How could pharma businesses get paid for preventing illness? Part of the answer may be found in the wider shift towards pricing based on value, outcomes, or risk – with data on overall wellbeing providing the foundation for the change.  

Payers are thinking less in terms of reimbursing services than buying outcomes. According to PwC, participation in value-based contracts among US-based executives increased from 25% in 2017 to 57% in 2019. This follows similar changes in Europe, where single-payer systems have been pushing pharma businesses towards risk or outcome-based pricing models for some time.  

Value-based pricing depends on two things: viable new reimbursement models and reliable field data on outcomes, called ‘Real-World Evidence’. So pharma organisations could use developments in value-based pricing to prepare for pre-imbursement models. 

A future scenario might be: a pharma organisation strikes a partnership with a payer – such as a health insurer – to develop a solution that is proven to prevent certain diseases. If the solution prevents a certain percentage of the disease, that saves the health insurer money. So the pharma organisation is reimbursed with an agreed percentage of the amount that the insurer saves. From a societal perspective, this sounds pretty promising – but there are several challenges to overcome.  

The challenge of proving prevention

Aside from the obvious differences in business motivation and mindset between pharma organisations and payers, there’s still the challenge of providing solid data that demonstrates a reliable “pre-diagnosis” and improved well being before actually becoming sick. While it can already be tricky to improve clinical endpoints by treatment in the traditional system, showing that a wellbeing outcome has been achieved is expected to be much harder. What are the measures of success – and what’s the underlying timeframe of prevention?  

Essentially, the problem is that traditional provider-collected or patient-reported models of outcome measurement have specific limitations for proving preventive value.  

On the provider side, clinical notes are unstructured and non-standardised – yet data-collection teams must still translate them into outcome-relevant insights. What’s more, notes are usually framed in granular, condition-specific language (for example, the recurrence of lower back pain) rather than in terms of the outcomes that matter to patients (like their ability to work, or their overall quality of life).  

When it comes to patients’ own reporting, the picture is even fuzzier. Outcome measurement is overly reliant on subjective perceptions, recall, and participation – and the standardisation problem is even worse. 

However, digital measurement could overcome many of these issues. Biosensors and clinically approved wearables could capture the standardised, objective, and qualitative data needed to support value-based conclusions.  

For instance, with current technology we might measure blood pressure or heart rate in patients with coronary artery disease. But a digital outcome-focused biosensor could add data on ambulation and sleep quality to get a more holistic understanding of preventive outcomes.  

3. The digitally enabled preventive healthcare ecosystem

Let’s suppose that data which fulfills all above mentioned criteria is available and a reimbursement model is agreed in principle. There’s still the question of how the various players (known ones and completely new ones) will collaborate. If digitally enabled preventive health is to become a reality, it will depend on an inherently holistic model of care.  

Traditional models of curative care comprise reactive, disjointed interactions with disconnected healthcare providers, oriented around a particular condition. The rise of electronic health records (ePA in Germany) will hopefully vastly improve this situation but the pace of that improvement is still unknown. In contrast, digitally enabled preventive healthcare is a continuous, joined-up experience involving payers, digital platforms, healthcare providers and (potentially) pharma businesses. And all these players will need to be connected to, and centered on, the patient themselves.  

This vision of care can only be realised by an interconnected ecosystem. Within this ecosystem, multi-disciplinary teams and multiple care delivery settings will collaborate closely, supported by interoperable digital platforms. A working model which usually differs quite significantly from the n=1 knowledge silos we face in our current healthcare system. 

Many diverse players are racing to carve out their own space in this new world. In addition to the official, governmental digitalised healthcare infrastructure (e.g. “Telematikinfrastruktur” in Germany) platform giants such as Google, Amazon and Microsoft are developing the digital infrastructure that the new healthcare ecosystem will depend on. And they’re doing so much more efficiently than the government. In addition to the infrastructure, these platform giants have access to a wealth of data – from health data captured by wearable devices (Fitbit was acquired by Google) to health concerns reverse-engineered from web searches, diet inferred from online grocery shopping, and even – movement speed calculated by GPS. 

Every interface with the user is important, but the most vital is the one that they use at the beginning of their healthcare journey (further reading recommendation: Heal Capital article about the importance of interface ownerships & VIMPROs). Once a user/future patient chooses a digital ecosystem, they’ll probably stick with it long term – partly because it’s familiar, partly because switching costs are high (particularly if data can’t be transferred out), and partly because of sheer inertia. It’s always easiest to just leave things as they are.  

No-one knows this better than the big tech providers, Amazon in particular. If you give people something they really value, while making it easy to stay and painful to switch, you can effectively lock the user in.  

Pharma organisations cannot match that sort of hold over the user. However, they have two big advantages over Amazon et al. The first is solid domain expertise, which takes years to acquire and can’t simply be bought on the open market. The second is pre-existing, trusted relationships and interfaces with the established players across the healthcare ecosystem – which, again, cannot easily be bought or replicated by firms in other sectors.  

To turn these resources into a digital advantage and thereby shape the digitally enabled prevention future, pharma companies will need to adopt a two-sided approach. First, they will need to build (which they’ve started doing) a core competency in digital innovation – not just alone, but within the context of an ecosystem. And second, they will need to prioritise rigorously, so they only invest in those innovations that truly represent a compelling, unique opportunity.  

One solution is to team up with more mature players in the digital space (decreasing the likelihood they become competitors in the future) or to create offerings that integrate with them. At Zühlke, we believe pharma organisations can and should work towards developing their own products in the digitally enabled healthcare space so they can not only contribute to, but also stay in the driver’s seat of the future of digitalised healthcare. And that’s precisely what we pursue for our clients every day. 

Early moves towards the preventive future

It will probably take several years to fully understand how far the emerging preventive healthcare initiatives will take us – or how disruptive the resulting models will turn out to be. However, it’s already clear that digital solutions and their generated data will play a major part in this journey. 

That’s why the time to think about how to shape preventive healthcare using digital solutions is now. Pharma organisations who commit to developing themselves into “digital natives” have the chance to shape the digitally-enabled preventive healthcare future.  

At Zühlke, we specialise in bringing digital health innovation visions to reality. We can help you use digital technology to carve out your own niche in the preventive healthcare system.  

If that sounds like an opportunity you’d like to take, please get in touch.  

Contact person for United Kingdom

James Graveston

Principal Business Consultant
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