Digital health is one of the fastest growing areas in the healthcare industry and holds the potential to significantly reshape today’s care. Healthcare companies across the globe have created (and sometimes already closed again) programs and partnerships in this field to support and extend their existing value proposition with digital solutions.   

Despite numerous benefits to their clients - HCPs and indirectly patients - bold moves by pharma and MedTech companies in this area are still limited. The reasons behind this are diverse, however important factors include:  

• Lack of direct touchpoints with consumers and patients 
• Increasing regulatory requirements 
• Execution challenges (e.g. strategy integration, organisational set up and pilot scaling) 
• Uncertainty about business value, models, and ROI 

The latter factor – uncertainty about business value, business models and return on investment – is one of the most frequently mentioned reasons limiting digital health activities. For many pharma and MedTech companies, digital health solutions are still perceived as ‘nice-to-have’ add-ons, rather than essential components of their digital revenue models. Sometimes, they are even seen as ‘margin killers’ rather than powerful drivers for business. Evidently, the value of digital health solutions is not always clear for pharma and MedTech. The complexity of business models in healthcare, especially in the era of digital transformation, lies in their often-indirect nature, where users are usually not customers, and the involvement of multiple stakeholders, where the same solution needs to generate value for patients, HCPs, and payers simultaneously. That’s why we want to shed some light on this at times confusing topic by sharing some of our key learnings from the last few years of consulting our healthcare clients. 

This article focuses on the strategic development of business models for digital health solutions, a crucial aspect of tech-driven business planning in today's healthcare landscape. Our aim is to offer structured guidance on how to navigate this landscape, supported by real-world examples and success stories. It is not intended to be exhaustive since new models can emerge rapidly; our aim is to address the most common patterns. We focus on the pharma, diagnostics, and MedTech perspective (hereafter ‘pharma and MedTech’) rather than start-ups, as their case often ends with selling to those industries ultimately. In particular, this chapter is useful for readers from commercial strategy and product teams, as well as experts from R&D and innovation management. Knowing that DH is a broad field, we've emphasised client-facing solutions including telemedicine, digital therapeutics (DTx), and similar solutions, rather than technologies which improve in-house processes in research, clinical trial, and commercial excellence. So, let’s dive in! 

When approaching the field of providing digital solutions to patients, the endeavour is often started by looking at unmet medical needs throughout the patient journey. For innovation managers, these are user needs. Such a user-centred approach is fully recommended, albeit some obvious strategic boundaries around where and why a company should solve these needs should be considered. In addition, the user needs of HCPs as key stakeholders should be considered in parallel. Successful innovation requires two other dimensions as well: feasibility and viability. Feasibility touches on technical, ethical, legal, and regulatory aspects. Viability addresses considerations about the business value creation. When addressing the question of how a solution should generate revenue, one of the first steps is to differentiate between direct and indirect revenue generation. Figure 1 summarises categories and gives an overview of business model archetypes.  

Direct revenue as a stand-alone business model 

Direct revenue generating solutions come with their own standalone business model - independent of other products like medical devices or drugs. They can be grouped into three sub-categories, the first are solutions which are eligible to be reimbursed by the established healthcare system. In addition, there are direct-to-consumer (D2C) solutions, sometimes called out-of-pocket (OOP), which are directly sold and paid for by end users (most likely patients). Note that D2C should not be used as a synonym for over the counter (OTC). While D2C is a business model type (for any product), OTC digital health is a medical device category by the FDA. Lastly, there are B2B sold solutions which generate direct revenue from organisations, including clinics and other companies. 

Indirect revenue to boost sales of established products 

In addition to direct revenue, digital health solutions can generate indirect revenue for pharma and MedTech companies by leveraging sales of established products such as drugs, medical devices, and other digital services. It’s worth noting that the term ‘core business’ is avoided intentionally due to change management reasons – supporting the perception of digital health as core products themselves. While there is a finite number of direct revenue models, numerous options for indirect revenue generation can be identified, based on the specific solution, expectations, and maturity of the company. Notably, a single solution can have multiple revenue streams from different categories. In fact, often a parallel approach of mixing direct and indirect models is pursued at the beginning and only later the more successful one is kept.  

Considering the broad spectrum of possibilities, it is important to understand which categories offer the most compelling opportunities.  

As ‘value generation’ - for indirect revenue generation in particular - strongly depends on the context, we will dive into the different perspectives on digital health solutions from pharma and MedTech individually in the next section.  

At the heart of direct business models lies the principle of creating and delivering digital health solutions that users are willing to pay for directly. This encompasses a range of offerings from telemedicine services and digital therapeutics (DTx) to wellness apps and beyond. Successful solutions should address specific user needs, offering convenience, personalised care, or, ideally, a new approach to managing health and wellness outside traditional healthcare settings. 

Reimbursement models

This is the traditional way how MedTech and pharma companies create revenue. We won’t dive deeper into this topic in this particular chapter as these models highly depend on the regulations of the local healthcare system. We have covered the potential reimbursement pathways for Germany in Switzerland in a deep dive article.

D2C models

The D2C model is a well-established one for digital solutions in industries other than healthcare. Services are often initially free while advanced features like personalised analytics or further enhancements are covered behind paywalls. In healthcare, this model is much trickier. A key reason for this is the mindset of end users who are not used to paying for health services themselves. It’s worth noting that the mindset can differ significantly by country. Strong differences are seen even throughout European countries, based on the offered service and digital savviness. For example, our recent Zühlke Digital Health Study across Germany, Austria, Switzerland and the UK showed that people from most countries are unwilling to pay for healthcare apps and instead expect their insurance company/ the NHS to cover such costs.  

An interesting ‘therapeutic area’ for D2C services is fertility. There is a very strong intrinsic motivation by people who are trying to get pregnant which translates to a high motivation to (co-) pay for (digital) services and treatments themselves. Except for specific areas, pharma and MedTech companies are experimenting with solutions in this area and learning how to boost conversion rates from free to paid versions with direct access to users. Interestingly, beyond the revenue stream itself, digital D2C channels, specifically social media, are leveraged for advertisement (where allowed by law, i.e., ‘Heilmittelwerbegesetz’) or as a patient recruitment tool by digital health solutions. In summary, D2C is often one of several pursued models, especially for start-ups trying to quickly gain adoption rates through lifestyle consumer apps and later switch their revenue-generation pathways. Overall, pharma and MedTech companies remain in the experimentation mode with this model. 

In addition, established models which are not specific to healthcare are pursued as well, including flat fees or pay-per-use models for clinics’ Software-as-a-service (SaaS).  Success stories for this model are the rise of Epic and Amazon’s latest acquisition One Medical – both of which offer clinics enterprise software suites. At their core, they have an electronic health record (EHR) on an underlying data platform which is extended along the patient journey with services like scheduling, telehealth, and others. Hence, they strongly contribute to a seamless blended care experience. For MedTech and Pharma, developing their own solutions of this magnitude seems too farfetched. However, integrating their (point)-solutions into such systems is essential and leveraging a similar revenue model is feasible. 

A common theme is also the idea of selling data to other companies, especially if large data sets have been created over time, e.g., by connected (medical) devices or patient-facing mobile apps. Despite the initial enthusiasm, companies quickly face limitations, either legal hurdles (e.g., prohibited secondary use) or simply because the specific needs of expected customers are not sufficiently understood (e.g., therapeutics area and drug-specific information for pharma). Also, the level of data processing is key. Selling raw data vs. derived insights makes a tremendous difference. A common challenge here is the lack of knowledge about how the offered data will generate business value. This is no new phenomenon as data from medical registries is often available but insufficiently used. Hence, educating target customers about its value is crucial, especially if they are not thought leaders in this field. One of the most successful models for selling data in healthcare is IQVIA. They sell various reports and data sets to pharma’s commercial departments, among other services.  

In summary, there are multiple B2B models for digital health solutions which sometimes overlap with other model categories. Most of them are pursued by start-ups selling services to pharma and MedTech. Direct revenue generation for those two industries through B2B models is possible in certain cases but a detailed understanding of customer needs is mandatory. 

For Pharma and MedTech, indirect business models for digital health solutions take a centre stage, either due to limited knowledge about alternatives or because the opportunities are much wider. While legal sales constraints need to be considered, e.g., no promotion of two products in the same client call, digital health offers high potential for boosting established products. In our engagements, we discuss different ways for a digital health solution to create value. We summarised the most common insights and indirect value drivers for pharma and MedTech in Figures 2 and 3 below. 

Interestingly, digital health solutions are still rarely managed by cross-functional teams, instead they’re ran by either the Commercial or R&D department, naturally creating silos. Depending on who’s in charge, different expectations are raised. Typically, the challenge of impact measurement comes to the forefront as metrics often paint a blurry picture and it’s generally difficult to quantify results due to parallel activities or missing data. What is essential is that digital health solutions must not be understood and managed like ‘nice to have gimmicks’ neither like drugs nor (medical) devices. Instead, they should be managed as tools that generate and exchange data with users. Hence, they are a product and a channel at the same time. Equally important is that the generated data sets should not be treated as data silos. They have to be integrated with additional internal and external data sources including market, medical (e.g., from registries), and commercial data. Only then, the real (indirect) business value for pharma and MedTech can be realised.

We hope you gained new insights from this article. As we embrace the digital transformation in healthcare, the journey ahead for Pharma and MedTech companies is marked by immense potential and challenges. The strategic adoption of digital health solutions offers a pathway to redefine patient care, making it more accessible and efficient. Despite all economic, regulatory and societal hurdles, the industry's resilience and innovation promise a future where digital health is integral to healthcare delivery. This global endeavour requires collaboration, sharing insights and successes to foster an interconnected healthcare ecosystem. Let us join forces to harness the power of digital health, shaping a future where technology empowers wellness and ensures universal access to care. The journey is complex, but the promise of digital health as a beacon of innovation and transformation can guide us forward. 

We thank various clients and colleagues for their excellent input and feedback to this article.