Pharma has invested in digital and connected health in an effort to gain competitive advantage, supplement molecule-based products, and improve patient compliance, loyalty and support. There's no question that digital and connected health solutions have tremendous potential to improve patient lives, provide clinical efficiencies and drive outcomes. The common challenge faced by digital pharma leaders is how to create solutions that provide value on a frequent basis to maximize the engagement of patients, providers and payers. The struggle to reach scale and realize value from digital health investment is real.
The uniqueness between types of digital health solutions and the behavioral interventions that support varied user types and therapy areas is vast. For example, designing a service to meaningfully engage audiences and improve outcomes for a sleep disorder requires a different set of mechanisms than solving for the complexities associated with medication adherence. There are design affordances and accelerators that can inform strategies and kickstart solution creation with scientific precision for the many types of digital health solutions and the different audiences that interact with them. Thanks to engagement patterns, digital health solution teams can guide planning and design activities that are rooted in a deep understanding of users’ needs as well as applying demonstrated best practices to optimize engagement.
Best practice engagement patterns incorporate proven mechanisms that can be applied to specific health scenarios. This is similar to how treatment protocols are followed in the care setting. For the most part, care providers and teams apply treatment protocols to standardize health practices and improve outcomes with consistency. It’s only when extreme cases emerge do care teams need to “invent” and create a specialized intervention. Why should a technology that extends and facilitates healthcare be any different? Risks associated with creating successful digital health solutions can be mitigated by applying best practice engagement patterns in a similar way that treatment protocols guide doctors.
It’s important to recognize that the complexity of designing digital health solutions cannot be reduced to a formulaic replication of user interface components. Still, there’s substantial value in having defined principles and a library of patterns to enhance a disciplined human-centered design process. Impactful digital health solutions are not designed with directions and a big box of user interface Lego pieces that can be endlessly assembled. Successful digital health product and design teams include customers (patients, care providers, payers, etc.) in the design process with high frequency to consider behavioral biases and apply a design systems approach when designing successful experiences. An effective design systems approach provides the foundational structure and cohesion so that an engagement pattern library connects to clear objectives and enables solution teams to relentlessly pursue customer value. Facilitating a meaningful experience that directly ties to great business and health outcomes requires equal parts innovation and reuse.
It’s most effective to initiate engagement patterns during early planning stages to inform strategy efforts and start teams on the right foot. These patterns provide primary and secondary stakeholders a foundational understanding of a given audience and the key components based on the solution type. Great value can be gained from industry-demonstrated patterns to guide digital health strategy and design an experience that leads to measurable results. The foundation of underlying engagement patterns root from a range of disciplines including behavior science, human-computer interaction and digital product management. Collectively applied, these interdisciplinary practices can help teams leap forward to recognize the opportunities of when and how to apply these patterns.
Here are three key principles that can be applied right now:
1. Align your design system with purpose. Engagement patterns support the specific goals of a solution and should be rooted in user centricity. Whether a solution aims to help patients adhere to their treatment or enables health providers to make clinical decisions with greater confidence, it’s essential that the needs of primary users be clearly understood and aligned to the right pattern. Here is a standardized overview of primary users and a range of purposes that define common solution types in digital health solutions:
2. Verify patterns through evidence. It’s integral that patterns have the evidence of measurable results. While there are various forms of evidence that can be examined, success is best defined through:
- Commercial evidence indicating market success such as acquisitions/venture funding, deal size, investor round, number of users/clients and partnerships
- Clinical evidence showing that a digital health solution has helped patients self-manage their disease or condition and achieve outcomes such as adherence, reduced weight, or the adoption or avoidance of any specific behavior
- Experience design evidence showing that target users value the solution and can complete key tasks with effectiveness, efficiency and satisfaction
3. Apply patterns with accuracy. Engagement patterns can dramatically impact the way teams create solutions since they have the power to enforce prioritization and accelerate design decisions. Planning and synthesizing patterns within a consistent framework and catalog format can be instrumental in aiding teams that are considering what’s most applicable and impactful to create successful solutions. Incorporating patterns during early stages of opportunity design can have an especially powerful effect by de-risking decisions and neutralizing guesswork that’s much more costly to address later.
Pharma companies can align planning and creation of digital health solutions to audience purpose, ensure that they are verified with evidence, and commit to accuracy of engagement patterns during the earliest stages of opportunity assessment. This knowledge can be a catalyst to guide several situations, from planning and conception to in-progress design and through in-market solutions that are underperforming. The science behind engagement patterns provides digital health solution teams a foundation based in proven best practices to build from and innovate while maximizing the user adoption and meaningful engagement that directly impacts great outcomes in digital health. For digital pharma leaders to realize the promise of digital health, the people that interact with these solutions and services must frequently recognize the value they provide for them to actively participate. Applying design systems can not only improve efficacy of a digital health solution but also improve project efficiencies, reduce technical debt and mitigate investment risk.
*Source: This classification is based on several available frameworks including the Classification of Digital Health Interventions v1.0 by the World Health Organization and the Digital Health Venture Database published by Rock Health.