In the United States alone, healthcare costs have continued to rise along with increasing rates of chronic illness (CDC). Innovation is moving faster than regulation can keep up with, and people are expecting more from their healthcare providers. In the last few years, the direct-to-consumer model has become the norm for consumer packaged goods, but now we’re seeing the trend moving to the healthcare market. Startups focused on single-point solutions, like Hims, SmileDirect and Care/of, are offering unbundled care, giving people increased autonomy over their care options. In addition, membership-based clinics are more prevalent, providing a more specialized or personalized provider experience.
While some providers feel that DTC models are too divorced from holistic care networks, leaving patients to self-diagnose or connect solutions to their complete health picture, consumers are more attracted to these options because it lets them be proactive and take their health into their own hands.
An abundance of new tools and technologies—especially in data analytics and virtual reality—are also aiding this shift in healthcare and insurance from legacy systems to more human-centered practices. A recent survey found that 77 percent of consumers are interested in using virtual healthcare, while 19 percent have already used the service (Advisory Board). Harnessing clinical data could fuel predictive analytics to aid in personalized patient treatments. We could soon see major leaps from health and fitness tracking to health monitoring and diagnosis.
There is an increasing need for applications to help consumers take control of their health, and in the next decade, we will see increased investment in consumer-centric healthcare solutions. Providers and insurers alike will have to contend with the new ways in which consumers are accessing care.
Once we have the tools in place to help consumers navigate their health and wellness, we’ll soon see two major trends impacting healthcare costs and participation: machine learning for pharmaceutical research and development (R&D), and digital therapeutics (DTx) for help treating chronic conditions.
As opposed to Moore’s Law, which posits that technology gets relatively cheaper to manufacture over time, when it comes to drug research and development, the cost roughly doubles each year (Eroom’s Law). As it is, the process is very expensive, extremely risky and excruciatingly slow. Getting a drug from R&D to approval takes roughly ten years, and costs more than $2.5 billion on average. Machine learning applied to healthcare data can potentially combat this crisis by helping to better predict clinical trial success through an increased understanding of drug candidates and efficacy likelihoods.
We’ve also seen the rise of interest in digital therapeutics, which are defined as “evidence-based therapeutic interventions to patients that are driven by high-quality software programs to prevent, manage, or treat a broad spectrum of physical, mental and behavioral conditions” (Digital Therapeutics Alliance). The FDA approved the first DTx in 2017, and since then there has been major interest in the tech and startup spheres using these solutions to help combat rising costs of managing chronic illness (Pear Therapeutics). The hope is that these new tech-enabled solutions will open up opportunities to improve the effectiveness of drugs and create direct relationships with patients, which could transform the way medicine is made, tested and prescribed.
Right now, startups and tech companies are the early entrants in this new space, but providers, insurers and pharmaceutical companies need to take note. While digital therapeutics may not upend the business models of traditional pharmaceutical or insurance companies just yet, they do present a substantive opportunity that will stretch their capabilities and push them into the provider space. For pharma companies that want to stay ahead, this will mean forming new partnerships or building brand new capabilities—from human-centered design to agile software development.