Rock Health and the Stanford Center for Digital Health release their findings from the 2019 Consumer Adoption Survey. In 2019, overall consumer adoption of digital health leveled off near the 2018 high water mark. The five-year picture represented in our annual survey is one of a steady transition to a progressively more digital consumer healthcare experience.
Digital therapeutic and pharmaceutical companies are partnering to build, validate, and expand access to new, software-based solutions that improve patient outcomes. This is new territory with few precedents, and the strategies for building successful alliances remain uncertain. Drawing from numerous interviews with digital therapeutic, pharma, and health plan leaders, this research outlines how to overcome execution risks and build successful pharma-digital therapeutic alliances.
With America's addiction epidemic taking a devastating toll on lives and communities, technology-based startups are offering a new path forward. These solutions focus on providing evidence-based, continuous, and accessible experiences for individuals living with an addiction. To understand how digital offerings are driving real value to patients, we interviewed six startups.
Results from our third national consumer survey (2017 data) on digital health adoption and sentiments.
To capitalize on the shift to value-based care and consumer demand for a better healthcare experience, a new type of business has emerged: next-generation payers and providers (“NGPPs”). Without the constraints of legacy payment models and operating systems, these companies were created to deliver a reimagined service to patients, prioritizing health and outcomes over utilization. We interviewed five NGPPs to understand their technology-supported strategies, with a focus on how they’ve partnered with startups and how they expect to keep pace with future innovation.
Last month, we released our whitepaper, Demystifying AI and Machine Learning in Healthcare. In this latest blog post, you’ll learn how venture funding gives us a glimpse into the AI/ML use cases taking hold now—and those areas that aren’t ripe yet. ICYMI: Our first post established a framework to understand the algorithms underpinning AI to allow stakeholders to more readily identify true breakthrough innovation.
AI in healthcare feels inevitable: Optimists predict that artificial intelligence and machine learning (AI/ML) will diagnose disease better and earlier, treat illness more precisely, and engage patients more efficiently than today’s healthcare system does. On top of this, AI/ML is expected to streamline business operations and restore sanity (and humanity) to the clinician experience. To separate hype from reality, read our 50-page white paper, Demystifying AI and Machine Learning in Healthcare.
For digital health startups, it’s increasingly a B2B world—and innovators are acutely feeling the challenges of enterprise sales. Selling to payers, providers, biopharma companies, and others is a tough game across the board. Sales cycles are long, requiring patience and a knack for relationship building. Finding the right buyer in a big organization can be disorienting. And crafting the pitch is tricky when talking to a complex, multi-faceted enterprise customer.
Results from our 2016 digital health consumer adoption survey.
The genomics industry has tremendous potential to move the needle in health. Delivering on the promise of genomics depends on three main factors—many of which are within the purview of digital health. Through our survey of one thousand consumers, we provide novel data and insights regarding adoption, willingness to pay for specific use cases, and explore concerns around privacy and ownership.
In healthcare, big data is only valuable when paired with a strong body of clinical evidence. Digital biomarkers are an opportunity to translate new data sources into informative, actionable insights.
Results from our landmark national survey on the adoption trends in digital health.
A look at the challenges and promises of using new and existing sources of data to deliver personalized care.
A review of the current landscape and future of biosensing wearables.