Rock Health supports entrepreneurs working to make our healthcare system massively better for every human being—and this work is made possible in large part by the industry leaders we partner with. As we continue to push for progress in healthcare, we are thrilled and honored to welcome one of our newest partners—Accenture.
One of the biggest challenges enterprises face in adopting innovation isn’t a failed pilot—it’s a successful one. With the need to scale, the real work begins: aligning stakeholders, finding the budget for full deployment, integrating new solutions into current workflows, and shifting hearts and minds in favor of organizational change.
On the heels of the biggest year in venture funding, the digital health space is starting off 2018 with a bang: record Q1 funding of $1.62B, three $100M+ mega-deals, and a massive exit. Compared to last year, the commotion from policy debates has largely settled and a path to regulatory clarity has emerged. On our end, we’ve launched a couple of new sections within our funding post—check out our deep investor analysis as well as an update on the sometimes elusive, always critical quest of every digital health company: validation.
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.
After seven years, we’ve seen $23B invested into thousands of digital health companies. But we wanted to know: what has been the real-world impact of digital health? We were moved to learn just how many lives had been significantly changed by a new wave of technology. We aim to shift the digital health dialogue from one focused on the degree of investment and future expectations to one about digital health's effect on patients and healthcare outcomes. In that spirit, this ongoing project brings you stories of people living far outside Silicon Valley and the companies shifting the healthcare status quo who have made an impact on their lives.
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.
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