It has been a long time since my last post. The digital health economic, clinical, regulatory, and political landscapes have changed significantly since then. The objective of my blog, which began in 2011, was and remains to educate the reader (clinicians, health care IT community, patients and caregivers, and other health care stakeholders about digital health technology and how it is relevant to the changing health care environment. The first post, “Can Moneyball Become Moneycare: How Predictive Informatics Can Make mHealth (digital health) a Success,” discussed artificial intelligence as it might relate to health care. It is time to recharge the blog to reflect on what has transpired in the past five years and serve as a present-day source of information and commentary. There have been resounding success stories (Kardia) and even more significant setbacks (Teledoc, Theranos, Proteus, Pear Therapeutics, and BetterHelp). The causes for the setbacks varied, and each presented a lesson in ethics or business practices/strategies. In a previous post, I discussed the elements of successful technology and its development. They included C-suite buy-in at the corporate level of the potential customer, commitment of resources, interdisciplinary team participation, and partnerships between private and public sectors. I want to update this list.
1. Be problem-solving, not burnout-producing. One of my tenets of the differences between a digital health tool and a solution is the ability to solve an existing problem. The difficulty may be operational, financial, workflow-related, clinical perspective, or a combination of these. A significant way to avoid having a technology seeking an indication (the “build it and they will come plan”) is to have a clinician and health care administrator (depending upon the type of technology) well-versed in digital health on the team. They will add a needed perspective on the tech’s value proposition, tech development, enterprise and other partnerships, and marketing. The EHR has been demonstrated to be a major source of physician burden and burnout. This was elegantly discussed in an interview with Dr. Barry Newman in 2021. I am proud to be a member of the HIMSS Physician Burden Reduction Task Force addressing this problem. Burnout is of a sufficient magnitude that physicians are unionizing, and many medical students plan on having jobs that do not involve seeing patients.
2. Create credibility. Digital health has been plagued by hype for over ten years, and hype cycles in digital health tech have been described. Simply put, the tech must do what it is professed to do (i.e., a working tool, not screenshots shown to potential investors or partnering companies). The best way to do this is to operate with alpha (early) testing during development to identify problems (technical, workflow, and usability issues) before they are more costly to address. Clinical tools require studies with outcome data. It is what patients and clinicians expect. The FDA has created the Digital Health Center of Excellence to assist. There is currently a disconnect between clinical evidence and investor funding. Not many companies have availed themselves of such a regulatory submission process. This may explain the failure rate of companies that have received even large investments.
3. Form digital partnerships. I believe that most digital health technologies are most successful when partnered with other technologies. There are multiple reasons for this. Customers do not have the desire, budget, or bandwidth to screen, pilot, or deploy many tools each year. Technologies can be transformed into more robust and effective offerings by combining technologies. For example, a wearable sensor device becomes more clinically beneficial and cost-effective if it measures multiple parameters and might be connected to a patient’s medication list for reminders. An app becomes more effective if it is combined with a language-translation tool. An inventory tracking platform becomes more effective when tied to the customer’s budget information.
4. Have medium and long-term growth strategies: Look beyond your first customers. To launch a digital health tool, especially if it is a clinical tool requiring regulatory approval, there are development and fundraising benchmarks. Once these are met, development improvements, further studies, and marketing benchmarks will be necessary to satisfy investors and real and potential customers. As in any start-up, an exit strategy should be considered. Infusion of funds can expand reach, improve technology, and lead to more and better partnerships to fulfill the company’s mission. One consideration is to seek investors as partners, providing expert advice and financial infusion.
5. Use obtained deidentified data to pivot or expand tech scope and adjust strategy. The data provided by usage of the technology itself can be useful in tweaking the app or changing marketing strategy. For example, there is a large divide between successful medical apps and the rest of the pack. According to recent research by the IQVIA Institute, “… a majority of apps (83 percent) are installed fewer than 5,000 times and collectively account for less than 1 percent of total downloads … In comparison, 110 apps have each been downloaded more than 10 million times and account for almost 50 percent of total downloads.” Analysis of data can perhaps demonstrate where the falloff occurs and can be forensically analyzed. Appropriately used artificial intelligence tools associated with a given technology can continuously gather de-identified data, providing operational or clinical insight to the company, which can then lead to improving its accuracy and focus.
This is not a comprehensive treatise on this subject, but an update on digital health and how I see it. Future posts will discuss digital health technologies related to mental health, health care navigation, diversity and inclusion, physician burnout, and others.
David Lee Scher is a cardiologist and digital health consultant.
