The market has been driving itself into a frenzy this past year with the potential for emerging technologies to influence the digital transformation of healthcare to a value-based care era. Every year, a new term becomes the buzzword around which the entire technology industry rallies to make its case and rise above the noise. This year, it’s been AI, and technology vendors have fallen over one another to demonstrate how their solutions are “AI-powered,” “AI-enabled” or “AI-led.” The indiscriminate use of the term “AI” has become so pervasive that the research firm Gartner has even invented a name for it: AI-washing.
Arguably, many technology solution providers in the digital health space are simply slapping an AI label onto their offerings in hopes that healthcare executives will be interested. Nothing can be further from the reality on the ground. At a conference I attended last week, the message I heard in practically every session was the same: Return on investment (ROI) is king. Healthcare is far too conservative to commit to any technology investment that does not have a solid ROI behind it. Healthcare executives are also savvy enough not to be distracted by terms like “soft ROI” and “social ROI.” They are looking for demonstrable benefits in real dollars.
Healthcare provider CIOs see budgets fall due to overall margin and cost pressures on their businesses. Even though the industry has consolidated over the past several years, their negotiating power does not seem to have improved; in fact, prices for healthcare services in highly concentrated markets have declined, suggesting that insurers are gaining the upper hand. However, this has not stopped providers from adopting digital health innovation to increase revenues, reduce costs, and improve patient and clinician experience. In fact, it may be the opposite; healthcare providers have no option but to innovate with technology to survive in the long term.
The use of innovative new models for digital health covers a spectrum of operational areas. At last week’s conference, a couple of presentations caught my attention:
- In one health system, a new billing application with a slick mobile interface provided a complete view of a patient’s account along with copays, deductibles, past dues, and an interest-free payment plan option. The application is a far cry from the inscrutable explanation of benefits (EOB) statements that most of us receive in the mail. Users were practically raving about the app in their online feedback, and the health system’s collections on overdue payments had improved significantly.
- A major staffing solutions provider is using machine learning algorithms to predict staffing shortages at hospitals in critical areas such as emergency rooms. The application helps streamline the work, eliminate delays and reduce clinician overload and burnout.
Innovation groups in health systems are scouring the market for solutions that can address the many challenges and inefficiencies in the healthcare ecosystem. However, CIOs and other technology executives are confused by the rash of digital health applications in the market that don’t seem to follow any standardization regarding security features or integration, such as the Fast Health Interoperability Resources (FHIR) APIs. To further compound the issue, many solutions fail to deliver the promised results, even when they should. An example is the data analytics space; when action is taken based on analytical insights, very often there is no impact. The missing element here is likely the human aspect; as one CIO put it, there has never been a time for technology to show more empathy to the people who use it. In more practical terms, technology has to improve the lives of everyone who uses it and not just a particular set of stakeholders. The need to design technologies around the needs of clinicians, in particular, has become the focus of design thinking for digital health experiences.
To be fair to solution providers, healthcare is in the early stages of creating value with emerging technologies. One major challenge is the access to data. Many emerging technology solutions mature over time and require large volumes of data over extended periods of time to train the algorithms (IBM Watson Health platform is one such case – a sophisticated cognitive computing platform that is trying to solve complex medical issues but has come under criticism). Another is the integration challenge that limits access to patient data that sits inside proprietary vendor systems, not to mention the emerging sources of structured and unstructured data that are increasingly part of a clinician’s toolkit in diagnosis and treatment.
Over the past year, there has been much progress: FHIR is gradually emerging as the de facto interoperability standard. The FDA has taken the lead on digital health and is approving solutions from innovative technology providers, such as genetic testing data from 23andME that was greenlighted for clinical use earlier this year and a slew of companies selected this past week to participate in the FDA’s digital health pre-certification program.
The key takeaway for me this past week was that opportunities are everywhere for digital health. The healthcare industry has lagged in consumer-oriented healthcare innovation, and it’s not hard to find new opportunities for digital health solutions. However, solution providers have to be laser-focused on demonstrating tangible benefits and get it right the first time. As the old advertising slogan goes, you don’t get a second chance to make a first impression.