Good afternoon! Today's edition focuses on bringing software into different health environments, so we asked a group of experts about the strategies they've found to be most effective in doing that. Questions or comments? Send us a note at email@example.com
Head of personalized healthcare strategy at Roche/Genentech
Health care software has made giant strides as the COVID-19 pandemic shifted patient care from hospital settings into patients’ homes. This has generated an incredible growth spurt in innovation. For example, Rock Health reports health care startups raised over $29.1 billion in 2021, and there is no sign of a slowdown.
Yet we have seen the many promises of digital health technology throughout the history of health care, only for them to fizzle out or create longer-lasting complexities. So the biggest hurdle becomes: How can health care software optimize long-term sustainability while minimizing burden on existing health care systems?
In reality, biopharma and technology are still treated as separate worlds. While technology giants have built platforms that disrupted nearly every industry, they are now grappling with the equitability of them. Meanwhile, health care has proven that deep investments across an ecosystem can benefit everyone: patients, health care providers, health systems, biotech, payers and regulators.
This creates ample opportunity for health care technology to reinvent itself as an open platform that truly integrates the best of both worlds. We can rebuild as an open economy — whether it is through the democratization of health care software via open APIs or modernizing the underlying digital infrastructure on open standards. In doing so, we will witness the next generation of health care software that truly delivers value- or outcome-based care for all.
Health care is an industry that has long struggled with interoperability and low levels of information sharing. Meanwhile, the world around us has become more data-driven and tech-dependent. The tension that this brings to medicine is really hard with the rise of the WebMD self-diagnosis and expectations of a data-driven doctor. The physician is asked to be more data-driven and faster, but they’re not given the tools to help them get there. For example, there is no existing EMR that has the correct medical “primitives” to understand the data we need to collect to instrument the human body, the human experience and then practice accordingly. Existing EMRs were built to bill insurance — they’re a byproduct of a fee-for-service driven system.
When an entire industry is built around flawed incentives and optimized for insurance profits, not consumers, you can’t just chip away at the problem. The only way to succeed is to build a completely independent system free from today’s broken incentive structure. That’s why we’re building everything in-house: a full-stack solution combining software, hardware, data infrastructure and doctors all under one roof.
The most effective way to overcome hurdles in bringing software to health care environments is to make it as seamless and least disruptive as possible, for both the clinical and technical teams. Integrating using interoperable IT and health care standards is just the beginning, and necessary to reduce implementation costs, but it is still too broad.
It is important to establish a steering committee made up of clinical and IT stakeholder champions, to craft an implementation, change management and support plans. Workflow and application integration is paramount; for example, if a user has to log into each standalone application with separate credentials, a lot of time will be wasted and risk the software not being used. Clinicians have a finite amount of time with every patient. New health care software must be integrated into the existing application workflows clinicians already use to minimize disruption. SDKs to augment software packages, like MONAI, incorporate medical standards like HL7 and DICOM to facilitate integration into the medical software ecosystem.
These applications also need a place to be deployed, whether on the edge, in the data center or in hybrid clouds. Health care IT must be ready for the next generation of solutions, with more computation and data flow than ever before. Establishing a data center technology road map will be key to overcome the hurdles in software deployment; any deviation from this road map slows the entire process down. Technical staff on-site are managing hundreds of applications, each with their own endpoints, and any specialization is going to increase project time and project risk.
President & CEO, clinical effectiveness at Wolters Kluwer Health
Software for health care environments has a higher threshold for vetting compared to other environments due to the potential to influence patient care. To overcome adoption hurdles, it is critical for new solutions to seamlessly integrate into clinician workflows and demonstrate a positive outcome to patients.
Health care innovators can overcome initial hurdles such as skepticism from end users or an unwillingness to try something new by aligning with solutions that have a proven track record of success. This is particularly important now, with a plethora of new solutions available for virtual health and patient engagement. As new companies come to market or traditional tech vendors enter the health care space, partnerships with companies that have built a strong, trusted reputation may help alleviate some of the initial vetting or validation that is critical with new software.
Once a software solution has been accepted into an organization, the next challenge is to ensure that the solution is delivering on its promise and is fully utilized. Organizations can ensure a smooth roll-out by designating internal champions who can advocate from inside the organization. This group should include clinical users and other trusted experts including influencers or the IT team who will support the solution. Internal champions often drive greater engagement and support traditional onboarding and training programs, helping cultivate organizational buy-in as new software is rolled out. They can also work with software providers to design a phased implementation plan to identify areas of early success as the platform is adopted across the organization.
Senior vice president and general manager, Edison AI and Platform at GE Healthcare
It’s important to make software and technology that is easy to implement and integrate in a hospital’s existing health system. Health systems want to focus on patient outcomes and providing improved connected care rather than spending time training and learning software. According to Gartner, digital health platforms will emerge as the most cost-effective and technically efficient way to scale new digital capabilities within and across health ecosystems, and will over time replace the monolithic era of the megasuite electronic health record.
Digital health platforms are designed to accelerate app integration by connecting devices and other data sources into an aggregated clinical data layer. A collection of data transformation services would be available on a platform to support data analytic applications and to enable the training and deployment of AI models using the aggregated data. Through open and published interfaces, health care providers and third-party developers would be expected to be able to seamlessly deploy their applications, with the platform supporting integration of the apps into existing workflows. All these features of a digital health platform allow health systems to seamlessly integrate different applications and have real-time access to immense amount of data while improving patient care.
Technology has the potential to completely transform the healthcare industry, providing benefits to patients, providers, health networks and employers alike. But implementing new software and changing day-to-day operations requires extra training and buy-in amongst providers, who are already experiencing alarming levels of burnout. Health tech should help make providers’ jobs easier, but data is showing it’s doing quite the opposite for many. In fact, a recent report found that 69% of clinicians predict the widespread use of health technologies will become an even more challenging burden in the future.
During my time at One Medical, I’ve found the most effective way to get buy-in for new software is to solicit input from our care teams who are driving how the technology is being utilized. We’ve built our technology from the ground up alongside providers to ensure that we are implementing meaningful solutions that solve real problems, and not just building tech for tech’s sake. Technology has the potential to cut down on the administrative burden care teams have, including proper documentation after appointments, sending referrals for specialists, calling in prescriptions, and more. By creating technology that takes a back seat to the real product—great care—we can remove hubris in the design and build for the humans on both sides of the care experience.
Kevin McAllister ( @k__mcallister) is a Research Editor at Protocol, leading the development of Braintrust. Prior to joining the team, he was a rankings data reporter at The Wall Street Journal, where he oversaw structured data projects for the Journal's strategy team.