In 2021 the Linux Foundation (LF) announced the formation of Linux Foundation Research, a new organization to broaden the understanding of open source ecosystems and to explore opportunities for new open source initiatives. Given my long involvement with Linux, the Linux Foundation and open source communities in general, I was invited to become a member of the newly created LF Research Advisory Board (RAB).
At a September, 2023 meeting of the Advisory Board, we discussed that one of the few industry sectors in which the LF does not have projects is healthcare, despite its size and importance around the world. The LF had launched healthcare initiatives in the past, but they all eventually failed. At that meeting, LF Research launched a study to understand what we should be doing in the healthcare sector. I’m involved in the study, and for the past several months, I’ve been learning about the opportunities of digital technologies in healthcare systems by reading a number of articles and talking to key experts.
“The Promise of Digital Health: Then, Now, and the Future,” a discussion paper published in June of 2022 by the US National Academy of Medicine is one of the articles that I found most instructive. The paper is based on the contributions of 25 member of the National Academy of Medicine (NAM), including two of the experts I’ve recently spoken with, John Halamka and Peter Lee.
“Digital health has evolved as a broad term encompassing electronically captured data, along with technical and communications infrastructure and applications in the health care ecosystem,” said the paper. “Revolutionary advances in digital health are transforming health, medicine, and biomedical science, and redefining and re-engineering the tools needed to create a healthier future. Developments such as cloud computing, artificial intelligence, machine learning, blockchain, digitally mediated diagnostics and treatment, telehealth, and consumer-facing mobile health applications are now routinely used in self-management, health care, and biomedical science. These developments promise to drive earlier diagnoses and interventions, improve outcomes, and support more engaged patients.”
But, the paper added, realizing the promise of digital health requires accelerated progress to overcome a number of major challenges. Let me discuss three of these challenges.
Interoperable healthcare technologies and systems. “Despite important gains in the last two decades, made possible by significant investment by payers, providers, and the federal government in electronic health records (EHRs), progress toward interoperable systems, and advanced technology to coordinate care and manage disease, the promise of digital health remains illusory. The ability to use interoperable digital technology to improve the effectiveness, efficiency, equity, and continuity of care remains substantially conceptual. For example, digital interfaces in inpatient care systems are often clumsy; volumes of health data are mostly sequestered, inaccessible, and difficult to aggregate in a meaningful and actionable way, in part due to the ongoing need for evolving data standards.”
Social and behavioral factors. “[R]esearch indicates that social and behavioral factors both outweigh medical care in determining health status and modulate the contributions of genetics and physical environments. Unfortunately, U.S. health policies and health system investments remain misaligned with these insights. In the U.S., approximately 90% of all health expenses go to disease and injury treatment rather than to addressing the predisposing factors of these illnesses and injuries. By 2020, U.S. health expenditures had grown to $4.1 trillion. Spending in the health sector is projected to increase to over $6 trillion annually and encompass 20% of the nation’s gross domestic product by 2028).” Despite spending almost twice as much as other high-income economies, the US “currently has a lower life expectancy, higher rate of death by suicide, higher chronic disease burden, higher rates of preventable hospitalizations, higher use of unnecessary expensive testing and procedures, and lower use of primary care than its peer countries.”
Coordinated clinical and public health. “In addition, digital tools and data are relatively ineffective in assisting clinicians in better understanding patient and family preferences and circumstances that facilitate health progress outside of the clinic. The notion of digital tools that can be applied in widespread fashion to coordinate health care organizations and public health efforts to identify and engage those at particular risk from behavioral, social, and environmental public health risks remains rudimentary at best. The expansive vision of real-time generation of evidence in a learning health system that links datasets and analyzes them using artificial intelligence and machine learning is nascent and limited to a few pilots.”
Digital technologies are already being applied in a number of health areas, including: health information, e.g., digital records and dashboards; knowledge integrators, e.g., predictive analytics and AI/ML; imaging, e.g., diagnostics and interpretation; personal health devices, e.g., mobile monitoring and assessment; and telemedicine, e.g., remote consultations and care coordination.
In addition, the paper examined the potential of digital innovations in a number of major healthcare areas:
Advancing Diagnosis and Treatment. A major proportion of health spending is attributed to chronic diseases and individual experiencing multiple medical conditions. Digital health solutions that promote self-management as part of the treatment of individuals with high-need, high-cost chronic conditions could both improve care and lower expenditures.
Ensuring Care Continuity. “Even the most sophisticated digital diagnostics will have little impact on clinical outcomes if they are implemented in a fragmented health care ecosystem.” This is a major area where promoting seamless interoperability and supporting increased individual control of their personal health data could make a major difference.
Off-Site Patient Management through Telemedicine. “Digital tools that collect data and support interventions outside the clinical setting offer meaningful opportunities to identify risks and engage patients.” Consumer-facing apps and clinical monitors that collect data can serve as an early warning systems for disease management. Studies have shown that 20% of all office care, outpatients, home heath services, and even emergency room care could be delivered virtually or near virtually.
Partnering with Individuals to Support Self-Management. “Given that most chronic disease management occurs outside of the traditional health care setting, partnering with individuals so that they can fully engage in their own care and meeting people where they are physically and mentally is essential to achieving better health outcomes, improving quality of life, and reducing health care spending.” The healthcare industry could significantly benefit by leveraging digital tools that have been successfully used in other industries such as consumer interactions, text communications, and personalized recommendations, and could result in a more robust partnership between individuals, families, and providers.
Reducing Error and Waste in the Delivery System. “Extensive research indicates that health care resources are inappropriately allocated within the current system. Waste has been shown to carry consequences for quality outcomes and patient safety (e.g., medical errors and delays) and economic efficiency (e.g., unnecessary spending). The digitization of health data has long been considered the foundation for patient safety, operational efficiency, and quality of care.”
Seamless System Interoperability. While there’s been considerable progress in data and interoperability standards, much more remains to be done. In addition, interoperability standards need to extend beyond the current focus on EHRs. For example, seamless communication among health care-related devices are essential for promoting optimal health. “Incompatible interfaces, corrupted data written between systems, or mismatched patient data have the potential to have dire consequences, requiring collective action to ensure adherence to standards to protect data integrity. Technological advancement and national policies have made possible the vision for a digital infrastructure that can facilitate seamless interfaces and real-time interoperability of devices and data streams.”
Artificial Intelligence and Machine Learning. “As the U.S. moves to value-based payment models, transparent and advanced analytics are needed to calculate population risk, the foundation upon which medical budgets are established in contracts between payers and providers. AI-driven predictive modeling and other sophisticated statistical techniques can be used to identify subpopulations for intense care management to prevent inappropriate emergency room use or early intervention for an acute worsening event to reduce hospital admissions.”
“Envisioning and achieving a seamless, healthier future through digital innovation will require a deeper investment in evidence-based research, more clinical and field studies, and commitment from diverse stakeholders,” said the National Academy of Medicine paper in conclusion. “But the potential for rewards is enormous. Validated information, curated across the health data continuum and easily shared, can deliver insight at the point of care, easing provider burden and augmenting clinical reasoning skills. An Internet of Things in health care serves the public’s need for accurate health advice, and a digital health ecosystem that provides high-quality, personalized, equitable care to all who need it is achievable and worthy of our best individual and collective efforts.”
Hi Irving,
An example of diagnosis in my new article https://arxiv.org/abs/2403.20239
Patent filed by Paris hospitals
Posted by: Marc Fiammante | April 05, 2024 at 07:44 AM