Introduction
Healthcare is an ever-evolving and complex industry consisting of many different stakeholders seeking to maximize the triad of performance based business measures, clinical effectiveness, and operating efficiencies. Structurally, the industry is largely aligned into the domains of Payor, Provider, Patient, Pharma, and Policy (the so-called “5 P’s”). Against this backdrop, digital transformation initiatives, and in particular, consumer digital health (CDH) are unlocking new opportunities to address patient experiences and clinician satisfaction, attracting a torrent of new entrants seeking to capitalize on an industry that is approximately 20% of U.S. GDP, according the U.S. Government Accountability Office (GAO, 2023). More recently, sustainability has become a tangential component motivating change across the healthcare industry, particularly with respect to the provision, treatment, and operation of care. Indeed, in a recently published global study, “if healthcare was a country, it would be the fifth-largest greenhouse gas emitter on the planet”, according to Health Care’s Climate Footprint, a report by Health Care Without Harm, in collaboration with Arup (Deloitte, 2023).
The Criticality of Data
Healthcare is a data-driven industry, and in many ways, it is very similar to both the financial and hospitality service industries. The former is heavily regulated, featuring specific workflows, and the latter is marketed, positioned, and placed to different clientele. A common thread is the criticality of data as a means to inform, operationalize, and curate new care pathways. And in a similar vein, information from data is also essential to train supervised and supervised machine learning models to develop augmented intelligence services to assist clinicians in decision making, reduce risk, and minimize variability of care. Mobile Edge Computing, high-performing wireless (i.e., 5G), and discombobulated services via Cloud-hosting is in turn unlocking tremendous new opportunities as exemplified by autonomous living initiatives for patients (for example, aging in place) and the U.S. Center for Medicare & Medicaid Services’ (CMS) Acute Hospital Care at Home (AHCaH) program, both of which rely extensively on data gleaned from a collage of Internet of Things (IoT) devices. The information and thus knowledge obtained from such approaches to healthcare are viewed by many as being crucial to addressing equity and equality of care as well as economic and environmental sustainability.
Charting a Safe Course
Navigating the complexity of data and information exchange in healthcare is a juggernaut, especially considering that pervasive interoperability has yet to be achieved, trust, privacy, and security are paramount, and purposeful control and compartmentalization of data are hallmarks of the industry. Notwithstanding these matters, different consumer (clinician and patient) digital literacies, changing data standards regarding data governance resist, and a culture of change management that eschews non-evidence based change act to stymie innovation, which is reflective of the state of the industry relative to others that have adopted digital transformation much earlier.
IoT Data and its Governance
To address the above considerations, in December of 2022, the IoT Community Healthcare Forum conducted a panel session that was well represented by major industry and thought-leader contributors focused on digital transformation across the healthcare industry. The purpose goal of the panel session was to explore the opportunities, challenges, risks, and threats arising from the collection, distribution, and management of information from IoT sensors, recognizing that torrent of data that is being collected from patient generated healthcare data (PGHD) sources, in-patient and/or at-home activity monitors, and The panel covered IoT interoperability and zero trust schemes that promote security and privacy, data storage and management including cloud hosting, access, and permissioning methods, and the application and use of Artificial Intelligence to organize and provide data management for consumption by different stakeholders.
The discussion began with opportunities and areas of impact aligned to CMS’ AHCaH, remote patient observation (ambulatory or in-patient), remote patient monitoring (RPM), virtual physical therapy (VPT), and independent living. Specific themes included key drivers on the adoption and use of IoT, how next generation devices and system are promoting its use, and the perspectives of the clinician and healthcare enterprise (Provider and Payor, respectively). Of note, the panel members shared how frequent collection of data positively impacts the effectiveness and efficiency of healthcare operations, and how growing use of machine learning (ML) and Artificial Intelligence (AI) in healthcare is helping to reduce the burden on clinicians and improving patient outcomes.
The next part segment of the panel session focused on how IoT in healthcare is being introduced. An emphasis on enabling technologies (such as private LTE, 5G, and Cloud Services) provoked a discussion about new clinical pathways that harmonize with traditional virtual health modalities such as telehealth. Privacy and security, an omni-present consideration, was juxtaposed with a conversation on new technical architectures that triggered a rich exchange about key considerations to ensure data veracity and consumer trust in an era of cloud-based data distribution across the care continuum. The panel also shared its thoughts on change management best practices both technically and from the lens of empathy to articulate the importance of all stakeholders in driving the adoption of IoT without loss of fidelity and confidence – in essence, making data collected from the IoT ecosphere transparent and of an ambient nature.
The final segment of the panel session focused on the theme of how data is managed. The conversation started on persona dependencies and expectations of the latter with respect to storage, rights of ownership, survivability, and de-identification for social reasons. Members of the panel described a matrix of solutions that use different technologies (depending on need and cost) to simplify support and management of data rich solution that employ or access IoT in healthcare. As a case example, the panel explored different strategies that healthcare enterprises can use on data structure, storage, and analysis to handle the estimated over million data points per hour per patient from IoT devices at scale under present assumptions. The panel concluded with an informative, future-forward discussion about how prospective enterprises might manage distributed health and wellness, where digital care is completely virtualized around centers of clinical excellence.
Conclusion
As a thought leader, the IoT Community Healthcare Forum is committed to continue to offer thought-provoking panel sessions on relevant topics such as this. We hope you will attend our 2023 series of events that will further probe the opportunities that lie ahead.
By:
Eric Abbott
Chair, IoT Community Healthcare IoT Center of Excellence
