Making Pervasive Computing Technology Pervasive for Health & Wellness in Aging

Abstract

During a research encounter I asked a ninety-year-old retired engineer, Mr. M, who for many years had been volunteering in a longitudinal healthy aging study, “would you use a fitness watch that measured your steps and active time?” He quickly replied, “why would I need that?” And then with a sly smile, added, “I’m still good at math. When I go for my daily walk, I note the time on my old watch and then when I return, I note the time again. A little subtraction tells me that I’ve been out for my usual hour constitutional.” This brief exchange encapsulates many of the key reasons why the adoption of various contemporary technologies—collectively called pervasive computing technologies (the ecosystem of technologies including sensors, mobile devices, and wireless communications) that harnesses the power of embedding computational capability into everyday life—by the aging population has been slow. This paper examines the challenges in this adoption phenomenon, especially in light of popular interest in harnessing technology in the service of helping to maintain health and wellness. Mr. M is very fortunate. He is healthy, active, cognitively intact, self-motivated, and remains independent. Unfortunately, he is not the norm for most of the aging population. For most, as one ages, the ability to remain independent and in particular to age in place or pursue one’s life of choice becomes a risk-laden venture, especially for those age 85 and older, a large and rapidly-growing portion of the population. After age 65, 70% of Americans will need some long-term care services (adult day services, home care, assisted living, nursing home) to maintain independence during the remainder of their lives (U.S. Department of Health and Human Services, 2015; Vassilev, 2015). The amount spent on these services in the United States in 2012 was $219.9 billion (George Washington University, 2012), not including care provided by family or friends on an unpaid basis (often called informal care). Approximately 42 million Americans (mostly women) provided unpaid support to an adult at an estimated economic value of $450 billion (AARP Public Policy Institute, 2011). Considering the growth of the aging population and that even just one major chronic condition such as Alzheimer’s disease is projected to require national care costs of over $1 trillion dollars by 2050, the status quo is not tenable (Kaye, Harrington, & LaPlante, 2010). Key to addressing these challenges is the ability to provide more effective means of facilitating independence and health for as long as possible. Aside from proposed shifts in policy such as age-friendly work rules or retirement programs, there has been continuing interest in what might be called “out-innovating aging”: developing and applying new technologies to facilitate sustainable wellness and effective interventions when decline occurs. In response to this idea a profusion of technologies and protocols have been introduced and developed over several decades. These technologies take advantage of important developments in sensing and pervasive computing, wearable technologies, mobile and wireless communications, health information technology systems, and “big data” analytics. Notwithstanding this abundance of opportunities, the true value of these approaches has yet to be fully evaluated, developed, or implemented. Despite indications of high promise (Lyons et al., 2015; Merrell & Doarn, 2015; Darkins, Kendall, Edmonson, Young, & Stressel, 2015), the evidence base remains incomplete. As I will develop further, this continues as a key challenge to realizing the potential of technology for the aging. The history of technology as a “fix” for aging’s challenges is relatively short. As noted, the need has grown out of the realization that a transformative response is needed that is equal to the profound impact that the “age-wave” itself will have on our health systems and communities. In this context, the vision of how technology can be transformative has been alluring. "Rodney selected his primary medical team from a variety of providers by comparing their credentials, performance rankings, and pricing online. Because of the widespread availability and use of reliable information, which has generated increased provider-level competition, the cost of health care has stabilized and in some cases has actually fallen, whereas quality and efficiency have risen. Rodney periodically accesses his multidisciplinary primary medical team using e-mail, video conferencing, and home blood monitoring. He owns his privacy-protected, electronic medical record. He also chose to have a tiny, radio-frequency computer chip implanted in his abdomen that monitors his blood chemistries and blood pressure." This description of a fictitious patient, Rodney Rogers, was presented in 2005 as a vision of healthcare in 2015 when then–senate majority leader William Frist delivered the venerable Shattuck Lecture, titled “Health Care in the 21st Century”, to the Massachusetts Medical Society (Frist, 2005). Although much of this now decade-old vision was quite prescient, even with the advent of new incremental technologies (such as smartphone-based apps and wearable devices) much of this vision remains aspirational or simply a series of yet-to-be-met goals. Dr. Frist’s vision and the general concept of technology as a facilitator toward better health and wellness for the aging has roots that go back more than a decade ago. In 2001 (well before the iPhone, Facebook, or Fitbit were available) the National Research Council contracted with the National Institute on Aging to conduct workshops on applications of technology needs of the aging population. Out of that effort a series of papers were compiled that included an important review authored by Eric Dishman (at Intel at the time) and colleagues titled “Everyday Health: Technology for Adaptive Aging” (National Research Council, 2004). The review pointed out not only the promise but also six key challenges of health-related technologies research: 1) imagination: moving beyond today’s clinical and computing models; 2) identification: finding and prioritizing problems to pursue; 3) iteration: concept testing and refinement; 4) infrastructure: deep dives on enabling technologies; 5) interfaces: exploration of human-machine interaction; and 6) integration: testing whole systems in situ. These challenges began to be tackled with a proliferation of smart home demonstrations and small pilot studies, but there remained a need for more work on integration and scalable, real-world demonstrations of efficacy and effectiveness (National Research Council, 2004). In the ensuing decade, several major efforts were launched to move in this direction. With National Institute on Aging (NIA) support, the Oregon Roybal Center for Aging & Technology (orcatech.org) established a fully integrated multi-domain home assessment platform, the Life Laboratory, in 2004. A collaboration supported by the Robert Wood Johnson Foundation, National Institutes of Health, National Science Foundation (NSF), and Intel established the Senior Independent Living Research initiative to determine the requirements for a scalable technology platform for independent living research across the United States. Extensive visioning and roadmap initiatives (with evocative acronyms) were also conducted across the European Union, including Ambient Assisted Living Innovation Alliance (AALIANCE), Common Awareness and Knowledge Platform for Studying and Enabling Independent Living (CAPSIL), Extending Professional Active Life (ePAL), Social, Ethical and Privacy Needs in ICT for Older People (SENIOR), and Bridging Research in Aging and ICT Development (BRAID) (Van Den Broek, 2010; Bennis, McGrath, Caulfield, Knapp, & Coghlan, 2010; Camarinha-Matos & Afsarmanesh, 2011; Wright, 2009). These initiatives created roadmaps for research to achieve effective and sustainable solutions to independent living based on in-depth analyses of independent living and information communication technology scenarios for Europe’s growing aging population. Subsequent workgroups (e.g., President’s Council of Advisors on Science and Technology [2014], the Trans-NIH/Interagency Workshop on the Use and Development of Assistive Technology for the Aging Population and People with Chronic Disabilities, and other initiatives like NSF Smart and Connected Homes) provided further grist for building the pathway forward to real-world evidence. In addition to the profusion of guiding documents and a few focused deployments, there more recently have been important islands of larger real-world efforts, forged to build in situ evidence of the value of some of these technologies. These have largely been within the domain of telecare, telehealth, or telemedicine (each related, but not the same) where the available technologies and response systems have been in development for many decades. Notable among these real-world experiments has been the U.S. Department of Veterans Affairs (VA) and their Care Coordination/Home Telehealth Program, which has enrolled tens of thousands of veterans (Kidholm et al., 2015); the Renewing Health Consortium, deployed across nine European countries (21 telemedicine pilots; 7000 patients; Cartwright et al., 2013; Henderson, Knapp, & Fernandez, 2013); and the Whole System Demonstrator, a randomized, controlled trial of telecare and telehealth completed in the United Kingdom (Bower et al., 2012). These important programs have remotely monitored thousands of patients with multiple chronic medical conditions, facilitated by dedicated home monitoring devices and messaging services supervised by care coordinators. In summary, the results have unfortunately been mixed. This has been borne out by a number of systematic reviews (Wootton, 2012; Black et al., 2011; Car, Huckvale, & Hermens, 2012; Deshpande, Khoja, & McKibbon, 2008; Polisena, Coyle, Coyle, & McGill, 2009; Pope, Rowsell, & O’Cathain, 2011; Vassilev, 2015). Many issues have been identified as contributing to these inconsistent findings: differences in patient populations, deployed technologies, user experience, training, costs, and variable outcome measures and analyses, to name a few. Despite many potential challenges and shortcomings, continuing interest in technology as a catalytic engine for health care improvement remains strong, fueled by the serious health policy implications of the aging of the population. Continuing rapidly-evolving technical capabilities in mobile and pervasive computing capacity, wireless technologies, and computationally intensive analytics, particularly in non–health care sectors (e.g., consumer electronics, manufacturing, finance) has shown tremendous growth. Today five of the top six most valuable companies are giants of the technology industry: only one was on the list 10 years ago (Microsoft). Technological innovation and growth has spawned more recent major movements that have become the buzz-words of today, with "digital health", "the internet of things", and "big data" touted as phenomena that will improve the health and well-being of everyone, including the aging population. As a measure of the unflagging interest in these areas, in just over the past four years, searches on these terms have increased up to three-fold (Google Trends, searched February 14, 2017). 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