Oct 25, 2018, 1:24 AM ETConference Presentation, Panel

Smart Cities for Healthy Aging

City-level innovation is primary: National health and aging reforms are often "boil-the-ocean" challenges, whereas city mayors possess the specific budgetary and political power to drive rapid, scalable change.
Technology is an enabler, not a cure: No technological solutions are missing; the primary barriers to progress are deployment, business models, administrative processes, and political will.
Aging demographics are urbanizing: Approximately 80% of people aged 65+ currently live in cities, with this percentage expected to rise, making urban infrastructure the critical locus for healthy aging.
Shift from segregation to integration: The traditional model of age-segregated communities (e.g., desert retirement villages) is rejected by current and future cohorts in favor of intergenerational integration within the fabric of the city.
Infrastructure timeline mismatch: City infrastructure planning takes 10–20 years, requiring strategies that account for the rapid generational shift from Boomers to Millennials (50+) and Gen Z (30+) whose tech expectations differ significantly.

Safety via Vision Zero: Boston is deploying sensors and data analytics at intersections to address traffic fatalities, noting that over 50% of pedestrian deaths involve older adults.
Public restroom mapping: The city mapped all public restrooms and launched a searchable online map plus a 311 phone service to assist residents in accessing facilities, prioritizing low-income and non-tech-savvy communities.
Age-friendly business certification: A program trains business owners to reduce ageism, improve lighting, enlarge print, and enhance customer service to better accommodate older shoppers.
Housing and retention goals: Boston aims to build 69,000 new housing units by 2030 to prevent the displacement of older residents due to rising costs.
Social isolation challenge: The Massachusetts Age-Friendly Challenge issued by the state and partners like GE is seeking solutions specifically targeting social isolation and community connection.

Scale of the problem: An estimated 3.5 to 4 million patient appointments are missed annually in the U.S. primarily due to transportation barriers.
Uber Health platform: Launched to provide HIPAA-compliant ride scheduling for healthcare organizations, allowing bookings up to 30 days in advance for patients and caregivers.
Low-barrier access: Solutions do not require patient smartphone ownership; rides can be requested via dashboard or SMS (e.g., sending a "1" to initiate a return trip).
Family coordination: New features allow caregivers to be "CC'd" on ride requests, receiving status updates (e.g., "Grandma arrived at doctor") without burdening the patient with manual logging.
Specialized vehicle fleets: Integration of Uber Assist (door-to-door) and Uber Wave (wheelchair-accessible) to address diverse mobility needs within urban environments.

Focus on prediction: Prevention is framed as "prediction," using AI to analyze hospital data to risk-score patients and prioritize interventions before acute events occur.
Interoperability challenges: The lack of data interoperability across institutional silos is identified as the single largest non-technical hurdle in healthcare technology deployment.
Employer leverage: Large corporations are using their purchasing power to offer preventive benefits, recognizing that employee health is a critical factor in recruitment and retention.
Smart city infrastructure: Cities must adopt AI, 5G, and "smart things" strategies not just for immediate use cases, but to create a foundational infrastructure capable of supporting future, unforeseen applications.
Pilot trap warning: Small Proof of Concepts (POCs) often fail to address scale issues; successful deployment requires moving to large-scale programs (e.g., NIH's "All of Us" million-person initiative) to test administrative and workflow scalability.

The "Middle Quintile" risk: The greatest economic vulnerability lies with the middle three quintiles of the population (net worth ~$200k, late 60s), who face a high risk of running out of funds by age 80.
Caregiving crisis: The current $500 billion in unpaid family caregiving is unsustainable; the future requires significant job creation in professional caregiving and new support industries.
Generational shifts in health behavior: Gen Z is showing higher focus on proactive health (diet, exercise) potentially driven by their increased involvement in caring for aging grandparents.
Reimagining urban space: As autonomous vehicles reduce the need for parking and retail shifts to e-commerce, cities have an opportunity to convert these spaces into community centers for intergenerational interaction.
Digital divide mitigation: Technology solutions must account for language diversity, varying levels of tech literacy, and income disparities to avoid leaving behind communities of color and low-income residents.

Collaboration mandate: Tech companies must engage directly with city residents and officials to understand specific needs rather than offering pre-packaged products.
Interdisciplinary innovation: Solving aging requires cross-departmental collaboration (housing, welfare, parks, garbage) which mayors are best positioned to orchestrate.
Rejection of "silver bullet": No single technology will solve aging; success depends on human-centered design that aligns with how people actually use tech for entertainment, efficiency, and connection.
High-touch vs. high-tech balance: Efficiency algorithms must be balanced with the human need for connection, such as preserving driver-passenger interaction in senior shuttle services.
Bipartisan potential: There is emerging optimism for bipartisan collaboration on aging infrastructure, driven by the universal nature of the demographic challenge.