Dec 6, 2017, 7:00 PM ETConference Presentation, Panel, Fireside Chat

Transforming Healthcare with Technology

Shift from Acute to Home-Based Care: The industry is pivoting from expensive hospital-centric models to patient-centric home care, driven by consumer demand for convenience and the need to reduce systemic costs.
Demographic Pressure: An aging global population will see the number of people over 65 rise to roughly 2 billion within 25 years, creating significant funding and resource pressure on healthcare systems.
Mental Health Prevalence: Current data suggests 100% of individuals with a brain will experience mental health issues, contrasting with the traditional "1 in 4" statistic, with anxiety and depression levels rising due to smartphone overuse.
Preventative vs. Curative: Technology is enabling a shift from "precision medicine" (treating illness) to "precision prevention" (tailoring plans to specific individuals to avoid illness), with the goal of delivering care where patients do not need to visit a doctor.

Value-Based Incentives: The transition from fee-for-service (volume-based) to value-based care (quality/cost-based) is identified as a critical prerequisite for justifying digital investments and realizing cost reductions.
Immediate Cost Reductions: Deploying specific digital tools, such as mental health apps or remote rehabilitation for COPD, can yield immediate within-year cost savings by reducing face-to-face consultation demand.
High-Cost Innovations: While digital tools lower per-unit costs for population management, high-tech therapies like gene editing for rare diseases operate on a different economic model with high per-unit costs, requiring new paradigms for both.
Total Cost of Care Models: Disruption of traditional delivery (e.g., the fertility sector's move to an e-commerce model) can increase service costs but reduce total costs by eliminating travel, accommodation, and emotional strain for patients.

The Data Paradox: The demographic requiring the most healthcare resources (the elderly and sick) is the least likely to engage with personal technology, creating a gap in data collection for the most vulnerable.
Connectivity Solutions: Real-time monitoring tools, such as connected pills and smart home sensors (e.g., smart toilets analyzing urine), can reduce disease management cycle times from months to days, improving outcomes and eliminating waste.
Data Fragmentation: Legacy systems in major economies like the US and UK suffer from poor data interoperability (e.g., duplicate insurance numbers), necessitating significant "plumbing" investment before advanced analytics can be effective.
Information Governance: Public trust remains a barrier; while most citizens consent to data usage for medical benefit, skepticism regarding exploitation and the need for clear governance frameworks persists.

Emergence of the "Informed Consumer": Consumers are increasingly self-managing health via smartphone apps (e.g., tracking diet, fitness, and mental health), creating a new market where individuals procure technology directly.
Regulatory Gaps: Unlike pharmaceuticals, the digital health app market lacks rigorous evidence-based regulation, allowing unverified "snake oil" claims to proliferate, necessitating urgent government and industry oversight.
Personalization vs. Consistency: A tension exists between the trend toward personalized, consumer-led care and the healthcare system's goal of delivering consistent, equitable outcomes across all regions.
Behavioral Nudges: Providing data (e.g., calorie counts) acts as a partial solution to behavioral inertia, though successful adoption requires combining technology with human engagement and incentives to ensure adherence.
Global Dissemination: Technology is being used to circumvent local skill shortages in regions like the Gulf (which produces fewer than 50 doctors annually) by implementing unmanned ICUs and remote telemedicine to reach scattered populations.