Rising sight loss: AI care-coordination and community support plan

Sight loss is rising as populations age: an estimated 3.6 million people in the target OECD markets currently live with vision impairment from causes such as AMD, diabetic retinopathy and glaucoma, and many face fragmented care, delayed referrals, and insufficient community support that drive preventable decline, social isolation and higher downstream costs. Health systems, payers, patients and unpaid caregivers all bear the burden of poor coordination and limited capacity for proactive outreach. You could build an AI-enabled care-coordination and community support platform that digitizes screening, risk scoring and triage, orchestrates referrals to community services and low-vision rehab, integrates with EHRs and clinician workflows, and measures functional outcomes to support outcomes-based contracting. With an addressable digitizable support cost of roughly $1,500 per person per year, the implied market opportunity is about $5.4 billion; the Market Score is 90/100 and Revenue Potential 82/100. Revenue models could include SaaS to health systems and payers, per-referral fees and value-sharing for avoided downstream costs. This market is attractive now because demographic trends and the shift to community-based care are creating demand for scalable remote triage and coordination, and advances in AI-enabled screening can meaningfully reduce clinic burden. To stand out against a medium-competition landscape you would need clinically validated algorithms, deep local resource mapping, strong interoperability, and payer/health system partnerships; key challenges are data quality, regulatory and reimbursement hurdles, and clinician adoption, all of which require upfront investment and rigorous validation rather than quick wins.