The information balance between insurer and insured is shifting

Wearables and continuous biomonitoring are giving individuals private knowledge of their own health risk. The Apple Heart Study screened more than 419,000 mostly asymptomatic smartwatch users and flagged irregular pulses; about a third of those alerted were later confirmed to have atrial fibrillation, although the device's sensitivity was modest and its effect on health outcomes was not established. As such risk information accumulates with the insured, while insurers in community-rated systems are restricted from pricing on it, the long-established conditions for adverse selection appear: when buyers understand their own risk better than the insurer can, lower-risk people may under-insure and higher-risk people over-insure, eroding the shared pool. The effect is not automatic. Evidence from the long-term care insurance market shows that private information is multidimensional: some who buy more cover are high-risk, others simply value insurance more and are in fact lower-risk. The net link between coverage and risk can be weak, or even reversed. A renewed wave of adverse selection is therefore a credible risk to plan for, not a certainty.

From symptom-based consultation to early-signal prevention

Continuous monitoring moves the point of clinical contact from the moment symptoms appear to the moment an early signal is detected. That shift changes both the timing and the cost of care: more case-finding, more preventive intervention, and far more data to interpret. For insurers it cuts two ways: earlier detection can raise near-term diagnostic and treatment costs, but it also offers the prospect of averting expensive late-stage disease. Reinventing the financing model therefore means pricing prevention rather than only illness, managing the data and its governance, and deciding (within the legal limits on health and genetic data) how risk is shared, not merely selected against. Practical responses include prevention-oriented products, investment in early intervention, revised risk-pooling and reinsurance, and closer partnership with providers and technology firms.

How we help insurers rethink financing

For insurers we typically:

• Quantify a book of business's exposure to information-driven selection, and stress-test the risk pool against rising consumer risk awareness.
• Design prevention-oriented products that price and reward early detection within the legal limits on health- and genetic-data use.
• Rethink risk-pooling, underwriting, and reinsurance so that continuous monitoring strengthens the pool rather than fragmenting it, and build the measurement to confirm that prevention reduces downstream cost.

For health-technology investors and founders

We also advise venture capital and corporate venture capital funds on health-technology investment.

The organising discipline is evidence. A Health Affairs study of the most heavily funded digital health companies found their peer-reviewed clinical evidence limited, with most studies conducted in healthy rather than high-burden populations and few measuring any effect on cost or access; a later analysis of 224 digital health companies found that 44% had completed no clinical trials or regulatory filings, and that the strength of clinical evidence bore no relation to the funding a company had raised. We help investors distinguish demonstrated clinical and economic value from claims, appraise regulatory and reimbursement pathways, and run evidence-based due diligence, so that capital is directed to products likely both to work and to be paid for.

For healthcare startups, we help turn clinical promise into the evidence that raises capital and secures reimbursement. Because funding has not historically tracked the strength of clinical evidence, founders who can show credible clinical and economic data, a defensible regulatory route, and a realistic payment pathway stand out to investors and payers alike. We support startups in shaping the evidence plan, the market and competitor analysis, and the financial narrative for a funding round, keeping the equity story within what the data can support.