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Though the sharing of medical data has the potential to lead to breakthroughsin health care, the sharing process itself exposes patients and health careproviders to various risks. Patients face risks due to the possible loss inprivacy or livelihood that can occur when medical data is stolen or used innon-permitted ways, whereas health care providers face risks due to theassociated liability. For medical data, these risks persist even afteranonymizing/deidentifying, according to the standards defined in existinglegislation, the data sets prior to sharing, because shared medical data canoften be deanonymized/reidentified using advanced artificial intelligence andmachine learning methodologies. As a result, health care providers are hesitantto share medical data. One possible solution to encourage health care providersto responsibly share data is through the use of cybersecurity insurancecontracts. This paper studies the problem of designing optimal cybersecurityinsurance contracts, with the goal of encouraging the sharing of the medicaldata. We use a principal-agent model with moral hazard to model variousscenarios, derive the optimal contract, discuss its implications, and performnumerical case studies. In particular, we consider two scenarios: the firstscenario is where a health care provider is selling medical data to atechnology firm who is developing an artificial intelligence algorithm usingthe shared data. The second scenario is where a group of health care providersshare health data amongst themselves for the purpose of furthering medicalresearch using the aggregated medical data.

Optimally Designing Cybersecurity Insurance Contracts to Encourage the Sharing of Medical Data