  Though the sharing of medical data has the potential to lead to breakthroughs
in health care, the sharing process itself exposes patients and health care
providers to various risks. Patients face risks due to the possible loss in
privacy or livelihood that can occur when medical data is stolen or used in
non-permitted ways, whereas health care providers face risks due to the
associated liability. For medical data, these risks persist even after
anonymizing/deidentifying, according to the standards defined in existing
legislation, the data sets prior to sharing, because shared medical data can
often be deanonymized/reidentified using advanced artificial intelligence and
machine learning methodologies. As a result, health care providers are hesitant
to share medical data. One possible solution to encourage health care providers
to responsibly share data is through the use of cybersecurity insurance
contracts. This paper studies the problem of designing optimal cybersecurity
insurance contracts, with the goal of encouraging the sharing of the medical
data. We use a principal-agent model with moral hazard to model various
scenarios, derive the optimal contract, discuss its implications, and perform
numerical case studies. In particular, we consider two scenarios: the first
scenario is where a health care provider is selling medical data to a
technology firm who is developing an artificial intelligence algorithm using
the shared data. The second scenario is where a group of health care providers
share health data amongst themselves for the purpose of furthering medical
research using the aggregated medical data.
