Optimizing Choice of Health Insurance For Diabetes (OrCHID) - PROJECT ABSTRACT
Diabetes affects 10% of the U.S. population and is responsible for $237 billion in direct medical costs annually.
Primary care and specialist visits, medications and testing supplies, durable medical equipment, lab testing,
and potential emergency and hospital visits can be costly. Patients with diabetes report a high level of financial
burden relative to patients without diabetes, struggling to pay for necessary health care, food, housing, and
retirement. Cost-related non-adherence (delaying filling a prescription or taking less medicine) for patients with
diabetes is high, and subsequently, patients in health insurance plans with poor coverage for needed services
and resources experience adverse outcomes like hyper- or hypoglycemia, acute cerebrovascular disease, and
ischemic heart disease due to delayed or forgone care. Therefore, choosing a health insurance plan that meets
your needs is critical to improve health, especially for patients with low income socioeconomic status.
Unfortunately, many consumers struggle to choose a health plan from among the many offered, focusing on a
single factor like costs, using heuristics to make decisions, falling subject to biases that challenge rational
decision-making theory, and failing to weigh trade-offs between plan features.
We hypothesize that health economic stated preference methods like discrete choice experiments and multi-
criteria decision analyses can be used to elicit health plan preferences and values. These tools specifically ask
patients to weigh trade-offs between multiple plan features and can assess which features influence patient
decisions the most. In this observational natural experiment study, we will use stated preference surveys to
systematically assess patient preferences for health plans that adequately cover diabetes care. We will
leverage our access to health plan and claims data from Harvard Pilgrim Health Care and the Tufts Health
Plan, two New England-based insurers with a combined 2.2 million covered lives. We will analyze the
concordance between patient preferences and their real-world health plan. Finally, we will assess the
relationship between preference-aligned health plan enrollment and adverse diabetes health outcomes, cost-
related treatment non-adherence, receipt of appropriate high-quality diabetes care, health care costs and
utilization, patient financial burden, and plan satisfaction. If preference-aligned health plans are associated with
better health and health care outcomes, future work will develop a decision aid that allows patients to clarify
their values and preferences for health care and choose a plan that will enable them to use preventive care
that reduces adverse health events and lowers their financial burden. If not, future research can use study
results to design a decision aid that directs consumers to plans with features associated with improved health,
health care utilization, health care costs, and consumer satisfaction.
