Healthcare

Patients whose transfer to the Intensive Care Unit (ICU) is unplanned are prone to higher mortality rates and longer length-of-stay than those who were admitted directly to the ICU. Recent advances in machine learning to predict patient deterioration have introduced the possibility of proactive transfer from the ward to the ICU. In this work, we study the problem of finding robust patient transfer policies which account for uncertainty in statistical estimates due to data limitations when optimizing to improve overall patient care.

We examine a Query Theory account of risky choice framing effects — when risky choices are framed as a gain, people are generally risky averse but, when an equivalent choice is framed as a loss, people are risk seeking. Consistent with Query Theory, frames affected the structure of participants’ arguments: gain frame participants listed arguments favoring the certain option earlier and more often than loss frame participants. These argumentative shifts mediated framing effects; manipulating participants initial arguments attenuated them.

We study how increasing contract length affects adverse selection in health insurance markets. Although health risks are persistent, private health insurance contracts in the United States have short, one-year terms. Short-term, community-rated contracts allow patients to increase their coverage only after risks materialize, which leads to market unraveling. Longer contracts ameliorate adverse selection because both demand and supply exhibit horizon effects. Intuitively, longer horizon risk is less predictable, thus elevating demand for coverage and lowering equilibrium premiums.

Objectives:

To examine whether and how step-down unit admission after ICU discharge affects patient outcomes.

Design:

Retrospective study using an instrumental variable approach to remove potential biases from unobserved differences in illness severity for patients admitted to the step-down unit after ICU discharge.

Setting:

Ten hospitals in an integrated healthcare delivery system in Northern California.

Patients: